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Author SHA1 Message Date
kimi
96acac5c5f refactor: break up shell.py::run() into helpers
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Extract _build_run_env() and _exec_subprocess() from the 89-line run()
method, reducing it to ~30 lines that validate and delegate.

Fixes #539

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-19 21:03:33 -04:00
140 changed files with 1276 additions and 25036 deletions

1
.gitignore vendored
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@@ -73,6 +73,7 @@ morning_briefing.txt
markdown_report.md
data/timmy_soul.jsonl
scripts/migrate_to_zeroclaw.py
src/infrastructure/db_pool.py
workspace/
# Loop orchestration state

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@@ -1,33 +0,0 @@
# Matrix World Configuration
# Serves lighting, environment, and feature settings to the Matrix frontend.
lighting:
ambient_color: "#FFAA55" # Warm amber (Workshop warmth)
ambient_intensity: 0.5
point_lights:
- color: "#FFAA55" # Warm amber (Workshop center light)
intensity: 1.2
position: { x: 0, y: 5, z: 0 }
- color: "#3B82F6" # Cool blue (Matrix accent)
intensity: 0.8
position: { x: -5, y: 3, z: -5 }
- color: "#A855F7" # Purple accent
intensity: 0.6
position: { x: 5, y: 3, z: 5 }
environment:
rain_enabled: false
starfield_enabled: true # Cool blue starfield (Matrix feel)
fog_color: "#0f0f23"
fog_density: 0.02
features:
chat_enabled: true
visitor_avatars: true
pip_familiar: true
workshop_portal: true
agents:
default_count: 5
max_count: 20
agents: []

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@@ -1,178 +0,0 @@
# ── Token Quest System Configuration ─────────────────────────────────────────
#
# Quests are special objectives that agents (and humans) can complete for
# bonus tokens. Each quest has:
# - id: Unique identifier
# - name: Display name
# - description: What the quest requires
# - reward_tokens: Number of tokens awarded on completion
# - criteria: Detection rules for completion
# - enabled: Whether this quest is active
# - repeatable: Whether this quest can be completed multiple times
# - cooldown_hours: Minimum hours between completions (if repeatable)
#
# Quest Types:
# - issue_count: Complete when N issues matching criteria are closed
# - issue_reduce: Complete when open issue count drops by N
# - docs_update: Complete when documentation files are updated
# - test_improve: Complete when test coverage/cases improve
# - daily_run: Complete Daily Run session objectives
# - custom: Special quests with manual completion
#
# ── Active Quests ─────────────────────────────────────────────────────────────
quests:
# ── Daily Run & Test Improvement Quests ───────────────────────────────────
close_flaky_tests:
id: close_flaky_tests
name: Flaky Test Hunter
description: Close 3 issues labeled "flaky-test"
reward_tokens: 150
type: issue_count
enabled: true
repeatable: true
cooldown_hours: 24
criteria:
issue_labels:
- flaky-test
target_count: 3
issue_state: closed
lookback_days: 7
notification_message: "Quest Complete! You closed 3 flaky-test issues and earned {tokens} tokens."
reduce_p1_issues:
id: reduce_p1_issues
name: Priority Firefighter
description: Reduce open P1 Daily Run issues by 2
reward_tokens: 200
type: issue_reduce
enabled: true
repeatable: true
cooldown_hours: 48
criteria:
issue_labels:
- layer:triage
- P1
target_reduction: 2
lookback_days: 3
notification_message: "Quest Complete! You reduced P1 issues by 2 and earned {tokens} tokens."
improve_test_coverage:
id: improve_test_coverage
name: Coverage Champion
description: Improve test coverage by 5% or add 10 new test cases
reward_tokens: 300
type: test_improve
enabled: true
repeatable: false
criteria:
coverage_increase_percent: 5
min_new_tests: 10
notification_message: "Quest Complete! You improved test coverage and earned {tokens} tokens."
complete_daily_run_session:
id: complete_daily_run_session
name: Daily Runner
description: Successfully complete 5 Daily Run sessions in a week
reward_tokens: 250
type: daily_run
enabled: true
repeatable: true
cooldown_hours: 168 # 1 week
criteria:
min_sessions: 5
lookback_days: 7
notification_message: "Quest Complete! You completed 5 Daily Run sessions and earned {tokens} tokens."
# ── Documentation & Maintenance Quests ────────────────────────────────────
improve_automation_docs:
id: improve_automation_docs
name: Documentation Hero
description: Improve documentation for automations (update 3+ doc files)
reward_tokens: 100
type: docs_update
enabled: true
repeatable: true
cooldown_hours: 72
criteria:
file_patterns:
- "docs/**/*.md"
- "**/README.md"
- "timmy_automations/**/*.md"
min_files_changed: 3
lookback_days: 7
notification_message: "Quest Complete! You improved automation docs and earned {tokens} tokens."
close_micro_fixes:
id: close_micro_fixes
name: Micro Fix Master
description: Close 5 issues labeled "layer:micro-fix"
reward_tokens: 125
type: issue_count
enabled: true
repeatable: true
cooldown_hours: 24
criteria:
issue_labels:
- layer:micro-fix
target_count: 5
issue_state: closed
lookback_days: 7
notification_message: "Quest Complete! You closed 5 micro-fix issues and earned {tokens} tokens."
# ── Special Achievements ──────────────────────────────────────────────────
first_contribution:
id: first_contribution
name: First Steps
description: Make your first contribution (close any issue)
reward_tokens: 50
type: issue_count
enabled: true
repeatable: false
criteria:
target_count: 1
issue_state: closed
lookback_days: 30
notification_message: "Welcome! You completed your first contribution and earned {tokens} tokens."
bug_squasher:
id: bug_squasher
name: Bug Squasher
description: Close 10 issues labeled "bug"
reward_tokens: 500
type: issue_count
enabled: true
repeatable: true
cooldown_hours: 168 # 1 week
criteria:
issue_labels:
- bug
target_count: 10
issue_state: closed
lookback_days: 7
notification_message: "Quest Complete! You squashed 10 bugs and earned {tokens} tokens."
# ── Quest System Settings ───────────────────────────────────────────────────
settings:
# Enable/disable quest notifications
notifications_enabled: true
# Maximum number of concurrent active quests per agent
max_concurrent_quests: 5
# Auto-detect quest completions on Daily Run metrics update
auto_detect_on_daily_run: true
# Gitea issue labels that indicate quest-related work
quest_work_labels:
- layer:triage
- layer:micro-fix
- layer:tests
- layer:economy
- flaky-test
- bug
- documentation

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@@ -1,912 +0,0 @@
# OpenClaw Architecture, Deployment Modes, and Ollama Integration
## Research Report for Timmy Time Dashboard Project
**Issue:** #721 — [Kimi Research] OpenClaw architecture, deployment modes, and Ollama integration
**Date:** 2026-03-21
**Author:** Kimi (Moonshot AI)
**Status:** Complete
---
## Executive Summary
OpenClaw is an open-source AI agent framework that bridges messaging platforms (WhatsApp, Telegram, Slack, Discord, iMessage) to AI coding agents through a centralized gateway. Originally known as Clawdbot and Moltbot, it was rebranded to OpenClaw in early 2026. This report provides a comprehensive analysis of OpenClaw's architecture, deployment options, Ollama integration capabilities, and suitability for deployment on resource-constrained VPS environments like the Hermes DigitalOcean droplet (2GB RAM / 1 vCPU).
**Key Finding:** Running OpenClaw with local LLMs on a 2GB RAM VPS is **not recommended**. The absolute minimum for a text-only agent with external API models is 4GB RAM. For local model inference via Ollama, 8-16GB RAM is the practical minimum. A hybrid approach using OpenRouter as the primary provider with Ollama as fallback is the most viable configuration for small VPS deployments.
---
## 1. Architecture Overview
### 1.1 Core Components
OpenClaw follows a **hub-and-spoke (轴辐式)** architecture optimized for multi-agent task execution:
```
┌─────────────────────────────────────────────────────────────────────────┐
│ OPENCLAW ARCHITECTURE │
├─────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ WhatsApp │ │ Telegram │ │ Discord │ │
│ │ Channel │ │ Channel │ │ Channel │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │
│ └────────────────────┼────────────────────┘ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ Gateway │◄─────── WebSocket/API │
│ │ (Port 18789) │ Control Plane │
│ └────────┬─────────┘ │
│ │ │
│ ┌──────────────┼──────────────┐ │
│ ▼ ▼ ▼ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Agent A │ │ Agent B │ │ Pi Agent│ │
│ │ (main) │ │ (coder) │ │(delegate)│ │
│ └────┬─────┘ └────┬─────┘ └────┬─────┘ │
│ │ │ │ │
│ └──────────────┼──────────────┘ │
│ ▼ │
│ ┌────────────────────────┐ │
│ │ LLM Router │ │
│ │ (Primary/Fallback) │ │
│ └───────────┬────────────┘ │
│ │ │
│ ┌─────────────────┼─────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │ Ollama │ │ OpenAI │ │Anthropic│ │
│ │(local) │ │(cloud) │ │(cloud) │ │
│ └─────────┘ └─────────┘ └─────────┘ │
│ │ ┌─────┐ │
│ └────────────────────────────────────────────────────►│ MCP │ │
│ │Tools│ │
│ └─────┘ │
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Memory │ │ Skills │ │ Workspace │ │
│ │ (SOUL.md) │ │ (SKILL.md) │ │ (sessions) │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────┘
```
### 1.2 Component Deep Dive
| Component | Purpose | Configuration File |
|-----------|---------|-------------------|
| **Gateway** | Central control plane, WebSocket/API server, session management | `gateway` section in `openclaw.json` |
| **Pi Agent** | Core agent runner, "指挥中心" - schedules LLM calls, tool execution, error handling | `agents` section in `openclaw.json` |
| **Channels** | Messaging platform integrations (Telegram, WhatsApp, Slack, Discord, iMessage) | `channels` section in `openclaw.json` |
| **SOUL.md** | Agent persona definition - personality, communication style, behavioral guidelines | `~/.openclaw/workspace/SOUL.md` |
| **AGENTS.md** | Multi-agent configuration, routing rules, agent specialization definitions | `~/.openclaw/workspace/AGENTS.md` |
| **Workspace** | File system for agent state, session data, temporary files | `~/.openclaw/workspace/` |
| **Skills** | Bundled tools, prompts, configurations that teach agents specific tasks | `~/.openclaw/workspace/skills/` |
| **Sessions** | Conversation history, context persistence between interactions | `~/.openclaw/agents/<agent>/sessions/` |
| **MCP Tools** | Model Context Protocol integration for external tool access | Via `mcporter` or native MCP |
### 1.3 Agent Runner Execution Flow
According to OpenClaw documentation, a complete agent run follows these stages:
1. **Queuing** - Session-level queue (serializes same-session requests) → Global queue (controls total concurrency)
2. **Preparation** - Parse workspace, provider/model, thinking level parameters
3. **Plugin Loading** - Load relevant skills based on task context
4. **Memory Retrieval** - Fetch relevant context from SOUL.md and conversation history
5. **LLM Inference** - Send prompt to configured provider with tool definitions
6. **Tool Execution** - Execute any tool calls returned by the LLM
7. **Response Generation** - Format and return final response to the channel
8. **Memory Storage** - Persist conversation and results to session storage
---
## 2. Deployment Modes
### 2.1 Comparison Matrix
| Deployment Mode | Best For | Setup Complexity | Resource Overhead | Stability |
|----------------|----------|------------------|-------------------|-----------|
| **npm global** | Development, quick testing | Low | Minimal (~200MB) | Moderate |
| **Docker** | Production, isolation, reproducibility | Medium | Higher (~2.5GB base image) | High |
| **Docker Compose** | Multi-service stacks, complex setups | Medium-High | Higher | High |
| **Bare metal/systemd** | Maximum performance, dedicated hardware | High | Minimal | Moderate |
### 2.2 NPM Global Installation (Recommended for Quick Start)
```bash
# One-line installer
curl -fsSL https://openclaw.ai/install.sh | bash
# Or manual npm install
npm install -g openclaw
# Initialize configuration
openclaw onboard
# Start gateway
openclaw gateway
```
**Pros:**
- Fastest setup (~30 seconds)
- Direct access to host resources
- Easy updates via `npm update -g openclaw`
**Cons:**
- Node.js 22+ dependency required
- No process isolation
- Manual dependency management
### 2.3 Docker Deployment (Recommended for Production)
```bash
# Pull and run
docker pull openclaw/openclaw:latest
docker run -d \
--name openclaw \
-p 127.0.0.1:18789:18789 \
-v ~/.openclaw:/root/.openclaw \
-e ANTHROPIC_API_KEY=sk-ant-... \
openclaw/openclaw:latest
# Or with Docker Compose
docker compose -f compose.yml --env-file .env up -d --build
```
**Docker Compose Configuration (production-ready):**
```yaml
version: '3.8'
services:
openclaw:
image: openclaw/openclaw:latest
container_name: openclaw
restart: unless-stopped
ports:
- "127.0.0.1:18789:18789" # Never expose to 0.0.0.0
volumes:
- ./openclaw-data:/root/.openclaw
- ./workspace:/root/.openclaw/workspace
environment:
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
- OPENROUTER_API_KEY=${OPENROUTER_API_KEY}
- OLLAMA_API_KEY=ollama-local
networks:
- openclaw-net
# Resource limits for small VPS
deploy:
resources:
limits:
cpus: '1.5'
memory: 3G
reservations:
cpus: '0.5'
memory: 1G
networks:
openclaw-net:
driver: bridge
```
### 2.4 Bare Metal / Systemd Installation
For running as a system service on Linux:
```bash
# Create systemd service
sudo tee /etc/systemd/system/openclaw.service > /dev/null <<EOF
[Unit]
Description=OpenClaw Gateway
After=network.target
[Service]
Type=simple
User=openclaw
Group=openclaw
WorkingDirectory=/home/openclaw
Environment="PATH=/usr/local/bin:/usr/bin:/bin"
Environment="NODE_ENV=production"
Environment="ANTHROPIC_API_KEY=sk-ant-..."
ExecStart=/usr/local/bin/openclaw gateway
Restart=always
RestartSec=10
[Install]
WantedBy=multi-user.target
EOF
sudo systemctl daemon-reload
sudo systemctl enable openclaw
sudo systemctl start openclaw
```
### 2.5 Recommended Deployment for 2GB RAM VPS
**⚠️ Critical Finding:** OpenClaw's official minimum is 4GB RAM. On a 2GB VPS:
1. **Do NOT run local LLMs** - Use external API providers exclusively
2. **Use npm installation** - Docker overhead is too heavy
3. **Disable browser automation** - Chromium requires 2-4GB alone
4. **Enable swap** - Critical for preventing OOM kills
5. **Use OpenRouter** - Cheap/free tier models reduce costs
**Setup script for 2GB VPS:**
```bash
#!/bin/bash
# openclaw-minimal-vps.sh
# Setup for 2GB RAM VPS - EXTERNAL API ONLY
# Create 4GB swap
sudo fallocate -l 4G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab
# Install Node.js 22
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo bash -
sudo apt-get install -y nodejs
# Install OpenClaw
npm install -g openclaw
# Configure for minimal resource usage
mkdir -p ~/.openclaw
cat > ~/.openclaw/openclaw.json <<'EOF'
{
"gateway": {
"bind": "127.0.0.1",
"port": 18789,
"mode": "local"
},
"agents": {
"defaults": {
"model": {
"primary": "openrouter/google/gemma-3-4b-it:free",
"fallbacks": [
"openrouter/meta/llama-3.1-8b-instruct:free"
]
},
"maxIterations": 15,
"timeout": 120
}
},
"channels": {
"telegram": {
"enabled": true,
"dmPolicy": "pairing"
}
}
}
EOF
# Set OpenRouter API key
export OPENROUTER_API_KEY="sk-or-v1-..."
# Start gateway
openclaw gateway &
```
---
## 3. Ollama Integration
### 3.1 Architecture
OpenClaw integrates with Ollama through its native `/api/chat` endpoint, supporting both streaming responses and tool calling simultaneously:
```
┌──────────────┐ HTTP/JSON ┌──────────────┐ GGUF/CPU/GPU ┌──────────┐
│ OpenClaw │◄───────────────────►│ Ollama │◄────────────────────►│ Local │
│ Gateway │ /api/chat │ Server │ Model inference │ LLM │
│ │ Port 11434 │ Port 11434 │ │ │
└──────────────┘ └──────────────┘ └──────────┘
```
### 3.2 Configuration
**Basic Ollama Setup:**
```bash
# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh
# Start server
ollama serve
# Pull a tool-capable model
ollama pull qwen2.5-coder:7b
ollama pull llama3.1:8b
# Configure OpenClaw
export OLLAMA_API_KEY="ollama-local" # Any non-empty string works
```
**OpenClaw Configuration for Ollama:**
```json
{
"models": {
"providers": {
"ollama": {
"baseUrl": "http://localhost:11434",
"apiKey": "ollama-local",
"api": "ollama",
"models": [
{
"id": "qwen2.5-coder:7b",
"name": "Qwen 2.5 Coder 7B",
"contextWindow": 32768,
"maxTokens": 8192,
"cost": { "input": 0, "output": 0 }
},
{
"id": "llama3.1:8b",
"name": "Llama 3.1 8B",
"contextWindow": 128000,
"maxTokens": 8192,
"cost": { "input": 0, "output": 0 }
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "ollama/qwen2.5-coder:7b",
"fallbacks": ["ollama/llama3.1:8b"]
}
}
}
}
```
### 3.3 Context Window Requirements
**⚠️ Critical Requirement:** OpenClaw requires a minimum **64K token context window** for reliable multi-step task execution.
| Model | Parameters | Context Window | Tool Support | OpenClaw Compatible |
|-------|-----------|----------------|--------------|---------------------|
| **llama3.1** | 8B | 128K | ✅ Yes | ✅ Yes |
| **qwen2.5-coder** | 7B | 32K | ✅ Yes | ⚠️ Below minimum |
| **qwen2.5-coder** | 32B | 128K | ✅ Yes | ✅ Yes |
| **gpt-oss** | 20B | 128K | ✅ Yes | ✅ Yes |
| **glm-4.7-flash** | - | 128K | ✅ Yes | ✅ Yes |
| **deepseek-coder-v2** | 33B | 128K | ✅ Yes | ✅ Yes |
| **mistral-small3.1** | - | 128K | ✅ Yes | ✅ Yes |
**Context Window Configuration:**
For models that don't report context window via Ollama's API:
```bash
# Create custom Modelfile with extended context
cat > ~/qwen-custom.modelfile <<EOF
FROM qwen2.5-coder:7b
PARAMETER num_ctx 65536
PARAMETER temperature 0.7
EOF
# Create custom model
ollama create qwen2.5-coder-64k -f ~/qwen-custom.modelfile
```
### 3.4 Models for Small VPS (≤8B Parameters)
For resource-constrained environments (2-4GB RAM):
| Model | Quantization | RAM Required | VRAM Required | Performance |
|-------|-------------|--------------|---------------|-------------|
| **Llama 3.1 8B** | Q4_K_M | ~5GB | ~6GB | Good |
| **Llama 3.2 3B** | Q4_K_M | ~2.5GB | ~3GB | Basic |
| **Qwen 2.5 7B** | Q4_K_M | ~5GB | ~6GB | Good |
| **Qwen 2.5 3B** | Q4_K_M | ~2.5GB | ~3GB | Basic |
| **DeepSeek 7B** | Q4_K_M | ~5GB | ~6GB | Good |
| **Phi-4 4B** | Q4_K_M | ~3GB | ~4GB | Moderate |
**⚠️ Verdict for 2GB VPS:** Running local LLMs is **NOT viable**. Use external APIs only.
---
## 4. OpenRouter Integration (Fallback Strategy)
### 4.1 Overview
OpenRouter provides a unified API gateway to multiple LLM providers, enabling:
- Single API key access to 200+ models
- Automatic failover between providers
- Free tier models for cost-conscious deployments
- Unified billing and usage tracking
### 4.2 Configuration
**Environment Variable Setup:**
```bash
export OPENROUTER_API_KEY="sk-or-v1-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
```
**OpenClaw Configuration:**
```json
{
"models": {
"providers": {
"openrouter": {
"apiKey": "${OPENROUTER_API_KEY}",
"baseUrl": "https://openrouter.ai/api/v1"
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "openrouter/anthropic/claude-sonnet-4-6",
"fallbacks": [
"openrouter/google/gemini-3.1-pro",
"openrouter/meta/llama-3.3-70b-instruct",
"openrouter/google/gemma-3-4b-it:free"
]
}
}
}
}
```
### 4.3 Recommended Free/Cheap Models on OpenRouter
For cost-conscious VPS deployments:
| Model | Cost | Context | Best For |
|-------|------|---------|----------|
| **google/gemma-3-4b-it:free** | Free | 128K | General tasks, simple automation |
| **meta/llama-3.1-8b-instruct:free** | Free | 128K | General tasks, longer contexts |
| **deepseek/deepseek-chat-v3.2** | $0.53/M | 64K | Code generation, reasoning |
| **xiaomi/mimo-v2-flash** | $0.40/M | 128K | Fast responses, basic tasks |
| **qwen/qwen3-coder-next** | $1.20/M | 128K | Code-focused tasks |
### 4.4 Hybrid Configuration (Recommended for Timmy)
A production-ready configuration for the Hermes VPS:
```json
{
"models": {
"providers": {
"openrouter": {
"apiKey": "${OPENROUTER_API_KEY}",
"models": [
{
"id": "google/gemma-3-4b-it:free",
"name": "Gemma 3 4B (Free)",
"contextWindow": 131072,
"maxTokens": 8192,
"cost": { "input": 0, "output": 0 }
},
{
"id": "deepseek/deepseek-chat-v3.2",
"name": "DeepSeek V3.2",
"contextWindow": 64000,
"maxTokens": 8192,
"cost": { "input": 0.00053, "output": 0.00053 }
}
]
},
"ollama": {
"baseUrl": "http://localhost:11434",
"apiKey": "ollama-local",
"models": [
{
"id": "llama3.2:3b",
"name": "Llama 3.2 3B (Local Fallback)",
"contextWindow": 128000,
"maxTokens": 4096,
"cost": { "input": 0, "output": 0 }
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "openrouter/google/gemma-3-4b-it:free",
"fallbacks": [
"openrouter/deepseek/deepseek-chat-v3.2",
"ollama/llama3.2:3b"
]
},
"maxIterations": 10,
"timeout": 90
}
}
}
```
---
## 5. Hardware Constraints & VPS Viability
### 5.1 System Requirements Summary
| Component | Minimum | Recommended | Notes |
|-----------|---------|-------------|-------|
| **CPU** | 2 vCPU | 4 vCPU | Dedicated preferred over shared |
| **RAM** | 4 GB | 8 GB | 2GB causes OOM with external APIs |
| **Storage** | 40 GB SSD | 80 GB NVMe | Docker images are ~10-15GB |
| **Network** | 100 Mbps | 1 Gbps | For API calls and model downloads |
| **OS** | Ubuntu 22.04/Debian 12 | Ubuntu 24.04 LTS | Linux required for production |
### 5.2 2GB RAM VPS Analysis
**Can it work?** Yes, with severe limitations:
**What works:**
- Text-only agents with external API providers
- Single Telegram/Discord channel
- Basic file operations and shell commands
- No browser automation
**What doesn't work:**
- Local LLM inference via Ollama
- Browser automation (Chromium needs 2-4GB)
- Multiple concurrent channels
- Python environment-heavy skills
**Required mitigations for 2GB VPS:**
```bash
# 1. Create substantial swap
sudo fallocate -l 4G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
# 2. Configure swappiness
echo 'vm.swappiness=60' | sudo tee -a /etc/sysctl.conf
sudo sysctl -p
# 3. Limit Node.js memory
export NODE_OPTIONS="--max-old-space-size=1536"
# 4. Use external APIs only - NO OLLAMA
# 5. Disable browser skills
# 6. Set conservative concurrency limits
```
### 5.3 4-bit Quantization Viability
**Qwen 2.5 7B Q4_K_M on 2GB VPS:**
- Model size: ~4.5GB
- RAM required at runtime: ~5-6GB
- **Verdict:** Will cause immediate OOM on 2GB VPS
- **Even with 4GB VPS:** Marginal, heavy swap usage, poor performance
**Viable models for 4GB VPS with Ollama:**
- Llama 3.2 3B Q4_K_M (~2.5GB RAM)
- Qwen 2.5 3B Q4_K_M (~2.5GB RAM)
- Phi-4 4B Q4_K_M (~3GB RAM)
---
## 6. Security Configuration
### 6.1 Network Ports
| Port | Purpose | Exposure |
|------|---------|----------|
| **18789/tcp** | OpenClaw Gateway (WebSocket/HTTP) | **NEVER expose to internet** |
| **11434/tcp** | Ollama API (if running locally) | Localhost only |
| **22/tcp** | SSH | Restrict to known IPs |
**⚠️ CRITICAL:** Never expose port 18789 to the public internet. Use Tailscale or SSH tunnels for remote access.
### 6.2 Tailscale Integration
Tailscale provides zero-configuration VPN mesh for secure remote access:
```bash
# Install Tailscale
curl -fsSL https://tailscale.com/install.sh | sh
sudo tailscale up
# Get Tailscale IP
tailscale ip
# Returns: 100.x.y.z
# Configure OpenClaw to bind to Tailscale
cat > ~/.openclaw/openclaw.json <<EOF
{
"gateway": {
"bind": "tailnet",
"port": 18789
},
"tailscale": {
"mode": "on",
"resetOnExit": false
}
}
EOF
```
**Tailscale vs SSH Tunnel:**
| Feature | Tailscale | SSH Tunnel |
|---------|-----------|------------|
| Setup | Very easy | Moderate |
| Persistence | Automatic | Requires autossh |
| Multiple devices | Built-in | One tunnel per connection |
| NAT traversal | Works | Requires exposed SSH |
| Access control | Tailscale ACL | SSH keys |
### 6.3 Firewall Configuration (UFW)
```bash
# Default deny
sudo ufw default deny incoming
sudo ufw default allow outgoing
# Allow SSH
sudo ufw allow 22/tcp
# Allow Tailscale only (if using)
sudo ufw allow in on tailscale0 to any port 18789
# Block public access to OpenClaw
# (bind is 127.0.0.1, so this is defense in depth)
sudo ufw enable
```
### 6.4 Authentication Configuration
```json
{
"gateway": {
"bind": "127.0.0.1",
"port": 18789,
"auth": {
"mode": "token",
"token": "your-64-char-hex-token-here"
},
"controlUi": {
"allowedOrigins": [
"http://localhost:18789",
"https://your-domain.tailnet-name.ts.net"
],
"allowInsecureAuth": false,
"dangerouslyDisableDeviceAuth": false
}
}
}
```
**Generate secure token:**
```bash
openssl rand -hex 32
```
### 6.5 Sandboxing Considerations
OpenClaw executes arbitrary shell commands and file operations by default. For production:
1. **Run as non-root user:**
```bash
sudo useradd -r -s /bin/false openclaw
sudo mkdir -p /home/openclaw/.openclaw
sudo chown -R openclaw:openclaw /home/openclaw
```
2. **Use Docker for isolation:**
```bash
docker run --security-opt=no-new-privileges \
--cap-drop=ALL \
--read-only \
--tmpfs /tmp:noexec,nosuid,size=100m \
openclaw/openclaw:latest
```
3. **Enable dmPolicy for channels:**
```json
{
"channels": {
"telegram": {
"dmPolicy": "pairing" // Require one-time code for new contacts
}
}
}
```
---
## 7. MCP (Model Context Protocol) Tools
### 7.1 Overview
MCP is an open standard created by Anthropic (donated to Linux Foundation in Dec 2025) that lets AI applications connect to external tools through a universal interface. Think of it as "USB-C for AI."
### 7.2 MCP vs OpenClaw Skills
| Aspect | MCP | OpenClaw Skills |
|--------|-----|-----------------|
| **Protocol** | Standardized (Anthropic) | OpenClaw-specific |
| **Isolation** | Process-isolated | Runs in agent context |
| **Security** | Higher (sandboxed) | Lower (full system access) |
| **Discovery** | Automatic via protocol | Manual via SKILL.md |
| **Ecosystem** | 10,000+ servers | 5400+ skills |
**Note:** OpenClaw currently has limited native MCP support. Use `mcporter` tool for MCP integration.
### 7.3 Using MCPorter (MCP Bridge)
```bash
# Install mcporter
clawhub install mcporter
# Configure MCP server
mcporter config add github \
--url "https://api.github.com/mcp" \
--token "ghp_..."
# List available tools
mcporter list
# Call MCP tool
mcporter call github.list_repos --owner "rockachopa"
```
### 7.4 Popular MCP Servers
| Server | Purpose | Integration |
|--------|---------|-------------|
| **GitHub** | Repo management, PRs, issues | `mcp-github` |
| **Slack** | Messaging, channel management | `mcp-slack` |
| **PostgreSQL** | Database queries | `mcp-postgres` |
| **Filesystem** | File operations (sandboxed) | `mcp-filesystem` |
| **Brave Search** | Web search | `mcp-brave` |
---
## 8. Recommendations for Timmy Time Dashboard
### 8.1 Deployment Strategy for Hermes VPS (2GB RAM)
Given the hardware constraints, here's the recommended approach:
**Option A: External API Only (Recommended)**
```
┌─────────────────────────────────────────┐
│ Hermes VPS (2GB RAM) │
│ ┌─────────────────────────────────┐ │
│ │ OpenClaw Gateway │ │
│ │ (npm global install) │ │
│ └─────────────┬───────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────┐ │
│ │ OpenRouter API (Free Tier) │ │
│ │ google/gemma-3-4b-it:free │ │
│ └─────────────────────────────────┘ │
│ │
│ NO OLLAMA - insufficient RAM │
└─────────────────────────────────────────┘
```
**Option B: Hybrid with External Ollama**
```
┌──────────────────────┐ ┌──────────────────────────┐
│ Hermes VPS (2GB) │ │ Separate Ollama Host │
│ ┌────────────────┐ │ │ ┌────────────────────┐ │
│ │ OpenClaw │ │◄────►│ │ Ollama Server │ │
│ │ (external API) │ │ │ │ (8GB+ RAM required)│ │
│ └────────────────┘ │ │ └────────────────────┘ │
└──────────────────────┘ └──────────────────────────┘
```
### 8.2 Configuration Summary
```json
{
"gateway": {
"bind": "127.0.0.1",
"port": 18789,
"auth": {
"mode": "token",
"token": "GENERATE_WITH_OPENSSL_RAND"
}
},
"models": {
"providers": {
"openrouter": {
"apiKey": "${OPENROUTER_API_KEY}",
"models": [
{
"id": "google/gemma-3-4b-it:free",
"contextWindow": 131072,
"maxTokens": 4096
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "openrouter/google/gemma-3-4b-it:free"
},
"maxIterations": 10,
"timeout": 90,
"maxConcurrent": 2
}
},
"channels": {
"telegram": {
"enabled": true,
"dmPolicy": "pairing"
}
}
}
```
### 8.3 Migration Path (Future)
When upgrading to a larger VPS (4-8GB RAM):
1. **Phase 1:** Enable Ollama with Llama 3.2 3B as fallback
2. **Phase 2:** Add browser automation skills (requires 4GB+ RAM)
3. **Phase 3:** Enable multi-agent routing with specialized agents
4. **Phase 4:** Add MCP server integration for external tools
---
## 9. References
1. OpenClaw Official Documentation: https://docs.openclaw.ai
2. Ollama Integration Guide: https://docs.ollama.com/integrations/openclaw
3. OpenRouter Documentation: https://openrouter.ai/docs
4. MCP Specification: https://modelcontextprotocol.io
5. OpenClaw Community Discord: https://discord.gg/openclaw
6. GitHub Repository: https://github.com/openclaw/openclaw
---
## 10. Appendix: Quick Command Reference
```bash
# Installation
curl -fsSL https://openclaw.ai/install.sh | bash
# Configuration
openclaw onboard # Interactive setup
openclaw configure # Edit config
openclaw config set <key> <value> # Set specific value
# Gateway management
openclaw gateway # Start gateway
openclaw gateway --verbose # Start with logs
openclaw gateway status # Check status
openclaw gateway restart # Restart gateway
openclaw gateway stop # Stop gateway
# Model management
openclaw models list # List available models
openclaw models set <model> # Set default model
openclaw models status # Check model status
# Diagnostics
openclaw doctor # System health check
openclaw doctor --repair # Auto-fix issues
openclaw security audit # Security check
# Dashboard
openclaw dashboard # Open web UI
```
---
*End of Research Report*

View File

@@ -20,7 +20,6 @@ packages = [
{ include = "spark", from = "src" },
{ include = "timmy", from = "src" },
{ include = "timmy_serve", from = "src" },
{ include = "timmyctl", from = "src" },
]
[tool.poetry.dependencies]
@@ -83,7 +82,6 @@ mypy = ">=1.0.0"
[tool.poetry.scripts]
timmy = "timmy.cli:main"
timmy-serve = "timmy_serve.cli:main"
timmyctl = "timmyctl.cli:main"
[tool.pytest.ini_options]
testpaths = ["tests"]

View File

@@ -54,7 +54,6 @@ REPO_ROOT = Path(__file__).resolve().parent.parent
RETRO_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
SUMMARY_FILE = REPO_ROOT / ".loop" / "retro" / "summary.json"
EPOCH_COUNTER_FILE = REPO_ROOT / ".loop" / "retro" / ".epoch_counter"
CYCLE_RESULT_FILE = REPO_ROOT / ".loop" / "cycle_result.json"
# How many recent entries to include in rolling summary
SUMMARY_WINDOW = 50
@@ -247,39 +246,9 @@ def update_summary() -> None:
SUMMARY_FILE.write_text(json.dumps(summary, indent=2) + "\n")
def _load_cycle_result() -> dict:
"""Read .loop/cycle_result.json if it exists; return empty dict on failure."""
if not CYCLE_RESULT_FILE.exists():
return {}
try:
raw = CYCLE_RESULT_FILE.read_text().strip()
# Strip hermes fence markers (```json ... ```) if present
if raw.startswith("```"):
lines = raw.splitlines()
lines = [l for l in lines if not l.startswith("```")]
raw = "\n".join(lines)
return json.loads(raw)
except (json.JSONDecodeError, OSError):
return {}
def main() -> None:
args = parse_args()
# Backfill from cycle_result.json when CLI args have defaults
cr = _load_cycle_result()
if cr:
if args.issue is None and cr.get("issue"):
args.issue = int(cr["issue"])
if args.type == "unknown" and cr.get("type"):
args.type = cr["type"]
if args.tests_passed == 0 and cr.get("tests_passed"):
args.tests_passed = int(cr["tests_passed"])
if not args.notes and cr.get("notes"):
args.notes = cr["notes"]
# Consume-once: delete after reading so stale results don't poison future cycles
CYCLE_RESULT_FILE.unlink(missing_ok=True)
# Auto-detect issue from branch when not explicitly provided
if args.issue is None:
args.issue = detect_issue_from_branch()

View File

@@ -27,15 +27,11 @@ from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parent.parent
QUEUE_FILE = REPO_ROOT / ".loop" / "queue.json"
IDLE_STATE_FILE = REPO_ROOT / ".loop" / "idle_state.json"
CYCLE_RESULT_FILE = REPO_ROOT / ".loop" / "cycle_result.json"
TOKEN_FILE = Path.home() / ".hermes" / "gitea_token"
GITEA_API = os.environ.get("GITEA_API", "http://143.198.27.163:3000/api/v1")
GITEA_API = os.environ.get("GITEA_API", "http://localhost:3000/api/v1")
REPO_SLUG = os.environ.get("REPO_SLUG", "rockachopa/Timmy-time-dashboard")
# Default cycle duration in seconds (5 min); stale threshold = 2× this
CYCLE_DURATION = int(os.environ.get("CYCLE_DURATION", "300"))
# Backoff sequence: 60s, 120s, 240s, 600s max
BACKOFF_BASE = 60
BACKOFF_MAX = 600
@@ -81,89 +77,6 @@ def _fetch_open_issue_numbers() -> set[int] | None:
return None
def _load_cycle_result() -> dict:
"""Read cycle_result.json, handling markdown-fenced JSON."""
if not CYCLE_RESULT_FILE.exists():
return {}
try:
raw = CYCLE_RESULT_FILE.read_text().strip()
if raw.startswith("```"):
lines = raw.splitlines()
lines = [ln for ln in lines if not ln.startswith("```")]
raw = "\n".join(lines)
return json.loads(raw)
except (json.JSONDecodeError, OSError):
return {}
def _is_issue_open(issue_number: int) -> bool | None:
"""Check if a single issue is open. Returns None on API failure."""
token = _get_token()
if not token:
return None
try:
url = f"{GITEA_API}/repos/{REPO_SLUG}/issues/{issue_number}"
req = urllib.request.Request(
url,
headers={
"Authorization": f"token {token}",
"Accept": "application/json",
},
)
with urllib.request.urlopen(req, timeout=10) as resp:
data = json.loads(resp.read())
return data.get("state") == "open"
except Exception:
return None
def validate_cycle_result() -> bool:
"""Pre-cycle validation: remove stale or invalid cycle_result.json.
Checks:
1. Age — if older than 2× CYCLE_DURATION, delete it.
2. Issue — if the referenced issue is closed, delete it.
Returns True if the file was removed, False otherwise.
"""
if not CYCLE_RESULT_FILE.exists():
return False
# Age check
try:
age = time.time() - CYCLE_RESULT_FILE.stat().st_mtime
except OSError:
return False
stale_threshold = CYCLE_DURATION * 2
if age > stale_threshold:
print(
f"[loop-guard] cycle_result.json is {int(age)}s old "
f"(threshold {stale_threshold}s) — removing stale file"
)
CYCLE_RESULT_FILE.unlink(missing_ok=True)
return True
# Issue check
cr = _load_cycle_result()
issue_num = cr.get("issue")
if issue_num is not None:
try:
issue_num = int(issue_num)
except (ValueError, TypeError):
return False
is_open = _is_issue_open(issue_num)
if is_open is False:
print(
f"[loop-guard] cycle_result.json references closed "
f"issue #{issue_num} — removing"
)
CYCLE_RESULT_FILE.unlink(missing_ok=True)
return True
# is_open is None (API failure) or True — keep file
return False
def load_queue() -> list[dict]:
"""Load queue.json and return ready items, filtering out closed issues."""
if not QUEUE_FILE.exists():
@@ -237,9 +150,6 @@ def main() -> int:
}, indent=2))
return 0
# Pre-cycle validation: remove stale cycle_result.json
validate_cycle_result()
ready = load_queue()
if ready:

View File

@@ -20,7 +20,7 @@ from datetime import datetime, timezone
from pathlib import Path
# ── Config ──────────────────────────────────────────────────────────────
GITEA_API = os.environ.get("GITEA_API", "http://143.198.27.163:3000/api/v1")
GITEA_API = os.environ.get("GITEA_API", "http://localhost:3000/api/v1")
REPO_SLUG = os.environ.get("REPO_SLUG", "rockachopa/Timmy-time-dashboard")
TOKEN_FILE = Path.home() / ".hermes" / "gitea_token"
REPO_ROOT = Path(__file__).resolve().parent.parent
@@ -327,31 +327,7 @@ def run_triage() -> list[dict]:
not_ready = [s for s in scored if not s["ready"]]
QUEUE_FILE.parent.mkdir(parents=True, exist_ok=True)
backup_file = QUEUE_FILE.with_suffix(".json.bak")
# Backup existing queue before overwriting
if QUEUE_FILE.exists():
try:
backup_file.write_text(QUEUE_FILE.read_text())
except OSError:
pass
# Write and validate
queue_json = json.dumps(ready, indent=2) + "\n"
QUEUE_FILE.write_text(queue_json)
# Validate by re-reading — restore backup on corruption
try:
validated = json.loads(QUEUE_FILE.read_text())
if not isinstance(validated, list):
raise ValueError("queue.json is not a list")
except (json.JSONDecodeError, ValueError) as e:
print(f"[triage] ERROR: queue.json validation failed: {e}", file=sys.stderr)
if backup_file.exists():
print("[triage] Restoring from backup", file=sys.stderr)
QUEUE_FILE.write_text(backup_file.read_text())
else:
QUEUE_FILE.write_text("[]\n")
QUEUE_FILE.write_text(json.dumps(ready, indent=2) + "\n")
# Write retro entry
retro_entry = {

View File

@@ -84,15 +84,10 @@ class Settings(BaseSettings):
# Only used when explicitly enabled and query complexity warrants it.
grok_enabled: bool = False
xai_api_key: str = ""
xai_base_url: str = "https://api.x.ai/v1"
grok_default_model: str = "grok-3-fast"
grok_max_sats_per_query: int = 200
grok_sats_hard_cap: int = 100 # Absolute ceiling on sats per Grok query
grok_free: bool = False # Skip Lightning invoice when user has own API key
# ── Database ──────────────────────────────────────────────────────────
db_busy_timeout_ms: int = 5000 # SQLite PRAGMA busy_timeout (ms)
# ── Claude (Anthropic) — cloud fallback backend ────────────────────────
# Used when Ollama is offline and local inference isn't available.
# Set ANTHROPIC_API_KEY to enable. Default model is Haiku (fast + cheap).
@@ -153,18 +148,6 @@ class Settings(BaseSettings):
"http://127.0.0.1:8000",
]
# ── Matrix Frontend Integration ────────────────────────────────────────
# URL of the Matrix frontend (Replit/Tailscale) for CORS.
# When set, this origin is added to CORS allowed_origins.
# Example: "http://100.124.176.28:8080" or "https://alexanderwhitestone.com"
matrix_frontend_url: str = "" # Empty = disabled
# WebSocket authentication token for Matrix connections.
# When set, clients must provide this token via ?token= query param
# or in the first message as {"type": "auth", "token": "..."}.
# Empty/unset = auth disabled (dev mode).
matrix_ws_token: str = ""
# Trusted hosts for the Host header check (TrustedHostMiddleware).
# Set TRUSTED_HOSTS as a comma-separated list. Wildcards supported (e.g. "*.ts.net").
# Defaults include localhost + Tailscale MagicDNS. Add your Tailscale IP if needed.
@@ -334,13 +317,6 @@ class Settings(BaseSettings):
autoresearch_max_iterations: int = 100
autoresearch_metric: str = "val_bpb" # metric to optimise (lower = better)
# ── Weekly Narrative Summary ───────────────────────────────────────
# Generates a human-readable weekly summary of development activity.
# Disabling this will stop the weekly narrative generation.
weekly_narrative_enabled: bool = True
weekly_narrative_lookback_days: int = 7
weekly_narrative_output_dir: str = ".loop"
# ── Local Hands (Shell + Git) ──────────────────────────────────────
# Enable local shell/git execution hands.
hands_shell_enabled: bool = True

View File

@@ -10,7 +10,6 @@ Key improvements:
import asyncio
import json
import logging
import re
from contextlib import asynccontextmanager
from pathlib import Path
@@ -24,7 +23,6 @@ from config import settings
# Import dedicated middleware
from dashboard.middleware.csrf import CSRFMiddleware
from dashboard.middleware.rate_limit import RateLimitMiddleware
from dashboard.middleware.request_logging import RequestLoggingMiddleware
from dashboard.middleware.security_headers import SecurityHeadersMiddleware
from dashboard.routes.agents import router as agents_router
@@ -32,7 +30,6 @@ from dashboard.routes.briefing import router as briefing_router
from dashboard.routes.calm import router as calm_router
from dashboard.routes.chat_api import router as chat_api_router
from dashboard.routes.chat_api_v1 import router as chat_api_v1_router
from dashboard.routes.daily_run import router as daily_run_router
from dashboard.routes.db_explorer import router as db_explorer_router
from dashboard.routes.discord import router as discord_router
from dashboard.routes.experiments import router as experiments_router
@@ -43,18 +40,14 @@ from dashboard.routes.memory import router as memory_router
from dashboard.routes.mobile import router as mobile_router
from dashboard.routes.models import api_router as models_api_router
from dashboard.routes.models import router as models_router
from dashboard.routes.quests import router as quests_router
from dashboard.routes.scorecards import router as scorecards_router
from dashboard.routes.spark import router as spark_router
from dashboard.routes.system import router as system_router
from dashboard.routes.tasks import router as tasks_router
from dashboard.routes.telegram import router as telegram_router
from dashboard.routes.thinking import router as thinking_router
from dashboard.routes.tools import router as tools_router
from dashboard.routes.tower import router as tower_router
from dashboard.routes.voice import router as voice_router
from dashboard.routes.work_orders import router as work_orders_router
from dashboard.routes.world import matrix_router
from dashboard.routes.world import router as world_router
from timmy.workshop_state import PRESENCE_FILE
@@ -383,78 +376,73 @@ def _startup_background_tasks() -> list[asyncio.Task]:
]
def _try_prune(label: str, prune_fn, days: int) -> None:
"""Run a prune function, log results, swallow errors."""
try:
pruned = prune_fn()
if pruned:
logger.info(
"%s auto-prune: removed %d entries older than %d days",
label,
pruned,
days,
)
except Exception as exc:
logger.debug("%s auto-prune skipped: %s", label, exc)
def _check_vault_size() -> None:
"""Warn if the memory vault exceeds the configured size limit."""
try:
vault_path = Path(settings.repo_root) / "memory" / "notes"
if vault_path.exists():
total_bytes = sum(f.stat().st_size for f in vault_path.rglob("*") if f.is_file())
total_mb = total_bytes / (1024 * 1024)
if total_mb > settings.memory_vault_max_mb:
logger.warning(
"Memory vault (%.1f MB) exceeds limit (%d MB) — consider archiving old notes",
total_mb,
settings.memory_vault_max_mb,
)
except Exception as exc:
logger.debug("Vault size check skipped: %s", exc)
def _startup_pruning() -> None:
"""Auto-prune old memories, thoughts, and events on startup."""
if settings.memory_prune_days > 0:
from timmy.memory_system import prune_memories
try:
from timmy.memory_system import prune_memories
_try_prune(
"Memory",
lambda: prune_memories(
pruned = prune_memories(
older_than_days=settings.memory_prune_days,
keep_facts=settings.memory_prune_keep_facts,
),
settings.memory_prune_days,
)
)
if pruned:
logger.info(
"Memory auto-prune: removed %d entries older than %d days",
pruned,
settings.memory_prune_days,
)
except Exception as exc:
logger.debug("Memory auto-prune skipped: %s", exc)
if settings.thoughts_prune_days > 0:
from timmy.thinking import thinking_engine
try:
from timmy.thinking import thinking_engine
_try_prune(
"Thought",
lambda: thinking_engine.prune_old_thoughts(
pruned = thinking_engine.prune_old_thoughts(
keep_days=settings.thoughts_prune_days,
keep_min=settings.thoughts_prune_keep_min,
),
settings.thoughts_prune_days,
)
)
if pruned:
logger.info(
"Thought auto-prune: removed %d entries older than %d days",
pruned,
settings.thoughts_prune_days,
)
except Exception as exc:
logger.debug("Thought auto-prune skipped: %s", exc)
if settings.events_prune_days > 0:
from swarm.event_log import prune_old_events
try:
from swarm.event_log import prune_old_events
_try_prune(
"Event",
lambda: prune_old_events(
pruned = prune_old_events(
keep_days=settings.events_prune_days,
keep_min=settings.events_prune_keep_min,
),
settings.events_prune_days,
)
)
if pruned:
logger.info(
"Event auto-prune: removed %d entries older than %d days",
pruned,
settings.events_prune_days,
)
except Exception as exc:
logger.debug("Event auto-prune skipped: %s", exc)
if settings.memory_vault_max_mb > 0:
_check_vault_size()
try:
vault_path = Path(settings.repo_root) / "memory" / "notes"
if vault_path.exists():
total_bytes = sum(f.stat().st_size for f in vault_path.rglob("*") if f.is_file())
total_mb = total_bytes / (1024 * 1024)
if total_mb > settings.memory_vault_max_mb:
logger.warning(
"Memory vault (%.1f MB) exceeds limit (%d MB) — consider archiving old notes",
total_mb,
settings.memory_vault_max_mb,
)
except Exception as exc:
logger.debug("Vault size check skipped: %s", exc)
async def _shutdown_cleanup(
@@ -525,55 +513,25 @@ app = FastAPI(
def _get_cors_origins() -> list[str]:
"""Get CORS origins from settings, rejecting wildcards in production.
Adds matrix_frontend_url when configured. Always allows Tailscale IPs
(100.x.x.x range) for development convenience.
"""
origins = list(settings.cors_origins)
# Strip wildcards in production (security)
"""Get CORS origins from settings, rejecting wildcards in production."""
origins = settings.cors_origins
if "*" in origins and not settings.debug:
logger.warning(
"Wildcard '*' in CORS_ORIGINS stripped in production — "
"set explicit origins via CORS_ORIGINS env var"
)
origins = [o for o in origins if o != "*"]
# Add Matrix frontend URL if configured
if settings.matrix_frontend_url:
url = settings.matrix_frontend_url.strip()
if url and url not in origins:
origins.append(url)
logger.debug("Added Matrix frontend to CORS: %s", url)
return origins
# Pattern to match Tailscale IPs (100.x.x.x) for CORS origin regex
_TAILSCALE_IP_PATTERN = re.compile(r"^https?://100\.\d{1,3}\.\d{1,3}\.\d{1,3}(?::\d+)?$")
def _is_tailscale_origin(origin: str) -> bool:
"""Check if origin is a Tailscale IP (100.x.x.x range)."""
return bool(_TAILSCALE_IP_PATTERN.match(origin))
# Add dedicated middleware in correct order
# 1. Logging (outermost to capture everything)
app.add_middleware(RequestLoggingMiddleware, skip_paths=["/health"])
# 2. Rate Limiting (before security to prevent abuse early)
app.add_middleware(
RateLimitMiddleware,
path_prefixes=["/api/matrix/"],
requests_per_minute=30,
)
# 3. Security Headers
# 2. Security Headers
app.add_middleware(SecurityHeadersMiddleware, production=not settings.debug)
# 4. CSRF Protection
# 3. CSRF Protection
app.add_middleware(CSRFMiddleware)
# 4. Standard FastAPI middleware
@@ -587,7 +545,6 @@ app.add_middleware(
app.add_middleware(
CORSMiddleware,
allow_origins=_get_cors_origins(),
allow_origin_regex=r"https?://100\.\d{1,3}\.\d{1,3}\.\d{1,3}(:\d+)?",
allow_credentials=True,
allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
allow_headers=["Content-Type", "Authorization"],
@@ -626,11 +583,6 @@ app.include_router(system_router)
app.include_router(experiments_router)
app.include_router(db_explorer_router)
app.include_router(world_router)
app.include_router(matrix_router)
app.include_router(tower_router)
app.include_router(daily_run_router)
app.include_router(quests_router)
app.include_router(scorecards_router)
@app.websocket("/ws")

View File

@@ -1,7 +1,6 @@
"""Dashboard middleware package."""
from .csrf import CSRFMiddleware, csrf_exempt, generate_csrf_token, validate_csrf_token
from .rate_limit import RateLimiter, RateLimitMiddleware
from .request_logging import RequestLoggingMiddleware
from .security_headers import SecurityHeadersMiddleware
@@ -10,8 +9,6 @@ __all__ = [
"csrf_exempt",
"generate_csrf_token",
"validate_csrf_token",
"RateLimiter",
"RateLimitMiddleware",
"SecurityHeadersMiddleware",
"RequestLoggingMiddleware",
]

View File

@@ -131,6 +131,7 @@ class CSRFMiddleware(BaseHTTPMiddleware):
For safe methods: Set a CSRF token cookie if not present.
For unsafe methods: Validate the CSRF token or check if exempt.
"""
# Bypass CSRF if explicitly disabled (e.g. in tests)
from config import settings
if settings.timmy_disable_csrf:
@@ -140,55 +141,52 @@ class CSRFMiddleware(BaseHTTPMiddleware):
if request.headers.get("upgrade", "").lower() == "websocket":
return await call_next(request)
# Get existing CSRF token from cookie
csrf_cookie = request.cookies.get(self.cookie_name)
# For safe methods, just ensure a token exists
if request.method in self.SAFE_METHODS:
return await self._handle_safe_method(request, call_next, csrf_cookie)
response = await call_next(request)
return await self._handle_unsafe_method(request, call_next, csrf_cookie)
# Set CSRF token cookie if not present
if not csrf_cookie:
new_token = generate_csrf_token()
response.set_cookie(
key=self.cookie_name,
value=new_token,
httponly=False, # Must be readable by JavaScript
secure=settings.csrf_cookie_secure,
samesite="Lax",
max_age=86400, # 24 hours
)
async def _handle_safe_method(
self, request: Request, call_next, csrf_cookie: str | None
) -> Response:
"""Handle safe HTTP methods (GET, HEAD, OPTIONS, TRACE).
return response
Forwards the request and sets a CSRF token cookie if not present.
"""
from config import settings
# For unsafe methods, we need to validate or check if exempt
# First, try to validate the CSRF token
if await self._validate_request(request, csrf_cookie):
# Token is valid, allow the request
return await call_next(request)
# Token validation failed, check if the path is exempt
path = request.url.path
if self._is_likely_exempt(path):
# Path is exempt, allow the request
return await call_next(request)
# Token validation failed and path is not exempt
# We still need to call the app to check if the endpoint is decorated
# with @csrf_exempt, so we'll let it through and check after routing
response = await call_next(request)
if not csrf_cookie:
new_token = generate_csrf_token()
response.set_cookie(
key=self.cookie_name,
value=new_token,
httponly=False, # Must be readable by JavaScript
secure=settings.csrf_cookie_secure,
samesite="Lax",
max_age=86400, # 24 hours
)
return response
async def _handle_unsafe_method(
self, request: Request, call_next, csrf_cookie: str | None
) -> Response:
"""Handle unsafe HTTP methods (POST, PUT, DELETE, PATCH).
Validates the CSRF token, checks path and endpoint exemptions,
or returns a 403 error.
"""
if await self._validate_request(request, csrf_cookie):
return await call_next(request)
if self._is_likely_exempt(request.url.path):
return await call_next(request)
endpoint = self._resolve_endpoint(request)
# After routing, check if the endpoint is marked as exempt
endpoint = request.scope.get("endpoint")
if endpoint and is_csrf_exempt(endpoint):
return await call_next(request)
# Endpoint is marked as exempt, allow the response
return response
# Endpoint is not exempt and token validation failed
# Return 403 error
return JSONResponse(
status_code=403,
content={
@@ -198,41 +196,6 @@ class CSRFMiddleware(BaseHTTPMiddleware):
},
)
def _resolve_endpoint(self, request: Request) -> Callable | None:
"""Resolve the route endpoint without executing it.
Walks the Starlette/FastAPI router to find which endpoint function
handles this request, so we can check @csrf_exempt before any
side effects occur.
Returns:
The endpoint callable, or None if no route matched.
"""
# If routing already happened (endpoint in scope), use it
endpoint = request.scope.get("endpoint")
if endpoint:
return endpoint
# Walk the middleware/app chain to find something with routes
from starlette.routing import Match
app = self.app
while app is not None:
if hasattr(app, "routes"):
for route in app.routes:
match, _ = route.matches(request.scope)
if match == Match.FULL:
return getattr(route, "endpoint", None)
# Try .router (FastAPI stores routes on app.router)
if hasattr(app, "router") and hasattr(app.router, "routes"):
for route in app.router.routes:
match, _ = route.matches(request.scope)
if match == Match.FULL:
return getattr(route, "endpoint", None)
app = getattr(app, "app", None)
return None
def _is_likely_exempt(self, path: str) -> bool:
"""Check if a path is likely to be CSRF exempt.

View File

@@ -1,209 +0,0 @@
"""Rate limiting middleware for FastAPI.
Simple in-memory rate limiter for API endpoints. Tracks requests per IP
with configurable limits and automatic cleanup of stale entries.
"""
import logging
import time
from collections import deque
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.requests import Request
from starlette.responses import JSONResponse, Response
logger = logging.getLogger(__name__)
class RateLimiter:
"""In-memory rate limiter for tracking requests per IP.
Stores request timestamps in a dict keyed by client IP.
Automatically cleans up stale entries every 60 seconds.
Attributes:
requests_per_minute: Maximum requests allowed per minute per IP.
cleanup_interval_seconds: How often to clean stale entries.
"""
def __init__(
self,
requests_per_minute: int = 30,
cleanup_interval_seconds: int = 60,
):
self.requests_per_minute = requests_per_minute
self.cleanup_interval_seconds = cleanup_interval_seconds
self._storage: dict[str, deque[float]] = {}
self._last_cleanup: float = time.time()
self._window_seconds: float = 60.0 # 1 minute window
def _get_client_ip(self, request: Request) -> str:
"""Extract client IP from request, respecting X-Forwarded-For header.
Args:
request: The incoming request.
Returns:
Client IP address string.
"""
# Check for forwarded IP (when behind proxy/load balancer)
forwarded = request.headers.get("x-forwarded-for")
if forwarded:
# Take the first IP in the chain
return forwarded.split(",")[0].strip()
real_ip = request.headers.get("x-real-ip")
if real_ip:
return real_ip
# Fall back to direct connection
if request.client:
return request.client.host
return "unknown"
def _cleanup_if_needed(self) -> None:
"""Remove stale entries older than the cleanup interval."""
now = time.time()
if now - self._last_cleanup < self.cleanup_interval_seconds:
return
cutoff = now - self._window_seconds
stale_ips: list[str] = []
for ip, timestamps in self._storage.items():
# Remove timestamps older than the window
while timestamps and timestamps[0] < cutoff:
timestamps.popleft()
# Mark IP for removal if no recent requests
if not timestamps:
stale_ips.append(ip)
# Remove stale IP entries
for ip in stale_ips:
del self._storage[ip]
self._last_cleanup = now
if stale_ips:
logger.debug("Rate limiter cleanup: removed %d stale IPs", len(stale_ips))
def is_allowed(self, client_ip: str) -> tuple[bool, float]:
"""Check if a request from the given IP is allowed.
Args:
client_ip: The client's IP address.
Returns:
Tuple of (allowed: bool, retry_after: float).
retry_after is seconds until next allowed request, 0 if allowed now.
"""
now = time.time()
cutoff = now - self._window_seconds
# Get or create timestamp deque for this IP
if client_ip not in self._storage:
self._storage[client_ip] = deque()
timestamps = self._storage[client_ip]
# Remove timestamps outside the window
while timestamps and timestamps[0] < cutoff:
timestamps.popleft()
# Check if limit exceeded
if len(timestamps) >= self.requests_per_minute:
# Calculate retry after time
oldest = timestamps[0]
retry_after = self._window_seconds - (now - oldest)
return False, max(0.0, retry_after)
# Record this request
timestamps.append(now)
return True, 0.0
def check_request(self, request: Request) -> tuple[bool, float]:
"""Check if the request is allowed under rate limits.
Args:
request: The incoming request.
Returns:
Tuple of (allowed: bool, retry_after: float).
"""
self._cleanup_if_needed()
client_ip = self._get_client_ip(request)
return self.is_allowed(client_ip)
class RateLimitMiddleware(BaseHTTPMiddleware):
"""Middleware to apply rate limiting to specific routes.
Usage:
# Apply to all routes (not recommended for public static files)
app.add_middleware(RateLimitMiddleware)
# Apply only to specific paths
app.add_middleware(
RateLimitMiddleware,
path_prefixes=["/api/matrix/"],
requests_per_minute=30,
)
Attributes:
path_prefixes: List of URL path prefixes to rate limit.
If empty, applies to all paths.
requests_per_minute: Maximum requests per minute per IP.
"""
def __init__(
self,
app,
path_prefixes: list[str] | None = None,
requests_per_minute: int = 30,
):
super().__init__(app)
self.path_prefixes = path_prefixes or []
self.limiter = RateLimiter(requests_per_minute=requests_per_minute)
def _should_rate_limit(self, path: str) -> bool:
"""Check if the given path should be rate limited.
Args:
path: The request URL path.
Returns:
True if path matches any configured prefix.
"""
if not self.path_prefixes:
return True
return any(path.startswith(prefix) for prefix in self.path_prefixes)
async def dispatch(self, request: Request, call_next) -> Response:
"""Apply rate limiting to configured paths.
Args:
request: The incoming request.
call_next: Callable to get the response from downstream.
Returns:
Response from downstream, or 429 if rate limited.
"""
# Skip if path doesn't match configured prefixes
if not self._should_rate_limit(request.url.path):
return await call_next(request)
# Check rate limit
allowed, retry_after = self.limiter.check_request(request)
if not allowed:
return JSONResponse(
status_code=429,
content={
"error": "Rate limit exceeded. Try again later.",
"retry_after": int(retry_after) + 1,
},
headers={"Retry-After": str(int(retry_after) + 1)},
)
# Process the request
return await call_next(request)

View File

@@ -42,114 +42,6 @@ class RequestLoggingMiddleware(BaseHTTPMiddleware):
self.skip_paths = set(skip_paths or [])
self.log_level = log_level
def _should_skip_path(self, path: str) -> bool:
"""Check if the request path should be skipped from logging.
Args:
path: The request URL path.
Returns:
True if the path should be skipped, False otherwise.
"""
return path in self.skip_paths
def _prepare_request_context(self, request: Request) -> tuple[str, float]:
"""Prepare context for request processing.
Generates a correlation ID and records the start time.
Args:
request: The incoming request.
Returns:
Tuple of (correlation_id, start_time).
"""
correlation_id = str(uuid.uuid4())[:8]
request.state.correlation_id = correlation_id
start_time = time.time()
return correlation_id, start_time
def _get_duration_ms(self, start_time: float) -> float:
"""Calculate the request duration in milliseconds.
Args:
start_time: The start time from time.time().
Returns:
Duration in milliseconds.
"""
return (time.time() - start_time) * 1000
def _log_success(
self,
request: Request,
response: Response,
correlation_id: str,
duration_ms: float,
client_ip: str,
user_agent: str,
) -> None:
"""Log a successful request.
Args:
request: The incoming request.
response: The response from downstream.
correlation_id: The request correlation ID.
duration_ms: Request duration in milliseconds.
client_ip: Client IP address.
user_agent: User-Agent header value.
"""
self._log_request(
method=request.method,
path=request.url.path,
status_code=response.status_code,
duration_ms=duration_ms,
client_ip=client_ip,
user_agent=user_agent,
correlation_id=correlation_id,
)
def _log_error(
self,
request: Request,
exc: Exception,
correlation_id: str,
duration_ms: float,
client_ip: str,
) -> None:
"""Log a failed request and capture the error.
Args:
request: The incoming request.
exc: The exception that was raised.
correlation_id: The request correlation ID.
duration_ms: Request duration in milliseconds.
client_ip: Client IP address.
"""
logger.error(
f"[{correlation_id}] {request.method} {request.url.path} "
f"- ERROR - {duration_ms:.2f}ms - {client_ip} - {str(exc)}"
)
# Auto-escalate: create bug report task from unhandled exception
try:
from infrastructure.error_capture import capture_error
capture_error(
exc,
source="http",
context={
"method": request.method,
"path": request.url.path,
"correlation_id": correlation_id,
"client_ip": client_ip,
"duration_ms": f"{duration_ms:.0f}",
},
)
except Exception:
logger.warning("Escalation logging error: capture failed")
# never let escalation break the request
async def dispatch(self, request: Request, call_next) -> Response:
"""Log the request and response details.
@@ -160,23 +52,74 @@ class RequestLoggingMiddleware(BaseHTTPMiddleware):
Returns:
The response from downstream.
"""
if self._should_skip_path(request.url.path):
# Check if we should skip logging this path
if request.url.path in self.skip_paths:
return await call_next(request)
correlation_id, start_time = self._prepare_request_context(request)
# Generate correlation ID
correlation_id = str(uuid.uuid4())[:8]
request.state.correlation_id = correlation_id
# Record start time
start_time = time.time()
# Get client info
client_ip = self._get_client_ip(request)
user_agent = request.headers.get("user-agent", "-")
try:
# Process the request
response = await call_next(request)
duration_ms = self._get_duration_ms(start_time)
self._log_success(request, response, correlation_id, duration_ms, client_ip, user_agent)
# Calculate duration
duration_ms = (time.time() - start_time) * 1000
# Log the request
self._log_request(
method=request.method,
path=request.url.path,
status_code=response.status_code,
duration_ms=duration_ms,
client_ip=client_ip,
user_agent=user_agent,
correlation_id=correlation_id,
)
# Add correlation ID to response headers
response.headers["X-Correlation-ID"] = correlation_id
return response
except Exception as exc:
duration_ms = self._get_duration_ms(start_time)
self._log_error(request, exc, correlation_id, duration_ms, client_ip)
# Calculate duration even for failed requests
duration_ms = (time.time() - start_time) * 1000
# Log the error
logger.error(
f"[{correlation_id}] {request.method} {request.url.path} "
f"- ERROR - {duration_ms:.2f}ms - {client_ip} - {str(exc)}"
)
# Auto-escalate: create bug report task from unhandled exception
try:
from infrastructure.error_capture import capture_error
capture_error(
exc,
source="http",
context={
"method": request.method,
"path": request.url.path,
"correlation_id": correlation_id,
"client_ip": client_ip,
"duration_ms": f"{duration_ms:.0f}",
},
)
except Exception as exc:
logger.debug("Escalation logging error: %s", exc)
pass # never let escalation break the request
# Re-raise the exception
raise
def _get_client_ip(self, request: Request) -> str:

View File

@@ -1,4 +1,4 @@
from datetime import UTC, date, datetime
from datetime import date, datetime
from enum import StrEnum
from sqlalchemy import JSON, Boolean, Column, Date, DateTime, Index, Integer, String
@@ -40,13 +40,8 @@ class Task(Base):
deferred_at = Column(DateTime, nullable=True)
# Timestamps
created_at = Column(DateTime, default=lambda: datetime.now(UTC), nullable=False)
updated_at = Column(
DateTime,
default=lambda: datetime.now(UTC),
onupdate=lambda: datetime.now(UTC),
nullable=False,
)
created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
__table_args__ = (Index("ix_task_state_order", "state", "sort_order"),)
@@ -64,4 +59,4 @@ class JournalEntry(Base):
gratitude = Column(String(500), nullable=True)
energy_level = Column(Integer, nullable=True) # User-reported, 1-10
created_at = Column(DateTime, default=lambda: datetime.now(UTC), nullable=False)
created_at = Column(DateTime, default=datetime.utcnow, nullable=False)

View File

@@ -1,5 +1,5 @@
import logging
from datetime import UTC, date, datetime
from datetime import date, datetime
from fastapi import APIRouter, Depends, Form, HTTPException, Request
from fastapi.responses import HTMLResponse
@@ -19,17 +19,14 @@ router = APIRouter(tags=["calm"])
# Helper functions for state machine logic
def get_now_task(db: Session) -> Task | None:
"""Return the single active NOW task, or None."""
return db.query(Task).filter(Task.state == TaskState.NOW).first()
def get_next_task(db: Session) -> Task | None:
"""Return the single queued NEXT task, or None."""
return db.query(Task).filter(Task.state == TaskState.NEXT).first()
def get_later_tasks(db: Session) -> list[Task]:
"""Return all LATER tasks ordered by MIT flag then sort_order."""
return (
db.query(Task)
.filter(Task.state == TaskState.LATER)
@@ -38,63 +35,7 @@ def get_later_tasks(db: Session) -> list[Task]:
)
def _create_mit_tasks(db: Session, titles: list[str | None]) -> list[int]:
"""Create MIT tasks from a list of titles, return their IDs."""
task_ids: list[int] = []
for title in titles:
if title:
task = Task(
title=title,
is_mit=True,
state=TaskState.LATER,
certainty=TaskCertainty.SOFT,
)
db.add(task)
db.commit()
db.refresh(task)
task_ids.append(task.id)
return task_ids
def _create_other_tasks(db: Session, other_tasks: str):
"""Create non-MIT tasks from newline-separated text."""
for line in other_tasks.split("\n"):
line = line.strip()
if line:
task = Task(
title=line,
state=TaskState.LATER,
certainty=TaskCertainty.FUZZY,
)
db.add(task)
def _seed_now_next(db: Session):
"""Set initial NOW/NEXT states when both slots are empty."""
if get_now_task(db) or get_next_task(db):
return
later_tasks = (
db.query(Task)
.filter(Task.state == TaskState.LATER)
.order_by(Task.is_mit.desc(), Task.sort_order)
.all()
)
if later_tasks:
later_tasks[0].state = TaskState.NOW
db.add(later_tasks[0])
db.flush()
if len(later_tasks) > 1:
later_tasks[1].state = TaskState.NEXT
db.add(later_tasks[1])
def promote_tasks(db: Session):
"""Enforce the NOW/NEXT/LATER state machine invariants.
- At most one NOW task (extras demoted to NEXT).
- If no NOW, promote NEXT -> NOW.
- If no NEXT, promote highest-priority LATER -> NEXT.
"""
# Ensure only one NOW task exists. If multiple, demote extras to NEXT.
now_tasks = db.query(Task).filter(Task.state == TaskState.NOW).all()
if len(now_tasks) > 1:
@@ -133,7 +74,6 @@ def promote_tasks(db: Session):
# Endpoints
@router.get("/calm", response_class=HTMLResponse)
async def get_calm_view(request: Request, db: Session = Depends(get_db)):
"""Render the main CALM dashboard with NOW/NEXT/LATER counts."""
now_task = get_now_task(db)
next_task = get_next_task(db)
later_tasks_count = len(get_later_tasks(db))
@@ -150,7 +90,6 @@ async def get_calm_view(request: Request, db: Session = Depends(get_db)):
@router.get("/calm/ritual/morning", response_class=HTMLResponse)
async def get_morning_ritual_form(request: Request):
"""Render the morning ritual intake form."""
return templates.TemplateResponse(request, "calm/morning_ritual_form.html", {})
@@ -163,20 +102,63 @@ async def post_morning_ritual(
mit3_title: str = Form(None),
other_tasks: str = Form(""),
):
"""Process morning ritual: create MITs, other tasks, and set initial states."""
# Create Journal Entry
mit_task_ids = []
journal_entry = JournalEntry(entry_date=date.today())
db.add(journal_entry)
db.commit()
db.refresh(journal_entry)
journal_entry.mit_task_ids = _create_mit_tasks(db, [mit1_title, mit2_title, mit3_title])
# Create MIT tasks
for mit_title in [mit1_title, mit2_title, mit3_title]:
if mit_title:
task = Task(
title=mit_title,
is_mit=True,
state=TaskState.LATER, # Initially LATER, will be promoted
certainty=TaskCertainty.SOFT,
)
db.add(task)
db.commit()
db.refresh(task)
mit_task_ids.append(task.id)
journal_entry.mit_task_ids = mit_task_ids
db.add(journal_entry)
_create_other_tasks(db, other_tasks)
# Create other tasks
for task_title in other_tasks.split("\n"):
task_title = task_title.strip()
if task_title:
task = Task(
title=task_title,
state=TaskState.LATER,
certainty=TaskCertainty.FUZZY,
)
db.add(task)
db.commit()
_seed_now_next(db)
db.commit()
# Set initial NOW/NEXT states
# Set initial NOW/NEXT states after all tasks are created
if not get_now_task(db) and not get_next_task(db):
later_tasks = (
db.query(Task)
.filter(Task.state == TaskState.LATER)
.order_by(Task.is_mit.desc(), Task.sort_order)
.all()
)
if later_tasks:
# Set the highest priority LATER task to NOW
later_tasks[0].state = TaskState.NOW
db.add(later_tasks[0])
db.flush() # Flush to make the change visible for the next query
# Set the next highest priority LATER task to NEXT
if len(later_tasks) > 1:
later_tasks[1].state = TaskState.NEXT
db.add(later_tasks[1])
db.commit() # Commit changes after initial NOW/NEXT setup
return templates.TemplateResponse(
request,
@@ -191,7 +173,6 @@ async def post_morning_ritual(
@router.get("/calm/ritual/evening", response_class=HTMLResponse)
async def get_evening_ritual_form(request: Request, db: Session = Depends(get_db)):
"""Render the evening ritual form for today's journal entry."""
journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
if not journal_entry:
raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -208,7 +189,6 @@ async def post_evening_ritual(
gratitude: str = Form(None),
energy_level: int = Form(None),
):
"""Process evening ritual: save reflection/gratitude, archive active tasks."""
journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
if not journal_entry:
raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -226,7 +206,7 @@ async def post_evening_ritual(
)
for task in active_tasks:
task.state = TaskState.DEFERRED # Or DONE, depending on desired archiving logic
task.deferred_at = datetime.now(UTC)
task.deferred_at = datetime.utcnow()
db.add(task)
db.commit()
@@ -243,7 +223,6 @@ async def create_new_task(
is_mit: bool = Form(False),
certainty: TaskCertainty = Form(TaskCertainty.SOFT),
):
"""Create a new task in LATER state and return updated count."""
task = Task(
title=title,
description=description,
@@ -268,7 +247,6 @@ async def start_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Move a task to NOW state, demoting the current NOW to NEXT."""
current_now_task = get_now_task(db)
if current_now_task and current_now_task.id != task_id:
current_now_task.state = TaskState.NEXT # Demote current NOW to NEXT
@@ -279,7 +257,7 @@ async def start_task(
raise HTTPException(status_code=404, detail="Task not found")
task.state = TaskState.NOW
task.started_at = datetime.now(UTC)
task.started_at = datetime.utcnow()
db.add(task)
db.commit()
@@ -303,13 +281,12 @@ async def complete_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Mark a task as DONE and trigger state promotion."""
task = db.query(Task).filter(Task.id == task_id).first()
if not task:
raise HTTPException(status_code=404, detail="Task not found")
task.state = TaskState.DONE
task.completed_at = datetime.now(UTC)
task.completed_at = datetime.utcnow()
db.add(task)
db.commit()
@@ -332,13 +309,12 @@ async def defer_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Defer a task and trigger state promotion."""
task = db.query(Task).filter(Task.id == task_id).first()
if not task:
raise HTTPException(status_code=404, detail="Task not found")
task.state = TaskState.DEFERRED
task.deferred_at = datetime.now(UTC)
task.deferred_at = datetime.utcnow()
db.add(task)
db.commit()
@@ -357,7 +333,6 @@ async def defer_task(
@router.get("/calm/partials/later_tasks_list", response_class=HTMLResponse)
async def get_later_tasks_list(request: Request, db: Session = Depends(get_db)):
"""Render the expandable list of LATER tasks."""
later_tasks = get_later_tasks(db)
return templates.TemplateResponse(
"calm/partials/later_tasks_list.html",
@@ -373,7 +348,6 @@ async def reorder_tasks(
later_task_ids: str = Form(""),
next_task_id: int | None = Form(None),
):
"""Reorder LATER tasks and optionally promote one to NEXT."""
# Reorder LATER tasks
if later_task_ids:
ids_in_order = [int(x.strip()) for x in later_task_ids.split(",") if x.strip()]

View File

@@ -1,435 +0,0 @@
"""Daily Run metrics routes — dashboard card for triage and session metrics."""
from __future__ import annotations
import json
import logging
import os
from dataclasses import dataclass
from datetime import UTC, datetime, timedelta
from pathlib import Path
from urllib.error import HTTPError, URLError
from urllib.request import Request as UrlRequest
from urllib.request import urlopen
from fastapi import APIRouter, Request
from fastapi.responses import HTMLResponse, JSONResponse
from config import settings
from dashboard.templating import templates
logger = logging.getLogger(__name__)
router = APIRouter(tags=["daily-run"])
REPO_ROOT = Path(settings.repo_root)
CONFIG_PATH = REPO_ROOT / "timmy_automations" / "config" / "daily_run.json"
DEFAULT_CONFIG = {
"gitea_api": "http://localhost:3000/api/v1",
"repo_slug": "rockachopa/Timmy-time-dashboard",
"token_file": "~/.hermes/gitea_token",
"layer_labels_prefix": "layer:",
}
LAYER_LABELS = ["layer:triage", "layer:micro-fix", "layer:tests", "layer:economy"]
def _load_config() -> dict:
"""Load configuration from config file with fallback to defaults."""
config = DEFAULT_CONFIG.copy()
if CONFIG_PATH.exists():
try:
file_config = json.loads(CONFIG_PATH.read_text())
if "orchestrator" in file_config:
config.update(file_config["orchestrator"])
except (json.JSONDecodeError, OSError) as exc:
logger.debug("Could not load daily_run config: %s", exc)
# Environment variable overrides
if os.environ.get("TIMMY_GITEA_API"):
config["gitea_api"] = os.environ.get("TIMMY_GITEA_API")
if os.environ.get("TIMMY_REPO_SLUG"):
config["repo_slug"] = os.environ.get("TIMMY_REPO_SLUG")
if os.environ.get("TIMMY_GITEA_TOKEN"):
config["token"] = os.environ.get("TIMMY_GITEA_TOKEN")
return config
def _get_token(config: dict) -> str | None:
"""Get Gitea token from environment or file."""
if "token" in config:
return config["token"]
token_file = Path(config["token_file"]).expanduser()
if token_file.exists():
return token_file.read_text().strip()
return None
class GiteaClient:
"""Simple Gitea API client with graceful degradation."""
def __init__(self, config: dict, token: str | None):
self.api_base = config["gitea_api"].rstrip("/")
self.repo_slug = config["repo_slug"]
self.token = token
self._available: bool | None = None
def _headers(self) -> dict:
headers = {"Accept": "application/json"}
if self.token:
headers["Authorization"] = f"token {self.token}"
return headers
def _api_url(self, path: str) -> str:
return f"{self.api_base}/repos/{self.repo_slug}/{path}"
def is_available(self) -> bool:
"""Check if Gitea API is reachable."""
if self._available is not None:
return self._available
try:
req = UrlRequest(
f"{self.api_base}/version",
headers=self._headers(),
method="GET",
)
with urlopen(req, timeout=5) as resp:
self._available = resp.status == 200
return self._available
except (HTTPError, URLError, TimeoutError):
self._available = False
return False
def get_paginated(self, path: str, params: dict | None = None) -> list:
"""Fetch all pages of a paginated endpoint."""
all_items = []
page = 1
limit = 50
while True:
url = self._api_url(path)
query_parts = [f"limit={limit}", f"page={page}"]
if params:
for key, val in params.items():
query_parts.append(f"{key}={val}")
url = f"{url}?{'&'.join(query_parts)}"
req = UrlRequest(url, headers=self._headers(), method="GET")
with urlopen(req, timeout=15) as resp:
batch = json.loads(resp.read())
if not batch:
break
all_items.extend(batch)
if len(batch) < limit:
break
page += 1
return all_items
@dataclass
class LayerMetrics:
"""Metrics for a single layer."""
name: str
label: str
current_count: int
previous_count: int
@property
def trend(self) -> str:
"""Return trend indicator."""
if self.previous_count == 0:
return "" if self.current_count == 0 else ""
diff = self.current_count - self.previous_count
pct = (diff / self.previous_count) * 100
if pct > 20:
return "↑↑"
elif pct > 5:
return ""
elif pct < -20:
return "↓↓"
elif pct < -5:
return ""
return ""
@property
def trend_color(self) -> str:
"""Return color for trend (CSS variable name)."""
trend = self.trend
if trend in ("↑↑", ""):
return "var(--green)" # More work = positive
elif trend in ("↓↓", ""):
return "var(--amber)" # Less work = caution
return "var(--text-dim)"
@dataclass
class DailyRunMetrics:
"""Complete Daily Run metrics."""
sessions_completed: int
sessions_previous: int
layers: list[LayerMetrics]
total_touched_current: int
total_touched_previous: int
lookback_days: int
generated_at: str
@property
def sessions_trend(self) -> str:
"""Return sessions trend indicator."""
if self.sessions_previous == 0:
return "" if self.sessions_completed == 0 else ""
diff = self.sessions_completed - self.sessions_previous
pct = (diff / self.sessions_previous) * 100
if pct > 20:
return "↑↑"
elif pct > 5:
return ""
elif pct < -20:
return "↓↓"
elif pct < -5:
return ""
return ""
@property
def sessions_trend_color(self) -> str:
"""Return color for sessions trend."""
trend = self.sessions_trend
if trend in ("↑↑", ""):
return "var(--green)"
elif trend in ("↓↓", ""):
return "var(--amber)"
return "var(--text-dim)"
def _extract_layer(labels: list[dict]) -> str | None:
"""Extract layer label from issue labels."""
for label in labels:
name = label.get("name", "")
if name.startswith("layer:"):
return name.replace("layer:", "")
return None
def _load_cycle_data(days: int = 14) -> dict:
"""Load cycle retrospective data for session counting."""
retro_file = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
if not retro_file.exists():
return {"current": 0, "previous": 0}
try:
entries = []
for line in retro_file.read_text().strip().splitlines():
try:
entries.append(json.loads(line))
except json.JSONDecodeError:
continue
now = datetime.now(UTC)
current_cutoff = now - timedelta(days=days)
previous_cutoff = now - timedelta(days=days * 2)
current_count = 0
previous_count = 0
for entry in entries:
ts_str = entry.get("timestamp", "")
if not ts_str:
continue
try:
ts = datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
if ts >= current_cutoff:
if entry.get("success", False):
current_count += 1
elif ts >= previous_cutoff:
if entry.get("success", False):
previous_count += 1
except (ValueError, TypeError):
continue
return {"current": current_count, "previous": previous_count}
except (OSError, ValueError) as exc:
logger.debug("Failed to load cycle data: %s", exc)
return {"current": 0, "previous": 0}
def _fetch_layer_metrics(
client: GiteaClient, lookback_days: int = 7
) -> tuple[list[LayerMetrics], int, int]:
"""Fetch metrics for each layer from Gitea issues."""
now = datetime.now(UTC)
current_cutoff = now - timedelta(days=lookback_days)
previous_cutoff = now - timedelta(days=lookback_days * 2)
layers = []
total_current = 0
total_previous = 0
for layer_label in LAYER_LABELS:
layer_name = layer_label.replace("layer:", "")
try:
# Fetch all issues with this layer label (both open and closed)
issues = client.get_paginated(
"issues",
{"state": "all", "labels": layer_label, "limit": 100},
)
current_count = 0
previous_count = 0
for issue in issues:
updated_at = issue.get("updated_at", "")
if not updated_at:
continue
try:
updated = datetime.fromisoformat(updated_at.replace("Z", "+00:00"))
if updated >= current_cutoff:
current_count += 1
elif updated >= previous_cutoff:
previous_count += 1
except (ValueError, TypeError):
continue
layers.append(
LayerMetrics(
name=layer_name,
label=layer_label,
current_count=current_count,
previous_count=previous_count,
)
)
total_current += current_count
total_previous += previous_count
except (HTTPError, URLError) as exc:
logger.debug("Failed to fetch issues for %s: %s", layer_label, exc)
layers.append(
LayerMetrics(
name=layer_name,
label=layer_label,
current_count=0,
previous_count=0,
)
)
return layers, total_current, total_previous
def _get_metrics(lookback_days: int = 7) -> DailyRunMetrics | None:
"""Get Daily Run metrics from Gitea API."""
config = _load_config()
token = _get_token(config)
client = GiteaClient(config, token)
if not client.is_available():
logger.debug("Gitea API not available for Daily Run metrics")
return None
try:
# Get layer metrics from issues
layers, total_current, total_previous = _fetch_layer_metrics(client, lookback_days)
# Get session data from cycle retrospectives
cycle_data = _load_cycle_data(days=lookback_days)
return DailyRunMetrics(
sessions_completed=cycle_data["current"],
sessions_previous=cycle_data["previous"],
layers=layers,
total_touched_current=total_current,
total_touched_previous=total_previous,
lookback_days=lookback_days,
generated_at=datetime.now(UTC).isoformat(),
)
except Exception as exc:
logger.debug("Error fetching Daily Run metrics: %s", exc)
return None
@router.get("/daily-run/metrics", response_class=JSONResponse)
async def daily_run_metrics_api(lookback_days: int = 7):
"""Return Daily Run metrics as JSON API."""
metrics = _get_metrics(lookback_days)
if not metrics:
return JSONResponse(
{"error": "Gitea API unavailable", "status": "unavailable"},
status_code=503,
)
# Check for quest completions based on Daily Run metrics
quest_rewards = []
try:
from dashboard.routes.quests import check_daily_run_quests
quest_rewards = await check_daily_run_quests(agent_id="system")
except Exception as exc:
logger.debug("Quest checking failed: %s", exc)
return JSONResponse(
{
"status": "ok",
"lookback_days": metrics.lookback_days,
"sessions": {
"completed": metrics.sessions_completed,
"previous": metrics.sessions_previous,
"trend": metrics.sessions_trend,
},
"layers": [
{
"name": layer.name,
"label": layer.label,
"current": layer.current_count,
"previous": layer.previous_count,
"trend": layer.trend,
}
for layer in metrics.layers
],
"totals": {
"current": metrics.total_touched_current,
"previous": metrics.total_touched_previous,
},
"generated_at": metrics.generated_at,
"quest_rewards": quest_rewards,
}
)
@router.get("/daily-run/panel", response_class=HTMLResponse)
async def daily_run_panel(request: Request, lookback_days: int = 7):
"""Return Daily Run metrics panel HTML for HTMX polling."""
metrics = _get_metrics(lookback_days)
# Build Gitea URLs for filtered issue lists
config = _load_config()
repo_slug = config.get("repo_slug", "rockachopa/Timmy-time-dashboard")
gitea_base = config.get("gitea_api", "http://localhost:3000/api/v1").replace("/api/v1", "")
# Logbook URL (link to issues with any layer label)
layer_labels = ",".join(LAYER_LABELS)
logbook_url = f"{gitea_base}/{repo_slug}/issues?labels={layer_labels}&state=all"
# Layer-specific URLs
layer_urls = {
layer: f"{gitea_base}/{repo_slug}/issues?labels=layer:{layer}&state=all"
for layer in ["triage", "micro-fix", "tests", "economy"]
}
return templates.TemplateResponse(
request,
"partials/daily_run_panel.html",
{
"metrics": metrics,
"logbook_url": logbook_url,
"layer_urls": layer_urls,
"gitea_available": metrics is not None,
},
)

View File

@@ -75,7 +75,6 @@ def _query_database(db_path: str) -> dict:
"truncated": count > MAX_ROWS,
}
except Exception as exc:
logger.exception("Failed to query table %s", table_name)
result["tables"][table_name] = {
"error": str(exc),
"columns": [],
@@ -84,7 +83,6 @@ def _query_database(db_path: str) -> dict:
"truncated": False,
}
except Exception as exc:
logger.exception("Failed to query database %s", db_path)
result["error"] = str(exc)
return result

View File

@@ -135,7 +135,6 @@ def _run_grok_query(message: str) -> dict:
result = backend.run(message)
return {"response": f"**[Grok]{invoice_note}:** {result.content}", "error": None}
except Exception as exc:
logger.exception("Grok query failed")
return {"response": None, "error": f"Grok error: {exc}"}
@@ -194,7 +193,6 @@ async def grok_stats():
"model": settings.grok_default_model,
}
except Exception as exc:
logger.exception("Failed to load Grok stats")
return {"error": str(exc)}

View File

@@ -148,7 +148,6 @@ def _check_sqlite() -> DependencyStatus:
details={"path": str(db_path)},
)
except Exception as exc:
logger.exception("SQLite health check failed")
return DependencyStatus(
name="SQLite Database",
status="unavailable",
@@ -275,54 +274,3 @@ async def component_status():
},
"timestamp": datetime.now(UTC).isoformat(),
}
@router.get("/health/snapshot")
async def health_snapshot():
"""Quick health snapshot before coding.
Returns a concise status summary including:
- CI pipeline status (pass/fail/unknown)
- Critical issues count (P0/P1)
- Test flakiness rate
- Token economy temperature
Fast execution (< 5 seconds) for pre-work checks.
Refs: #710
"""
import sys
from pathlib import Path
# Import the health snapshot module
snapshot_path = Path(settings.repo_root) / "timmy_automations" / "daily_run"
if str(snapshot_path) not in sys.path:
sys.path.insert(0, str(snapshot_path))
try:
from health_snapshot import generate_snapshot, get_token, load_config
config = load_config()
token = get_token(config)
# Run the health snapshot (in thread to avoid blocking)
snapshot = await asyncio.to_thread(generate_snapshot, config, token)
return snapshot.to_dict()
except Exception as exc:
logger.warning("Health snapshot failed: %s", exc)
# Return graceful fallback
return {
"timestamp": datetime.now(UTC).isoformat(),
"overall_status": "unknown",
"error": str(exc),
"ci": {"status": "unknown", "message": "Snapshot failed"},
"issues": {"count": 0, "p0_count": 0, "p1_count": 0, "issues": []},
"flakiness": {
"status": "unknown",
"recent_failures": 0,
"recent_cycles": 0,
"failure_rate": 0.0,
"message": "Snapshot failed",
},
"tokens": {"status": "unknown", "message": "Snapshot failed"},
}

View File

@@ -1,377 +0,0 @@
"""Quest system routes for agent token rewards.
Provides API endpoints for:
- Listing quests and their status
- Claiming quest rewards
- Getting quest leaderboard
- Quest progress tracking
"""
from __future__ import annotations
import logging
from typing import Any
from fastapi import APIRouter, Request
from fastapi.responses import HTMLResponse, JSONResponse
from pydantic import BaseModel
from dashboard.templating import templates
from timmy.quest_system import (
QuestStatus,
auto_evaluate_all_quests,
claim_quest_reward,
evaluate_quest_progress,
get_active_quests,
get_agent_quests_status,
get_quest_definition,
get_quest_leaderboard,
load_quest_config,
)
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/quests", tags=["quests"])
class ClaimQuestRequest(BaseModel):
"""Request to claim a quest reward."""
agent_id: str
quest_id: str
class EvaluateQuestRequest(BaseModel):
"""Request to manually evaluate quest progress."""
agent_id: str
quest_id: str
# ---------------------------------------------------------------------------
# API Endpoints
# ---------------------------------------------------------------------------
@router.get("/api/definitions")
async def get_quest_definitions_api() -> JSONResponse:
"""Get all quest definitions.
Returns:
JSON list of all quest definitions with their criteria.
"""
definitions = get_active_quests()
return JSONResponse(
{
"quests": [
{
"id": q.id,
"name": q.name,
"description": q.description,
"reward_tokens": q.reward_tokens,
"type": q.quest_type.value,
"repeatable": q.repeatable,
"cooldown_hours": q.cooldown_hours,
"criteria": q.criteria,
}
for q in definitions
]
}
)
@router.get("/api/status/{agent_id}")
async def get_agent_quest_status(agent_id: str) -> JSONResponse:
"""Get quest status for a specific agent.
Returns:
Complete quest status including progress, completion counts,
and tokens earned.
"""
status = get_agent_quests_status(agent_id)
return JSONResponse(status)
@router.post("/api/claim")
async def claim_quest_reward_api(request: ClaimQuestRequest) -> JSONResponse:
"""Claim a quest reward for an agent.
The quest must be completed but not yet claimed.
"""
reward = claim_quest_reward(request.quest_id, request.agent_id)
if not reward:
return JSONResponse(
{
"success": False,
"error": "Quest not completed, already claimed, or on cooldown",
},
status_code=400,
)
return JSONResponse(
{
"success": True,
"reward": reward,
}
)
@router.post("/api/evaluate")
async def evaluate_quest_api(request: EvaluateQuestRequest) -> JSONResponse:
"""Manually evaluate quest progress with provided context.
This is useful for testing or when the quest completion
needs to be triggered manually.
"""
quest = get_quest_definition(request.quest_id)
if not quest:
return JSONResponse(
{"success": False, "error": "Quest not found"},
status_code=404,
)
# Build evaluation context based on quest type
context = await _build_evaluation_context(quest)
progress = evaluate_quest_progress(request.quest_id, request.agent_id, context)
if not progress:
return JSONResponse(
{"success": False, "error": "Failed to evaluate quest"},
status_code=500,
)
# Auto-claim if completed
reward = None
if progress.status == QuestStatus.COMPLETED:
reward = claim_quest_reward(request.quest_id, request.agent_id)
return JSONResponse(
{
"success": True,
"progress": progress.to_dict(),
"reward": reward,
"completed": progress.status == QuestStatus.COMPLETED,
}
)
@router.get("/api/leaderboard")
async def get_leaderboard_api() -> JSONResponse:
"""Get the quest completion leaderboard.
Returns agents sorted by total tokens earned.
"""
leaderboard = get_quest_leaderboard()
return JSONResponse(
{
"leaderboard": leaderboard,
}
)
@router.post("/api/reload")
async def reload_quest_config_api() -> JSONResponse:
"""Reload quest configuration from quests.yaml.
Useful for applying quest changes without restarting.
"""
definitions, quest_settings = load_quest_config()
return JSONResponse(
{
"success": True,
"quests_loaded": len(definitions),
"settings": quest_settings,
}
)
# ---------------------------------------------------------------------------
# Dashboard UI Endpoints
# ---------------------------------------------------------------------------
@router.get("", response_class=HTMLResponse)
async def quests_dashboard(request: Request) -> HTMLResponse:
"""Main quests dashboard page."""
return templates.TemplateResponse(
request,
"quests.html",
{"agent_id": "current_user"},
)
@router.get("/panel/{agent_id}", response_class=HTMLResponse)
async def quests_panel(request: Request, agent_id: str) -> HTMLResponse:
"""Quest panel for HTMX partial updates."""
status = get_agent_quests_status(agent_id)
return templates.TemplateResponse(
request,
"partials/quests_panel.html",
{
"agent_id": agent_id,
"quests": status["quests"],
"total_tokens": status["total_tokens_earned"],
"completed_count": status["total_quests_completed"],
},
)
# ---------------------------------------------------------------------------
# Internal Functions
# ---------------------------------------------------------------------------
async def _build_evaluation_context(quest) -> dict[str, Any]:
"""Build evaluation context for a quest based on its type."""
context: dict[str, Any] = {}
if quest.quest_type.value == "issue_count":
# Fetch closed issues with relevant labels
context["closed_issues"] = await _fetch_closed_issues(
quest.criteria.get("issue_labels", [])
)
elif quest.quest_type.value == "issue_reduce":
# Fetch current and previous issue counts
labels = quest.criteria.get("issue_labels", [])
context["current_issue_count"] = await _fetch_open_issue_count(labels)
context["previous_issue_count"] = await _fetch_previous_issue_count(
labels, quest.criteria.get("lookback_days", 7)
)
elif quest.quest_type.value == "daily_run":
# Fetch Daily Run metrics
metrics = await _fetch_daily_run_metrics()
context["sessions_completed"] = metrics.get("sessions_completed", 0)
return context
async def _fetch_closed_issues(labels: list[str]) -> list[dict]:
"""Fetch closed issues matching the given labels."""
try:
from dashboard.routes.daily_run import GiteaClient, _load_config
config = _load_config()
token = _get_gitea_token(config)
client = GiteaClient(config, token)
if not client.is_available():
return []
# Build label filter
label_filter = ",".join(labels) if labels else ""
issues = client.get_paginated(
"issues",
{"state": "closed", "labels": label_filter, "limit": 100},
)
return issues
except Exception as exc:
logger.debug("Failed to fetch closed issues: %s", exc)
return []
async def _fetch_open_issue_count(labels: list[str]) -> int:
"""Fetch count of open issues with given labels."""
try:
from dashboard.routes.daily_run import GiteaClient, _load_config
config = _load_config()
token = _get_gitea_token(config)
client = GiteaClient(config, token)
if not client.is_available():
return 0
label_filter = ",".join(labels) if labels else ""
issues = client.get_paginated(
"issues",
{"state": "open", "labels": label_filter, "limit": 100},
)
return len(issues)
except Exception as exc:
logger.debug("Failed to fetch open issue count: %s", exc)
return 0
async def _fetch_previous_issue_count(labels: list[str], lookback_days: int) -> int:
"""Fetch previous issue count (simplified - uses current for now)."""
# This is a simplified implementation
# In production, you'd query historical data
return await _fetch_open_issue_count(labels)
async def _fetch_daily_run_metrics() -> dict[str, Any]:
"""Fetch Daily Run metrics."""
try:
from dashboard.routes.daily_run import _get_metrics
metrics = _get_metrics(lookback_days=7)
if metrics:
return {
"sessions_completed": metrics.sessions_completed,
"sessions_previous": metrics.sessions_previous,
}
except Exception as exc:
logger.debug("Failed to fetch Daily Run metrics: %s", exc)
return {"sessions_completed": 0, "sessions_previous": 0}
def _get_gitea_token(config: dict) -> str | None:
"""Get Gitea token from config."""
if "token" in config:
return config["token"]
from pathlib import Path
token_file = Path(config.get("token_file", "~/.hermes/gitea_token")).expanduser()
if token_file.exists():
return token_file.read_text().strip()
return None
# ---------------------------------------------------------------------------
# Daily Run Integration
# ---------------------------------------------------------------------------
async def check_daily_run_quests(agent_id: str = "system") -> list[dict]:
"""Check and award Daily Run related quests.
Called by the Daily Run system when metrics are updated.
Returns:
List of rewards awarded
"""
# Check if auto-detect is enabled
_, quest_settings = load_quest_config()
if not quest_settings.get("auto_detect_on_daily_run", True):
return []
# Build context from Daily Run metrics
metrics = await _fetch_daily_run_metrics()
context = {
"sessions_completed": metrics.get("sessions_completed", 0),
"sessions_previous": metrics.get("sessions_previous", 0),
}
# Add closed issues for issue_count quests
active_quests = get_active_quests()
for quest in active_quests:
if quest.quest_type.value == "issue_count":
labels = quest.criteria.get("issue_labels", [])
context["closed_issues"] = await _fetch_closed_issues(labels)
break # Only need to fetch once
# Evaluate all quests
rewards = auto_evaluate_all_quests(agent_id, context)
return rewards

View File

@@ -1,353 +0,0 @@
"""Agent scorecard routes — API endpoints for generating and viewing scorecards."""
from __future__ import annotations
import logging
from datetime import datetime
from fastapi import APIRouter, Query, Request
from fastapi.responses import HTMLResponse, JSONResponse
from dashboard.services.scorecard_service import (
PeriodType,
generate_all_scorecards,
generate_scorecard,
get_tracked_agents,
)
from dashboard.templating import templates
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/scorecards", tags=["scorecards"])
def _format_period_label(period_type: PeriodType) -> str:
"""Format a period type for display."""
return "Daily" if period_type == PeriodType.daily else "Weekly"
@router.get("/api/agents")
async def list_tracked_agents() -> dict[str, list[str]]:
"""Return the list of tracked agent IDs.
Returns:
Dict with "agents" key containing list of agent IDs
"""
return {"agents": get_tracked_agents()}
@router.get("/api/{agent_id}")
async def get_agent_scorecard(
agent_id: str,
period: str = Query(default="daily", description="Period type: 'daily' or 'weekly'"),
) -> JSONResponse:
"""Generate a scorecard for a specific agent.
Args:
agent_id: The agent ID (e.g., 'kimi', 'claude')
period: 'daily' or 'weekly' (default: daily)
Returns:
JSON response with scorecard data
"""
try:
period_type = PeriodType(period.lower())
except ValueError:
return JSONResponse(
status_code=400,
content={"error": f"Invalid period '{period}'. Use 'daily' or 'weekly'."},
)
try:
scorecard = generate_scorecard(agent_id, period_type)
if scorecard is None:
return JSONResponse(
status_code=404,
content={"error": f"No scorecard found for agent '{agent_id}'"},
)
return JSONResponse(content=scorecard.to_dict())
except Exception as exc:
logger.error("Failed to generate scorecard for %s: %s", agent_id, exc)
return JSONResponse(
status_code=500,
content={"error": f"Failed to generate scorecard: {str(exc)}"},
)
@router.get("/api")
async def get_all_scorecards(
period: str = Query(default="daily", description="Period type: 'daily' or 'weekly'"),
) -> JSONResponse:
"""Generate scorecards for all tracked agents.
Args:
period: 'daily' or 'weekly' (default: daily)
Returns:
JSON response with list of scorecard data
"""
try:
period_type = PeriodType(period.lower())
except ValueError:
return JSONResponse(
status_code=400,
content={"error": f"Invalid period '{period}'. Use 'daily' or 'weekly'."},
)
try:
scorecards = generate_all_scorecards(period_type)
return JSONResponse(
content={
"period": period_type.value,
"scorecards": [s.to_dict() for s in scorecards],
"count": len(scorecards),
}
)
except Exception as exc:
logger.error("Failed to generate scorecards: %s", exc)
return JSONResponse(
status_code=500,
content={"error": f"Failed to generate scorecards: {str(exc)}"},
)
@router.get("", response_class=HTMLResponse)
async def scorecards_page(request: Request) -> HTMLResponse:
"""Render the scorecards dashboard page.
Returns:
HTML page with scorecard interface
"""
agents = get_tracked_agents()
return templates.TemplateResponse(
request,
"scorecards.html",
{
"agents": agents,
"periods": ["daily", "weekly"],
},
)
@router.get("/panel/{agent_id}", response_class=HTMLResponse)
async def agent_scorecard_panel(
request: Request,
agent_id: str,
period: str = Query(default="daily"),
) -> HTMLResponse:
"""Render an individual agent scorecard panel (for HTMX).
Args:
request: The request object
agent_id: The agent ID
period: 'daily' or 'weekly'
Returns:
HTML panel with scorecard content
"""
try:
period_type = PeriodType(period.lower())
except ValueError:
period_type = PeriodType.daily
try:
scorecard = generate_scorecard(agent_id, period_type)
if scorecard is None:
return HTMLResponse(
content=f"""
<div class="card mc-panel">
<h5 class="card-title">{agent_id.title()}</h5>
<p class="text-muted">No activity recorded for this period.</p>
</div>
""",
status_code=200,
)
data = scorecard.to_dict()
# Build patterns HTML
patterns_html = ""
if data["patterns"]:
patterns_list = "".join([f"<li>{p}</li>" for p in data["patterns"]])
patterns_html = f"""
<div class="mt-3">
<h6>Patterns</h6>
<ul class="list-unstyled text-info">
{patterns_list}
</ul>
</div>
"""
# Build bullets HTML
bullets_html = "".join([f"<li>{b}</li>" for b in data["narrative_bullets"]])
# Build metrics summary
metrics = data["metrics"]
html_content = f"""
<div class="card mc-panel">
<div class="card-header d-flex justify-content-between align-items-center">
<h5 class="card-title mb-0">{agent_id.title()}</h5>
<span class="badge bg-secondary">{_format_period_label(period_type)}</span>
</div>
<div class="card-body">
<ul class="list-unstyled mb-3">
{bullets_html}
</ul>
<div class="row text-center small">
<div class="col">
<div class="text-muted">PRs</div>
<div class="fw-bold">{metrics["prs_opened"]}/{metrics["prs_merged"]}</div>
<div class="text-muted" style="font-size: 0.75rem;">
{int(metrics["pr_merge_rate"] * 100)}% merged
</div>
</div>
<div class="col">
<div class="text-muted">Issues</div>
<div class="fw-bold">{metrics["issues_touched"]}</div>
</div>
<div class="col">
<div class="text-muted">Tests</div>
<div class="fw-bold">{metrics["tests_affected"]}</div>
</div>
<div class="col">
<div class="text-muted">Tokens</div>
<div class="fw-bold {"text-success" if metrics["token_net"] >= 0 else "text-danger"}">
{"+" if metrics["token_net"] > 0 else ""}{metrics["token_net"]}
</div>
</div>
</div>
{patterns_html}
</div>
</div>
"""
return HTMLResponse(content=html_content)
except Exception as exc:
logger.error("Failed to render scorecard panel for %s: %s", agent_id, exc)
return HTMLResponse(
content=f"""
<div class="card mc-panel border-danger">
<h5 class="card-title">{agent_id.title()}</h5>
<p class="text-danger">Error loading scorecard: {str(exc)}</p>
</div>
""",
status_code=200,
)
@router.get("/all/panels", response_class=HTMLResponse)
async def all_scorecard_panels(
request: Request,
period: str = Query(default="daily"),
) -> HTMLResponse:
"""Render all agent scorecard panels (for HTMX).
Args:
request: The request object
period: 'daily' or 'weekly'
Returns:
HTML with all scorecard panels
"""
try:
period_type = PeriodType(period.lower())
except ValueError:
period_type = PeriodType.daily
try:
scorecards = generate_all_scorecards(period_type)
panels: list[str] = []
for scorecard in scorecards:
data = scorecard.to_dict()
# Build patterns HTML
patterns_html = ""
if data["patterns"]:
patterns_list = "".join([f"<li>{p}</li>" for p in data["patterns"]])
patterns_html = f"""
<div class="mt-3">
<h6>Patterns</h6>
<ul class="list-unstyled text-info">
{patterns_list}
</ul>
</div>
"""
# Build bullets HTML
bullets_html = "".join([f"<li>{b}</li>" for b in data["narrative_bullets"]])
metrics = data["metrics"]
panel_html = f"""
<div class="col-md-6 col-lg-4 mb-3">
<div class="card mc-panel">
<div class="card-header d-flex justify-content-between align-items-center">
<h5 class="card-title mb-0">{scorecard.agent_id.title()}</h5>
<span class="badge bg-secondary">{_format_period_label(period_type)}</span>
</div>
<div class="card-body">
<ul class="list-unstyled mb-3">
{bullets_html}
</ul>
<div class="row text-center small">
<div class="col">
<div class="text-muted">PRs</div>
<div class="fw-bold">{metrics["prs_opened"]}/{metrics["prs_merged"]}</div>
<div class="text-muted" style="font-size: 0.75rem;">
{int(metrics["pr_merge_rate"] * 100)}% merged
</div>
</div>
<div class="col">
<div class="text-muted">Issues</div>
<div class="fw-bold">{metrics["issues_touched"]}</div>
</div>
<div class="col">
<div class="text-muted">Tests</div>
<div class="fw-bold">{metrics["tests_affected"]}</div>
</div>
<div class="col">
<div class="text-muted">Tokens</div>
<div class="fw-bold {"text-success" if metrics["token_net"] >= 0 else "text-danger"}">
{"+" if metrics["token_net"] > 0 else ""}{metrics["token_net"]}
</div>
</div>
</div>
{patterns_html}
</div>
</div>
</div>
"""
panels.append(panel_html)
html_content = f"""
<div class="row">
{"".join(panels)}
</div>
<div class="text-muted small mt-2">
Generated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S UTC")}
</div>
"""
return HTMLResponse(content=html_content)
except Exception as exc:
logger.error("Failed to render all scorecard panels: %s", exc)
return HTMLResponse(
content=f"""
<div class="alert alert-danger">
Error loading scorecards: {str(exc)}
</div>
""",
status_code=200,
)

View File

@@ -16,11 +16,52 @@ router = APIRouter(tags=["system"])
@router.get("/lightning/ledger", response_class=HTMLResponse)
async def lightning_ledger(request: Request):
"""Ledger and balance page backed by the in-memory Lightning ledger."""
from lightning.ledger import get_balance, get_transactions
"""Ledger and balance page."""
# Mock data for now, as this seems to be a UI-first feature
balance = {
"available_sats": 1337,
"incoming_total_sats": 2000,
"outgoing_total_sats": 663,
"fees_paid_sats": 5,
"net_sats": 1337,
"pending_incoming_sats": 0,
"pending_outgoing_sats": 0,
}
balance = get_balance()
transactions = get_transactions()
# Mock transactions
from collections import namedtuple
from enum import Enum
class TxType(Enum):
incoming = "incoming"
outgoing = "outgoing"
class TxStatus(Enum):
completed = "completed"
pending = "pending"
Tx = namedtuple(
"Tx", ["tx_type", "status", "amount_sats", "payment_hash", "memo", "created_at"]
)
transactions = [
Tx(
TxType.outgoing,
TxStatus.completed,
50,
"hash1",
"Model inference",
"2026-03-04 10:00:00",
),
Tx(
TxType.incoming,
TxStatus.completed,
1000,
"hash2",
"Manual deposit",
"2026-03-03 15:00:00",
),
]
return templates.TemplateResponse(
request,
@@ -29,7 +70,7 @@ async def lightning_ledger(request: Request):
"balance": balance,
"transactions": transactions,
"tx_types": ["incoming", "outgoing"],
"tx_statuses": ["pending", "settled", "failed", "expired"],
"tx_statuses": ["completed", "pending"],
"filter_type": None,
"filter_status": None,
"stats": {},

View File

@@ -5,7 +5,7 @@ import sqlite3
import uuid
from collections.abc import Generator
from contextlib import closing, contextmanager
from datetime import UTC, datetime
from datetime import datetime
from pathlib import Path
from fastapi import APIRouter, Form, HTTPException, Request
@@ -219,7 +219,7 @@ async def create_task_form(
raise HTTPException(status_code=400, detail="Task title cannot be empty")
task_id = str(uuid.uuid4())
now = datetime.now(UTC).isoformat()
now = datetime.utcnow().isoformat()
priority = priority if priority in VALID_PRIORITIES else "normal"
with _get_db() as db:
@@ -287,7 +287,7 @@ async def modify_task(
async def _set_status(request: Request, task_id: str, new_status: str):
"""Helper to update status and return refreshed task card."""
completed_at = (
datetime.now(UTC).isoformat() if new_status in ("completed", "vetoed", "failed") else None
datetime.utcnow().isoformat() if new_status in ("completed", "vetoed", "failed") else None
)
with _get_db() as db:
db.execute(
@@ -316,7 +316,7 @@ async def api_create_task(request: Request):
raise HTTPException(422, "title is required")
task_id = str(uuid.uuid4())
now = datetime.now(UTC).isoformat()
now = datetime.utcnow().isoformat()
priority = body.get("priority", "normal")
if priority not in VALID_PRIORITIES:
priority = "normal"
@@ -358,7 +358,7 @@ async def api_update_status(task_id: str, request: Request):
raise HTTPException(422, f"Invalid status. Must be one of: {VALID_STATUSES}")
completed_at = (
datetime.now(UTC).isoformat() if new_status in ("completed", "vetoed", "failed") else None
datetime.utcnow().isoformat() if new_status in ("completed", "vetoed", "failed") else None
)
with _get_db() as db:
db.execute(

View File

@@ -1,108 +0,0 @@
"""Tower dashboard — real-time Spark visualization via WebSocket.
GET /tower — HTML Tower dashboard (Thinking / Predicting / Advising)
WS /tower/ws — WebSocket stream of Spark engine state updates
"""
import asyncio
import json
import logging
from fastapi import APIRouter, Request, WebSocket
from fastapi.responses import HTMLResponse
from dashboard.templating import templates
from spark.engine import spark_engine
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/tower", tags=["tower"])
_PUSH_INTERVAL = 5 # seconds between state broadcasts
def _spark_snapshot() -> dict:
"""Build a JSON-serialisable snapshot of Spark state."""
status = spark_engine.status()
timeline = spark_engine.get_timeline(limit=10)
events = []
for ev in timeline:
entry = {
"event_type": ev.event_type,
"description": ev.description,
"importance": ev.importance,
"created_at": ev.created_at,
}
if ev.agent_id:
entry["agent_id"] = ev.agent_id[:8]
if ev.task_id:
entry["task_id"] = ev.task_id[:8]
try:
entry["data"] = json.loads(ev.data)
except (json.JSONDecodeError, TypeError):
entry["data"] = {}
events.append(entry)
predictions = spark_engine.get_predictions(limit=5)
preds = []
for p in predictions:
pred = {
"task_id": p.task_id[:8] if p.task_id else "?",
"accuracy": p.accuracy,
"evaluated": p.evaluated_at is not None,
"created_at": p.created_at,
}
try:
pred["predicted"] = json.loads(p.predicted_value)
except (json.JSONDecodeError, TypeError):
pred["predicted"] = {}
preds.append(pred)
advisories = spark_engine.get_advisories()
advs = [
{
"category": a.category,
"priority": a.priority,
"title": a.title,
"detail": a.detail,
"suggested_action": a.suggested_action,
}
for a in advisories
]
return {
"type": "spark_state",
"status": status,
"events": events,
"predictions": preds,
"advisories": advs,
}
@router.get("", response_class=HTMLResponse)
async def tower_ui(request: Request):
"""Render the Tower dashboard page."""
snapshot = _spark_snapshot()
return templates.TemplateResponse(
request,
"tower.html",
{"snapshot": snapshot},
)
@router.websocket("/ws")
async def tower_ws(websocket: WebSocket) -> None:
"""Stream Spark state snapshots to the Tower dashboard."""
await websocket.accept()
logger.info("Tower WS connected")
try:
# Send initial snapshot
await websocket.send_text(json.dumps(_spark_snapshot()))
while True:
await asyncio.sleep(_PUSH_INTERVAL)
await websocket.send_text(json.dumps(_spark_snapshot()))
except Exception:
logger.debug("Tower WS disconnected")

View File

@@ -59,7 +59,6 @@ async def tts_speak(text: str = Form(...)):
voice_tts.speak(text)
return {"spoken": True, "text": text}
except Exception as exc:
logger.exception("TTS speak failed")
return {"spoken": False, "reason": str(exc)}

View File

@@ -5,7 +5,7 @@ import sqlite3
import uuid
from collections.abc import Generator
from contextlib import closing, contextmanager
from datetime import UTC, datetime
from datetime import datetime
from pathlib import Path
from fastapi import APIRouter, Form, HTTPException, Request
@@ -144,7 +144,7 @@ async def submit_work_order(
related_files: str = Form(""),
):
wo_id = str(uuid.uuid4())
now = datetime.now(UTC).isoformat()
now = datetime.utcnow().isoformat()
priority = priority if priority in PRIORITIES else "medium"
category = category if category in CATEGORIES else "suggestion"
@@ -211,7 +211,7 @@ async def active_partial(request: Request):
async def _update_status(request: Request, wo_id: str, new_status: str, **extra):
completed_at = (
datetime.now(UTC).isoformat() if new_status in ("completed", "rejected") else None
datetime.utcnow().isoformat() if new_status in ("completed", "rejected") else None
)
with _get_db() as db:
sets = ["status=?", "completed_at=COALESCE(?, completed_at)"]

View File

@@ -17,221 +17,16 @@ or missing.
import asyncio
import json
import logging
import math
import re
import time
from collections import deque
from datetime import UTC, datetime
from pathlib import Path
from typing import Any
import yaml
from fastapi import APIRouter, Request, WebSocket
from fastapi import APIRouter, WebSocket
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from config import settings
from infrastructure.presence import produce_bark, serialize_presence
from timmy.memory_system import search_memories
from timmy.workshop_state import PRESENCE_FILE
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/world", tags=["world"])
matrix_router = APIRouter(prefix="/api/matrix", tags=["matrix"])
# ---------------------------------------------------------------------------
# Matrix Bark Endpoint — HTTP fallback for bark messages
# ---------------------------------------------------------------------------
# Rate limiting: 1 request per 3 seconds per visitor_id
_BARK_RATE_LIMIT_SECONDS = 3
_bark_last_request: dict[str, float] = {}
class BarkRequest(BaseModel):
"""Request body for POST /api/matrix/bark."""
text: str
visitor_id: str
@matrix_router.post("/bark")
async def post_matrix_bark(request: BarkRequest) -> JSONResponse:
"""Generate a bark response for a visitor message.
HTTP fallback for when WebSocket isn't available. The Matrix frontend
can POST a message and get Timmy's bark response back as JSON.
Rate limited to 1 request per 3 seconds per visitor_id.
Request body:
- text: The visitor's message text
- visitor_id: Unique identifier for the visitor (used for rate limiting)
Returns:
- 200: Bark message in produce_bark() format
- 429: Rate limit exceeded (try again later)
- 422: Invalid request (missing/invalid fields)
"""
# Validate inputs
text = request.text.strip() if request.text else ""
visitor_id = request.visitor_id.strip() if request.visitor_id else ""
if not text:
return JSONResponse(
status_code=422,
content={"error": "text is required"},
)
if not visitor_id:
return JSONResponse(
status_code=422,
content={"error": "visitor_id is required"},
)
# Rate limiting check
now = time.time()
last_request = _bark_last_request.get(visitor_id, 0)
time_since_last = now - last_request
if time_since_last < _BARK_RATE_LIMIT_SECONDS:
retry_after = _BARK_RATE_LIMIT_SECONDS - time_since_last
return JSONResponse(
status_code=429,
content={"error": "Rate limit exceeded. Try again later."},
headers={"Retry-After": str(int(retry_after) + 1)},
)
# Record this request
_bark_last_request[visitor_id] = now
# Generate bark response
try:
reply = await _generate_bark(text)
except Exception as exc:
logger.warning("Bark generation failed: %s", exc)
reply = "Hmm, my thoughts are a bit tangled right now."
# Build bark response using produce_bark format
bark = produce_bark(agent_id="timmy", text=reply, style="speech")
return JSONResponse(
content=bark,
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# Matrix Agent Registry — serves agents to the Matrix visualization
# ---------------------------------------------------------------------------
# Agent color mapping — consistent with Matrix visual identity
_AGENT_COLORS: dict[str, str] = {
"timmy": "#FFD700", # Gold
"orchestrator": "#FFD700", # Gold
"perplexity": "#3B82F6", # Blue
"replit": "#F97316", # Orange
"kimi": "#06B6D4", # Cyan
"claude": "#A855F7", # Purple
"researcher": "#10B981", # Emerald
"coder": "#EF4444", # Red
"writer": "#EC4899", # Pink
"memory": "#8B5CF6", # Violet
"experimenter": "#14B8A6", # Teal
"forge": "#EF4444", # Red (coder alias)
"seer": "#10B981", # Emerald (researcher alias)
"quill": "#EC4899", # Pink (writer alias)
"echo": "#8B5CF6", # Violet (memory alias)
"lab": "#14B8A6", # Teal (experimenter alias)
}
# Agent shape mapping for 3D visualization
_AGENT_SHAPES: dict[str, str] = {
"timmy": "sphere",
"orchestrator": "sphere",
"perplexity": "cube",
"replit": "cylinder",
"kimi": "dodecahedron",
"claude": "octahedron",
"researcher": "icosahedron",
"coder": "cube",
"writer": "cone",
"memory": "torus",
"experimenter": "tetrahedron",
"forge": "cube",
"seer": "icosahedron",
"quill": "cone",
"echo": "torus",
"lab": "tetrahedron",
}
# Default fallback values
_DEFAULT_COLOR = "#9CA3AF" # Gray
_DEFAULT_SHAPE = "sphere"
_DEFAULT_STATUS = "available"
def _get_agent_color(agent_id: str) -> str:
"""Get the Matrix color for an agent."""
return _AGENT_COLORS.get(agent_id.lower(), _DEFAULT_COLOR)
def _get_agent_shape(agent_id: str) -> str:
"""Get the Matrix shape for an agent."""
return _AGENT_SHAPES.get(agent_id.lower(), _DEFAULT_SHAPE)
def _compute_circular_positions(count: int, radius: float = 3.0) -> list[dict[str, float]]:
"""Compute circular positions for agents in the Matrix.
Agents are arranged in a circle on the XZ plane at y=0.
"""
positions = []
for i in range(count):
angle = (2 * math.pi * i) / count
x = radius * math.cos(angle)
z = radius * math.sin(angle)
positions.append({"x": round(x, 2), "y": 0.0, "z": round(z, 2)})
return positions
def _build_matrix_agents_response() -> list[dict[str, Any]]:
"""Build the Matrix agent registry response.
Reads from agents.yaml and returns agents with Matrix-compatible
formatting including colors, shapes, and positions.
"""
try:
from timmy.agents.loader import list_agents
agents = list_agents()
if not agents:
return []
positions = _compute_circular_positions(len(agents))
result = []
for i, agent in enumerate(agents):
agent_id = agent.get("id", "")
result.append(
{
"id": agent_id,
"display_name": agent.get("name", agent_id.title()),
"role": agent.get("role", "general"),
"color": _get_agent_color(agent_id),
"position": positions[i],
"shape": _get_agent_shape(agent_id),
"status": agent.get("status", _DEFAULT_STATUS),
}
)
return result
except Exception as exc:
logger.warning("Failed to load agents for Matrix: %s", exc)
return []
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/world", tags=["world"])
@@ -354,7 +149,21 @@ def _read_presence_file() -> dict | None:
def _build_world_state(presence: dict) -> dict:
"""Transform presence dict into the world/state API response."""
return serialize_presence(presence)
return {
"timmyState": {
"mood": presence.get("mood", "calm"),
"activity": presence.get("current_focus", "idle"),
"energy": presence.get("energy", 0.5),
"confidence": presence.get("confidence", 0.7),
},
"familiar": presence.get("familiar"),
"activeThreads": presence.get("active_threads", []),
"recentEvents": presence.get("recent_events", []),
"concerns": presence.get("concerns", []),
"visitorPresent": False,
"updatedAt": presence.get("liveness", datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")),
"version": presence.get("version", 1),
}
def _get_current_state() -> dict:
@@ -415,50 +224,6 @@ async def _heartbeat(websocket: WebSocket) -> None:
logger.debug("Heartbeat stopped — connection gone")
async def _authenticate_ws(websocket: WebSocket) -> bool:
"""Authenticate WebSocket connection using matrix_ws_token.
Checks for token in query param ?token= first. If no query param,
accepts the connection and waits for first message with
{"type": "auth", "token": "..."}.
Returns True if authenticated (or if auth is disabled).
Returns False and closes connection with code 4001 if invalid.
"""
token_setting = settings.matrix_ws_token
# Auth disabled in dev mode (empty/unset token)
if not token_setting:
return True
# Check query param first (can validate before accept)
query_token = websocket.query_params.get("token", "")
if query_token:
if query_token == token_setting:
return True
# Invalid token in query param - we need to accept to close properly
await websocket.accept()
await websocket.close(code=4001, reason="Invalid token")
return False
# No query token - accept and wait for auth message
await websocket.accept()
# Wait for auth message as first message
try:
raw = await websocket.receive_text()
data = json.loads(raw)
if data.get("type") == "auth" and data.get("token") == token_setting:
return True
# Invalid auth message
await websocket.close(code=4001, reason="Invalid token")
return False
except (json.JSONDecodeError, TypeError):
# Non-JSON first message without valid token
await websocket.close(code=4001, reason="Authentication required")
return False
@router.websocket("/ws")
async def world_ws(websocket: WebSocket) -> None:
"""Accept a Workshop client and keep it alive for state broadcasts.
@@ -467,28 +232,8 @@ async def world_ws(websocket: WebSocket) -> None:
client never starts from a blank slate. Incoming frames are parsed
as JSON — ``visitor_message`` triggers a bark response. A background
heartbeat ping runs every 15 s to detect dead connections early.
Authentication:
- If matrix_ws_token is configured, clients must provide it via
?token= query param or in the first message as
{"type": "auth", "token": "..."}.
- Invalid token results in close code 4001.
- Valid token receives a connection_ack message.
"""
# Authenticate (may accept connection internally)
is_authed = await _authenticate_ws(websocket)
if not is_authed:
logger.info("World WS connection rejected — invalid token")
return
# Auth passed - accept if not already accepted
if websocket.client_state.name != "CONNECTED":
await websocket.accept()
# Send connection_ack if auth was required
if settings.matrix_ws_token:
await websocket.send_text(json.dumps({"type": "connection_ack"}))
await websocket.accept()
_ws_clients.append(websocket)
logger.info("World WS connected — %d clients", len(_ws_clients))
@@ -638,428 +383,3 @@ async def _generate_bark(visitor_text: str) -> str:
except Exception as exc:
logger.warning("Bark generation failed: %s", exc)
return "Hmm, my thoughts are a bit tangled right now."
# ---------------------------------------------------------------------------
# Matrix Configuration Endpoint
# ---------------------------------------------------------------------------
# Default Matrix configuration (fallback when matrix.yaml is missing/corrupt)
_DEFAULT_MATRIX_CONFIG: dict[str, Any] = {
"lighting": {
"ambient_color": "#1a1a2e",
"ambient_intensity": 0.4,
"point_lights": [
{"color": "#FFD700", "intensity": 1.2, "position": {"x": 0, "y": 5, "z": 0}},
{"color": "#3B82F6", "intensity": 0.8, "position": {"x": -5, "y": 3, "z": -5}},
{"color": "#A855F7", "intensity": 0.6, "position": {"x": 5, "y": 3, "z": 5}},
],
},
"environment": {
"rain_enabled": False,
"starfield_enabled": True,
"fog_color": "#0f0f23",
"fog_density": 0.02,
},
"features": {
"chat_enabled": True,
"visitor_avatars": True,
"pip_familiar": True,
"workshop_portal": True,
},
}
def _load_matrix_config() -> dict[str, Any]:
"""Load Matrix world configuration from matrix.yaml with fallback to defaults.
Returns a dict with sections: lighting, environment, features.
If the config file is missing or invalid, returns sensible defaults.
"""
try:
config_path = Path(settings.repo_root) / "config" / "matrix.yaml"
if not config_path.exists():
logger.debug("matrix.yaml not found, using default config")
return _DEFAULT_MATRIX_CONFIG.copy()
raw = config_path.read_text()
config = yaml.safe_load(raw)
if not isinstance(config, dict):
logger.warning("matrix.yaml invalid format, using defaults")
return _DEFAULT_MATRIX_CONFIG.copy()
# Merge with defaults to ensure all required fields exist
result: dict[str, Any] = {
"lighting": {
**_DEFAULT_MATRIX_CONFIG["lighting"],
**config.get("lighting", {}),
},
"environment": {
**_DEFAULT_MATRIX_CONFIG["environment"],
**config.get("environment", {}),
},
"features": {
**_DEFAULT_MATRIX_CONFIG["features"],
**config.get("features", {}),
},
}
# Ensure point_lights is a list
if "point_lights" in config.get("lighting", {}):
result["lighting"]["point_lights"] = config["lighting"]["point_lights"]
else:
result["lighting"]["point_lights"] = _DEFAULT_MATRIX_CONFIG["lighting"]["point_lights"]
return result
except Exception as exc:
logger.warning("Failed to load matrix config: %s, using defaults", exc)
return _DEFAULT_MATRIX_CONFIG.copy()
@matrix_router.get("/config")
async def get_matrix_config() -> JSONResponse:
"""Return Matrix world configuration.
Serves lighting presets, environment settings, and feature flags
to the Matrix frontend so it can be config-driven rather than
hardcoded. Reads from config/matrix.yaml with sensible defaults.
Response structure:
- lighting: ambient_color, ambient_intensity, point_lights[]
- environment: rain_enabled, starfield_enabled, fog_color, fog_density
- features: chat_enabled, visitor_avatars, pip_familiar, workshop_portal
"""
config = _load_matrix_config()
return JSONResponse(
content=config,
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# Matrix Agent Registry Endpoint
# ---------------------------------------------------------------------------
@matrix_router.get("/agents")
async def get_matrix_agents() -> JSONResponse:
"""Return the agent registry for Matrix visualization.
Serves agents from agents.yaml with Matrix-compatible formatting:
- id: agent identifier
- display_name: human-readable name
- role: functional role
- color: hex color code for visualization
- position: {x, y, z} coordinates in 3D space
- shape: 3D shape type
- status: availability status
Agents are arranged in a circular layout by default.
Returns 200 with empty list if no agents configured.
"""
agents = _build_matrix_agents_response()
return JSONResponse(
content=agents,
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# Matrix Thoughts Endpoint — Timmy's recent thought stream for Matrix display
# ---------------------------------------------------------------------------
_MAX_THOUGHT_LIMIT = 50 # Maximum thoughts allowed per request
_DEFAULT_THOUGHT_LIMIT = 10 # Default number of thoughts to return
_MAX_THOUGHT_TEXT_LEN = 500 # Max characters for thought text
def _build_matrix_thoughts_response(limit: int = _DEFAULT_THOUGHT_LIMIT) -> list[dict[str, Any]]:
"""Build the Matrix thoughts response from the thinking engine.
Returns recent thoughts formatted for Matrix display:
- id: thought UUID
- text: thought content (truncated to 500 chars)
- created_at: ISO-8601 timestamp
- chain_id: parent thought ID (or null if root thought)
Returns empty list if thinking engine is disabled or fails.
"""
try:
from timmy.thinking import thinking_engine
thoughts = thinking_engine.get_recent_thoughts(limit=limit)
return [
{
"id": t.id,
"text": t.content[:_MAX_THOUGHT_TEXT_LEN],
"created_at": t.created_at,
"chain_id": t.parent_id,
}
for t in thoughts
]
except Exception as exc:
logger.warning("Failed to load thoughts for Matrix: %s", exc)
return []
@matrix_router.get("/thoughts")
async def get_matrix_thoughts(limit: int = _DEFAULT_THOUGHT_LIMIT) -> JSONResponse:
"""Return Timmy's recent thoughts formatted for Matrix display.
This is the REST companion to the thought WebSocket messages,
allowing the Matrix frontend to display what Timmy is actually
thinking about rather than canned contextual lines.
Query params:
- limit: Number of thoughts to return (default 10, max 50)
Response: JSON array of thought objects:
- id: thought UUID
- text: thought content (truncated to 500 chars)
- created_at: ISO-8601 timestamp
- chain_id: parent thought ID (null if root thought)
Returns empty array if thinking engine is disabled or fails.
"""
# Clamp limit to valid range
if limit < 1:
limit = 1
elif limit > _MAX_THOUGHT_LIMIT:
limit = _MAX_THOUGHT_LIMIT
thoughts = _build_matrix_thoughts_response(limit=limit)
return JSONResponse(
content=thoughts,
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# Matrix Health Endpoint — backend capability discovery
# ---------------------------------------------------------------------------
# Health check cache (5-second TTL for capability checks)
_health_cache: dict | None = None
_health_cache_ts: float = 0.0
_HEALTH_CACHE_TTL = 5.0
def _check_capability_thinking() -> bool:
"""Check if thinking engine is available."""
try:
from timmy.thinking import thinking_engine
# Check if the engine has been initialized (has a db path)
return hasattr(thinking_engine, "_db") and thinking_engine._db is not None
except Exception:
return False
def _check_capability_memory() -> bool:
"""Check if memory system is available."""
try:
from timmy.memory_system import HOT_MEMORY_PATH
return HOT_MEMORY_PATH.exists()
except Exception:
return False
def _check_capability_bark() -> bool:
"""Check if bark production is available."""
try:
from infrastructure.presence import produce_bark
return callable(produce_bark)
except Exception:
return False
def _check_capability_familiar() -> bool:
"""Check if familiar (Pip) is available."""
try:
from timmy.familiar import pip_familiar
return pip_familiar is not None
except Exception:
return False
def _check_capability_lightning() -> bool:
"""Check if Lightning payments are available."""
# Lightning is currently disabled per health.py
# Returns False until properly re-implemented
return False
def _build_matrix_health_response() -> dict[str, Any]:
"""Build the Matrix health response with capability checks.
Performs lightweight checks (<100ms total) to determine which features
are available. Returns 200 even if some capabilities are degraded.
"""
capabilities = {
"thinking": _check_capability_thinking(),
"memory": _check_capability_memory(),
"bark": _check_capability_bark(),
"familiar": _check_capability_familiar(),
"lightning": _check_capability_lightning(),
}
# Status is ok if core capabilities (thinking, memory, bark) are available
core_caps = ["thinking", "memory", "bark"]
core_available = all(capabilities[c] for c in core_caps)
status = "ok" if core_available else "degraded"
return {
"status": status,
"version": "1.0.0",
"capabilities": capabilities,
}
@matrix_router.get("/health")
async def get_matrix_health() -> JSONResponse:
"""Return health status and capability availability for Matrix frontend.
This endpoint allows the Matrix frontend to discover what backend
capabilities are available so it can show/hide UI elements:
- thinking: Show thought bubbles if enabled
- memory: Show crystal ball memory search if available
- bark: Enable visitor chat responses
- familiar: Show Pip the familiar
- lightning: Enable payment features
Response time is <100ms (no heavy checks). Returns 200 even if
some capabilities are degraded.
Response:
- status: "ok" or "degraded"
- version: API version string
- capabilities: dict of feature:bool
"""
response = _build_matrix_health_response()
status_code = 200 # Always 200, even if degraded
return JSONResponse(
content=response,
status_code=status_code,
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# Matrix Memory Search Endpoint — visitors query Timmy's memory
# ---------------------------------------------------------------------------
# Rate limiting: 1 search per 5 seconds per IP
_MEMORY_SEARCH_RATE_LIMIT_SECONDS = 5
_memory_search_last_request: dict[str, float] = {}
_MAX_MEMORY_RESULTS = 5
_MAX_MEMORY_TEXT_LENGTH = 200
def _get_client_ip(request) -> str:
"""Extract client IP from request, respecting X-Forwarded-For header."""
# Check for forwarded IP (when behind proxy)
forwarded = request.headers.get("X-Forwarded-For")
if forwarded:
# Take the first IP in the chain
return forwarded.split(",")[0].strip()
# Fall back to direct client IP
if request.client:
return request.client.host
return "unknown"
def _build_matrix_memory_response(
memories: list,
) -> list[dict[str, Any]]:
"""Build the Matrix memory search response.
Formats memory entries for Matrix display:
- text: truncated to 200 characters
- relevance: 0-1 score from relevance_score
- created_at: ISO-8601 timestamp
- context_type: the memory type
Results are capped at _MAX_MEMORY_RESULTS.
"""
results = []
for mem in memories[:_MAX_MEMORY_RESULTS]:
text = mem.content
if len(text) > _MAX_MEMORY_TEXT_LENGTH:
text = text[:_MAX_MEMORY_TEXT_LENGTH] + "..."
results.append(
{
"text": text,
"relevance": round(mem.relevance_score or 0.0, 4),
"created_at": mem.timestamp,
"context_type": mem.context_type,
}
)
return results
@matrix_router.get("/memory/search")
async def get_matrix_memory_search(request: Request, q: str | None = None) -> JSONResponse:
"""Search Timmy's memory for relevant snippets.
Allows Matrix visitors to query Timmy's memory ("what do you remember
about sovereignty?"). Results appear as floating crystal-ball text
in the Workshop room.
Query params:
- q: Search query text (required)
Response: JSON array of memory objects:
- text: Memory content (truncated to 200 chars)
- relevance: Similarity score 0-1
- created_at: ISO-8601 timestamp
- context_type: Memory type (conversation, fact, etc.)
Rate limited to 1 search per 5 seconds per IP.
Returns:
- 200: JSON array of memory results (max 5)
- 400: Missing or empty query parameter
- 429: Rate limit exceeded
"""
# Validate query parameter
query = q.strip() if q else ""
if not query:
return JSONResponse(
status_code=400,
content={"error": "Query parameter 'q' is required"},
)
# Rate limiting check by IP
client_ip = _get_client_ip(request)
now = time.time()
last_request = _memory_search_last_request.get(client_ip, 0)
time_since_last = now - last_request
if time_since_last < _MEMORY_SEARCH_RATE_LIMIT_SECONDS:
retry_after = _MEMORY_SEARCH_RATE_LIMIT_SECONDS - time_since_last
return JSONResponse(
status_code=429,
content={"error": "Rate limit exceeded. Try again later."},
headers={"Retry-After": str(int(retry_after) + 1)},
)
# Record this request
_memory_search_last_request[client_ip] = now
# Search memories
try:
memories = search_memories(query, limit=_MAX_MEMORY_RESULTS)
results = _build_matrix_memory_response(memories)
except Exception as exc:
logger.warning("Memory search failed: %s", exc)
results = []
return JSONResponse(
content=results,
headers={"Cache-Control": "no-cache, no-store"},
)

View File

@@ -1,17 +0,0 @@
"""Dashboard services for business logic."""
from dashboard.services.scorecard_service import (
PeriodType,
ScorecardSummary,
generate_all_scorecards,
generate_scorecard,
get_tracked_agents,
)
__all__ = [
"PeriodType",
"ScorecardSummary",
"generate_all_scorecards",
"generate_scorecard",
"get_tracked_agents",
]

View File

@@ -1,515 +0,0 @@
"""Agent scorecard service — track and summarize agent performance.
Generates daily/weekly scorecards showing:
- Issues touched, PRs opened/merged
- Tests affected, tokens earned/spent
- Pattern highlights (merge rate, activity quality)
"""
from __future__ import annotations
import logging
from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta
from enum import StrEnum
from typing import Any
from infrastructure.events.bus import Event, get_event_bus
logger = logging.getLogger(__name__)
# Bot/agent usernames to track
TRACKED_AGENTS = frozenset({"hermes", "kimi", "manus", "claude", "gemini"})
class PeriodType(StrEnum):
daily = "daily"
weekly = "weekly"
@dataclass
class AgentMetrics:
"""Raw metrics collected for an agent over a period."""
agent_id: str
issues_touched: set[int] = field(default_factory=set)
prs_opened: set[int] = field(default_factory=set)
prs_merged: set[int] = field(default_factory=set)
tests_affected: set[str] = field(default_factory=set)
tokens_earned: int = 0
tokens_spent: int = 0
commits: int = 0
comments: int = 0
@property
def pr_merge_rate(self) -> float:
"""Calculate PR merge rate (0.0 - 1.0)."""
opened = len(self.prs_opened)
if opened == 0:
return 0.0
return len(self.prs_merged) / opened
@dataclass
class ScorecardSummary:
"""A generated scorecard with narrative summary."""
agent_id: str
period_type: PeriodType
period_start: datetime
period_end: datetime
metrics: AgentMetrics
narrative_bullets: list[str] = field(default_factory=list)
patterns: list[str] = field(default_factory=list)
def to_dict(self) -> dict[str, Any]:
"""Convert scorecard to dictionary for JSON serialization."""
return {
"agent_id": self.agent_id,
"period_type": self.period_type.value,
"period_start": self.period_start.isoformat(),
"period_end": self.period_end.isoformat(),
"metrics": {
"issues_touched": len(self.metrics.issues_touched),
"prs_opened": len(self.metrics.prs_opened),
"prs_merged": len(self.metrics.prs_merged),
"pr_merge_rate": round(self.metrics.pr_merge_rate, 2),
"tests_affected": len(self.tests_affected),
"commits": self.metrics.commits,
"comments": self.metrics.comments,
"tokens_earned": self.metrics.tokens_earned,
"tokens_spent": self.metrics.tokens_spent,
"token_net": self.metrics.tokens_earned - self.metrics.tokens_spent,
},
"narrative_bullets": self.narrative_bullets,
"patterns": self.patterns,
}
@property
def tests_affected(self) -> set[str]:
"""Alias for metrics.tests_affected."""
return self.metrics.tests_affected
def _get_period_bounds(
period_type: PeriodType, reference_date: datetime | None = None
) -> tuple[datetime, datetime]:
"""Calculate start and end timestamps for a period.
Args:
period_type: daily or weekly
reference_date: The date to calculate from (defaults to now)
Returns:
Tuple of (period_start, period_end) in UTC
"""
if reference_date is None:
reference_date = datetime.now(UTC)
# Normalize to start of day
end = reference_date.replace(hour=0, minute=0, second=0, microsecond=0)
if period_type == PeriodType.daily:
start = end - timedelta(days=1)
else: # weekly
start = end - timedelta(days=7)
return start, end
def _collect_events_for_period(
start: datetime, end: datetime, agent_id: str | None = None
) -> list[Event]:
"""Collect events from the event bus for a time period.
Args:
start: Period start time
end: Period end time
agent_id: Optional agent filter
Returns:
List of matching events
"""
bus = get_event_bus()
events: list[Event] = []
# Query persisted events for relevant types
event_types = [
"gitea.push",
"gitea.issue.opened",
"gitea.issue.comment",
"gitea.pull_request",
"agent.task.completed",
"test.execution",
]
for event_type in event_types:
try:
type_events = bus.replay(
event_type=event_type,
source=agent_id,
limit=1000,
)
events.extend(type_events)
except Exception as exc:
logger.debug("Failed to replay events for %s: %s", event_type, exc)
# Filter by timestamp
filtered = []
for event in events:
try:
event_time = datetime.fromisoformat(event.timestamp.replace("Z", "+00:00"))
if start <= event_time < end:
filtered.append(event)
except (ValueError, AttributeError):
continue
return filtered
def _extract_actor_from_event(event: Event) -> str:
"""Extract the actor/agent from an event."""
# Try data fields first
if "actor" in event.data:
return event.data["actor"]
if "agent_id" in event.data:
return event.data["agent_id"]
# Fall back to source
return event.source
def _is_tracked_agent(actor: str) -> bool:
"""Check if an actor is a tracked agent."""
return actor.lower() in TRACKED_AGENTS
def _aggregate_metrics(events: list[Event]) -> dict[str, AgentMetrics]:
"""Aggregate metrics from events grouped by agent.
Args:
events: List of events to process
Returns:
Dict mapping agent_id -> AgentMetrics
"""
metrics_by_agent: dict[str, AgentMetrics] = {}
for event in events:
actor = _extract_actor_from_event(event)
# Skip non-agent events unless they explicitly have an agent_id
if not _is_tracked_agent(actor) and "agent_id" not in event.data:
continue
if actor not in metrics_by_agent:
metrics_by_agent[actor] = AgentMetrics(agent_id=actor)
metrics = metrics_by_agent[actor]
# Process based on event type
event_type = event.type
if event_type == "gitea.push":
metrics.commits += event.data.get("num_commits", 1)
elif event_type == "gitea.issue.opened":
issue_num = event.data.get("issue_number", 0)
if issue_num:
metrics.issues_touched.add(issue_num)
elif event_type == "gitea.issue.comment":
metrics.comments += 1
issue_num = event.data.get("issue_number", 0)
if issue_num:
metrics.issues_touched.add(issue_num)
elif event_type == "gitea.pull_request":
pr_num = event.data.get("pr_number", 0)
action = event.data.get("action", "")
merged = event.data.get("merged", False)
if pr_num:
if action == "opened":
metrics.prs_opened.add(pr_num)
elif action == "closed" and merged:
metrics.prs_merged.add(pr_num)
# Also count as touched issue for tracking
metrics.issues_touched.add(pr_num)
elif event_type == "agent.task.completed":
# Extract test files from task data
affected = event.data.get("tests_affected", [])
for test in affected:
metrics.tests_affected.add(test)
# Token rewards from task completion
reward = event.data.get("token_reward", 0)
if reward:
metrics.tokens_earned += reward
elif event_type == "test.execution":
# Track test files that were executed
test_files = event.data.get("test_files", [])
for test in test_files:
metrics.tests_affected.add(test)
return metrics_by_agent
def _query_token_transactions(agent_id: str, start: datetime, end: datetime) -> tuple[int, int]:
"""Query the lightning ledger for token transactions.
Args:
agent_id: The agent to query for
start: Period start
end: Period end
Returns:
Tuple of (tokens_earned, tokens_spent)
"""
try:
from lightning.ledger import get_transactions
transactions = get_transactions(limit=1000)
earned = 0
spent = 0
for tx in transactions:
# Filter by agent if specified
if tx.agent_id and tx.agent_id != agent_id:
continue
# Filter by timestamp
try:
tx_time = datetime.fromisoformat(tx.created_at.replace("Z", "+00:00"))
if not (start <= tx_time < end):
continue
except (ValueError, AttributeError):
continue
if tx.tx_type.value == "incoming":
earned += tx.amount_sats
else:
spent += tx.amount_sats
return earned, spent
except Exception as exc:
logger.debug("Failed to query token transactions: %s", exc)
return 0, 0
def _generate_narrative_bullets(metrics: AgentMetrics, period_type: PeriodType) -> list[str]:
"""Generate narrative summary bullets for a scorecard.
Args:
metrics: The agent's metrics
period_type: daily or weekly
Returns:
List of narrative bullet points
"""
bullets: list[str] = []
period_label = "day" if period_type == PeriodType.daily else "week"
# Activity summary
activities = []
if metrics.commits:
activities.append(f"{metrics.commits} commit{'s' if metrics.commits != 1 else ''}")
if len(metrics.prs_opened):
activities.append(
f"{len(metrics.prs_opened)} PR{'s' if len(metrics.prs_opened) != 1 else ''} opened"
)
if len(metrics.prs_merged):
activities.append(
f"{len(metrics.prs_merged)} PR{'s' if len(metrics.prs_merged) != 1 else ''} merged"
)
if len(metrics.issues_touched):
activities.append(
f"{len(metrics.issues_touched)} issue{'s' if len(metrics.issues_touched) != 1 else ''} touched"
)
if metrics.comments:
activities.append(f"{metrics.comments} comment{'s' if metrics.comments != 1 else ''}")
if activities:
bullets.append(f"Active across {', '.join(activities)} this {period_label}.")
# Test activity
if len(metrics.tests_affected):
bullets.append(
f"Affected {len(metrics.tests_affected)} test file{'s' if len(metrics.tests_affected) != 1 else ''}."
)
# Token summary
net_tokens = metrics.tokens_earned - metrics.tokens_spent
if metrics.tokens_earned or metrics.tokens_spent:
if net_tokens > 0:
bullets.append(
f"Net earned {net_tokens} tokens ({metrics.tokens_earned} earned, {metrics.tokens_spent} spent)."
)
elif net_tokens < 0:
bullets.append(
f"Net spent {abs(net_tokens)} tokens ({metrics.tokens_earned} earned, {metrics.tokens_spent} spent)."
)
else:
bullets.append(
f"Balanced token flow ({metrics.tokens_earned} earned, {metrics.tokens_spent} spent)."
)
# Handle empty case
if not bullets:
bullets.append(f"No recorded activity this {period_label}.")
return bullets
def _detect_patterns(metrics: AgentMetrics) -> list[str]:
"""Detect interesting patterns in agent behavior.
Args:
metrics: The agent's metrics
Returns:
List of pattern descriptions
"""
patterns: list[str] = []
pr_opened = len(metrics.prs_opened)
merge_rate = metrics.pr_merge_rate
# Merge rate patterns
if pr_opened >= 3:
if merge_rate >= 0.8:
patterns.append("High merge rate with few failures — code quality focus.")
elif merge_rate <= 0.3:
patterns.append("Lots of noisy PRs, low merge rate — may need review support.")
# Activity patterns
if metrics.commits > 10 and pr_opened == 0:
patterns.append("High commit volume without PRs — working directly on main?")
if len(metrics.issues_touched) > 5 and metrics.comments == 0:
patterns.append("Touching many issues but low comment volume — silent worker.")
if metrics.comments > len(metrics.issues_touched) * 2:
patterns.append("Highly communicative — lots of discussion relative to work items.")
# Token patterns
net_tokens = metrics.tokens_earned - metrics.tokens_spent
if net_tokens > 100:
patterns.append("Strong token accumulation — high value delivery.")
elif net_tokens < -50:
patterns.append("High token spend — may be in experimentation phase.")
return patterns
def generate_scorecard(
agent_id: str,
period_type: PeriodType = PeriodType.daily,
reference_date: datetime | None = None,
) -> ScorecardSummary | None:
"""Generate a scorecard for a single agent.
Args:
agent_id: The agent to generate scorecard for
period_type: daily or weekly
reference_date: The date to calculate from (defaults to now)
Returns:
ScorecardSummary or None if agent has no activity
"""
start, end = _get_period_bounds(period_type, reference_date)
# Collect events
events = _collect_events_for_period(start, end, agent_id)
# Aggregate metrics
all_metrics = _aggregate_metrics(events)
# Get metrics for this specific agent
if agent_id not in all_metrics:
# Create empty metrics - still generate a scorecard
metrics = AgentMetrics(agent_id=agent_id)
else:
metrics = all_metrics[agent_id]
# Augment with token data from ledger
tokens_earned, tokens_spent = _query_token_transactions(agent_id, start, end)
metrics.tokens_earned = max(metrics.tokens_earned, tokens_earned)
metrics.tokens_spent = max(metrics.tokens_spent, tokens_spent)
# Generate narrative and patterns
narrative = _generate_narrative_bullets(metrics, period_type)
patterns = _detect_patterns(metrics)
return ScorecardSummary(
agent_id=agent_id,
period_type=period_type,
period_start=start,
period_end=end,
metrics=metrics,
narrative_bullets=narrative,
patterns=patterns,
)
def generate_all_scorecards(
period_type: PeriodType = PeriodType.daily,
reference_date: datetime | None = None,
) -> list[ScorecardSummary]:
"""Generate scorecards for all tracked agents.
Args:
period_type: daily or weekly
reference_date: The date to calculate from (defaults to now)
Returns:
List of ScorecardSummary for all agents with activity
"""
start, end = _get_period_bounds(period_type, reference_date)
# Collect all events
events = _collect_events_for_period(start, end)
# Aggregate metrics for all agents
all_metrics = _aggregate_metrics(events)
# Include tracked agents even if no activity
for agent_id in TRACKED_AGENTS:
if agent_id not in all_metrics:
all_metrics[agent_id] = AgentMetrics(agent_id=agent_id)
# Generate scorecards
scorecards: list[ScorecardSummary] = []
for agent_id, metrics in all_metrics.items():
# Augment with token data
tokens_earned, tokens_spent = _query_token_transactions(agent_id, start, end)
metrics.tokens_earned = max(metrics.tokens_earned, tokens_earned)
metrics.tokens_spent = max(metrics.tokens_spent, tokens_spent)
narrative = _generate_narrative_bullets(metrics, period_type)
patterns = _detect_patterns(metrics)
scorecard = ScorecardSummary(
agent_id=agent_id,
period_type=period_type,
period_start=start,
period_end=end,
metrics=metrics,
narrative_bullets=narrative,
patterns=patterns,
)
scorecards.append(scorecard)
# Sort by agent_id for consistent ordering
scorecards.sort(key=lambda s: s.agent_id)
return scorecards
def get_tracked_agents() -> list[str]:
"""Return the list of tracked agent IDs."""
return sorted(TRACKED_AGENTS)

View File

@@ -51,7 +51,6 @@
<a href="/thinking" class="mc-test-link mc-link-thinking">THINKING</a>
<a href="/swarm/mission-control" class="mc-test-link">MISSION CTRL</a>
<a href="/swarm/live" class="mc-test-link">SWARM</a>
<a href="/scorecards" class="mc-test-link">SCORECARDS</a>
<a href="/bugs" class="mc-test-link mc-link-bugs">BUGS</a>
</div>
</div>
@@ -124,7 +123,6 @@
<a href="/thinking" class="mc-mobile-link">THINKING</a>
<a href="/swarm/mission-control" class="mc-mobile-link">MISSION CONTROL</a>
<a href="/swarm/live" class="mc-mobile-link">SWARM</a>
<a href="/scorecards" class="mc-mobile-link">SCORECARDS</a>
<a href="/bugs" class="mc-mobile-link">BUGS</a>
<div class="mc-mobile-section-label">INTELLIGENCE</div>
<a href="/spark/ui" class="mc-mobile-link">SPARK</a>

View File

@@ -21,11 +21,6 @@
</div>
{% endcall %}
<!-- Daily Run Metrics (HTMX polled) -->
{% call panel("DAILY RUN", hx_get="/daily-run/panel", hx_trigger="every 60s") %}
<div class="mc-loading-placeholder">LOADING...</div>
{% endcall %}
</div>
<!-- Main panel — swappable via HTMX; defaults to Timmy on load -->

View File

@@ -138,47 +138,6 @@
</div>
</div>
<!-- Spark Intelligence -->
{% from "macros.html" import panel %}
<div class="mc-card-spaced">
<div class="card">
<div class="card-header">
<h2 class="card-title">Spark Intelligence</h2>
<div>
<span class="badge" id="spark-status-badge">Loading...</span>
</div>
</div>
<div class="grid grid-3">
<div class="stat">
<div class="stat-value" id="spark-events">-</div>
<div class="stat-label">Events</div>
</div>
<div class="stat">
<div class="stat-value" id="spark-memories">-</div>
<div class="stat-label">Memories</div>
</div>
<div class="stat">
<div class="stat-value" id="spark-predictions">-</div>
<div class="stat-label">Predictions</div>
</div>
</div>
</div>
<div class="grid grid-2 mc-section-gap">
{% call panel("SPARK TIMELINE", id="spark-timeline-panel",
hx_get="/spark/timeline",
hx_trigger="load, every 10s") %}
<div class="spark-timeline-scroll">
<p class="chat-history-placeholder">Loading timeline...</p>
</div>
{% endcall %}
{% call panel("SPARK INSIGHTS", id="spark-insights-panel",
hx_get="/spark/insights",
hx_trigger="load, every 30s") %}
<p class="chat-history-placeholder">Loading insights...</p>
{% endcall %}
</div>
</div>
<!-- Chat History -->
<div class="card mc-card-spaced">
<div class="card-header">
@@ -469,34 +428,7 @@ async function loadGrokStats() {
}
}
// Load Spark status
async function loadSparkStatus() {
try {
var response = await fetch('/spark');
var data = await response.json();
var st = data.status || {};
document.getElementById('spark-events').textContent = st.total_events || 0;
document.getElementById('spark-memories').textContent = st.total_memories || 0;
document.getElementById('spark-predictions').textContent = st.total_predictions || 0;
var badge = document.getElementById('spark-status-badge');
if (st.total_events > 0) {
badge.textContent = 'Active';
badge.className = 'badge badge-success';
} else {
badge.textContent = 'Idle';
badge.className = 'badge badge-warning';
}
} catch (error) {
var badge = document.getElementById('spark-status-badge');
badge.textContent = 'Offline';
badge.className = 'badge badge-danger';
}
}
// Initial load
loadSparkStatus();
loadSovereignty();
loadHealth();
loadSwarmStats();
@@ -510,6 +442,5 @@ setInterval(loadHealth, 10000);
setInterval(loadSwarmStats, 5000);
setInterval(updateHeartbeat, 5000);
setInterval(loadGrokStats, 10000);
setInterval(loadSparkStatus, 15000);
</script>
{% endblock %}

View File

@@ -1,54 +0,0 @@
<div class="card-header mc-panel-header">// DAILY RUN METRICS</div>
<div class="card-body p-3">
{% if not gitea_available %}
<div class="mc-muted" style="font-size: 0.85rem; padding: 8px 0;">
<span style="color: var(--amber);"></span> Gitea API unavailable
</div>
{% else %}
{% set m = metrics %}
<!-- Sessions summary -->
<div class="dr-section" style="margin-bottom: 16px;">
<div class="dr-row" style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
<span class="dr-label" style="font-size: 0.85rem; color: var(--text-dim);">Sessions ({{ m.lookback_days }}d)</span>
<a href="{{ logbook_url }}" target="_blank" class="dr-link" style="font-size: 0.75rem; color: var(--green); text-decoration: none;">
Logbook →
</a>
</div>
<div class="dr-stat" style="display: flex; align-items: baseline; gap: 8px;">
<span class="dr-value" style="font-size: 1.5rem; font-weight: 600; color: var(--text-bright);">{{ m.sessions_completed }}</span>
<span class="dr-trend" style="font-size: 0.9rem; color: {{ m.sessions_trend_color }};">{{ m.sessions_trend }}</span>
<span class="dr-prev" style="font-size: 0.75rem; color: var(--text-dim);">vs {{ m.sessions_previous }} prev</span>
</div>
</div>
<!-- Layer breakdown -->
<div class="dr-section">
<div class="dr-label" style="font-size: 0.85rem; color: var(--text-dim); margin-bottom: 8px;">Issues by Layer</div>
<div class="dr-layers" style="display: flex; flex-direction: column; gap: 6px;">
{% for layer in m.layers %}
<div class="dr-layer-row" style="display: flex; justify-content: space-between; align-items: center;">
<a href="{{ layer_urls[layer.name] }}" target="_blank" class="dr-layer-name" style="font-size: 0.8rem; color: var(--text); text-decoration: none; text-transform: capitalize;">
{{ layer.name.replace('-', ' ') }}
</a>
<div class="dr-layer-stat" style="display: flex; align-items: center; gap: 6px;">
<span class="dr-layer-value" style="font-size: 0.9rem; font-weight: 500; color: var(--text-bright);">{{ layer.current_count }}</span>
<span class="dr-layer-trend" style="font-size: 0.75rem; color: {{ layer.trend_color }}; width: 18px; text-align: center;">{{ layer.trend }}</span>
</div>
</div>
{% endfor %}
</div>
</div>
<!-- Total touched -->
<div class="dr-section" style="margin-top: 12px; padding-top: 12px; border-top: 1px solid var(--border);">
<div class="dr-row" style="display: flex; justify-content: space-between; align-items: center;">
<span class="dr-label" style="font-size: 0.8rem; color: var(--text-dim);">Total Issues Touched</span>
<div class="dr-total-stat" style="display: flex; align-items: center; gap: 6px;">
<span class="dr-total-value" style="font-size: 1rem; font-weight: 600; color: var(--text-bright);">{{ m.total_touched_current }}</span>
<span class="dr-total-prev" style="font-size: 0.7rem; color: var(--text-dim);">/ {{ m.total_touched_previous }} prev</span>
</div>
</div>
</div>
{% endif %}
</div>

View File

@@ -1,80 +0,0 @@
{% from "macros.html" import panel %}
<div class="quests-summary mb-4">
<div class="row">
<div class="col-md-4">
<div class="stat-card">
<div class="stat-value">{{ total_tokens }}</div>
<div class="stat-label">Tokens Earned</div>
</div>
</div>
<div class="col-md-4">
<div class="stat-card">
<div class="stat-value">{{ completed_count }}</div>
<div class="stat-label">Quests Completed</div>
</div>
</div>
<div class="col-md-4">
<div class="stat-card">
<div class="stat-value">{{ quests|selectattr('enabled', 'equalto', true)|list|length }}</div>
<div class="stat-label">Active Quests</div>
</div>
</div>
</div>
</div>
<div class="quests-list">
{% for quest in quests %}
{% if quest.enabled %}
<div class="quest-card quest-status-{{ quest.status }}">
<div class="quest-header">
<h5 class="quest-name">{{ quest.name }}</h5>
<span class="quest-reward">+{{ quest.reward_tokens }} ⚡</span>
</div>
<p class="quest-description">{{ quest.description }}</p>
<div class="quest-progress">
{% if quest.status == 'completed' %}
<div class="progress">
<div class="progress-bar bg-success" style="width: 100%"></div>
</div>
<span class="quest-status-badge completed">Completed</span>
{% elif quest.status == 'claimed' %}
<div class="progress">
<div class="progress-bar bg-success" style="width: 100%"></div>
</div>
<span class="quest-status-badge claimed">Reward Claimed</span>
{% elif quest.on_cooldown %}
<div class="progress">
<div class="progress-bar bg-secondary" style="width: 100%"></div>
</div>
<span class="quest-status-badge cooldown">
Cooldown: {{ quest.cooldown_hours_remaining }}h remaining
</span>
{% else %}
<div class="progress">
<div class="progress-bar" style="width: {{ (quest.current_value / quest.target_value * 100)|int }}%"></div>
</div>
<span class="quest-progress-text">{{ quest.current_value }} / {{ quest.target_value }}</span>
{% endif %}
</div>
<div class="quest-meta">
<span class="quest-type">{{ quest.type }}</span>
{% if quest.repeatable %}
<span class="quest-repeatable">↻ Repeatable</span>
{% endif %}
{% if quest.completion_count > 0 %}
<span class="quest-completions">Completed {{ quest.completion_count }} time{% if quest.completion_count != 1 %}s{% endif %}</span>
{% endif %}
</div>
</div>
{% endif %}
{% endfor %}
</div>
{% if not quests|selectattr('enabled', 'equalto', true)|list|length %}
<div class="alert alert-info">
No active quests available. Check back later or contact an administrator.
</div>
{% endif %}

View File

@@ -1,50 +0,0 @@
{% extends "base.html" %}
{% block title %}Quests — Mission Control{% endblock %}
{% block content %}
<div class="container-fluid">
<div class="row">
<div class="col-12">
<h1 class="mc-title">Token Quests</h1>
<p class="mc-subtitle">Complete quests to earn bonus tokens</p>
</div>
</div>
<div class="row mt-4">
<div class="col-md-8">
<div id="quests-panel" hx-get="/quests/panel/{{ agent_id }}" hx-trigger="load, every 30s">
<div class="mc-loading">Loading quests...</div>
</div>
</div>
<div class="col-md-4">
<div class="card mc-panel">
<div class="card-header">
<h5 class="mb-0">Leaderboard</h5>
</div>
<div class="card-body">
<div id="leaderboard" hx-get="/quests/api/leaderboard" hx-trigger="load, every 60s">
<div class="mc-loading">Loading leaderboard...</div>
</div>
</div>
</div>
<div class="card mc-panel mt-4">
<div class="card-header">
<h5 class="mb-0">About Quests</h5>
</div>
<div class="card-body">
<p class="mb-2">Quests are special objectives that reward tokens upon completion.</p>
<ul class="mc-list mb-0">
<li>Complete Daily Run sessions</li>
<li>Close flaky-test issues</li>
<li>Reduce P1 issue backlog</li>
<li>Improve documentation</li>
</ul>
</div>
</div>
</div>
</div>
</div>
{% endblock %}

View File

@@ -1,113 +0,0 @@
{% extends "base.html" %}
{% block title %}Agent Scorecards - Timmy Time{% endblock %}
{% block extra_styles %}{% endblock %}
{% block content %}
<div class="container-fluid py-4">
<!-- Header -->
<div class="d-flex justify-content-between align-items-center mb-4">
<div>
<h1 class="h3 mb-0">AGENT SCORECARDS</h1>
<p class="text-muted small mb-0">Track agent performance across issues, PRs, tests, and tokens</p>
</div>
<div class="d-flex gap-2">
<select id="period-select" class="form-select form-select-sm" style="width: auto;">
<option value="daily" selected>Daily</option>
<option value="weekly">Weekly</option>
</select>
<button class="btn btn-sm btn-primary" onclick="refreshScorecards()">
<span>Refresh</span>
</button>
</div>
</div>
<!-- Scorecards Grid -->
<div id="scorecards-container"
hx-get="/scorecards/all/panels?period=daily"
hx-trigger="load"
hx-swap="innerHTML">
<div class="text-center py-5">
<div class="spinner-border text-secondary" role="status">
<span class="visually-hidden">Loading...</span>
</div>
<p class="text-muted mt-2">Loading scorecards...</p>
</div>
</div>
<!-- API Reference -->
<div class="mt-5 pt-4 border-top">
<h5 class="text-muted">API Reference</h5>
<div class="row g-3">
<div class="col-md-6">
<div class="card mc-panel">
<div class="card-body">
<h6 class="card-title">List Tracked Agents</h6>
<code>GET /scorecards/api/agents</code>
<p class="small text-muted mt-2">Returns all tracked agent IDs</p>
</div>
</div>
</div>
<div class="col-md-6">
<div class="card mc-panel">
<div class="card-body">
<h6 class="card-title">Get All Scorecards</h6>
<code>GET /scorecards/api?period=daily|weekly</code>
<p class="small text-muted mt-2">Returns scorecards for all agents</p>
</div>
</div>
</div>
<div class="col-md-6">
<div class="card mc-panel">
<div class="card-body">
<h6 class="card-title">Get Agent Scorecard</h6>
<code>GET /scorecards/api/{agent_id}?period=daily|weekly</code>
<p class="small text-muted mt-2">Returns scorecard for a specific agent</p>
</div>
</div>
</div>
<div class="col-md-6">
<div class="card mc-panel">
<div class="card-body">
<h6 class="card-title">HTML Panel (HTMX)</h6>
<code>GET /scorecards/panel/{agent_id}?period=daily|weekly</code>
<p class="small text-muted mt-2">Returns HTML panel for embedding</p>
</div>
</div>
</div>
</div>
</div>
</div>
<script>
// Period selector change handler
document.getElementById('period-select').addEventListener('change', function() {
refreshScorecards();
});
function refreshScorecards() {
var period = document.getElementById('period-select').value;
var container = document.getElementById('scorecards-container');
// Show loading state
container.innerHTML = `
<div class="text-center py-5">
<div class="spinner-border text-secondary" role="status">
<span class="visually-hidden">Loading...</span>
</div>
<p class="text-muted mt-2">Loading scorecards...</p>
</div>
`;
// Trigger HTMX request
htmx.ajax('GET', '/scorecards/all/panels?period=' + period, {
target: '#scorecards-container',
swap: 'innerHTML'
});
}
// Auto-refresh every 5 minutes
setInterval(refreshScorecards, 300000);
</script>
{% endblock %}

View File

@@ -1,180 +0,0 @@
{% extends "base.html" %}
{% block title %}Timmy Time — Tower{% endblock %}
{% block extra_styles %}{% endblock %}
{% block content %}
<div class="container-fluid tower-container py-3">
<div class="tower-header">
<div class="tower-title">TOWER</div>
<div class="tower-subtitle">
Real-time Spark visualization &mdash;
<span id="tower-conn" class="tower-conn-badge tower-conn-connecting">CONNECTING</span>
</div>
</div>
<div class="row g-3">
<!-- Left: THINKING (events) -->
<div class="col-12 col-lg-4 d-flex flex-column gap-3">
<div class="card mc-panel tower-phase-card">
<div class="card-header mc-panel-header tower-phase-thinking">// THINKING</div>
<div class="card-body p-3 tower-scroll" id="tower-events">
<div class="tower-empty">Waiting for Spark data&hellip;</div>
</div>
</div>
</div>
<!-- Middle: PREDICTING (EIDOS) -->
<div class="col-12 col-lg-4 d-flex flex-column gap-3">
<div class="card mc-panel tower-phase-card">
<div class="card-header mc-panel-header tower-phase-predicting">// PREDICTING</div>
<div class="card-body p-3" id="tower-predictions">
<div class="tower-empty">Waiting for Spark data&hellip;</div>
</div>
</div>
<div class="card mc-panel">
<div class="card-header mc-panel-header">// EIDOS STATS</div>
<div class="card-body p-3">
<div class="tower-stat-grid" id="tower-stats">
<div class="tower-stat"><span class="tower-stat-label">EVENTS</span><span class="tower-stat-value" id="ts-events">0</span></div>
<div class="tower-stat"><span class="tower-stat-label">MEMORIES</span><span class="tower-stat-value" id="ts-memories">0</span></div>
<div class="tower-stat"><span class="tower-stat-label">PREDICTIONS</span><span class="tower-stat-value" id="ts-preds">0</span></div>
<div class="tower-stat"><span class="tower-stat-label">ACCURACY</span><span class="tower-stat-value" id="ts-accuracy"></span></div>
</div>
</div>
</div>
</div>
<!-- Right: ADVISING -->
<div class="col-12 col-lg-4 d-flex flex-column gap-3">
<div class="card mc-panel tower-phase-card">
<div class="card-header mc-panel-header tower-phase-advising">// ADVISING</div>
<div class="card-body p-3 tower-scroll" id="tower-advisories">
<div class="tower-empty">Waiting for Spark data&hellip;</div>
</div>
</div>
</div>
</div>
</div>
<script>
(function() {
var ws = null;
var badge = document.getElementById('tower-conn');
function setConn(state) {
badge.textContent = state.toUpperCase();
badge.className = 'tower-conn-badge tower-conn-' + state;
}
function esc(s) { var d = document.createElement('div'); d.textContent = s; return d.innerHTML; }
function renderEvents(events) {
var el = document.getElementById('tower-events');
if (!events || !events.length) { el.innerHTML = '<div class="tower-empty">No events captured yet.</div>'; return; }
var html = '';
for (var i = 0; i < events.length; i++) {
var ev = events[i];
var dots = ev.importance >= 0.8 ? '\u25cf\u25cf\u25cf' : ev.importance >= 0.5 ? '\u25cf\u25cf' : '\u25cf';
html += '<div class="tower-event tower-etype-' + esc(ev.event_type) + '">'
+ '<div class="tower-ev-head">'
+ '<span class="tower-ev-badge">' + esc(ev.event_type.replace(/_/g, ' ').toUpperCase()) + '</span>'
+ '<span class="tower-ev-dots">' + dots + '</span>'
+ '</div>'
+ '<div class="tower-ev-desc">' + esc(ev.description) + '</div>'
+ '<div class="tower-ev-time">' + esc((ev.created_at || '').slice(0, 19)) + '</div>'
+ '</div>';
}
el.innerHTML = html;
}
function renderPredictions(preds) {
var el = document.getElementById('tower-predictions');
if (!preds || !preds.length) { el.innerHTML = '<div class="tower-empty">No predictions yet.</div>'; return; }
var html = '';
for (var i = 0; i < preds.length; i++) {
var p = preds[i];
var cls = p.evaluated ? 'tower-pred-done' : 'tower-pred-pending';
var accTxt = p.accuracy != null ? Math.round(p.accuracy * 100) + '%' : 'PENDING';
var accCls = p.accuracy != null ? (p.accuracy >= 0.7 ? 'text-success' : p.accuracy < 0.4 ? 'text-danger' : 'text-warning') : '';
html += '<div class="tower-pred ' + cls + '">'
+ '<div class="tower-pred-head">'
+ '<span class="tower-pred-task">' + esc(p.task_id) + '</span>'
+ '<span class="tower-pred-acc ' + accCls + '">' + accTxt + '</span>'
+ '</div>';
if (p.predicted) {
var pr = p.predicted;
html += '<div class="tower-pred-detail">';
if (pr.likely_winner) html += '<span>Winner: ' + esc(pr.likely_winner.slice(0, 8)) + '</span> ';
if (pr.success_probability != null) html += '<span>Success: ' + Math.round(pr.success_probability * 100) + '%</span> ';
html += '</div>';
}
html += '<div class="tower-ev-time">' + esc((p.created_at || '').slice(0, 19)) + '</div>'
+ '</div>';
}
el.innerHTML = html;
}
function renderAdvisories(advs) {
var el = document.getElementById('tower-advisories');
if (!advs || !advs.length) { el.innerHTML = '<div class="tower-empty">No advisories yet.</div>'; return; }
var html = '';
for (var i = 0; i < advs.length; i++) {
var a = advs[i];
var prio = a.priority >= 0.7 ? 'high' : a.priority >= 0.4 ? 'medium' : 'low';
html += '<div class="tower-advisory tower-adv-' + prio + '">'
+ '<div class="tower-adv-head">'
+ '<span class="tower-adv-cat">' + esc(a.category.replace(/_/g, ' ').toUpperCase()) + '</span>'
+ '<span class="tower-adv-prio">' + Math.round(a.priority * 100) + '%</span>'
+ '</div>'
+ '<div class="tower-adv-title">' + esc(a.title) + '</div>'
+ '<div class="tower-adv-detail">' + esc(a.detail) + '</div>'
+ '<div class="tower-adv-action">' + esc(a.suggested_action) + '</div>'
+ '</div>';
}
el.innerHTML = html;
}
function renderStats(status) {
if (!status) return;
document.getElementById('ts-events').textContent = status.events_captured || 0;
document.getElementById('ts-memories').textContent = status.memories_stored || 0;
var p = status.predictions || {};
document.getElementById('ts-preds').textContent = p.total_predictions || 0;
var acc = p.avg_accuracy;
var accEl = document.getElementById('ts-accuracy');
if (acc != null) {
accEl.textContent = Math.round(acc * 100) + '%';
accEl.className = 'tower-stat-value ' + (acc >= 0.7 ? 'text-success' : acc < 0.4 ? 'text-danger' : 'text-warning');
} else {
accEl.textContent = '\u2014';
}
}
function handleMsg(data) {
if (data.type !== 'spark_state') return;
renderEvents(data.events);
renderPredictions(data.predictions);
renderAdvisories(data.advisories);
renderStats(data.status);
}
function connect() {
var proto = location.protocol === 'https:' ? 'wss:' : 'ws:';
ws = new WebSocket(proto + '//' + location.host + '/tower/ws');
ws.onopen = function() { setConn('live'); };
ws.onclose = function() { setConn('offline'); setTimeout(connect, 3000); };
ws.onerror = function() { setConn('offline'); };
ws.onmessage = function(e) {
try { handleMsg(JSON.parse(e.data)); } catch(err) { console.error('Tower WS parse error', err); }
};
}
connect();
})();
</script>
{% endblock %}

View File

@@ -1,84 +0,0 @@
"""Thread-local SQLite connection pool.
Provides a ConnectionPool class that manages SQLite connections per thread,
with support for context managers and automatic cleanup.
"""
import sqlite3
import threading
from collections.abc import Generator
from contextlib import contextmanager
from pathlib import Path
class ConnectionPool:
"""Thread-local SQLite connection pool.
Each thread gets its own connection, which is reused for subsequent
requests from the same thread. Connections are automatically cleaned
up when close_connection() is called or the context manager exits.
"""
def __init__(self, db_path: Path | str) -> None:
"""Initialize the connection pool.
Args:
db_path: Path to the SQLite database file.
"""
self._db_path = Path(db_path)
self._local = threading.local()
def _ensure_db_exists(self) -> None:
"""Ensure the database directory exists."""
self._db_path.parent.mkdir(parents=True, exist_ok=True)
def get_connection(self) -> sqlite3.Connection:
"""Get a connection for the current thread.
Creates a new connection if one doesn't exist for this thread,
otherwise returns the existing connection.
Returns:
A sqlite3 Connection object.
"""
if not hasattr(self._local, "conn") or self._local.conn is None:
self._ensure_db_exists()
self._local.conn = sqlite3.connect(str(self._db_path), check_same_thread=False)
self._local.conn.row_factory = sqlite3.Row
return self._local.conn
def close_connection(self) -> None:
"""Close the connection for the current thread.
Cleans up the thread-local storage. Safe to call even if
no connection exists for this thread.
"""
if hasattr(self._local, "conn") and self._local.conn is not None:
self._local.conn.close()
self._local.conn = None
@contextmanager
def connection(self) -> Generator[sqlite3.Connection, None, None]:
"""Context manager for getting and automatically closing a connection.
Yields:
A sqlite3 Connection object.
Example:
with pool.connection() as conn:
cursor = conn.execute("SELECT 1")
result = cursor.fetchone()
"""
conn = self.get_connection()
try:
yield conn
finally:
self.close_connection()
def close_all(self) -> None:
"""Close all connections (useful for testing).
Note: This only closes the connection for the current thread.
In a multi-threaded environment, each thread must close its own.
"""
self.close_connection()

View File

@@ -149,52 +149,6 @@ def _log_error_event(
logger.debug("Failed to log error event: %s", log_exc)
def _build_report_description(
exc: Exception,
source: str,
context: dict | None,
error_hash: str,
tb_str: str,
affected_file: str,
affected_line: int,
git_ctx: dict,
) -> str:
"""Build the markdown description for a bug report task."""
parts = [
f"**Error:** {type(exc).__name__}: {str(exc)}",
f"**Source:** {source}",
f"**File:** {affected_file}:{affected_line}",
f"**Git:** {git_ctx.get('branch', '?')} @ {git_ctx.get('commit', '?')}",
f"**Time:** {datetime.now(UTC).isoformat()}",
f"**Hash:** {error_hash}",
]
if context:
ctx_str = ", ".join(f"{k}={v}" for k, v in context.items())
parts.append(f"**Context:** {ctx_str}")
parts.append(f"\n**Stack Trace:**\n```\n{tb_str[:2000]}\n```")
return "\n".join(parts)
def _log_bug_report_created(source: str, task_id: str, error_hash: str, title: str) -> None:
"""Log a BUG_REPORT_CREATED event (best-effort)."""
try:
from swarm.event_log import EventType, log_event
log_event(
EventType.BUG_REPORT_CREATED,
source=source,
task_id=task_id,
data={
"error_hash": error_hash,
"title": title[:100],
},
)
except Exception as exc:
logger.warning("Bug report event log error: %s", exc)
def _create_bug_report(
exc: Exception,
source: str,
@@ -210,20 +164,25 @@ def _create_bug_report(
from swarm.task_queue.models import create_task
title = f"[BUG] {type(exc).__name__}: {str(exc)[:80]}"
description = _build_report_description(
exc,
source,
context,
error_hash,
tb_str,
affected_file,
affected_line,
git_ctx,
)
description_parts = [
f"**Error:** {type(exc).__name__}: {str(exc)}",
f"**Source:** {source}",
f"**File:** {affected_file}:{affected_line}",
f"**Git:** {git_ctx.get('branch', '?')} @ {git_ctx.get('commit', '?')}",
f"**Time:** {datetime.now(UTC).isoformat()}",
f"**Hash:** {error_hash}",
]
if context:
ctx_str = ", ".join(f"{k}={v}" for k, v in context.items())
description_parts.append(f"**Context:** {ctx_str}")
description_parts.append(f"\n**Stack Trace:**\n```\n{tb_str[:2000]}\n```")
task = create_task(
title=title,
description=description,
description="\n".join(description_parts),
assigned_to="default",
created_by="system",
priority="normal",
@@ -231,9 +190,24 @@ def _create_bug_report(
auto_approve=True,
task_type="bug_report",
)
task_id = task.id
_log_bug_report_created(source, task.id, error_hash, title)
return task.id
try:
from swarm.event_log import EventType, log_event
log_event(
EventType.BUG_REPORT_CREATED,
source=source,
task_id=task_id,
data={
"error_hash": error_hash,
"title": title[:100],
},
)
except Exception as exc:
logger.warning("Bug report screenshot error: %s", exc)
return task_id
except Exception as task_exc:
logger.debug("Failed to create bug report task: %s", task_exc)

View File

@@ -64,7 +64,7 @@ class EventBus:
@bus.subscribe("agent.task.*")
async def handle_task(event: Event):
logger.debug("Task event: %s", event.data)
logger.debug(f"Task event: {event.data}")
await bus.publish(Event(
type="agent.task.assigned",

View File

@@ -146,7 +146,7 @@ class ShellHand:
@staticmethod
def _build_run_env(env: dict | None) -> dict:
"""Merge *env* overrides into a copy of the current environment."""
"""Merge *env* overrides into the current process environment."""
import os
run_env = os.environ.copy()
@@ -154,7 +154,7 @@ class ShellHand:
run_env.update(env)
return run_env
async def _execute_subprocess(
async def _exec_subprocess(
self,
command: str,
effective_timeout: int,
@@ -162,7 +162,7 @@ class ShellHand:
run_env: dict,
start: float,
) -> ShellResult:
"""Run *command* as a subprocess with timeout enforcement."""
"""Launch *command*, enforce timeout, and return the result."""
proc = await asyncio.create_subprocess_shell(
command,
stdout=asyncio.subprocess.PIPE,
@@ -178,29 +178,24 @@ class ShellHand:
except TimeoutError:
proc.kill()
await proc.wait()
latency = (time.time() - start) * 1000
logger.warning("Shell command timed out after %ds: %s", effective_timeout, command)
return ShellResult(
command=command,
success=False,
exit_code=-1,
error=f"Command timed out after {effective_timeout}s",
latency_ms=latency,
latency_ms=(time.time() - start) * 1000,
timed_out=True,
)
latency = (time.time() - start) * 1000
exit_code = proc.returncode if proc.returncode is not None else -1
stdout = stdout_bytes.decode("utf-8", errors="replace").strip()
stderr = stderr_bytes.decode("utf-8", errors="replace").strip()
return ShellResult(
command=command,
success=exit_code == 0,
exit_code=exit_code,
stdout=stdout,
stderr=stderr,
latency_ms=latency,
stdout=stdout_bytes.decode("utf-8", errors="replace").strip(),
stderr=stderr_bytes.decode("utf-8", errors="replace").strip(),
latency_ms=(time.time() - start) * 1000,
)
async def run(
@@ -232,20 +227,21 @@ class ShellHand:
latency_ms=(time.time() - start) * 1000,
)
effective_timeout = timeout or self._default_timeout
cwd = working_dir or self._working_dir
try:
run_env = self._build_run_env(env)
return await self._execute_subprocess(command, effective_timeout, cwd, run_env, start)
return await self._exec_subprocess(
command,
effective_timeout=timeout or self._default_timeout,
cwd=working_dir or self._working_dir,
run_env=self._build_run_env(env),
start=start,
)
except Exception as exc:
latency = (time.time() - start) * 1000
logger.warning("Shell command failed: %s%s", command, exc)
return ShellResult(
command=command,
success=False,
error=str(exc),
latency_ms=latency,
latency_ms=(time.time() - start) * 1000,
)
def status(self) -> dict:

View File

@@ -1,266 +0,0 @@
"""Matrix configuration loader utility.
Provides a typed dataclass for Matrix world configuration and a loader
that fetches settings from YAML with sensible defaults.
"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
import yaml
logger = logging.getLogger(__name__)
@dataclass
class PointLight:
"""A single point light in the Matrix world."""
color: str = "#FFFFFF"
intensity: float = 1.0
position: dict[str, float] = field(default_factory=lambda: {"x": 0, "y": 0, "z": 0})
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "PointLight":
"""Create a PointLight from a dictionary with defaults."""
return cls(
color=data.get("color", "#FFFFFF"),
intensity=data.get("intensity", 1.0),
position=data.get("position", {"x": 0, "y": 0, "z": 0}),
)
def _default_point_lights_factory() -> list[PointLight]:
"""Factory function for default point lights."""
return [
PointLight(
color="#FFAA55", # Warm amber (Workshop)
intensity=1.2,
position={"x": 0, "y": 5, "z": 0},
),
PointLight(
color="#3B82F6", # Cool blue (Matrix)
intensity=0.8,
position={"x": -5, "y": 3, "z": -5},
),
PointLight(
color="#A855F7", # Purple accent
intensity=0.6,
position={"x": 5, "y": 3, "z": 5},
),
]
@dataclass
class LightingConfig:
"""Lighting configuration for the Matrix world."""
ambient_color: str = "#FFAA55" # Warm amber (Workshop warmth)
ambient_intensity: float = 0.5
point_lights: list[PointLight] = field(default_factory=_default_point_lights_factory)
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "LightingConfig":
"""Create a LightingConfig from a dictionary with defaults."""
if data is None:
data = {}
point_lights_data = data.get("point_lights", [])
point_lights = (
[PointLight.from_dict(pl) for pl in point_lights_data]
if point_lights_data
else _default_point_lights_factory()
)
return cls(
ambient_color=data.get("ambient_color", "#FFAA55"),
ambient_intensity=data.get("ambient_intensity", 0.5),
point_lights=point_lights,
)
@dataclass
class EnvironmentConfig:
"""Environment settings for the Matrix world."""
rain_enabled: bool = False
starfield_enabled: bool = True
fog_color: str = "#0f0f23"
fog_density: float = 0.02
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "EnvironmentConfig":
"""Create an EnvironmentConfig from a dictionary with defaults."""
if data is None:
data = {}
return cls(
rain_enabled=data.get("rain_enabled", False),
starfield_enabled=data.get("starfield_enabled", True),
fog_color=data.get("fog_color", "#0f0f23"),
fog_density=data.get("fog_density", 0.02),
)
@dataclass
class FeaturesConfig:
"""Feature toggles for the Matrix world."""
chat_enabled: bool = True
visitor_avatars: bool = True
pip_familiar: bool = True
workshop_portal: bool = True
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "FeaturesConfig":
"""Create a FeaturesConfig from a dictionary with defaults."""
if data is None:
data = {}
return cls(
chat_enabled=data.get("chat_enabled", True),
visitor_avatars=data.get("visitor_avatars", True),
pip_familiar=data.get("pip_familiar", True),
workshop_portal=data.get("workshop_portal", True),
)
@dataclass
class AgentConfig:
"""Configuration for a single Matrix agent."""
name: str = ""
role: str = ""
enabled: bool = True
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "AgentConfig":
"""Create an AgentConfig from a dictionary with defaults."""
return cls(
name=data.get("name", ""),
role=data.get("role", ""),
enabled=data.get("enabled", True),
)
@dataclass
class AgentsConfig:
"""Agent registry configuration."""
default_count: int = 5
max_count: int = 20
agents: list[AgentConfig] = field(default_factory=list)
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "AgentsConfig":
"""Create an AgentsConfig from a dictionary with defaults."""
if data is None:
data = {}
agents_data = data.get("agents", [])
agents = [AgentConfig.from_dict(a) for a in agents_data] if agents_data else []
return cls(
default_count=data.get("default_count", 5),
max_count=data.get("max_count", 20),
agents=agents,
)
@dataclass
class MatrixConfig:
"""Complete Matrix world configuration.
Combines lighting, environment, features, and agent settings
into a single configuration object.
"""
lighting: LightingConfig = field(default_factory=LightingConfig)
environment: EnvironmentConfig = field(default_factory=EnvironmentConfig)
features: FeaturesConfig = field(default_factory=FeaturesConfig)
agents: AgentsConfig = field(default_factory=AgentsConfig)
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "MatrixConfig":
"""Create a MatrixConfig from a dictionary with defaults for missing sections."""
if data is None:
data = {}
return cls(
lighting=LightingConfig.from_dict(data.get("lighting")),
environment=EnvironmentConfig.from_dict(data.get("environment")),
features=FeaturesConfig.from_dict(data.get("features")),
agents=AgentsConfig.from_dict(data.get("agents")),
)
def to_dict(self) -> dict[str, Any]:
"""Convert the configuration to a plain dictionary."""
return {
"lighting": {
"ambient_color": self.lighting.ambient_color,
"ambient_intensity": self.lighting.ambient_intensity,
"point_lights": [
{
"color": pl.color,
"intensity": pl.intensity,
"position": pl.position,
}
for pl in self.lighting.point_lights
],
},
"environment": {
"rain_enabled": self.environment.rain_enabled,
"starfield_enabled": self.environment.starfield_enabled,
"fog_color": self.environment.fog_color,
"fog_density": self.environment.fog_density,
},
"features": {
"chat_enabled": self.features.chat_enabled,
"visitor_avatars": self.features.visitor_avatars,
"pip_familiar": self.features.pip_familiar,
"workshop_portal": self.features.workshop_portal,
},
"agents": {
"default_count": self.agents.default_count,
"max_count": self.agents.max_count,
"agents": [
{"name": a.name, "role": a.role, "enabled": a.enabled}
for a in self.agents.agents
],
},
}
def load_from_yaml(path: str | Path) -> MatrixConfig:
"""Load Matrix configuration from a YAML file.
Missing keys are filled with sensible defaults. If the file
cannot be read or parsed, returns a fully default configuration.
Args:
path: Path to the YAML configuration file.
Returns:
A MatrixConfig instance with loaded or default values.
"""
path = Path(path)
if not path.exists():
logger.warning("Matrix config file not found: %s, using defaults", path)
return MatrixConfig()
try:
with open(path, encoding="utf-8") as f:
raw_data = yaml.safe_load(f)
if not isinstance(raw_data, dict):
logger.warning("Matrix config invalid format, using defaults")
return MatrixConfig()
return MatrixConfig.from_dict(raw_data)
except yaml.YAMLError as exc:
logger.warning("Matrix config YAML parse error: %s, using defaults", exc)
return MatrixConfig()
except OSError as exc:
logger.warning("Matrix config read error: %s, using defaults", exc)
return MatrixConfig()

View File

@@ -1,333 +0,0 @@
"""Presence state serializer — transforms ADR-023 presence dicts for consumers.
Converts the raw presence schema (version, liveness, mood, energy, etc.)
into the camelCase world-state payload consumed by the Workshop 3D renderer
and WebSocket gateway.
"""
import logging
import time
from datetime import UTC, datetime
logger = logging.getLogger(__name__)
# Default Pip familiar state (used when familiar module unavailable)
DEFAULT_PIP_STATE = {
"name": "Pip",
"mood": "sleepy",
"energy": 0.5,
"color": "0x00b450", # emerald green
"trail_color": "0xdaa520", # gold
}
def _get_familiar_state() -> dict:
"""Get Pip familiar state from familiar module, with graceful fallback.
Returns a dict with name, mood, energy, color, and trail_color.
Falls back to default state if familiar module unavailable or raises.
"""
try:
from timmy.familiar import pip_familiar
snapshot = pip_familiar.snapshot()
# Map PipSnapshot fields to the expected agent_state format
return {
"name": snapshot.name,
"mood": snapshot.state,
"energy": DEFAULT_PIP_STATE["energy"], # Pip doesn't track energy yet
"color": DEFAULT_PIP_STATE["color"],
"trail_color": DEFAULT_PIP_STATE["trail_color"],
}
except Exception as exc:
logger.warning("Familiar state unavailable, using default: %s", exc)
return DEFAULT_PIP_STATE.copy()
# Valid bark styles for Matrix protocol
BARK_STYLES = {"speech", "thought", "whisper", "shout"}
def produce_bark(agent_id: str, text: str, reply_to: str = None, style: str = "speech") -> dict:
"""Format a chat response as a Matrix bark message.
Barks appear as floating text above agents in the Matrix 3D world with
typing animation. This function formats the text for the Matrix protocol.
Parameters
----------
agent_id:
Unique identifier for the agent (e.g. ``"timmy"``).
text:
The chat response text to display as a bark.
reply_to:
Optional message ID or reference this bark is replying to.
style:
Visual style of the bark. One of: "speech" (default), "thought",
"whisper", "shout". Invalid styles fall back to "speech".
Returns
-------
dict
Bark message with keys ``type``, ``agent_id``, ``data`` (containing
``text``, ``reply_to``, ``style``), and ``ts``.
Examples
--------
>>> produce_bark("timmy", "Hello world!")
{
"type": "bark",
"agent_id": "timmy",
"data": {"text": "Hello world!", "reply_to": None, "style": "speech"},
"ts": 1742529600,
}
"""
# Validate and normalize style
if style not in BARK_STYLES:
style = "speech"
# Truncate text to 280 characters (bark, not essay)
truncated_text = text[:280] if text else ""
return {
"type": "bark",
"agent_id": agent_id,
"data": {
"text": truncated_text,
"reply_to": reply_to,
"style": style,
},
"ts": int(time.time()),
}
def produce_thought(
agent_id: str, thought_text: str, thought_id: int, chain_id: str = None
) -> dict:
"""Format a thinking engine thought as a Matrix thought message.
Thoughts appear as subtle floating text in the 3D world, streaming from
Timmy's thinking engine (/thinking/api). This function wraps thoughts in
Matrix protocol format.
Parameters
----------
agent_id:
Unique identifier for the agent (e.g. ``"timmy"``).
thought_text:
The thought text to display. Truncated to 500 characters.
thought_id:
Unique identifier for this thought (sequence number).
chain_id:
Optional chain identifier grouping related thoughts.
Returns
-------
dict
Thought message with keys ``type``, ``agent_id``, ``data`` (containing
``text``, ``thought_id``, ``chain_id``), and ``ts``.
Examples
--------
>>> produce_thought("timmy", "Considering the options...", 42, "chain-123")
{
"type": "thought",
"agent_id": "timmy",
"data": {"text": "Considering the options...", "thought_id": 42, "chain_id": "chain-123"},
"ts": 1742529600,
}
"""
# Truncate text to 500 characters (thoughts can be longer than barks)
truncated_text = thought_text[:500] if thought_text else ""
return {
"type": "thought",
"agent_id": agent_id,
"data": {
"text": truncated_text,
"thought_id": thought_id,
"chain_id": chain_id,
},
"ts": int(time.time()),
}
def serialize_presence(presence: dict) -> dict:
"""Transform an ADR-023 presence dict into the world-state API shape.
Parameters
----------
presence:
Raw presence dict as written by
:func:`~timmy.workshop_state.get_state_dict` or read from
``~/.timmy/presence.json``.
Returns
-------
dict
CamelCase world-state payload with ``timmyState``, ``familiar``,
``activeThreads``, ``recentEvents``, ``concerns``, ``visitorPresent``,
``updatedAt``, and ``version`` keys.
"""
return {
"timmyState": {
"mood": presence.get("mood", "calm"),
"activity": presence.get("current_focus", "idle"),
"energy": presence.get("energy", 0.5),
"confidence": presence.get("confidence", 0.7),
},
"familiar": presence.get("familiar"),
"activeThreads": presence.get("active_threads", []),
"recentEvents": presence.get("recent_events", []),
"concerns": presence.get("concerns", []),
"visitorPresent": False,
"updatedAt": presence.get("liveness", datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")),
"version": presence.get("version", 1),
}
# ---------------------------------------------------------------------------
# Status mapping: ADR-023 current_focus → Matrix agent status
# ---------------------------------------------------------------------------
_STATUS_KEYWORDS: dict[str, str] = {
"thinking": "thinking",
"speaking": "speaking",
"talking": "speaking",
"idle": "idle",
}
def _derive_status(current_focus: str) -> str:
"""Map a free-text current_focus value to a Matrix status enum.
Returns one of: online, idle, thinking, speaking.
"""
focus_lower = current_focus.lower()
for keyword, status in _STATUS_KEYWORDS.items():
if keyword in focus_lower:
return status
if current_focus and current_focus != "idle":
return "online"
return "idle"
def produce_agent_state(agent_id: str, presence: dict) -> dict:
"""Build a Matrix-compatible ``agent_state`` message from presence data.
Parameters
----------
agent_id:
Unique identifier for the agent (e.g. ``"timmy"``).
presence:
Raw ADR-023 presence dict.
Returns
-------
dict
Message with keys ``type``, ``agent_id``, ``data``, and ``ts``.
"""
return {
"type": "agent_state",
"agent_id": agent_id,
"data": {
"display_name": presence.get("display_name", agent_id.title()),
"role": presence.get("role", "assistant"),
"status": _derive_status(presence.get("current_focus", "idle")),
"mood": presence.get("mood", "calm"),
"energy": presence.get("energy", 0.5),
"bark": presence.get("bark", ""),
"familiar": _get_familiar_state(),
},
"ts": int(time.time()),
}
def produce_system_status() -> dict:
"""Generate a system_status message for the Matrix.
Returns a dict with system health metrics including agent count,
visitor count, uptime, thinking engine status, and memory count.
Returns
-------
dict
Message with keys ``type``, ``data`` (containing ``agents_online``,
``visitors``, ``uptime_seconds``, ``thinking_active``, ``memory_count``),
and ``ts``.
Examples
--------
>>> produce_system_status()
{
"type": "system_status",
"data": {
"agents_online": 5,
"visitors": 2,
"uptime_seconds": 3600,
"thinking_active": True,
"memory_count": 150,
},
"ts": 1742529600,
}
"""
# Count agents with status != offline
agents_online = 0
try:
from timmy.agents.loader import list_agents
agents = list_agents()
agents_online = sum(1 for a in agents if a.get("status", "") not in ("offline", ""))
except Exception as exc:
logger.debug("Failed to count agents: %s", exc)
# Count visitors from WebSocket clients
visitors = 0
try:
from dashboard.routes.world import _ws_clients
visitors = len(_ws_clients)
except Exception as exc:
logger.debug("Failed to count visitors: %s", exc)
# Calculate uptime
uptime_seconds = 0
try:
from datetime import UTC
from config import APP_START_TIME
uptime_seconds = int((datetime.now(UTC) - APP_START_TIME).total_seconds())
except Exception as exc:
logger.debug("Failed to calculate uptime: %s", exc)
# Check thinking engine status
thinking_active = False
try:
from config import settings
from timmy.thinking import thinking_engine
thinking_active = settings.thinking_enabled and thinking_engine is not None
except Exception as exc:
logger.debug("Failed to check thinking status: %s", exc)
# Count memories in vector store
memory_count = 0
try:
from timmy.memory_system import get_memory_stats
stats = get_memory_stats()
memory_count = stats.get("total_entries", 0)
except Exception as exc:
logger.debug("Failed to count memories: %s", exc)
return {
"type": "system_status",
"data": {
"agents_online": agents_online,
"visitors": visitors,
"uptime_seconds": uptime_seconds,
"thinking_active": thinking_active,
"memory_count": memory_count,
},
"ts": int(time.time()),
}

View File

@@ -1,261 +0,0 @@
"""Shared WebSocket message protocol for the Matrix frontend.
Defines all WebSocket message types as an enum and typed dataclasses
with ``to_json()`` / ``from_json()`` helpers so every producer and the
gateway speak the same language.
Message wire format
-------------------
.. code-block:: json
{"type": "agent_state", "agent_id": "timmy", "data": {...}, "ts": 1234567890}
"""
import json
import logging
import time
from dataclasses import asdict, dataclass, field
from enum import StrEnum
from typing import Any
logger = logging.getLogger(__name__)
class MessageType(StrEnum):
"""All WebSocket message types defined by the Matrix PROTOCOL.md."""
AGENT_STATE = "agent_state"
VISITOR_STATE = "visitor_state"
BARK = "bark"
THOUGHT = "thought"
SYSTEM_STATUS = "system_status"
CONNECTION_ACK = "connection_ack"
ERROR = "error"
TASK_UPDATE = "task_update"
MEMORY_FLASH = "memory_flash"
# ---------------------------------------------------------------------------
# Base message
# ---------------------------------------------------------------------------
@dataclass
class WSMessage:
"""Base WebSocket message with common envelope fields."""
type: str
ts: float = field(default_factory=time.time)
def to_json(self) -> str:
"""Serialise the message to a JSON string."""
return json.dumps(asdict(self))
@classmethod
def from_json(cls, raw: str) -> "WSMessage":
"""Deserialise a JSON string into the correct message subclass.
Falls back to the base ``WSMessage`` when the ``type`` field is
unrecognised.
"""
data = json.loads(raw)
msg_type = data.get("type")
sub = _REGISTRY.get(msg_type)
if sub is not None:
return sub.from_json(raw)
return cls(**data)
# ---------------------------------------------------------------------------
# Concrete message types
# ---------------------------------------------------------------------------
@dataclass
class AgentStateMessage(WSMessage):
"""State update for a single agent."""
type: str = field(default=MessageType.AGENT_STATE)
agent_id: str = ""
data: dict[str, Any] = field(default_factory=dict)
@classmethod
def from_json(cls, raw: str) -> "AgentStateMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.AGENT_STATE),
ts=payload.get("ts", time.time()),
agent_id=payload.get("agent_id", ""),
data=payload.get("data", {}),
)
@dataclass
class VisitorStateMessage(WSMessage):
"""State update for a visitor / user session."""
type: str = field(default=MessageType.VISITOR_STATE)
visitor_id: str = ""
data: dict[str, Any] = field(default_factory=dict)
@classmethod
def from_json(cls, raw: str) -> "VisitorStateMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.VISITOR_STATE),
ts=payload.get("ts", time.time()),
visitor_id=payload.get("visitor_id", ""),
data=payload.get("data", {}),
)
@dataclass
class BarkMessage(WSMessage):
"""A bark (chat-like utterance) from an agent."""
type: str = field(default=MessageType.BARK)
agent_id: str = ""
content: str = ""
@classmethod
def from_json(cls, raw: str) -> "BarkMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.BARK),
ts=payload.get("ts", time.time()),
agent_id=payload.get("agent_id", ""),
content=payload.get("content", ""),
)
@dataclass
class ThoughtMessage(WSMessage):
"""An inner thought from an agent."""
type: str = field(default=MessageType.THOUGHT)
agent_id: str = ""
content: str = ""
@classmethod
def from_json(cls, raw: str) -> "ThoughtMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.THOUGHT),
ts=payload.get("ts", time.time()),
agent_id=payload.get("agent_id", ""),
content=payload.get("content", ""),
)
@dataclass
class SystemStatusMessage(WSMessage):
"""System-wide status broadcast."""
type: str = field(default=MessageType.SYSTEM_STATUS)
status: str = ""
data: dict[str, Any] = field(default_factory=dict)
@classmethod
def from_json(cls, raw: str) -> "SystemStatusMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.SYSTEM_STATUS),
ts=payload.get("ts", time.time()),
status=payload.get("status", ""),
data=payload.get("data", {}),
)
@dataclass
class ConnectionAckMessage(WSMessage):
"""Acknowledgement sent when a client connects."""
type: str = field(default=MessageType.CONNECTION_ACK)
client_id: str = ""
@classmethod
def from_json(cls, raw: str) -> "ConnectionAckMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.CONNECTION_ACK),
ts=payload.get("ts", time.time()),
client_id=payload.get("client_id", ""),
)
@dataclass
class ErrorMessage(WSMessage):
"""Error message sent to a client."""
type: str = field(default=MessageType.ERROR)
code: str = ""
message: str = ""
@classmethod
def from_json(cls, raw: str) -> "ErrorMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.ERROR),
ts=payload.get("ts", time.time()),
code=payload.get("code", ""),
message=payload.get("message", ""),
)
@dataclass
class TaskUpdateMessage(WSMessage):
"""Update about a task (created, assigned, completed, etc.)."""
type: str = field(default=MessageType.TASK_UPDATE)
task_id: str = ""
status: str = ""
data: dict[str, Any] = field(default_factory=dict)
@classmethod
def from_json(cls, raw: str) -> "TaskUpdateMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.TASK_UPDATE),
ts=payload.get("ts", time.time()),
task_id=payload.get("task_id", ""),
status=payload.get("status", ""),
data=payload.get("data", {}),
)
@dataclass
class MemoryFlashMessage(WSMessage):
"""A flash of memory — a recalled or stored memory event."""
type: str = field(default=MessageType.MEMORY_FLASH)
agent_id: str = ""
memory_key: str = ""
content: str = ""
@classmethod
def from_json(cls, raw: str) -> "MemoryFlashMessage":
payload = json.loads(raw)
return cls(
type=payload.get("type", MessageType.MEMORY_FLASH),
ts=payload.get("ts", time.time()),
agent_id=payload.get("agent_id", ""),
memory_key=payload.get("memory_key", ""),
content=payload.get("content", ""),
)
# ---------------------------------------------------------------------------
# Registry for from_json dispatch
# ---------------------------------------------------------------------------
_REGISTRY: dict[str, type[WSMessage]] = {
MessageType.AGENT_STATE: AgentStateMessage,
MessageType.VISITOR_STATE: VisitorStateMessage,
MessageType.BARK: BarkMessage,
MessageType.THOUGHT: ThoughtMessage,
MessageType.SYSTEM_STATUS: SystemStatusMessage,
MessageType.CONNECTION_ACK: ConnectionAckMessage,
MessageType.ERROR: ErrorMessage,
MessageType.TASK_UPDATE: TaskUpdateMessage,
MessageType.MEMORY_FLASH: MemoryFlashMessage,
}

View File

@@ -2,7 +2,6 @@
from .api import router
from .cascade import CascadeRouter, Provider, ProviderStatus, get_router
from .history import HealthHistoryStore, get_history_store
__all__ = [
"CascadeRouter",
@@ -10,6 +9,4 @@ __all__ = [
"ProviderStatus",
"get_router",
"router",
"HealthHistoryStore",
"get_history_store",
]

View File

@@ -8,7 +8,6 @@ from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from .cascade import CascadeRouter, get_router
from .history import HealthHistoryStore, get_history_store
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/v1/router", tags=["router"])
@@ -200,17 +199,6 @@ async def reload_config(
raise HTTPException(status_code=500, detail=f"Reload failed: {exc}") from exc
@router.get("/history")
async def get_history(
hours: int = 24,
store: Annotated[HealthHistoryStore, Depends(get_history_store)] = None,
) -> list[dict[str, Any]]:
"""Get provider health history for the last N hours."""
if store is None:
store = get_history_store()
return store.get_history(hours=hours)
@router.get("/config")
async def get_config(
cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],

View File

@@ -221,56 +221,65 @@ class CascadeRouter:
raise RuntimeError("PyYAML not installed")
content = self.config_path.read_text()
# Expand environment variables
content = self._expand_env_vars(content)
data = yaml.safe_load(content)
self.config = self._parse_router_config(data)
self._load_providers(data)
# Load cascade settings
cascade = data.get("cascade", {})
# Load fallback chains
fallback_chains = data.get("fallback_chains", {})
# Load multi-modal settings
multimodal = data.get("multimodal", {})
self.config = RouterConfig(
timeout_seconds=cascade.get("timeout_seconds", 30),
max_retries_per_provider=cascade.get("max_retries_per_provider", 2),
retry_delay_seconds=cascade.get("retry_delay_seconds", 1),
circuit_breaker_failure_threshold=cascade.get("circuit_breaker", {}).get(
"failure_threshold", 5
),
circuit_breaker_recovery_timeout=cascade.get("circuit_breaker", {}).get(
"recovery_timeout", 60
),
circuit_breaker_half_open_max_calls=cascade.get("circuit_breaker", {}).get(
"half_open_max_calls", 2
),
auto_pull_models=multimodal.get("auto_pull", True),
fallback_chains=fallback_chains,
)
# Load providers
for p_data in data.get("providers", []):
# Skip disabled providers
if not p_data.get("enabled", False):
continue
provider = Provider(
name=p_data["name"],
type=p_data["type"],
enabled=p_data.get("enabled", True),
priority=p_data.get("priority", 99),
url=p_data.get("url"),
api_key=p_data.get("api_key"),
base_url=p_data.get("base_url"),
models=p_data.get("models", []),
)
# Check if provider is actually available
if self._check_provider_available(provider):
self.providers.append(provider)
else:
logger.warning("Provider %s not available, skipping", provider.name)
# Sort by priority
self.providers.sort(key=lambda p: p.priority)
except Exception as exc:
logger.error("Failed to load config: %s", exc)
def _parse_router_config(self, data: dict) -> RouterConfig:
"""Build a RouterConfig from parsed YAML data."""
cascade = data.get("cascade", {})
cb = cascade.get("circuit_breaker", {})
multimodal = data.get("multimodal", {})
return RouterConfig(
timeout_seconds=cascade.get("timeout_seconds", 30),
max_retries_per_provider=cascade.get("max_retries_per_provider", 2),
retry_delay_seconds=cascade.get("retry_delay_seconds", 1),
circuit_breaker_failure_threshold=cb.get("failure_threshold", 5),
circuit_breaker_recovery_timeout=cb.get("recovery_timeout", 60),
circuit_breaker_half_open_max_calls=cb.get("half_open_max_calls", 2),
auto_pull_models=multimodal.get("auto_pull", True),
fallback_chains=data.get("fallback_chains", {}),
)
def _load_providers(self, data: dict) -> None:
"""Load, filter, and sort providers from parsed YAML data."""
for p_data in data.get("providers", []):
if not p_data.get("enabled", False):
continue
provider = Provider(
name=p_data["name"],
type=p_data["type"],
enabled=p_data.get("enabled", True),
priority=p_data.get("priority", 99),
url=p_data.get("url"),
api_key=p_data.get("api_key"),
base_url=p_data.get("base_url"),
models=p_data.get("models", []),
)
if self._check_provider_available(provider):
self.providers.append(provider)
else:
logger.warning("Provider %s not available, skipping", provider.name)
self.providers.sort(key=lambda p: p.priority)
def _expand_env_vars(self, content: str) -> str:
"""Expand ${VAR} syntax in YAML content.
@@ -555,7 +564,6 @@ class CascadeRouter:
messages=messages,
model=model or provider.get_default_model(),
temperature=temperature,
max_tokens=max_tokens,
content_type=content_type,
)
elif provider.type == "openai":
@@ -596,7 +604,6 @@ class CascadeRouter:
messages: list[dict],
model: str,
temperature: float,
max_tokens: int | None = None,
content_type: ContentType = ContentType.TEXT,
) -> dict:
"""Call Ollama API with multi-modal support."""
@@ -607,15 +614,13 @@ class CascadeRouter:
# Transform messages for Ollama format (including images)
transformed_messages = self._transform_messages_for_ollama(messages)
options = {"temperature": temperature}
if max_tokens:
options["num_predict"] = max_tokens
payload = {
"model": model,
"messages": transformed_messages,
"stream": False,
"options": options,
"options": {
"temperature": temperature,
},
}
timeout = aiohttp.ClientTimeout(total=self.config.timeout_seconds)
@@ -759,7 +764,7 @@ class CascadeRouter:
client = openai.AsyncOpenAI(
api_key=provider.api_key,
base_url=provider.base_url or settings.xai_base_url,
base_url=provider.base_url or "https://api.x.ai/v1",
timeout=httpx.Timeout(300.0),
)

View File

@@ -1,152 +0,0 @@
"""Provider health history — time-series snapshots for dashboard visualization."""
import asyncio
import logging
import sqlite3
from datetime import UTC, datetime, timedelta
from pathlib import Path
logger = logging.getLogger(__name__)
_store: "HealthHistoryStore | None" = None
class HealthHistoryStore:
"""Stores timestamped provider health snapshots in SQLite."""
def __init__(self, db_path: str = "data/router_history.db") -> None:
self.db_path = db_path
if db_path != ":memory:":
Path(db_path).parent.mkdir(parents=True, exist_ok=True)
self._conn = sqlite3.connect(db_path, check_same_thread=False)
self._conn.row_factory = sqlite3.Row
self._init_schema()
self._bg_task: asyncio.Task | None = None
def _init_schema(self) -> None:
self._conn.execute("""
CREATE TABLE IF NOT EXISTS snapshots (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
provider_name TEXT NOT NULL,
status TEXT NOT NULL,
error_rate REAL NOT NULL,
avg_latency_ms REAL NOT NULL,
circuit_state TEXT NOT NULL,
total_requests INTEGER NOT NULL
)
""")
self._conn.execute("""
CREATE INDEX IF NOT EXISTS idx_snapshots_ts
ON snapshots(timestamp)
""")
self._conn.commit()
def record_snapshot(self, providers: list[dict]) -> None:
"""Record a health snapshot for all providers."""
ts = datetime.now(UTC).isoformat()
rows = [
(
ts,
p["name"],
p["status"],
p["error_rate"],
p["avg_latency_ms"],
p["circuit_state"],
p["total_requests"],
)
for p in providers
]
self._conn.executemany(
"""INSERT INTO snapshots
(timestamp, provider_name, status, error_rate,
avg_latency_ms, circuit_state, total_requests)
VALUES (?, ?, ?, ?, ?, ?, ?)""",
rows,
)
self._conn.commit()
def get_history(self, hours: int = 24) -> list[dict]:
"""Return snapshots from the last N hours, grouped by timestamp."""
cutoff = (datetime.now(UTC) - timedelta(hours=hours)).isoformat()
rows = self._conn.execute(
"""SELECT timestamp, provider_name, status, error_rate,
avg_latency_ms, circuit_state, total_requests
FROM snapshots WHERE timestamp >= ? ORDER BY timestamp""",
(cutoff,),
).fetchall()
# Group by timestamp
snapshots: dict[str, list[dict]] = {}
for row in rows:
ts = row["timestamp"]
if ts not in snapshots:
snapshots[ts] = []
snapshots[ts].append(
{
"name": row["provider_name"],
"status": row["status"],
"error_rate": row["error_rate"],
"avg_latency_ms": row["avg_latency_ms"],
"circuit_state": row["circuit_state"],
"total_requests": row["total_requests"],
}
)
return [{"timestamp": ts, "providers": providers} for ts, providers in snapshots.items()]
def prune(self, keep_hours: int = 168) -> int:
"""Remove snapshots older than keep_hours. Returns rows deleted."""
cutoff = (datetime.now(UTC) - timedelta(hours=keep_hours)).isoformat()
cursor = self._conn.execute("DELETE FROM snapshots WHERE timestamp < ?", (cutoff,))
self._conn.commit()
return cursor.rowcount
def close(self) -> None:
"""Close the database connection."""
if self._bg_task and not self._bg_task.done():
self._bg_task.cancel()
self._conn.close()
def _capture_snapshot(self, cascade_router) -> None: # noqa: ANN001
"""Capture current provider state as a snapshot."""
providers = []
for p in cascade_router.providers:
providers.append(
{
"name": p.name,
"status": p.status.value,
"error_rate": round(p.metrics.error_rate, 4),
"avg_latency_ms": round(p.metrics.avg_latency_ms, 2),
"circuit_state": p.circuit_state.value,
"total_requests": p.metrics.total_requests,
}
)
self.record_snapshot(providers)
async def start_background_task(
self,
cascade_router,
interval_seconds: int = 60, # noqa: ANN001
) -> None:
"""Start periodic snapshot capture."""
async def _loop() -> None:
while True:
try:
self._capture_snapshot(cascade_router)
logger.debug("Recorded health snapshot")
except Exception:
logger.exception("Failed to record health snapshot")
await asyncio.sleep(interval_seconds)
self._bg_task = asyncio.create_task(_loop())
logger.info("Health history background task started (interval=%ds)", interval_seconds)
def get_history_store() -> HealthHistoryStore:
"""Get or create the singleton history store."""
global _store # noqa: PLW0603
if _store is None:
_store = HealthHistoryStore()
return _store

View File

@@ -1,166 +0,0 @@
"""Visitor state tracking for the Matrix frontend.
Tracks active visitors as they connect and move around the 3D world,
and provides serialization for Matrix protocol broadcast messages.
"""
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime
@dataclass
class VisitorState:
"""State for a single visitor in the Matrix.
Attributes
----------
visitor_id: Unique identifier for the visitor (client ID).
display_name: Human-readable name shown above the visitor.
position: 3D coordinates (x, y, z) in the world.
rotation: Rotation angle in degrees (0-360).
connected_at: ISO timestamp when the visitor connected.
"""
visitor_id: str
display_name: str = ""
position: dict[str, float] = field(default_factory=lambda: {"x": 0.0, "y": 0.0, "z": 0.0})
rotation: float = 0.0
connected_at: str = field(
default_factory=lambda: datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")
)
def __post_init__(self):
"""Set display_name to visitor_id if not provided; copy position dict."""
if not self.display_name:
self.display_name = self.visitor_id
# Copy position to avoid shared mutable state
self.position = dict(self.position)
class VisitorRegistry:
"""Registry of active visitors in the Matrix.
Thread-safe singleton pattern (Python GIL protects dict operations).
Used by the WebSocket layer to track and broadcast visitor positions.
"""
_instance: "VisitorRegistry | None" = None
def __new__(cls) -> "VisitorRegistry":
"""Singleton constructor."""
if cls._instance is None:
cls._instance = super().__new__(cls)
cls._instance._visitors: dict[str, VisitorState] = {}
return cls._instance
def add(
self, visitor_id: str, display_name: str = "", position: dict | None = None
) -> VisitorState:
"""Add a new visitor to the registry.
Parameters
----------
visitor_id: Unique identifier for the visitor.
display_name: Optional display name (defaults to visitor_id).
position: Optional initial position (defaults to origin).
Returns
-------
The newly created VisitorState.
"""
visitor = VisitorState(
visitor_id=visitor_id,
display_name=display_name,
position=position if position else {"x": 0.0, "y": 0.0, "z": 0.0},
)
self._visitors[visitor_id] = visitor
return visitor
def remove(self, visitor_id: str) -> bool:
"""Remove a visitor from the registry.
Parameters
----------
visitor_id: The visitor to remove.
Returns
-------
True if the visitor was found and removed, False otherwise.
"""
if visitor_id in self._visitors:
del self._visitors[visitor_id]
return True
return False
def update_position(
self,
visitor_id: str,
position: dict[str, float],
rotation: float | None = None,
) -> bool:
"""Update a visitor's position and rotation.
Parameters
----------
visitor_id: The visitor to update.
position: New 3D coordinates (x, y, z).
rotation: Optional new rotation angle.
Returns
-------
True if the visitor was found and updated, False otherwise.
"""
if visitor_id not in self._visitors:
return False
self._visitors[visitor_id].position = position
if rotation is not None:
self._visitors[visitor_id].rotation = rotation
return True
def get(self, visitor_id: str) -> VisitorState | None:
"""Get a single visitor's state.
Parameters
----------
visitor_id: The visitor to retrieve.
Returns
-------
The VisitorState if found, None otherwise.
"""
return self._visitors.get(visitor_id)
def get_all(self) -> list[dict]:
"""Get all active visitors as Matrix protocol message dicts.
Returns
-------
List of visitor_state dicts ready for WebSocket broadcast.
Each dict has: type, visitor_id, data (with display_name,
position, rotation, connected_at), and ts.
"""
now = int(time.time())
return [
{
"type": "visitor_state",
"visitor_id": v.visitor_id,
"data": {
"display_name": v.display_name,
"position": v.position,
"rotation": v.rotation,
"connected_at": v.connected_at,
},
"ts": now,
}
for v in self._visitors.values()
]
def clear(self) -> None:
"""Remove all visitors (useful for testing)."""
self._visitors.clear()
def __len__(self) -> int:
"""Return the number of active visitors."""
return len(self._visitors)

View File

@@ -1,29 +0,0 @@
"""World interface — engine-agnostic adapter pattern for embodied agents.
Provides the ``WorldInterface`` ABC and an adapter registry so Timmy can
observe, act, and speak in any game world (Morrowind, Luanti, Godot, …)
through a single contract.
Quick start::
from infrastructure.world import get_adapter, register_adapter
from infrastructure.world.interface import WorldInterface
register_adapter("mock", MockWorldAdapter)
world = get_adapter("mock")
perception = world.observe()
"""
from infrastructure.world.registry import AdapterRegistry
_registry = AdapterRegistry()
register_adapter = _registry.register
get_adapter = _registry.get
list_adapters = _registry.list_adapters
__all__ = [
"register_adapter",
"get_adapter",
"list_adapters",
]

View File

@@ -1 +0,0 @@
"""Built-in world adapters."""

View File

@@ -1,99 +0,0 @@
"""Mock world adapter — returns canned perception and logs commands.
Useful for testing the heartbeat loop and WorldInterface contract
without a running game server.
"""
from __future__ import annotations
import logging
from dataclasses import dataclass
from datetime import UTC, datetime
from infrastructure.world.interface import WorldInterface
from infrastructure.world.types import (
ActionResult,
ActionStatus,
CommandInput,
PerceptionOutput,
)
logger = logging.getLogger(__name__)
@dataclass
class _ActionLog:
"""Record of an action dispatched to the mock world."""
command: CommandInput
timestamp: datetime
class MockWorldAdapter(WorldInterface):
"""In-memory mock adapter for testing.
* ``observe()`` returns configurable canned perception.
* ``act()`` logs the command and returns success.
* ``speak()`` logs the message.
Inspect ``action_log`` and ``speech_log`` to verify behaviour in tests.
"""
def __init__(
self,
*,
location: str = "Test Chamber",
entities: list[str] | None = None,
events: list[str] | None = None,
) -> None:
self._location = location
self._entities = entities or ["TestNPC"]
self._events = events or []
self._connected = False
self.action_log: list[_ActionLog] = []
self.speech_log: list[dict] = []
# -- lifecycle ---------------------------------------------------------
def connect(self) -> None:
self._connected = True
logger.info("MockWorldAdapter connected")
def disconnect(self) -> None:
self._connected = False
logger.info("MockWorldAdapter disconnected")
@property
def is_connected(self) -> bool:
return self._connected
# -- core contract -----------------------------------------------------
def observe(self) -> PerceptionOutput:
logger.debug("MockWorldAdapter.observe()")
return PerceptionOutput(
timestamp=datetime.now(UTC),
location=self._location,
entities=list(self._entities),
events=list(self._events),
raw={"adapter": "mock"},
)
def act(self, command: CommandInput) -> ActionResult:
logger.debug("MockWorldAdapter.act(%s)", command.action)
self.action_log.append(_ActionLog(command=command, timestamp=datetime.now(UTC)))
return ActionResult(
status=ActionStatus.SUCCESS,
message=f"Mock executed: {command.action}",
data={"adapter": "mock"},
)
def speak(self, message: str, target: str | None = None) -> None:
logger.debug("MockWorldAdapter.speak(%r, target=%r)", message, target)
self.speech_log.append(
{
"message": message,
"target": target,
"timestamp": datetime.now(UTC).isoformat(),
}
)

View File

@@ -1,58 +0,0 @@
"""TES3MP world adapter — stub for Morrowind multiplayer via TES3MP.
This adapter will eventually connect to a TES3MP server and translate
the WorldInterface contract into TES3MP commands. For now every method
raises ``NotImplementedError`` with guidance on what needs wiring up.
Once PR #864 merges, import PerceptionOutput and CommandInput directly
from ``infrastructure.morrowind.schemas`` if their shapes differ from
the canonical types in ``infrastructure.world.types``.
"""
from __future__ import annotations
import logging
from infrastructure.world.interface import WorldInterface
from infrastructure.world.types import ActionResult, CommandInput, PerceptionOutput
logger = logging.getLogger(__name__)
class TES3MPWorldAdapter(WorldInterface):
"""Stub adapter for TES3MP (Morrowind multiplayer).
All core methods raise ``NotImplementedError``.
Implement ``connect()`` first — it should open a socket to the
TES3MP server and authenticate.
"""
def __init__(self, *, host: str = "localhost", port: int = 25565) -> None:
self._host = host
self._port = port
self._connected = False
# -- lifecycle ---------------------------------------------------------
def connect(self) -> None:
raise NotImplementedError("TES3MPWorldAdapter.connect() — wire up TES3MP server socket")
def disconnect(self) -> None:
raise NotImplementedError("TES3MPWorldAdapter.disconnect() — close TES3MP server socket")
@property
def is_connected(self) -> bool:
return self._connected
# -- core contract (stubs) ---------------------------------------------
def observe(self) -> PerceptionOutput:
raise NotImplementedError("TES3MPWorldAdapter.observe() — poll TES3MP for player/NPC state")
def act(self, command: CommandInput) -> ActionResult:
raise NotImplementedError(
"TES3MPWorldAdapter.act() — translate CommandInput to TES3MP packet"
)
def speak(self, message: str, target: str | None = None) -> None:
raise NotImplementedError("TES3MPWorldAdapter.speak() — send chat message via TES3MP")

View File

@@ -1,64 +0,0 @@
"""Abstract WorldInterface — the contract every game-world adapter must fulfil.
Follows a Gymnasium-inspired pattern: observe → act → speak, with each
method returning strongly-typed data structures.
Any future engine (TES3MP, Luanti, Godot, …) plugs in by subclassing
``WorldInterface`` and implementing the three methods.
"""
from __future__ import annotations
from abc import ABC, abstractmethod
from infrastructure.world.types import ActionResult, CommandInput, PerceptionOutput
class WorldInterface(ABC):
"""Engine-agnostic base class for world adapters.
Subclasses must implement:
- ``observe()`` — gather structured perception from the world
- ``act()`` — dispatch a command and return the outcome
- ``speak()`` — send a message to an NPC / player / broadcast
Lifecycle hooks ``connect()`` and ``disconnect()`` are optional.
"""
# -- lifecycle (optional overrides) ------------------------------------
def connect(self) -> None: # noqa: B027
"""Establish connection to the game world.
Default implementation is a no-op. Override to open sockets,
authenticate, etc.
"""
def disconnect(self) -> None: # noqa: B027
"""Tear down the connection.
Default implementation is a no-op.
"""
@property
def is_connected(self) -> bool:
"""Return ``True`` if the adapter has an active connection.
Default returns ``True``. Override for adapters that maintain
persistent connections.
"""
return True
# -- core contract (must implement) ------------------------------------
@abstractmethod
def observe(self) -> PerceptionOutput:
"""Return a structured snapshot of the current world state."""
@abstractmethod
def act(self, command: CommandInput) -> ActionResult:
"""Execute *command* in the world and return the result."""
@abstractmethod
def speak(self, message: str, target: str | None = None) -> None:
"""Send *message* in the world, optionally directed at *target*."""

View File

@@ -1,54 +0,0 @@
"""Adapter registry — register and instantiate world adapters by name.
Usage::
registry = AdapterRegistry()
registry.register("mock", MockWorldAdapter)
adapter = registry.get("mock", some_kwarg="value")
"""
from __future__ import annotations
import logging
from typing import Any
from infrastructure.world.interface import WorldInterface
logger = logging.getLogger(__name__)
class AdapterRegistry:
"""Name → WorldInterface class registry with instantiation."""
def __init__(self) -> None:
self._adapters: dict[str, type[WorldInterface]] = {}
def register(self, name: str, cls: type[WorldInterface]) -> None:
"""Register an adapter class under *name*.
Raises ``TypeError`` if *cls* is not a ``WorldInterface`` subclass.
"""
if not (isinstance(cls, type) and issubclass(cls, WorldInterface)):
raise TypeError(f"{cls!r} is not a WorldInterface subclass")
if name in self._adapters:
logger.warning("Overwriting adapter %r (was %r)", name, self._adapters[name])
self._adapters[name] = cls
logger.info("Registered world adapter: %s%s", name, cls.__name__)
def get(self, name: str, **kwargs: Any) -> WorldInterface:
"""Instantiate and return the adapter registered as *name*.
Raises ``KeyError`` if *name* is not registered.
"""
cls = self._adapters[name]
return cls(**kwargs)
def list_adapters(self) -> list[str]:
"""Return sorted list of registered adapter names."""
return sorted(self._adapters)
def __contains__(self, name: str) -> bool:
return name in self._adapters
def __len__(self) -> int:
return len(self._adapters)

View File

@@ -1,71 +0,0 @@
"""Canonical data types for world interaction.
These mirror the PerceptionOutput / CommandInput types from PR #864's
``morrowind/schemas.py``. When that PR merges, these can be replaced
with re-exports — but until then they serve as the stable contract for
every WorldInterface adapter.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import UTC, datetime
from enum import StrEnum
class ActionStatus(StrEnum):
"""Outcome of an action dispatched to the world."""
SUCCESS = "success"
FAILURE = "failure"
PENDING = "pending"
NOOP = "noop"
@dataclass
class PerceptionOutput:
"""Structured world state returned by ``WorldInterface.observe()``.
Attributes:
timestamp: When the observation was captured.
location: Free-form location descriptor (e.g. "Balmora, Fighters Guild").
entities: List of nearby entity descriptions.
events: Recent game events since last observation.
raw: Optional raw / engine-specific payload for advanced consumers.
"""
timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
location: str = ""
entities: list[str] = field(default_factory=list)
events: list[str] = field(default_factory=list)
raw: dict = field(default_factory=dict)
@dataclass
class CommandInput:
"""Action command sent via ``WorldInterface.act()``.
Attributes:
action: Verb / action name (e.g. "move", "attack", "use_item").
target: Optional target identifier.
parameters: Arbitrary key-value payload for engine-specific params.
"""
action: str
target: str | None = None
parameters: dict = field(default_factory=dict)
@dataclass
class ActionResult:
"""Outcome returned by ``WorldInterface.act()``.
Attributes:
status: Whether the action succeeded, failed, etc.
message: Human-readable description of the outcome.
data: Arbitrary engine-specific result payload.
"""
status: ActionStatus = ActionStatus.SUCCESS
message: str = ""
data: dict = field(default_factory=dict)

View File

@@ -515,36 +515,25 @@ class DiscordVendor(ChatPlatform):
async def _handle_message(self, message) -> None:
"""Process an incoming message and respond via a thread."""
content = self._extract_content(message)
if not content:
return
thread = await self._get_or_create_thread(message)
target = thread or message.channel
session_id = f"discord_{thread.id}" if thread else f"discord_{message.channel.id}"
run_output, response = await self._invoke_agent(content, session_id, target)
if run_output is not None:
await self._handle_paused_run(run_output, target, session_id)
raw_content = run_output.content if hasattr(run_output, "content") else ""
response = _clean_response(raw_content or "")
await self._send_response(response, target)
def _extract_content(self, message) -> str:
"""Strip the bot mention and return clean message text."""
# Strip the bot mention from the message content
content = message.content
if self._client.user:
content = content.replace(f"<@{self._client.user.id}>", "").strip()
return content
async def _invoke_agent(self, content: str, session_id: str, target):
"""Run chat_with_tools with a typing indicator and timeout.
if not content:
return
Returns a (run_output, error_response) tuple. On success the
error_response is ``None``; on failure run_output is ``None``.
"""
# Create or reuse a thread for this conversation
thread = await self._get_or_create_thread(message)
target = thread or message.channel
# Derive session_id for per-conversation history via Agno's SQLite
if thread:
session_id = f"discord_{thread.id}"
else:
session_id = f"discord_{message.channel.id}"
# Run Timmy agent with typing indicator and timeout
run_output = None
response = None
try:
@@ -559,57 +548,51 @@ class DiscordVendor(ChatPlatform):
except Exception as exc:
logger.error("Discord: chat_with_tools() failed: %s", exc)
response = "I'm having trouble reaching my inference backend right now. Please try again shortly."
return run_output, response
async def _handle_paused_run(self, run_output, target, session_id: str) -> None:
"""If Agno paused the run for tool confirmation, enqueue approvals."""
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
# Check if Agno paused the run for tool confirmation
if run_output is not None:
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
if not (is_paused and getattr(run_output, "active_requirements", None)):
return
if is_paused and getattr(run_output, "active_requirements", None):
from config import settings
from config import settings
if settings.discord_confirm_actions:
for req in run_output.active_requirements:
if getattr(req, "needs_confirmation", False):
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
if not settings.discord_confirm_actions:
return
from timmy.approvals import create_item
for req in run_output.active_requirements:
if not getattr(req, "needs_confirmation", False):
continue
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
item = create_item(
title=f"Discord: {tool_name}",
description=_format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=_get_impact_level(tool_name),
)
self._pending_actions[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
"target": target,
"session_id": session_id,
}
await self._send_confirmation(target, tool_name, tool_args, item.id)
from timmy.approvals import create_item
raw_content = run_output.content if hasattr(run_output, "content") else ""
response = _clean_response(raw_content or "")
item = create_item(
title=f"Discord: {tool_name}",
description=_format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=_get_impact_level(tool_name),
)
self._pending_actions[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
"target": target,
"session_id": session_id,
}
await self._send_confirmation(target, tool_name, tool_args, item.id)
@staticmethod
async def _send_response(response: str | None, target) -> None:
"""Send a response to Discord, chunked to the 2000-char limit."""
if not response or not response.strip():
return
for chunk in _chunk_message(response, 2000):
try:
await target.send(chunk)
except Exception as exc:
logger.error("Discord: failed to send message chunk: %s", exc)
break
# Discord has a 2000 character limit — send with error handling
if response and response.strip():
for chunk in _chunk_message(response, 2000):
try:
await target.send(chunk)
except Exception as exc:
logger.error("Discord: failed to send message chunk: %s", exc)
break
async def _get_or_create_thread(self, message):
"""Get the active thread for a channel, or create one.

View File

@@ -1 +0,0 @@
"""Lightning Network integration for tool-usage micro-payments."""

View File

@@ -1,69 +0,0 @@
"""Lightning backend factory.
Returns a mock or real LND backend based on ``settings.lightning_backend``.
"""
from __future__ import annotations
import hashlib
import logging
import secrets
from dataclasses import dataclass
from config import settings
logger = logging.getLogger(__name__)
@dataclass
class Invoice:
"""Minimal Lightning invoice representation."""
payment_hash: str
payment_request: str
amount_sats: int
memo: str
class MockBackend:
"""In-memory mock Lightning backend for development and testing."""
def create_invoice(self, amount_sats: int, memo: str = "") -> Invoice:
"""Create a fake invoice with a random payment hash."""
raw = secrets.token_bytes(32)
payment_hash = hashlib.sha256(raw).hexdigest()
payment_request = f"lnbc{amount_sats}mock{payment_hash[:20]}"
logger.debug("Mock invoice: %s sats — %s", amount_sats, payment_hash[:12])
return Invoice(
payment_hash=payment_hash,
payment_request=payment_request,
amount_sats=amount_sats,
memo=memo,
)
# Singleton — lazily created
_backend: MockBackend | None = None
def get_backend() -> MockBackend:
"""Return the configured Lightning backend (currently mock-only).
Raises ``ValueError`` if an unsupported backend is requested.
"""
global _backend # noqa: PLW0603
if _backend is not None:
return _backend
kind = settings.lightning_backend
if kind == "mock":
_backend = MockBackend()
elif kind == "lnd":
# LND gRPC integration is on the roadmap — for now fall back to mock.
logger.warning("LND backend not yet implemented — using mock")
_backend = MockBackend()
else:
raise ValueError(f"Unknown lightning_backend: {kind!r}")
logger.info("Lightning backend: %s", kind)
return _backend

View File

@@ -1,146 +0,0 @@
"""In-memory Lightning transaction ledger.
Tracks invoices, settlements, and balances per the schema in
``docs/adr/018-lightning-ledger.md``. Uses a simple in-memory list so the
dashboard can display real (ephemeral) data without requiring SQLite yet.
"""
from __future__ import annotations
import logging
import uuid
from dataclasses import dataclass
from datetime import UTC, datetime
from enum import StrEnum
logger = logging.getLogger(__name__)
class TxType(StrEnum):
incoming = "incoming"
outgoing = "outgoing"
class TxStatus(StrEnum):
pending = "pending"
settled = "settled"
failed = "failed"
expired = "expired"
@dataclass
class LedgerEntry:
"""Single ledger row matching the ADR-018 schema."""
id: str
tx_type: TxType
status: TxStatus
payment_hash: str
amount_sats: int
memo: str
source: str
created_at: str
invoice: str = ""
preimage: str = ""
task_id: str = ""
agent_id: str = ""
settled_at: str = ""
fee_sats: int = 0
# ── In-memory store ──────────────────────────────────────────────────
_entries: list[LedgerEntry] = []
def create_invoice_entry(
payment_hash: str,
amount_sats: int,
memo: str = "",
source: str = "tool_usage",
task_id: str = "",
agent_id: str = "",
invoice: str = "",
) -> LedgerEntry:
"""Record a new incoming invoice in the ledger."""
entry = LedgerEntry(
id=uuid.uuid4().hex[:16],
tx_type=TxType.incoming,
status=TxStatus.pending,
payment_hash=payment_hash,
amount_sats=amount_sats,
memo=memo,
source=source,
task_id=task_id,
agent_id=agent_id,
invoice=invoice,
created_at=datetime.now(UTC).isoformat(),
)
_entries.append(entry)
logger.debug("Ledger entry created: %s (%s sats)", entry.id, amount_sats)
return entry
def mark_settled(payment_hash: str, preimage: str = "") -> LedgerEntry | None:
"""Mark a pending entry as settled by payment hash."""
for entry in _entries:
if entry.payment_hash == payment_hash and entry.status == TxStatus.pending:
entry.status = TxStatus.settled
entry.preimage = preimage
entry.settled_at = datetime.now(UTC).isoformat()
logger.debug("Ledger settled: %s", payment_hash[:12])
return entry
return None
def get_balance() -> dict:
"""Compute the current balance from settled and pending entries."""
incoming_total = sum(
e.amount_sats
for e in _entries
if e.tx_type == TxType.incoming and e.status == TxStatus.settled
)
outgoing_total = sum(
e.amount_sats
for e in _entries
if e.tx_type == TxType.outgoing and e.status == TxStatus.settled
)
fees = sum(e.fee_sats for e in _entries if e.status == TxStatus.settled)
pending_in = sum(
e.amount_sats
for e in _entries
if e.tx_type == TxType.incoming and e.status == TxStatus.pending
)
pending_out = sum(
e.amount_sats
for e in _entries
if e.tx_type == TxType.outgoing and e.status == TxStatus.pending
)
net = incoming_total - outgoing_total - fees
return {
"incoming_total_sats": incoming_total,
"outgoing_total_sats": outgoing_total,
"fees_paid_sats": fees,
"net_sats": net,
"pending_incoming_sats": pending_in,
"pending_outgoing_sats": pending_out,
"available_sats": net - pending_out,
}
def get_transactions(
tx_type: str | None = None,
status: str | None = None,
limit: int = 50,
) -> list[LedgerEntry]:
"""Return ledger entries, optionally filtered."""
result = _entries
if tx_type:
result = [e for e in result if e.tx_type.value == tx_type]
if status:
result = [e for e in result if e.status.value == status]
return list(reversed(result))[:limit]
def clear() -> None:
"""Reset the ledger (for testing)."""
_entries.clear()

View File

@@ -1,286 +0,0 @@
"""Heartbeat v2 — WorldInterface-driven cognitive loop.
Drives real observe → reason → act → reflect cycles through whatever
``WorldInterface`` adapter is connected. When no adapter is present,
gracefully falls back to the existing ``run_cycle()`` behaviour.
Usage::
heartbeat = Heartbeat(world=adapter, interval=30.0)
await heartbeat.run_once() # single cycle
await heartbeat.start() # background loop
heartbeat.stop() # graceful shutdown
"""
from __future__ import annotations
import asyncio
import logging
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime
from loop.phase1_gather import gather
from loop.phase2_reason import reason
from loop.phase3_act import act
from loop.schema import ContextPayload
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Cycle log entry
# ---------------------------------------------------------------------------
@dataclass
class CycleRecord:
"""One observe → reason → act → reflect cycle."""
cycle_id: int
timestamp: str
observation: dict = field(default_factory=dict)
reasoning_summary: str = ""
action_taken: str = ""
action_status: str = ""
reflect_notes: str = ""
duration_ms: int = 0
# ---------------------------------------------------------------------------
# Heartbeat
# ---------------------------------------------------------------------------
class Heartbeat:
"""Manages the recurring cognitive loop with optional world adapter.
Parameters
----------
world:
A ``WorldInterface`` instance (or ``None`` for passive mode).
interval:
Seconds between heartbeat ticks. 30 s for embodied mode,
300 s (5 min) for passive thinking.
on_cycle:
Optional async callback invoked after each cycle with the
``CycleRecord``.
"""
def __init__(
self,
*,
world=None, # WorldInterface | None
interval: float = 30.0,
on_cycle=None, # Callable[[CycleRecord], Awaitable[None]] | None
) -> None:
self._world = world
self._interval = interval
self._on_cycle = on_cycle
self._cycle_count: int = 0
self._running = False
self._task: asyncio.Task | None = None
self.history: list[CycleRecord] = []
# -- properties --------------------------------------------------------
@property
def world(self):
return self._world
@world.setter
def world(self, adapter) -> None:
self._world = adapter
@property
def interval(self) -> float:
return self._interval
@interval.setter
def interval(self, value: float) -> None:
self._interval = max(1.0, value)
@property
def is_running(self) -> bool:
return self._running
@property
def cycle_count(self) -> int:
return self._cycle_count
# -- single cycle ------------------------------------------------------
async def run_once(self) -> CycleRecord:
"""Execute one full heartbeat cycle.
If a world adapter is present:
1. Observe — ``world.observe()``
2. Gather + Reason + Act via the three-phase loop, with the
observation injected into the payload
3. Dispatch the decided action back to ``world.act()``
4. Reflect — log the cycle
Without an adapter the existing loop runs on a timer-sourced
payload (passive thinking).
"""
self._cycle_count += 1
start = time.monotonic()
record = CycleRecord(
cycle_id=self._cycle_count,
timestamp=datetime.now(UTC).isoformat(),
)
if self._world is not None:
record = await self._embodied_cycle(record)
else:
record = await self._passive_cycle(record)
record.duration_ms = int((time.monotonic() - start) * 1000)
self.history.append(record)
# Broadcast via WebSocket (best-effort)
await self._broadcast(record)
if self._on_cycle:
await self._on_cycle(record)
logger.info(
"Heartbeat cycle #%d complete (%d ms) — action=%s status=%s",
record.cycle_id,
record.duration_ms,
record.action_taken or "(passive)",
record.action_status or "n/a",
)
return record
# -- background loop ---------------------------------------------------
async def start(self) -> None:
"""Start the recurring heartbeat loop as a background task."""
if self._running:
logger.warning("Heartbeat already running")
return
self._running = True
self._task = asyncio.current_task() or asyncio.ensure_future(self._loop())
if self._task is not asyncio.current_task():
return
await self._loop()
async def _loop(self) -> None:
logger.info(
"Heartbeat loop started (interval=%.1fs, adapter=%s)",
self._interval,
type(self._world).__name__ if self._world else "None",
)
while self._running:
try:
await self.run_once()
except Exception:
logger.exception("Heartbeat cycle failed")
await asyncio.sleep(self._interval)
def stop(self) -> None:
"""Signal the heartbeat loop to stop after the current cycle."""
self._running = False
logger.info("Heartbeat stop requested")
# -- internal: embodied cycle ------------------------------------------
async def _embodied_cycle(self, record: CycleRecord) -> CycleRecord:
"""Cycle with a live world adapter: observe → reason → act → reflect."""
from infrastructure.world.types import ActionStatus, CommandInput
# 1. Observe
perception = self._world.observe()
record.observation = {
"location": perception.location,
"entities": perception.entities,
"events": perception.events,
}
# 2. Feed observation into the three-phase loop
obs_content = (
f"Location: {perception.location}\n"
f"Entities: {', '.join(perception.entities)}\n"
f"Events: {', '.join(perception.events)}"
)
payload = ContextPayload(
source="world",
content=obs_content,
metadata={"perception": record.observation},
)
gathered = gather(payload)
reasoned = reason(gathered)
acted = act(reasoned)
# Extract action decision from the acted payload
action_name = acted.metadata.get("action", "idle")
action_target = acted.metadata.get("action_target")
action_params = acted.metadata.get("action_params", {})
record.reasoning_summary = acted.metadata.get("reasoning", acted.content[:200])
# 3. Dispatch action to world
if action_name != "idle":
cmd = CommandInput(
action=action_name,
target=action_target,
parameters=action_params,
)
result = self._world.act(cmd)
record.action_taken = action_name
record.action_status = result.status.value
else:
record.action_taken = "idle"
record.action_status = ActionStatus.NOOP.value
# 4. Reflect
record.reflect_notes = (
f"Observed {len(perception.entities)} entities at {perception.location}. "
f"Action: {record.action_taken}{record.action_status}."
)
return record
# -- internal: passive cycle -------------------------------------------
async def _passive_cycle(self, record: CycleRecord) -> CycleRecord:
"""Cycle without a world adapter — existing think_once() behaviour."""
payload = ContextPayload(
source="timer",
content="heartbeat",
metadata={"mode": "passive"},
)
gathered = gather(payload)
reasoned = reason(gathered)
acted = act(reasoned)
record.reasoning_summary = acted.content[:200]
record.action_taken = "think"
record.action_status = "noop"
record.reflect_notes = "Passive thinking cycle — no world adapter connected."
return record
# -- broadcast ---------------------------------------------------------
async def _broadcast(self, record: CycleRecord) -> None:
"""Emit heartbeat cycle data via WebSocket (best-effort)."""
try:
from infrastructure.ws_manager.handler import ws_manager
await ws_manager.broadcast(
"heartbeat.cycle",
{
"cycle_id": record.cycle_id,
"timestamp": record.timestamp,
"action": record.action_taken,
"action_status": record.action_status,
"reasoning_summary": record.reasoning_summary[:300],
"observation": record.observation,
"duration_ms": record.duration_ms,
},
)
except (ImportError, AttributeError, ConnectionError, RuntimeError) as exc:
logger.debug("Heartbeat broadcast skipped: %s", exc)

View File

@@ -17,9 +17,9 @@ logger = logging.getLogger(__name__)
def gather(payload: ContextPayload) -> ContextPayload:
"""Accept raw input and return structured context for reasoning.
When the payload carries a ``perception`` dict in metadata (injected by
the heartbeat loop from a WorldInterface adapter), that observation is
folded into the gathered context. Otherwise behaves as before.
Stub: tags the payload with phase=gather and logs transit.
Timmy will flesh this out with context selection, memory lookup,
adapter polling, and attention-residual weighting.
"""
logger.info(
"Phase 1 (Gather) received: source=%s content_len=%d tokens=%d",
@@ -28,20 +28,7 @@ def gather(payload: ContextPayload) -> ContextPayload:
payload.token_count,
)
extra: dict = {"phase": "gather", "gathered": True}
# Enrich with world observation when present
perception = payload.metadata.get("perception")
if perception:
extra["world_observation"] = perception
logger.info(
"Phase 1 (Gather) world observation: location=%s entities=%d events=%d",
perception.get("location", "?"),
len(perception.get("entities", [])),
len(perception.get("events", [])),
)
result = payload.with_metadata(**extra)
result = payload.with_metadata(phase="gather", gathered=True)
logger.info(
"Phase 1 (Gather) produced: metadata_keys=%s",

View File

@@ -119,84 +119,75 @@ class BaseAgent(ABC):
"""
pass
# Transient errors that indicate Ollama contention or temporary
# unavailability — these deserve a retry with backoff.
_TRANSIENT = (
httpx.ConnectError,
httpx.ReadError,
httpx.ReadTimeout,
httpx.ConnectTimeout,
ConnectionError,
TimeoutError,
)
async def run(self, message: str) -> str:
"""Run the agent with a message.
async def run(self, message: str, *, max_retries: int = 3) -> str:
"""Run the agent with a message, retrying on transient failures.
Retries on transient failures (connection errors, timeouts) with
exponential backoff. GPU contention from concurrent Ollama
requests causes ReadError / ReadTimeout — these are transient
and should be retried, not raised immediately (#70).
GPU contention from concurrent Ollama requests causes ReadError /
ReadTimeout — these are transient and retried with exponential
backoff (#70).
Returns:
Agent response
"""
response = await self._run_with_retries(message, max_retries)
await self._emit_response_event(message, response)
return response
max_retries = 3
last_exception = None
# Transient errors that indicate Ollama contention or temporary
# unavailability — these deserve a retry with backoff.
_transient = (
httpx.ConnectError,
httpx.ReadError,
httpx.ReadTimeout,
httpx.ConnectTimeout,
ConnectionError,
TimeoutError,
)
async def _run_with_retries(self, message: str, max_retries: int) -> str:
"""Execute agent.run() with retry logic for transient errors."""
for attempt in range(1, max_retries + 1):
try:
result = self.agent.run(message, stream=False)
return result.content if hasattr(result, "content") else str(result)
except self._TRANSIENT as exc:
self._handle_retry_or_raise(
exc,
attempt,
max_retries,
transient=True,
)
await asyncio.sleep(min(2**attempt, 16))
response = result.content if hasattr(result, "content") else str(result)
break # Success, exit the retry loop
except _transient as exc:
last_exception = exc
if attempt < max_retries:
# Contention backoff — longer waits because the GPU
# needs time to finish the other request.
wait = min(2**attempt, 16)
logger.warning(
"Ollama contention on attempt %d/%d: %s. Waiting %ds before retry...",
attempt,
max_retries,
type(exc).__name__,
wait,
)
await asyncio.sleep(wait)
else:
logger.error(
"Ollama unreachable after %d attempts: %s",
max_retries,
exc,
)
raise last_exception from exc
except Exception as exc:
self._handle_retry_or_raise(
exc,
attempt,
max_retries,
transient=False,
)
await asyncio.sleep(min(2 ** (attempt - 1), 8))
# Unreachable — _handle_retry_or_raise raises on last attempt.
raise RuntimeError("retry loop exited unexpectedly") # pragma: no cover
last_exception = exc
if attempt < max_retries:
logger.warning(
"Agent run failed on attempt %d/%d: %s. Retrying...",
attempt,
max_retries,
exc,
)
await asyncio.sleep(min(2 ** (attempt - 1), 8))
else:
logger.error(
"Agent run failed after %d attempts: %s",
max_retries,
exc,
)
raise last_exception from exc
@staticmethod
def _handle_retry_or_raise(
exc: Exception,
attempt: int,
max_retries: int,
*,
transient: bool,
) -> None:
"""Log a retry warning or raise after exhausting attempts."""
if attempt < max_retries:
if transient:
logger.warning(
"Ollama contention on attempt %d/%d: %s. Waiting before retry...",
attempt,
max_retries,
type(exc).__name__,
)
else:
logger.warning(
"Agent run failed on attempt %d/%d: %s. Retrying...",
attempt,
max_retries,
exc,
)
else:
label = "Ollama unreachable" if transient else "Agent run failed"
logger.error("%s after %d attempts: %s", label, max_retries, exc)
raise exc
async def _emit_response_event(self, message: str, response: str) -> None:
"""Publish a completion event to the event bus if connected."""
# Emit completion event
if self.event_bus:
await self.event_bus.publish(
Event(
@@ -206,6 +197,8 @@ class BaseAgent(ABC):
)
)
return response
def get_capabilities(self) -> list[str]:
"""Get list of capabilities this agent provides."""
return self.tools

View File

@@ -102,11 +102,9 @@ class GrokBackend:
import httpx
from openai import OpenAI
from config import settings
return OpenAI(
api_key=self._api_key,
base_url=settings.xai_base_url,
base_url="https://api.x.ai/v1",
timeout=httpx.Timeout(300.0),
)
@@ -115,11 +113,9 @@ class GrokBackend:
import httpx
from openai import AsyncOpenAI
from config import settings
return AsyncOpenAI(
api_key=self._api_key,
base_url=settings.xai_base_url,
base_url="https://api.x.ai/v1",
timeout=httpx.Timeout(300.0),
)
@@ -264,7 +260,6 @@ class GrokBackend:
},
}
except Exception as exc:
logger.exception("Grok health check failed")
return {
"ok": False,
"error": str(exc),
@@ -431,7 +426,6 @@ class ClaudeBackend:
)
return {"ok": True, "error": None, "backend": "claude", "model": self._model}
except Exception as exc:
logger.exception("Claude health check failed")
return {"ok": False, "error": str(exc), "backend": "claude", "model": self._model}
# ── Private helpers ───────────────────────────────────────────────────

View File

@@ -37,68 +37,6 @@ def _is_interactive() -> bool:
return hasattr(sys.stdin, "isatty") and sys.stdin.isatty()
def _read_message_input(message: list[str]) -> str:
"""Join CLI args into a message, reading from stdin when requested.
Returns the final message string. Raises ``typer.Exit(1)`` when
stdin is explicitly requested (``-``) but empty.
"""
message_str = " ".join(message)
if message_str == "-" or not _is_interactive():
try:
stdin_content = sys.stdin.read().strip()
except (KeyboardInterrupt, EOFError):
stdin_content = ""
if stdin_content:
message_str = stdin_content
elif message_str == "-":
typer.echo("No input provided via stdin.", err=True)
raise typer.Exit(1)
return message_str
def _resolve_session_id(session_id: str | None, new_session: bool) -> str:
"""Return the effective session ID for a chat invocation."""
import uuid
if session_id is not None:
return session_id
if new_session:
return str(uuid.uuid4())
return _CLI_SESSION_ID
def _prompt_interactive(req, tool_name: str, tool_args: dict) -> None:
"""Display tool details and prompt the human for approval."""
description = format_action_description(tool_name, tool_args)
impact = get_impact_level(tool_name)
typer.echo()
typer.echo(typer.style("Tool confirmation required", bold=True))
typer.echo(f" Impact: {impact.upper()}")
typer.echo(f" {description}")
typer.echo()
if typer.confirm("Allow this action?", default=False):
req.confirm()
logger.info("CLI: approved %s", tool_name)
else:
req.reject(note="User rejected from CLI")
logger.info("CLI: rejected %s", tool_name)
def _decide_autonomous(req, tool_name: str, tool_args: dict) -> None:
"""Auto-approve allowlisted tools; reject everything else."""
if is_allowlisted(tool_name, tool_args):
req.confirm()
logger.info("AUTO-APPROVED (allowlist): %s", tool_name)
else:
req.reject(note="Auto-rejected: not in allowlist")
logger.info("AUTO-REJECTED (not allowlisted): %s %s", tool_name, str(tool_args)[:100])
def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous: bool = False):
"""Prompt user to approve/reject dangerous tool calls.
@@ -113,7 +51,6 @@ def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous:
Returns the final RunOutput after all confirmations are resolved.
"""
interactive = _is_interactive() and not autonomous
decide = _prompt_interactive if interactive else _decide_autonomous
max_rounds = 10 # safety limit
for _ in range(max_rounds):
@@ -129,10 +66,39 @@ def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous:
for req in reqs:
if not getattr(req, "needs_confirmation", False):
continue
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
decide(req, tool_name, tool_args)
if interactive:
# Human present — prompt for approval
description = format_action_description(tool_name, tool_args)
impact = get_impact_level(tool_name)
typer.echo()
typer.echo(typer.style("Tool confirmation required", bold=True))
typer.echo(f" Impact: {impact.upper()}")
typer.echo(f" {description}")
typer.echo()
approved = typer.confirm("Allow this action?", default=False)
if approved:
req.confirm()
logger.info("CLI: approved %s", tool_name)
else:
req.reject(note="User rejected from CLI")
logger.info("CLI: rejected %s", tool_name)
else:
# Autonomous mode — check allowlist
if is_allowlisted(tool_name, tool_args):
req.confirm()
logger.info("AUTO-APPROVED (allowlist): %s", tool_name)
else:
req.reject(note="Auto-rejected: not in allowlist")
logger.info(
"AUTO-REJECTED (not allowlisted): %s %s", tool_name, str(tool_args)[:100]
)
# Resume the run so the agent sees the confirmation result
try:
@@ -172,39 +138,10 @@ def think(
model_size: str | None = _MODEL_SIZE_OPTION,
):
"""Ask Timmy to think carefully about a topic."""
timmy = create_timmy(backend=backend, session_id=_CLI_SESSION_ID)
timmy = create_timmy(backend=backend, model_size=model_size, session_id=_CLI_SESSION_ID)
timmy.print_response(f"Think carefully about: {topic}", stream=True, session_id=_CLI_SESSION_ID)
def _read_message_input(message: list[str]) -> str:
"""Join CLI arguments and read from stdin when appropriate."""
message_str = " ".join(message)
if message_str == "-" or not _is_interactive():
try:
stdin_content = sys.stdin.read().strip()
except (KeyboardInterrupt, EOFError):
stdin_content = ""
if stdin_content:
message_str = stdin_content
elif message_str == "-":
typer.echo("No input provided via stdin.", err=True)
raise typer.Exit(1)
return message_str
def _resolve_session_id(session_id: str | None, new_session: bool) -> str:
"""Return the effective session ID based on CLI flags."""
import uuid
if session_id is not None:
return session_id
if new_session:
return str(uuid.uuid4())
return _CLI_SESSION_ID
@app.command()
def chat(
message: list[str] = typer.Argument(
@@ -241,13 +178,38 @@ def chat(
Read from stdin by passing "-" as the message or piping input.
"""
message_str = _read_message_input(message)
session_id = _resolve_session_id(session_id, new_session)
timmy = create_timmy(backend=backend, session_id=session_id)
import uuid
# Join multiple arguments into a single message string
message_str = " ".join(message)
# Handle stdin input if "-" is passed or stdin is not a tty
if message_str == "-" or not _is_interactive():
try:
stdin_content = sys.stdin.read().strip()
except (KeyboardInterrupt, EOFError):
stdin_content = ""
if stdin_content:
message_str = stdin_content
elif message_str == "-":
typer.echo("No input provided via stdin.", err=True)
raise typer.Exit(1)
if session_id is not None:
pass # use the provided value
elif new_session:
session_id = str(uuid.uuid4())
else:
session_id = _CLI_SESSION_ID
timmy = create_timmy(backend=backend, model_size=model_size, session_id=session_id)
# Use agent.run() so we can intercept paused runs for tool confirmation.
run_output = timmy.run(message_str, stream=False, session_id=session_id)
# Handle paused runs — dangerous tools need user approval
run_output = _handle_tool_confirmation(timmy, run_output, session_id, autonomous=autonomous)
# Print the final response
content = run_output.content if hasattr(run_output, "content") else str(run_output)
if content:
from timmy.session import _clean_response
@@ -316,7 +278,7 @@ def status(
model_size: str | None = _MODEL_SIZE_OPTION,
):
"""Print Timmy's operational status."""
timmy = create_timmy(backend=backend, session_id=_CLI_SESSION_ID)
timmy = create_timmy(backend=backend, model_size=model_size, session_id=_CLI_SESSION_ID)
timmy.print_response(STATUS_PROMPT, stream=False, session_id=_CLI_SESSION_ID)
@@ -489,43 +451,5 @@ def focus(
typer.echo("No active focus (broad mode).")
@app.command(name="healthcheck")
def healthcheck(
json_output: bool = typer.Option(False, "--json", "-j", help="Output as JSON"),
verbose: bool = typer.Option(
False, "--verbose", "-v", help="Show verbose output including issue details"
),
quiet: bool = typer.Option(False, "--quiet", "-q", help="Only show status line (no details)"),
):
"""Quick health snapshot before coding.
Shows CI status, critical issues (P0/P1), test flakiness, and token economy.
Fast execution (< 5 seconds) for pre-work checks.
Refs: #710
"""
import subprocess
import sys
from pathlib import Path
script_path = (
Path(__file__).resolve().parent.parent.parent
/ "timmy_automations"
/ "daily_run"
/ "health_snapshot.py"
)
cmd = [sys.executable, str(script_path)]
if json_output:
cmd.append("--json")
if verbose:
cmd.append("--verbose")
if quiet:
cmd.append("--quiet")
result = subprocess.run(cmd)
raise typer.Exit(result.returncode)
def main():
app()

View File

@@ -174,8 +174,15 @@ class ConversationManager:
return None
_TOOL_KEYWORDS = frozenset(
{
def should_use_tools(self, message: str, context: ConversationContext) -> bool:
"""Determine if this message likely requires tools.
Returns True if tools are likely needed, False for simple chat.
"""
message_lower = message.lower().strip()
# Tool keywords that suggest tool usage is needed
tool_keywords = [
"search",
"look up",
"find",
@@ -196,11 +203,10 @@ class ConversationManager:
"shell",
"command",
"install",
}
)
]
_CHAT_ONLY_KEYWORDS = frozenset(
{
# Chat-only keywords that definitely don't need tools
chat_only = [
"hello",
"hi ",
"hey",
@@ -215,47 +221,30 @@ class ConversationManager:
"goodbye",
"tell me about yourself",
"what can you do",
}
)
]
_SIMPLE_QUESTION_PREFIXES = ("what is", "who is", "how does", "why is", "when did", "where is")
_TIME_WORDS = ("today", "now", "current", "latest", "this week", "this month")
# Check for chat-only patterns first
for pattern in chat_only:
if pattern in message_lower:
return False
def _is_chat_only(self, message_lower: str) -> bool:
"""Return True if the message matches a chat-only pattern."""
return any(kw in message_lower for kw in self._CHAT_ONLY_KEYWORDS)
# Check for tool keywords
for keyword in tool_keywords:
if keyword in message_lower:
return True
def _has_tool_keyword(self, message_lower: str) -> bool:
"""Return True if the message contains a tool-related keyword."""
return any(kw in message_lower for kw in self._TOOL_KEYWORDS)
def _is_simple_question(self, message_lower: str) -> bool | None:
"""Check if message is a simple question.
Returns True if it needs tools (real-time info), False if it
doesn't, or None if the message isn't a simple question.
"""
for prefix in self._SIMPLE_QUESTION_PREFIXES:
if message_lower.startswith(prefix):
return any(t in message_lower for t in self._TIME_WORDS)
return None
def should_use_tools(self, message: str, context: ConversationContext) -> bool:
"""Determine if this message likely requires tools.
Returns True if tools are likely needed, False for simple chat.
"""
message_lower = message.lower().strip()
if self._is_chat_only(message_lower):
return False
if self._has_tool_keyword(message_lower):
return True
simple = self._is_simple_question(message_lower)
if simple is not None:
return simple
# Simple questions (starting with what, who, how, why, when, where)
# usually don't need tools unless about current/real-time info
simple_question_words = ["what is", "who is", "how does", "why is", "when did", "where is"]
for word in simple_question_words:
if message_lower.startswith(word):
# Check if it's asking about current/real-time info
time_words = ["today", "now", "current", "latest", "this week", "this month"]
if any(t in message_lower for t in time_words):
return True
return False
# Default: don't use tools for unclear cases
return False

View File

@@ -97,7 +97,6 @@ async def probe_tool_use() -> dict:
"error_type": "empty_result",
}
except Exception as exc:
logger.exception("Tool use probe failed")
return {
"success": False,
"capability": cap,
@@ -130,7 +129,6 @@ async def probe_multistep_planning() -> dict:
"error_type": "verification_failed",
}
except Exception as exc:
logger.exception("Multistep planning probe failed")
return {
"success": False,
"capability": cap,
@@ -153,7 +151,6 @@ async def probe_memory_write() -> dict:
"error_type": None,
}
except Exception as exc:
logger.exception("Memory write probe failed")
return {
"success": False,
"capability": cap,
@@ -182,7 +179,6 @@ async def probe_memory_read() -> dict:
"error_type": "empty_result",
}
except Exception as exc:
logger.exception("Memory read probe failed")
return {
"success": False,
"capability": cap,
@@ -218,7 +214,6 @@ async def probe_self_coding() -> dict:
"error_type": "verification_failed",
}
except Exception as exc:
logger.exception("Self-coding probe failed")
return {
"success": False,
"capability": cap,
@@ -330,7 +325,6 @@ class LoopQAOrchestrator:
result = await probe_fn()
except Exception as exc:
# Probe itself crashed — record failure and report
logger.exception("Loop QA probe %s crashed", cap.value)
capture_error(exc, source="loop_qa", context={"capability": cap.value})
result = {
"success": False,

View File

@@ -21,16 +21,12 @@ Usage::
from __future__ import annotations
import logging
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from PIL import ImageDraw
import os
import shutil
import sqlite3
import uuid
from contextlib import closing
from datetime import UTC, datetime
from datetime import datetime
from pathlib import Path
import httpx
@@ -196,7 +192,7 @@ def _bridge_to_work_order(title: str, body: str, category: str) -> None:
body,
category,
"timmy-thinking",
datetime.now(UTC).isoformat(),
datetime.utcnow().isoformat(),
),
)
conn.commit()
@@ -204,61 +200,15 @@ def _bridge_to_work_order(title: str, body: str, category: str) -> None:
logger.debug("Work order bridge failed: %s", exc)
async def _ensure_issue_session():
"""Get or create the cached MCP session, connecting if needed.
Returns the connected ``MCPTools`` instance.
"""
from agno.tools.mcp import MCPTools
global _issue_session
if _issue_session is None:
_issue_session = MCPTools(
server_params=_gitea_server_params(),
timeout_seconds=settings.mcp_timeout,
)
if not getattr(_issue_session, "_connected", False):
await _issue_session.connect()
_issue_session._connected = True
return _issue_session
def _build_issue_body(body: str) -> str:
"""Append the auto-filing signature to the issue body."""
full_body = body
if full_body:
full_body += "\n\n"
full_body += "---\n*Auto-filed by Timmy's thinking engine*"
return full_body
def _build_issue_args(title: str, full_body: str) -> dict:
"""Build MCP tool arguments for ``issue_write`` with method=create."""
owner, repo = settings.gitea_repo.split("/", 1)
return {
"method": "create",
"owner": owner,
"repo": repo,
"title": title,
"body": full_body,
}
def _category_from_labels(labels: str) -> str:
"""Derive a work-order category from comma-separated label names."""
label_list = [tag.strip() for tag in labels.split(",") if tag.strip()] if labels else []
return "bug" if "bug" in label_list else "suggestion"
async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "") -> str:
"""File a Gitea issue via the MCP server (standalone, no LLM loop).
Used by the thinking engine's ``_maybe_file_issues()`` post-hook.
Manages its own MCPTools session with lazy connect + graceful failure.
Uses ``tools.session.call_tool()`` for direct MCP invocation — the
``MCPTools`` wrapper itself does not expose ``call_tool()``.
Args:
title: Issue title.
body: Issue body (markdown).
@@ -271,13 +221,46 @@ async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "
return "Gitea integration is not configured."
try:
session = await _ensure_issue_session()
full_body = _build_issue_body(body)
args = _build_issue_args(title, full_body)
from agno.tools.mcp import MCPTools
result = await session.session.call_tool("issue_write", arguments=args)
global _issue_session
_bridge_to_work_order(title, body, _category_from_labels(labels))
if _issue_session is None:
_issue_session = MCPTools(
server_params=_gitea_server_params(),
timeout_seconds=settings.mcp_timeout,
)
# Ensure connected
if not getattr(_issue_session, "_connected", False):
await _issue_session.connect()
_issue_session._connected = True
# Append auto-filing signature
full_body = body
if full_body:
full_body += "\n\n"
full_body += "---\n*Auto-filed by Timmy's thinking engine*"
# Parse owner/repo from settings
owner, repo = settings.gitea_repo.split("/", 1)
# Build tool arguments — gitea-mcp uses issue_write with method="create"
args = {
"method": "create",
"owner": owner,
"repo": repo,
"title": title,
"body": full_body,
}
# Call via the underlying MCP session (MCPTools doesn't expose call_tool)
result = await _issue_session.session.call_tool("issue_write", arguments=args)
# Bridge to local work order
label_list = [tag.strip() for tag in labels.split(",") if tag.strip()] if labels else []
category = "bug" if "bug" in label_list else "suggestion"
_bridge_to_work_order(title, body, category)
logger.info("Created Gitea issue via MCP: %s", title[:60])
return f"Created issue: {title}\n{result}"
@@ -287,8 +270,20 @@ async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "
return f"Failed to create issue via MCP: {exc}"
def _draw_background(draw: ImageDraw.ImageDraw, size: int) -> None:
"""Draw radial gradient background with concentric circles."""
def _generate_avatar_image() -> bytes:
"""Generate a Timmy-themed avatar image using Pillow.
Creates a 512x512 wizard-themed avatar with emerald/purple/gold palette.
Returns raw PNG bytes. Falls back to a minimal solid-color image if
Pillow drawing primitives fail.
"""
from PIL import Image, ImageDraw
size = 512
img = Image.new("RGB", (size, size), (15, 25, 20))
draw = ImageDraw.Draw(img)
# Background gradient effect — concentric circles
for i in range(size // 2, 0, -4):
g = int(25 + (i / (size // 2)) * 30)
draw.ellipse(
@@ -296,45 +291,33 @@ def _draw_background(draw: ImageDraw.ImageDraw, size: int) -> None:
fill=(10, g, 20),
)
def _draw_wizard(draw: ImageDraw.ImageDraw) -> None:
"""Draw wizard hat, face, eyes, smile, monogram, and robe."""
# Wizard hat (triangle)
hat_color = (100, 50, 160) # purple
hat_outline = (180, 130, 255)
gold = (220, 190, 50)
pupil = (30, 30, 60)
# Hat + brim
draw.polygon([(256, 40), (160, 220), (352, 220)], fill=hat_color, outline=hat_outline)
draw.ellipse([140, 200, 372, 250], fill=hat_color, outline=hat_outline)
# Face
draw.ellipse([190, 220, 322, 370], fill=(60, 180, 100), outline=(80, 220, 120))
# Eyes (whites + pupils)
draw.ellipse([220, 275, 248, 310], fill=(255, 255, 255))
draw.ellipse([264, 275, 292, 310], fill=(255, 255, 255))
draw.ellipse([228, 285, 242, 300], fill=pupil)
draw.ellipse([272, 285, 286, 300], fill=pupil)
# Smile
draw.arc([225, 300, 287, 355], start=10, end=170, fill=pupil, width=3)
# "T" monogram on hat
draw.text((243, 100), "T", fill=gold)
# Robe
draw.polygon(
[(180, 370), (140, 500), (372, 500), (332, 370)],
fill=(40, 100, 70),
outline=(60, 160, 100),
[(256, 40), (160, 220), (352, 220)],
fill=hat_color,
outline=(180, 130, 255),
)
# Hat brim
draw.ellipse([140, 200, 372, 250], fill=hat_color, outline=(180, 130, 255))
def _draw_stars(draw: ImageDraw.ImageDraw) -> None:
"""Draw decorative gold stars around the wizard hat."""
# Face circle
draw.ellipse([190, 220, 322, 370], fill=(60, 180, 100), outline=(80, 220, 120))
# Eyes
draw.ellipse([220, 275, 248, 310], fill=(255, 255, 255))
draw.ellipse([264, 275, 292, 310], fill=(255, 255, 255))
draw.ellipse([228, 285, 242, 300], fill=(30, 30, 60))
draw.ellipse([272, 285, 286, 300], fill=(30, 30, 60))
# Smile
draw.arc([225, 300, 287, 355], start=10, end=170, fill=(30, 30, 60), width=3)
# Stars around the hat
gold = (220, 190, 50)
for sx, sy in [(120, 100), (380, 120), (100, 300), (400, 280), (256, 10)]:
star_positions = [(120, 100), (380, 120), (100, 300), (400, 280), (256, 10)]
for sx, sy in star_positions:
r = 8
draw.polygon(
[
@@ -350,26 +333,18 @@ def _draw_stars(draw: ImageDraw.ImageDraw) -> None:
fill=gold,
)
# "T" monogram on the hat
draw.text((243, 100), "T", fill=gold)
def _generate_avatar_image() -> bytes:
"""Generate a Timmy-themed avatar image using Pillow.
# Robe / body
draw.polygon(
[(180, 370), (140, 500), (372, 500), (332, 370)],
fill=(40, 100, 70),
outline=(60, 160, 100),
)
Creates a 512x512 wizard-themed avatar with emerald/purple/gold palette.
Returns raw PNG bytes. Falls back to a minimal solid-color image if
Pillow drawing primitives fail.
"""
import io
from PIL import Image, ImageDraw
size = 512
img = Image.new("RGB", (size, size), (15, 25, 20))
draw = ImageDraw.Draw(img)
_draw_background(draw, size)
_draw_wizard(draw)
_draw_stars(draw)
buf = io.BytesIO()
img.save(buf, format="PNG")
return buf.getvalue()

View File

@@ -14,8 +14,6 @@ from dataclasses import dataclass, field
from datetime import UTC, datetime
from pathlib import Path
from config import settings
logger = logging.getLogger(__name__)
# Paths
@@ -30,7 +28,7 @@ def get_connection() -> Generator[sqlite3.Connection, None, None]:
with closing(sqlite3.connect(str(DB_PATH))) as conn:
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute(f"PRAGMA busy_timeout={settings.db_busy_timeout_ms}")
conn.execute("PRAGMA busy_timeout=5000")
_ensure_schema(conn)
yield conn
@@ -80,88 +78,83 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
tables = {row[0] for row in cursor.fetchall()}
if "memories" not in tables:
has_memories = "memories" in tables
has_episodes = "episodes" in tables
has_chunks = "chunks" in tables
has_facts = "facts" in tables
# Check if we need to migrate (old schema exists but new one doesn't fully)
if not has_memories:
logger.info("Migration: Creating unified memories table")
# Schema will be created by _ensure_schema above
conn.commit()
return
# Schema will be created above
# Migrate episodes -> memories
if has_episodes and has_memories:
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
# Migrate chunks -> memories as vault_chunk
if has_chunks and has_memories:
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
# Drop old facts table
if has_facts:
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
_migrate_episodes(conn, tables)
_migrate_chunks(conn, tables)
_drop_legacy_tables(conn, tables)
conn.commit()
def _migrate_episodes(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Migrate episodes table rows into the unified memories table."""
if "episodes" not in tables:
return
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
def _migrate_chunks(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Migrate chunks table rows into the unified memories table as vault_chunk."""
if "chunks" not in tables:
return
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
def _drop_legacy_tables(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Drop old facts table if it exists."""
if "facts" not in tables:
return
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
"""Get the column names for a table."""
cursor = conn.execute(f"PRAGMA table_info({table_name})")

View File

@@ -20,7 +20,6 @@ from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta
from pathlib import Path
from config import settings
from timmy.memory.embeddings import (
EMBEDDING_DIM,
EMBEDDING_MODEL, # noqa: F401 — re-exported for backward compatibility
@@ -47,64 +46,6 @@ DB_PATH = PROJECT_ROOT / "data" / "memory.db"
# ───────────────────────────────────────────────────────────────────────────────
_DEFAULT_HOT_MEMORY_TEMPLATE = """\
# Timmy Hot Memory
> Working RAM — always loaded, ~300 lines max, pruned monthly
> Last updated: {date}
---
## Current Status
**Agent State:** Operational
**Mode:** Development
**Active Tasks:** 0
**Pending Decisions:** None
---
## Standing Rules
1. **Sovereignty First** — No cloud dependencies
2. **Local-Only Inference** — Ollama on localhost
3. **Privacy by Design** — Telemetry disabled
4. **Tool Minimalism** — Use tools only when necessary
5. **Memory Discipline** — Write handoffs at session end
---
## Agent Roster
| Agent | Role | Status |
|-------|------|--------|
| Timmy | Core | Active |
---
## User Profile
**Name:** (not set)
**Interests:** (to be learned)
---
## Key Decisions
(none yet)
---
## Pending Actions
- [ ] Learn user's name
---
*Prune date: {prune_date}*
"""
@contextmanager
def get_connection() -> Generator[sqlite3.Connection, None, None]:
"""Get database connection to unified memory database."""
@@ -112,7 +53,7 @@ def get_connection() -> Generator[sqlite3.Connection, None, None]:
with closing(sqlite3.connect(str(DB_PATH))) as conn:
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute(f"PRAGMA busy_timeout={settings.db_busy_timeout_ms}")
conn.execute("PRAGMA busy_timeout=5000")
_ensure_schema(conn)
yield conn
@@ -157,73 +98,6 @@ def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
return {row[1] for row in cursor.fetchall()}
def _migrate_episodes(conn: sqlite3.Connection) -> None:
"""Migrate episodes table rows into the unified memories table."""
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
def _migrate_chunks(conn: sqlite3.Connection) -> None:
"""Migrate chunks table rows into the unified memories table."""
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
def _drop_legacy_table(conn: sqlite3.Connection, table: str) -> None:
"""Drop a legacy table if it exists."""
try:
conn.execute(f"DROP TABLE {table}") # noqa: S608
logger.info("Migration: Dropped old %s table", table)
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop %s: %s", table, exc)
def _migrate_schema(conn: sqlite3.Connection) -> None:
"""Migrate from old three-table schema to unified memories table.
@@ -236,16 +110,78 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
tables = {row[0] for row in cursor.fetchall()}
has_memories = "memories" in tables
has_episodes = "episodes" in tables
has_chunks = "chunks" in tables
has_facts = "facts" in tables
if not has_memories and (tables & {"episodes", "chunks", "facts"}):
# Check if we need to migrate (old schema exists)
if not has_memories and (has_episodes or has_chunks or has_facts):
logger.info("Migration: Creating unified memories table")
# Schema will be created by _ensure_schema above
if "episodes" in tables and has_memories:
_migrate_episodes(conn)
if "chunks" in tables and has_memories:
_migrate_chunks(conn)
if "facts" in tables:
_drop_legacy_table(conn, "facts")
# Migrate episodes -> memories
if has_episodes and has_memories:
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
# Migrate chunks -> memories as vault_chunk
if has_chunks and has_memories:
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
# Drop old tables
if has_facts:
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
conn.commit()
@@ -362,85 +298,6 @@ def store_memory(
return entry
def _build_search_filters(
context_type: str | None,
agent_id: str | None,
session_id: str | None,
) -> tuple[str, list]:
"""Build SQL WHERE clause and params from search filters."""
conditions: list[str] = []
params: list = []
if context_type:
conditions.append("memory_type = ?")
params.append(context_type)
if agent_id:
conditions.append("agent_id = ?")
params.append(agent_id)
if session_id:
conditions.append("session_id = ?")
params.append(session_id)
where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
return where_clause, params
def _fetch_memory_candidates(
where_clause: str, params: list, candidate_limit: int
) -> list[sqlite3.Row]:
"""Fetch candidate memory rows from the database."""
query_sql = f"""
SELECT * FROM memories
{where_clause}
ORDER BY created_at DESC
LIMIT ?
"""
params.append(candidate_limit)
with get_connection() as conn:
return conn.execute(query_sql, params).fetchall()
def _row_to_entry(row: sqlite3.Row) -> MemoryEntry:
"""Convert a database row to a MemoryEntry."""
return MemoryEntry(
id=row["id"],
content=row["content"],
source=row["source"],
context_type=row["memory_type"], # DB column -> API field
agent_id=row["agent_id"],
task_id=row["task_id"],
session_id=row["session_id"],
metadata=json.loads(row["metadata"]) if row["metadata"] else None,
embedding=json.loads(row["embedding"]) if row["embedding"] else None,
timestamp=row["created_at"],
)
def _score_and_filter(
rows: list[sqlite3.Row],
query: str,
query_embedding: list[float],
min_relevance: float,
) -> list[MemoryEntry]:
"""Score candidate rows by similarity and filter by min_relevance."""
results = []
for row in rows:
entry = _row_to_entry(row)
if entry.embedding:
score = cosine_similarity(query_embedding, entry.embedding)
else:
score = _keyword_overlap(query, entry.content)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
return results
def search_memories(
query: str,
limit: int = 10,
@@ -463,9 +320,65 @@ def search_memories(
List of MemoryEntry objects sorted by relevance
"""
query_embedding = embed_text(query)
where_clause, params = _build_search_filters(context_type, agent_id, session_id)
rows = _fetch_memory_candidates(where_clause, params, limit * 3)
results = _score_and_filter(rows, query, query_embedding, min_relevance)
# Build query with filters
conditions = []
params = []
if context_type:
conditions.append("memory_type = ?")
params.append(context_type)
if agent_id:
conditions.append("agent_id = ?")
params.append(agent_id)
if session_id:
conditions.append("session_id = ?")
params.append(session_id)
where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
# Fetch candidates (we'll do in-memory similarity for now)
query_sql = f"""
SELECT * FROM memories
{where_clause}
ORDER BY created_at DESC
LIMIT ?
"""
params.append(limit * 3) # Get more candidates for ranking
with get_connection() as conn:
rows = conn.execute(query_sql, params).fetchall()
# Compute similarity scores
results = []
for row in rows:
entry = MemoryEntry(
id=row["id"],
content=row["content"],
source=row["source"],
context_type=row["memory_type"], # DB column -> API field
agent_id=row["agent_id"],
task_id=row["task_id"],
session_id=row["session_id"],
metadata=json.loads(row["metadata"]) if row["metadata"] else None,
embedding=json.loads(row["embedding"]) if row["embedding"] else None,
timestamp=row["created_at"],
)
if entry.embedding:
score = cosine_similarity(query_embedding, entry.embedding)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
else:
# Fallback: check for keyword overlap
score = _keyword_overlap(query, entry.content)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
# Sort by relevance and return top results
results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
return results[:limit]
@@ -791,12 +704,66 @@ class HotMemory:
logger.debug(
"HotMemory._create_default() - creating default MEMORY.md for backward compatibility"
)
now = datetime.now(UTC)
content = _DEFAULT_HOT_MEMORY_TEMPLATE.format(
date=now.strftime("%Y-%m-%d"),
prune_date=now.replace(day=25).strftime("%Y-%m-%d"),
default_content = """# Timmy Hot Memory
> Working RAM — always loaded, ~300 lines max, pruned monthly
> Last updated: {date}
---
## Current Status
**Agent State:** Operational
**Mode:** Development
**Active Tasks:** 0
**Pending Decisions:** None
---
## Standing Rules
1. **Sovereignty First** — No cloud dependencies
2. **Local-Only Inference** — Ollama on localhost
3. **Privacy by Design** — Telemetry disabled
4. **Tool Minimalism** — Use tools only when necessary
5. **Memory Discipline** — Write handoffs at session end
---
## Agent Roster
| Agent | Role | Status |
|-------|------|--------|
| Timmy | Core | Active |
---
## User Profile
**Name:** (not set)
**Interests:** (to be learned)
---
## Key Decisions
(none yet)
---
## Pending Actions
- [ ] Learn user's name
---
*Prune date: {prune_date}*
""".format(
date=datetime.now(UTC).strftime("%Y-%m-%d"),
prune_date=(datetime.now(UTC).replace(day=25)).strftime("%Y-%m-%d"),
)
self.path.write_text(content)
self.path.write_text(default_content)
logger.info("HotMemory: Created default MEMORY.md")
@@ -950,7 +917,7 @@ class SemanticMemory:
with closing(sqlite3.connect(str(self.db_path))) as conn:
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute(f"PRAGMA busy_timeout={settings.db_busy_timeout_ms}")
conn.execute("PRAGMA busy_timeout=5000")
# Ensure schema exists
conn.execute("""
CREATE TABLE IF NOT EXISTS memories (

View File

@@ -1,581 +0,0 @@
"""Token Quest System for agent rewards.
Provides quest definitions, progress tracking, completion detection,
and token awards for agent accomplishments.
Quests are defined in config/quests.yaml and loaded at runtime.
"""
from __future__ import annotations
import logging
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta
from enum import StrEnum
from pathlib import Path
from typing import Any
import yaml
from config import settings
logger = logging.getLogger(__name__)
# Path to quest configuration
QUEST_CONFIG_PATH = Path(settings.repo_root) / "config" / "quests.yaml"
class QuestType(StrEnum):
"""Types of quests supported by the system."""
ISSUE_COUNT = "issue_count"
ISSUE_REDUCE = "issue_reduce"
DOCS_UPDATE = "docs_update"
TEST_IMPROVE = "test_improve"
DAILY_RUN = "daily_run"
CUSTOM = "custom"
class QuestStatus(StrEnum):
"""Status of a quest for an agent."""
NOT_STARTED = "not_started"
IN_PROGRESS = "in_progress"
COMPLETED = "completed"
CLAIMED = "claimed"
EXPIRED = "expired"
@dataclass
class QuestDefinition:
"""Definition of a quest from configuration."""
id: str
name: str
description: str
reward_tokens: int
quest_type: QuestType
enabled: bool
repeatable: bool
cooldown_hours: int
criteria: dict[str, Any]
notification_message: str
@classmethod
def from_dict(cls, data: dict[str, Any]) -> QuestDefinition:
"""Create a QuestDefinition from a dictionary."""
return cls(
id=data["id"],
name=data.get("name", "Unnamed Quest"),
description=data.get("description", ""),
reward_tokens=data.get("reward_tokens", 0),
quest_type=QuestType(data.get("type", "custom")),
enabled=data.get("enabled", True),
repeatable=data.get("repeatable", False),
cooldown_hours=data.get("cooldown_hours", 0),
criteria=data.get("criteria", {}),
notification_message=data.get(
"notification_message", "Quest Complete! You earned {tokens} tokens."
),
)
@dataclass
class QuestProgress:
"""Progress of a quest for a specific agent."""
quest_id: str
agent_id: str
status: QuestStatus
current_value: int = 0
target_value: int = 0
started_at: str = ""
completed_at: str = ""
claimed_at: str = ""
completion_count: int = 0
last_completed_at: str = ""
metadata: dict[str, Any] = field(default_factory=dict)
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for serialization."""
return {
"quest_id": self.quest_id,
"agent_id": self.agent_id,
"status": self.status.value,
"current_value": self.current_value,
"target_value": self.target_value,
"started_at": self.started_at,
"completed_at": self.completed_at,
"claimed_at": self.claimed_at,
"completion_count": self.completion_count,
"last_completed_at": self.last_completed_at,
"metadata": self.metadata,
}
# In-memory storage for quest progress
_quest_progress: dict[str, QuestProgress] = {}
_quest_definitions: dict[str, QuestDefinition] = {}
_quest_settings: dict[str, Any] = {}
def _get_progress_key(quest_id: str, agent_id: str) -> str:
"""Generate a unique key for quest progress."""
return f"{agent_id}:{quest_id}"
def load_quest_config() -> tuple[dict[str, QuestDefinition], dict[str, Any]]:
"""Load quest definitions from quests.yaml.
Returns:
Tuple of (quest definitions dict, settings dict)
"""
global _quest_definitions, _quest_settings
if not QUEST_CONFIG_PATH.exists():
logger.warning("Quest config not found at %s", QUEST_CONFIG_PATH)
return {}, {}
try:
raw = QUEST_CONFIG_PATH.read_text()
config = yaml.safe_load(raw)
if not isinstance(config, dict):
logger.warning("Invalid quest config format")
return {}, {}
# Load quest definitions
quests_data = config.get("quests", {})
definitions = {}
for quest_id, quest_data in quests_data.items():
quest_data["id"] = quest_id
try:
definition = QuestDefinition.from_dict(quest_data)
definitions[quest_id] = definition
except (ValueError, KeyError) as exc:
logger.warning("Failed to load quest %s: %s", quest_id, exc)
# Load settings
_quest_settings = config.get("settings", {})
_quest_definitions = definitions
logger.debug("Loaded %d quest definitions", len(definitions))
return definitions, _quest_settings
except (OSError, yaml.YAMLError) as exc:
logger.warning("Failed to load quest config: %s", exc)
return {}, {}
def get_quest_definitions() -> dict[str, QuestDefinition]:
"""Get all quest definitions, loading if necessary."""
global _quest_definitions
if not _quest_definitions:
_quest_definitions, _ = load_quest_config()
return _quest_definitions
def get_quest_definition(quest_id: str) -> QuestDefinition | None:
"""Get a specific quest definition by ID."""
definitions = get_quest_definitions()
return definitions.get(quest_id)
def get_active_quests() -> list[QuestDefinition]:
"""Get all enabled quest definitions."""
definitions = get_quest_definitions()
return [q for q in definitions.values() if q.enabled]
def get_quest_progress(quest_id: str, agent_id: str) -> QuestProgress | None:
"""Get progress for a specific quest and agent."""
key = _get_progress_key(quest_id, agent_id)
return _quest_progress.get(key)
def get_or_create_progress(quest_id: str, agent_id: str) -> QuestProgress:
"""Get existing progress or create new for quest/agent."""
key = _get_progress_key(quest_id, agent_id)
if key not in _quest_progress:
quest = get_quest_definition(quest_id)
if not quest:
raise ValueError(f"Quest {quest_id} not found")
target = _get_target_value(quest)
_quest_progress[key] = QuestProgress(
quest_id=quest_id,
agent_id=agent_id,
status=QuestStatus.NOT_STARTED,
current_value=0,
target_value=target,
started_at=datetime.now(UTC).isoformat(),
)
return _quest_progress[key]
def _get_target_value(quest: QuestDefinition) -> int:
"""Extract target value from quest criteria."""
criteria = quest.criteria
if quest.quest_type == QuestType.ISSUE_COUNT:
return criteria.get("target_count", 1)
elif quest.quest_type == QuestType.ISSUE_REDUCE:
return criteria.get("target_reduction", 1)
elif quest.quest_type == QuestType.DAILY_RUN:
return criteria.get("min_sessions", 1)
elif quest.quest_type == QuestType.DOCS_UPDATE:
return criteria.get("min_files_changed", 1)
elif quest.quest_type == QuestType.TEST_IMPROVE:
return criteria.get("min_new_tests", 1)
return 1
def update_quest_progress(
quest_id: str,
agent_id: str,
current_value: int,
metadata: dict[str, Any] | None = None,
) -> QuestProgress:
"""Update progress for a quest."""
progress = get_or_create_progress(quest_id, agent_id)
progress.current_value = current_value
if metadata:
progress.metadata.update(metadata)
# Check if quest is now complete
if progress.current_value >= progress.target_value:
if progress.status not in (QuestStatus.COMPLETED, QuestStatus.CLAIMED):
progress.status = QuestStatus.COMPLETED
progress.completed_at = datetime.now(UTC).isoformat()
logger.info("Quest %s completed for agent %s", quest_id, agent_id)
return progress
def _is_on_cooldown(progress: QuestProgress, quest: QuestDefinition) -> bool:
"""Check if a repeatable quest is on cooldown."""
if not quest.repeatable or not progress.last_completed_at:
return False
if quest.cooldown_hours <= 0:
return False
try:
last_completed = datetime.fromisoformat(progress.last_completed_at)
cooldown_end = last_completed + timedelta(hours=quest.cooldown_hours)
return datetime.now(UTC) < cooldown_end
except (ValueError, TypeError):
return False
def claim_quest_reward(quest_id: str, agent_id: str) -> dict[str, Any] | None:
"""Claim the token reward for a completed quest.
Returns:
Reward info dict if successful, None if not claimable
"""
progress = get_quest_progress(quest_id, agent_id)
if not progress:
return None
quest = get_quest_definition(quest_id)
if not quest:
return None
# Check if quest is completed but not yet claimed
if progress.status != QuestStatus.COMPLETED:
return None
# Check cooldown for repeatable quests
if _is_on_cooldown(progress, quest):
return None
try:
# Award tokens via ledger
from lightning.ledger import create_invoice_entry, mark_settled
# Create a mock invoice for the reward
invoice_entry = create_invoice_entry(
payment_hash=f"quest_{quest_id}_{agent_id}_{int(time.time())}",
amount_sats=quest.reward_tokens,
memo=f"Quest reward: {quest.name}",
source="quest_reward",
agent_id=agent_id,
)
# Mark as settled immediately (quest rewards are auto-settled)
mark_settled(invoice_entry.payment_hash, preimage=f"quest_{quest_id}")
# Update progress
progress.status = QuestStatus.CLAIMED
progress.claimed_at = datetime.now(UTC).isoformat()
progress.completion_count += 1
progress.last_completed_at = progress.claimed_at
# Reset for repeatable quests
if quest.repeatable:
progress.status = QuestStatus.NOT_STARTED
progress.current_value = 0
progress.completed_at = ""
progress.claimed_at = ""
notification = quest.notification_message.format(tokens=quest.reward_tokens)
return {
"quest_id": quest_id,
"agent_id": agent_id,
"tokens_awarded": quest.reward_tokens,
"notification": notification,
"completion_count": progress.completion_count,
}
except Exception as exc:
logger.error("Failed to award quest reward: %s", exc)
return None
def check_issue_count_quest(
quest: QuestDefinition,
agent_id: str,
closed_issues: list[dict],
) -> QuestProgress | None:
"""Check progress for issue_count type quest."""
criteria = quest.criteria
target_labels = set(criteria.get("issue_labels", []))
# target_count is available in criteria but not used directly here
# Count matching issues
matching_count = 0
for issue in closed_issues:
issue_labels = {label.get("name", "") for label in issue.get("labels", [])}
if target_labels.issubset(issue_labels) or (not target_labels and issue_labels):
matching_count += 1
progress = update_quest_progress(
quest.id, agent_id, matching_count, {"matching_issues": matching_count}
)
return progress
def check_issue_reduce_quest(
quest: QuestDefinition,
agent_id: str,
previous_count: int,
current_count: int,
) -> QuestProgress | None:
"""Check progress for issue_reduce type quest."""
# target_reduction available in quest.criteria but we track actual reduction
reduction = max(0, previous_count - current_count)
progress = update_quest_progress(quest.id, agent_id, reduction, {"reduction": reduction})
return progress
def check_daily_run_quest(
quest: QuestDefinition,
agent_id: str,
sessions_completed: int,
) -> QuestProgress | None:
"""Check progress for daily_run type quest."""
# min_sessions available in quest.criteria but we track actual sessions
progress = update_quest_progress(
quest.id, agent_id, sessions_completed, {"sessions": sessions_completed}
)
return progress
def evaluate_quest_progress(
quest_id: str,
agent_id: str,
context: dict[str, Any],
) -> QuestProgress | None:
"""Evaluate quest progress based on quest type and context.
Args:
quest_id: The quest to evaluate
agent_id: The agent to evaluate for
context: Context data for evaluation (issues, metrics, etc.)
Returns:
Updated QuestProgress or None if evaluation failed
"""
quest = get_quest_definition(quest_id)
if not quest or not quest.enabled:
return None
progress = get_quest_progress(quest_id, agent_id)
# Check cooldown for repeatable quests
if progress and _is_on_cooldown(progress, quest):
return progress
try:
if quest.quest_type == QuestType.ISSUE_COUNT:
closed_issues = context.get("closed_issues", [])
return check_issue_count_quest(quest, agent_id, closed_issues)
elif quest.quest_type == QuestType.ISSUE_REDUCE:
prev_count = context.get("previous_issue_count", 0)
curr_count = context.get("current_issue_count", 0)
return check_issue_reduce_quest(quest, agent_id, prev_count, curr_count)
elif quest.quest_type == QuestType.DAILY_RUN:
sessions = context.get("sessions_completed", 0)
return check_daily_run_quest(quest, agent_id, sessions)
elif quest.quest_type == QuestType.CUSTOM:
# Custom quests require manual completion
return progress
else:
logger.debug("Quest type %s not yet implemented", quest.quest_type)
return progress
except Exception as exc:
logger.warning("Quest evaluation failed for %s: %s", quest_id, exc)
return progress
def auto_evaluate_all_quests(agent_id: str, context: dict[str, Any]) -> list[dict]:
"""Evaluate all active quests for an agent and award rewards.
Returns:
List of reward info for newly completed quests
"""
rewards = []
active_quests = get_active_quests()
for quest in active_quests:
progress = evaluate_quest_progress(quest.id, agent_id, context)
if progress and progress.status == QuestStatus.COMPLETED:
# Auto-claim the reward
reward = claim_quest_reward(quest.id, agent_id)
if reward:
rewards.append(reward)
return rewards
def get_agent_quests_status(agent_id: str) -> dict[str, Any]:
"""Get complete quest status for an agent."""
definitions = get_quest_definitions()
quests_status = []
total_rewards = 0
completed_count = 0
for quest_id, quest in definitions.items():
progress = get_quest_progress(quest_id, agent_id)
if not progress:
progress = get_or_create_progress(quest_id, agent_id)
is_on_cooldown = _is_on_cooldown(progress, quest) if quest.repeatable else False
quest_info = {
"quest_id": quest_id,
"name": quest.name,
"description": quest.description,
"reward_tokens": quest.reward_tokens,
"type": quest.quest_type.value,
"enabled": quest.enabled,
"repeatable": quest.repeatable,
"status": progress.status.value,
"current_value": progress.current_value,
"target_value": progress.target_value,
"completion_count": progress.completion_count,
"on_cooldown": is_on_cooldown,
"cooldown_hours_remaining": 0,
}
if is_on_cooldown and progress.last_completed_at:
try:
last = datetime.fromisoformat(progress.last_completed_at)
cooldown_end = last + timedelta(hours=quest.cooldown_hours)
hours_remaining = (cooldown_end - datetime.now(UTC)).total_seconds() / 3600
quest_info["cooldown_hours_remaining"] = round(max(0, hours_remaining), 1)
except (ValueError, TypeError):
pass
quests_status.append(quest_info)
total_rewards += progress.completion_count * quest.reward_tokens
completed_count += progress.completion_count
return {
"agent_id": agent_id,
"quests": quests_status,
"total_tokens_earned": total_rewards,
"total_quests_completed": completed_count,
"active_quests_count": len([q for q in quests_status if q["enabled"]]),
}
def reset_quest_progress(quest_id: str | None = None, agent_id: str | None = None) -> int:
"""Reset quest progress. Useful for testing.
Args:
quest_id: Specific quest to reset, or None for all
agent_id: Specific agent to reset, or None for all
Returns:
Number of progress entries reset
"""
global _quest_progress
count = 0
keys_to_reset = []
for key, _progress in _quest_progress.items():
key_agent, key_quest = key.split(":", 1)
if (quest_id is None or key_quest == quest_id) and (
agent_id is None or key_agent == agent_id
):
keys_to_reset.append(key)
for key in keys_to_reset:
del _quest_progress[key]
count += 1
return count
def get_quest_leaderboard() -> list[dict[str, Any]]:
"""Get a leaderboard of agents by quest completion."""
agent_stats: dict[str, dict[str, Any]] = {}
for _key, progress in _quest_progress.items():
agent_id = progress.agent_id
if agent_id not in agent_stats:
agent_stats[agent_id] = {
"agent_id": agent_id,
"total_completions": 0,
"total_tokens": 0,
"quests_completed": set(),
}
quest = get_quest_definition(progress.quest_id)
if quest:
agent_stats[agent_id]["total_completions"] += progress.completion_count
agent_stats[agent_id]["total_tokens"] += progress.completion_count * quest.reward_tokens
if progress.completion_count > 0:
agent_stats[agent_id]["quests_completed"].add(quest.id)
leaderboard = []
for stats in agent_stats.values():
leaderboard.append(
{
"agent_id": stats["agent_id"],
"total_completions": stats["total_completions"],
"total_tokens": stats["total_tokens"],
"unique_quests_completed": len(stats["quests_completed"]),
}
)
# Sort by total tokens (descending)
leaderboard.sort(key=lambda x: x["total_tokens"], reverse=True)
return leaderboard
# Initialize on module load
load_quest_config()

View File

@@ -392,26 +392,31 @@ def _build_insights(
return insights or ["Conversations look healthy. Keep up the good work."]
def _format_recurring_topics(repeated: list[tuple[str, int]]) -> list[str]:
"""Format the recurring-topics section of a reflection report."""
if repeated:
lines = ["### Recurring Topics"]
for word, count in repeated:
lines.append(f'- "{word}" ({count} mentions)')
lines.append("")
return lines
return ["### Recurring Topics\nNo strong patterns detected.\n"]
def self_reflect(limit: int = 30) -> str:
"""Review recent conversations and reflect on Timmy's own behavior.
Scans past session entries for patterns: low-confidence responses,
errors, repeated topics, and conversation quality signals. Returns
a structured reflection that Timmy can use to improve.
def _assemble_report(
entries: list[dict],
errors: list[dict],
timmy_msgs: list[dict],
user_msgs: list[dict],
low_conf: list[dict],
repeated: list[tuple[str, int]],
) -> str:
"""Assemble the full self-reflection report from analyzed data."""
Args:
limit: How many recent entries to review (default 30).
Returns:
A formatted self-reflection report.
"""
sl = get_session_logger()
sl.flush()
entries = sl.get_recent_entries(limit=limit)
if not entries:
return "No conversation history to reflect on yet."
_messages, errors, timmy_msgs, user_msgs = _categorize_entries(entries)
low_conf = _find_low_confidence(timmy_msgs)
repeated = _find_repeated_topics(user_msgs)
# Build reflection report
sections: list[str] = ["## Self-Reflection Report\n"]
sections.append(
f"Reviewed {len(entries)} recent entries: "
@@ -441,37 +446,16 @@ def _assemble_report(
)
)
sections.extend(_format_recurring_topics(repeated))
if repeated:
sections.append("### Recurring Topics")
for word, count in repeated:
sections.append(f'- "{word}" ({count} mentions)')
sections.append("")
else:
sections.append("### Recurring Topics\nNo strong patterns detected.\n")
sections.append("### Insights")
for insight in _build_insights(low_conf, errors, repeated):
sections.append(f"- {insight}")
return "\n".join(sections)
def self_reflect(limit: int = 30) -> str:
"""Review recent conversations and reflect on Timmy's own behavior.
Scans past session entries for patterns: low-confidence responses,
errors, repeated topics, and conversation quality signals. Returns
a structured reflection that Timmy can use to improve.
Args:
limit: How many recent entries to review (default 30).
Returns:
A formatted self-reflection report.
"""
sl = get_session_logger()
sl.flush()
entries = sl.get_recent_entries(limit=limit)
if not entries:
return "No conversation history to reflect on yet."
_messages, errors, timmy_msgs, user_msgs = _categorize_entries(entries)
low_conf = _find_low_confidence(timmy_msgs)
repeated = _find_repeated_topics(user_msgs)
return _assemble_report(entries, errors, timmy_msgs, user_msgs, low_conf, repeated)

View File

@@ -341,11 +341,6 @@ class ThinkingEngine:
)
return None
# Capture arrival time *before* the LLM call so the thought
# timestamp reflects when the cycle started, not when the
# (potentially slow) generation finished. Fixes #582.
arrived_at = datetime.now(UTC).isoformat()
memory_context, system_context, recent_thoughts = self._build_thinking_context()
content, seed_type = await self._generate_novel_thought(
@@ -357,7 +352,7 @@ class ThinkingEngine:
if not content:
return None
thought = self._store_thought(content, seed_type, arrived_at=arrived_at)
thought = self._store_thought(content, seed_type)
self._last_thought_id = thought.id
await self._process_thinking_result(thought)
@@ -1178,25 +1173,14 @@ class ThinkingEngine:
raw = run.content if hasattr(run, "content") else str(run)
return _THINK_TAG_RE.sub("", raw) if raw else raw
def _store_thought(
self,
content: str,
seed_type: str,
*,
arrived_at: str | None = None,
) -> Thought:
"""Persist a thought to SQLite.
Args:
arrived_at: ISO-8601 timestamp captured when the thinking cycle
started. Falls back to now() for callers that don't supply it.
"""
def _store_thought(self, content: str, seed_type: str) -> Thought:
"""Persist a thought to SQLite."""
thought = Thought(
id=str(uuid.uuid4()),
content=content,
seed_type=seed_type,
parent_id=self._last_thought_id,
created_at=arrived_at or datetime.now(UTC).isoformat(),
created_at=datetime.now(UTC).isoformat(),
)
with _get_conn(self._db_path) as conn:
@@ -1277,53 +1261,6 @@ class ThinkingEngine:
logger.debug("Failed to broadcast thought: %s", exc)
def _query_thoughts(
db_path: Path, query: str, seed_type: str | None, limit: int
) -> list[sqlite3.Row]:
"""Run the thought-search SQL and return matching rows."""
pattern = f"%{query}%"
with _get_conn(db_path) as conn:
if seed_type:
return conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ? AND seed_type = ?
ORDER BY created_at DESC
LIMIT ?
""",
(pattern, seed_type, limit),
).fetchall()
return conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ?
ORDER BY created_at DESC
LIMIT ?
""",
(pattern, limit),
).fetchall()
def _format_thought_rows(rows: list[sqlite3.Row], query: str, seed_type: str | None) -> str:
"""Format thought rows into a human-readable string."""
lines = [f'Found {len(rows)} thought(s) matching "{query}":']
if seed_type:
lines[0] += f' [seed_type="{seed_type}"]'
lines.append("")
for row in rows:
ts = datetime.fromisoformat(row["created_at"])
local_ts = ts.astimezone()
time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
seed = row["seed_type"]
content = row["content"].replace("\n", " ") # Flatten newlines for display
lines.append(f"[{time_str}] ({seed}) {content[:150]}")
return "\n".join(lines)
def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -> str:
"""Search Timmy's thought history for reflections matching a query.
@@ -1341,17 +1278,58 @@ def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -
Formatted string with matching thoughts, newest first, including
timestamps and seed types. Returns a helpful message if no matches found.
"""
# Clamp limit to reasonable bounds
limit = max(1, min(limit, 50))
try:
rows = _query_thoughts(thinking_engine._db_path, query, seed_type, limit)
engine = thinking_engine
db_path = engine._db_path
# Build query with optional seed_type filter
with _get_conn(db_path) as conn:
if seed_type:
rows = conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ? AND seed_type = ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", seed_type, limit),
).fetchall()
else:
rows = conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", limit),
).fetchall()
if not rows:
if seed_type:
return f'No thoughts found matching "{query}" with seed_type="{seed_type}".'
return f'No thoughts found matching "{query}".'
return _format_thought_rows(rows, query, seed_type)
# Format results
lines = [f'Found {len(rows)} thought(s) matching "{query}":']
if seed_type:
lines[0] += f' [seed_type="{seed_type}"]'
lines.append("")
for row in rows:
ts = datetime.fromisoformat(row["created_at"])
local_ts = ts.astimezone()
time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
seed = row["seed_type"]
content = row["content"].replace("\n", " ") # Flatten newlines for display
lines.append(f"[{time_str}] ({seed}) {content[:150]}")
return "\n".join(lines)
except Exception as exc:
logger.warning("Thought search failed: %s", exc)

View File

@@ -24,9 +24,6 @@ from config import settings
logger = logging.getLogger(__name__)
# Max characters of user query included in Lightning invoice memo
_INVOICE_MEMO_MAX_LEN = 50
# Lazy imports to handle test mocking
_ImportError = None
try:
@@ -450,6 +447,7 @@ def consult_grok(query: str) -> str:
)
except (ImportError, AttributeError) as exc:
logger.warning("Tool execution failed (consult_grok logging): %s", exc)
pass
# Generate Lightning invoice for monetization (unless free mode)
invoice_info = ""
@@ -458,11 +456,12 @@ def consult_grok(query: str) -> str:
from lightning.factory import get_backend as get_ln_backend
ln = get_ln_backend()
sats = min(settings.grok_max_sats_per_query, settings.grok_sats_hard_cap)
inv = ln.create_invoice(sats, f"Grok query: {query[:_INVOICE_MEMO_MAX_LEN]}")
sats = min(settings.grok_max_sats_per_query, 100)
inv = ln.create_invoice(sats, f"Grok query: {query[:50]}")
invoice_info = f"\n[Lightning invoice: {sats} sats — {inv.payment_request[:40]}...]"
except (ImportError, OSError, ValueError) as exc:
logger.warning("Tool execution failed (Lightning invoice): %s", exc)
pass
result = backend.run(query)
@@ -910,38 +909,85 @@ def _experiment_tool_catalog() -> dict:
}
_CREATIVE_CATALOG_SOURCES: list[tuple[str, str, list[str]]] = [
("creative.tools.git_tools", "GIT_TOOL_CATALOG", ["forge", "helm", "orchestrator"]),
("creative.tools.image_tools", "IMAGE_TOOL_CATALOG", ["pixel", "orchestrator"]),
("creative.tools.music_tools", "MUSIC_TOOL_CATALOG", ["lyra", "orchestrator"]),
("creative.tools.video_tools", "VIDEO_TOOL_CATALOG", ["reel", "orchestrator"]),
("creative.director", "DIRECTOR_TOOL_CATALOG", ["orchestrator"]),
("creative.assembler", "ASSEMBLER_TOOL_CATALOG", ["reel", "orchestrator"]),
]
def _import_creative_catalogs(catalog: dict) -> None:
"""Import and merge creative tool catalogs from creative module."""
for module_path, attr_name, available_in in _CREATIVE_CATALOG_SOURCES:
_merge_catalog(catalog, module_path, attr_name, available_in)
def _merge_catalog(
catalog: dict, module_path: str, attr_name: str, available_in: list[str]
) -> None:
"""Import a single creative catalog and merge its entries."""
# ── Git tools ─────────────────────────────────────────────────────────────
try:
from importlib import import_module
from creative.tools.git_tools import GIT_TOOL_CATALOG
source_catalog = getattr(import_module(module_path), attr_name)
for tool_id, info in source_catalog.items():
for tool_id, info in GIT_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": available_in,
"available_in": ["forge", "helm", "orchestrator"],
}
except ImportError:
logger.debug("Optional catalog %s.%s not available", module_path, attr_name)
pass
# ── Image tools ────────────────────────────────────────────────────────────
try:
from creative.tools.image_tools import IMAGE_TOOL_CATALOG
for tool_id, info in IMAGE_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["pixel", "orchestrator"],
}
except ImportError:
pass
# ── Music tools ────────────────────────────────────────────────────────────
try:
from creative.tools.music_tools import MUSIC_TOOL_CATALOG
for tool_id, info in MUSIC_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["lyra", "orchestrator"],
}
except ImportError:
pass
# ── Video tools ────────────────────────────────────────────────────────────
try:
from creative.tools.video_tools import VIDEO_TOOL_CATALOG
for tool_id, info in VIDEO_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["reel", "orchestrator"],
}
except ImportError:
pass
# ── Creative pipeline ──────────────────────────────────────────────────────
try:
from creative.director import DIRECTOR_TOOL_CATALOG
for tool_id, info in DIRECTOR_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["orchestrator"],
}
except ImportError:
pass
# ── Assembler tools ───────────────────────────────────────────────────────
try:
from creative.assembler import ASSEMBLER_TOOL_CATALOG
for tool_id, info in ASSEMBLER_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["reel", "orchestrator"],
}
except ImportError:
pass
def get_all_available_tools() -> dict[str, dict]:

View File

@@ -89,31 +89,45 @@ def list_swarm_agents() -> dict[str, Any]:
}
def _find_kimi_cli() -> str | None:
"""Return the path to the kimi CLI binary, or None if not installed."""
def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
"""Delegate a coding task to Kimi, the external coding agent.
Kimi has 262K context and is optimized for code tasks: writing,
debugging, refactoring, test writing. Timmy thinks and plans,
Kimi executes bulk code changes.
Args:
task: Clear, specific coding task description. Include file paths
and expected behavior. Good: "Fix the bug in src/timmy/session.py
where sessions don't persist." Bad: "Fix all bugs."
working_directory: Directory for Kimi to work in. Defaults to repo root.
Returns:
Dict with success status and Kimi's output or error.
"""
import shutil
return shutil.which("kimi")
def _resolve_workdir(working_directory: str) -> str | dict[str, Any]:
"""Return a validated working directory path, or an error dict."""
import subprocess
from pathlib import Path
from config import settings
kimi_path = shutil.which("kimi")
if not kimi_path:
return {
"success": False,
"error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
}
workdir = working_directory or settings.repo_root
if not Path(workdir).is_dir():
return {
"success": False,
"error": f"Working directory does not exist: {workdir}",
}
return workdir
cmd = [kimi_path, "--print", "-p", task]
def _run_kimi(cmd: list[str], workdir: str) -> dict[str, Any]:
"""Execute the kimi subprocess and return a result dict."""
import subprocess
logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
try:
result = subprocess.run(
@@ -139,39 +153,7 @@ def _run_kimi(cmd: list[str], workdir: str) -> dict[str, Any]:
"error": "Kimi timed out after 300s. Task may be too broad — try breaking it into smaller pieces.",
}
except Exception as exc:
logger.exception("Failed to run Kimi subprocess")
return {
"success": False,
"error": f"Failed to run Kimi: {exc}",
}
def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
"""Delegate a coding task to Kimi, the external coding agent.
Kimi has 262K context and is optimized for code tasks: writing,
debugging, refactoring, test writing. Timmy thinks and plans,
Kimi executes bulk code changes.
Args:
task: Clear, specific coding task description. Include file paths
and expected behavior. Good: "Fix the bug in src/timmy/session.py
where sessions don't persist." Bad: "Fix all bugs."
working_directory: Directory for Kimi to work in. Defaults to repo root.
Returns:
Dict with success status and Kimi's output or error.
"""
kimi_path = _find_kimi_cli()
if not kimi_path:
return {
"success": False,
"error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
}
workdir = _resolve_workdir(working_directory)
if isinstance(workdir, dict):
return workdir
logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
return _run_kimi([kimi_path, "--print", "-p", task], workdir)

View File

@@ -122,7 +122,6 @@ def check_ollama_health() -> dict[str, Any]:
models = response.json().get("models", [])
result["available_models"] = [m.get("name", "") for m in models]
except Exception as e:
logger.exception("Ollama health check failed")
result["error"] = str(e)
return result
@@ -290,7 +289,6 @@ def get_live_system_status() -> dict[str, Any]:
try:
result["system"] = get_system_info()
except Exception as exc:
logger.exception("Failed to get system info")
result["system"] = {"error": str(exc)}
# Task queue
@@ -303,7 +301,6 @@ def get_live_system_status() -> dict[str, Any]:
try:
result["memory"] = get_memory_status()
except Exception as exc:
logger.exception("Failed to get memory status")
result["memory"] = {"error": str(exc)}
# Uptime
@@ -329,46 +326,6 @@ def get_live_system_status() -> dict[str, Any]:
return result
def _build_pytest_cmd(venv_python: Path, scope: str) -> list[str]:
"""Build the pytest command list for the given scope."""
cmd = [str(venv_python), "-m", "pytest", "-x", "-q", "--tb=short", "--timeout=30"]
if scope == "fast":
cmd.extend(
[
"--ignore=tests/functional",
"--ignore=tests/e2e",
"--ignore=tests/integrations",
"tests/",
]
)
elif scope == "full":
cmd.append("tests/")
else:
cmd.append(scope)
return cmd
def _parse_pytest_output(output: str) -> dict[str, int]:
"""Extract passed/failed/error counts from pytest output."""
import re
passed = failed = errors = 0
for line in output.splitlines():
if "passed" in line or "failed" in line or "error" in line:
nums = re.findall(r"(\d+) (passed|failed|error)", line)
for count, kind in nums:
if kind == "passed":
passed = int(count)
elif kind == "failed":
failed = int(count)
elif kind == "error":
errors = int(count)
return {"passed": passed, "failed": failed, "errors": errors}
def run_self_tests(scope: str = "fast", _repo_root: str | None = None) -> dict[str, Any]:
"""Run Timmy's own test suite and report results.
@@ -392,22 +349,53 @@ def run_self_tests(scope: str = "fast", _repo_root: str | None = None) -> dict[s
if not venv_python.exists():
return {"success": False, "error": f"No venv found at {venv_python}"}
cmd = _build_pytest_cmd(venv_python, scope)
cmd = [str(venv_python), "-m", "pytest", "-x", "-q", "--tb=short", "--timeout=30"]
if scope == "fast":
# Unit tests only — skip functional/e2e/integration
cmd.extend(
[
"--ignore=tests/functional",
"--ignore=tests/e2e",
"--ignore=tests/integrations",
"tests/",
]
)
elif scope == "full":
cmd.append("tests/")
else:
# Specific path
cmd.append(scope)
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=120, cwd=repo)
output = result.stdout + result.stderr
counts = _parse_pytest_output(output)
# Parse pytest output for counts
passed = failed = errors = 0
for line in output.splitlines():
if "passed" in line or "failed" in line or "error" in line:
import re
nums = re.findall(r"(\d+) (passed|failed|error)", line)
for count, kind in nums:
if kind == "passed":
passed = int(count)
elif kind == "failed":
failed = int(count)
elif kind == "error":
errors = int(count)
return {
"success": result.returncode == 0,
**counts,
"total": counts["passed"] + counts["failed"] + counts["errors"],
"passed": passed,
"failed": failed,
"errors": errors,
"total": passed + failed + errors,
"return_code": result.returncode,
"summary": output[-2000:] if len(output) > 2000 else output,
}
except subprocess.TimeoutExpired:
return {"success": False, "error": "Test run timed out (120s limit)"}
except Exception as exc:
logger.exception("Self-test run failed")
return {"success": False, "error": str(exc)}

View File

@@ -78,11 +78,6 @@ DEFAULT_MAX_UTTERANCE = 30.0 # safety cap — don't record forever
DEFAULT_SESSION_ID = "voice"
def _rms(block: np.ndarray) -> float:
"""Compute root-mean-square energy of an audio block."""
return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
@dataclass
class VoiceConfig:
"""Configuration for the voice loop."""
@@ -166,6 +161,13 @@ class VoiceLoop:
min_blocks = int(self.config.min_utterance / 0.1)
max_blocks = int(self.config.max_utterance / 0.1)
audio_chunks: list[np.ndarray] = []
silent_count = 0
recording = False
def _rms(block: np.ndarray) -> float:
return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
sys.stdout.write("\n 🎤 Listening... (speak now)\n")
sys.stdout.flush()
@@ -175,69 +177,42 @@ class VoiceLoop:
dtype="float32",
blocksize=block_size,
) as stream:
chunks = self._capture_audio_blocks(stream, block_size, silence_blocks, max_blocks)
while self._running:
block, overflowed = stream.read(block_size)
if overflowed:
logger.debug("Audio buffer overflowed")
return self._finalize_utterance(chunks, min_blocks, sr)
rms = _rms(block)
def _capture_audio_blocks(
self,
stream,
block_size: int,
silence_blocks: int,
max_blocks: int,
) -> list[np.ndarray]:
"""Read audio blocks from *stream* until silence or max length.
Returns the list of captured audio chunks (may be empty).
"""
chunks: list[np.ndarray] = []
silent_count = 0
recording = False
while self._running:
block, overflowed = stream.read(block_size)
if overflowed:
logger.debug("Audio buffer overflowed")
rms = _rms(block)
if not recording:
if rms > self.config.silence_threshold:
recording = True
silent_count = 0
chunks.append(block.copy())
sys.stdout.write(" 📢 Recording...\r")
sys.stdout.flush()
else:
chunks.append(block.copy())
if rms < self.config.silence_threshold:
silent_count += 1
if not recording:
if rms > self.config.silence_threshold:
recording = True
silent_count = 0
audio_chunks.append(block.copy())
sys.stdout.write(" 📢 Recording...\r")
sys.stdout.flush()
else:
silent_count = 0
audio_chunks.append(block.copy())
if silent_count >= silence_blocks:
break
if rms < self.config.silence_threshold:
silent_count += 1
else:
silent_count = 0
if len(chunks) >= max_blocks:
logger.info("Max utterance length reached, stopping.")
break
# End of utterance
if silent_count >= silence_blocks:
break
return chunks
# Safety cap
if len(audio_chunks) >= max_blocks:
logger.info("Max utterance length reached, stopping.")
break
@staticmethod
def _finalize_utterance(
chunks: list[np.ndarray], min_blocks: int, sample_rate: int
) -> np.ndarray | None:
"""Concatenate recorded chunks and report duration.
Returns ``None`` if the utterance is too short to be meaningful.
"""
if not chunks or len(chunks) < min_blocks:
if not audio_chunks or len(audio_chunks) < min_blocks:
return None
audio = np.concatenate(chunks, axis=0).flatten()
duration = len(audio) / sample_rate
audio = np.concatenate(audio_chunks, axis=0).flatten()
duration = len(audio) / sr
sys.stdout.write(f" ✂️ Captured {duration:.1f}s of audio\n")
sys.stdout.flush()
return audio
@@ -394,33 +369,15 @@ class VoiceLoop:
# ── Main Loop ───────────────────────────────────────────────────────
# Whisper hallucinates these on silence/noise — skip them.
_WHISPER_HALLUCINATIONS = frozenset(
{
"you",
"thanks.",
"thank you.",
"bye.",
"",
"thanks for watching!",
"thank you for watching!",
}
)
def run(self) -> None:
"""Run the voice loop. Blocks until Ctrl-C."""
self._ensure_piper()
# Spoken phrases that end the voice session.
_EXIT_COMMANDS = frozenset(
{
"goodbye",
"exit",
"quit",
"stop",
"goodbye timmy",
"stop listening",
}
)
# Suppress MCP / Agno stderr noise during voice mode.
_suppress_mcp_noise()
# Suppress MCP async-generator teardown tracebacks on exit.
_install_quiet_asyncgen_hooks()
def _log_banner(self) -> None:
"""Log the startup banner with STT/TTS/LLM configuration."""
tts_label = (
"macOS say"
if self.config.use_say_fallback
@@ -436,50 +393,52 @@ class VoiceLoop:
" Press Ctrl-C to exit.\n" + "=" * 60
)
def _is_hallucination(self, text: str) -> bool:
"""Return True if *text* is a known Whisper hallucination."""
return not text or text.lower() in self._WHISPER_HALLUCINATIONS
def _is_exit_command(self, text: str) -> bool:
"""Return True if the user asked to stop the voice session."""
return text.lower().strip().rstrip(".!") in self._EXIT_COMMANDS
def _process_turn(self, text: str) -> None:
"""Handle a single listen-think-speak turn after transcription."""
sys.stdout.write(f"\n 👤 You: {text}\n")
sys.stdout.flush()
response = self._think(text)
sys.stdout.write(f" 🤖 Timmy: {response}\n")
sys.stdout.flush()
self._speak(response)
def run(self) -> None:
"""Run the voice loop. Blocks until Ctrl-C."""
self._ensure_piper()
_suppress_mcp_noise()
_install_quiet_asyncgen_hooks()
self._log_banner()
self._running = True
try:
while self._running:
# 1. LISTEN — record until silence
audio = self._record_utterance()
if audio is None:
continue
# 2. TRANSCRIBE — Whisper STT
text = self._transcribe(audio)
if self._is_hallucination(text):
if not text or text.lower() in (
"you",
"thanks.",
"thank you.",
"bye.",
"",
"thanks for watching!",
"thank you for watching!",
):
# Whisper hallucinations on silence/noise
logger.debug("Ignoring likely Whisper hallucination: '%s'", text)
continue
if self._is_exit_command(text):
sys.stdout.write(f"\n 👤 You: {text}\n")
sys.stdout.flush()
# Exit commands
if text.lower().strip().rstrip(".!") in (
"goodbye",
"exit",
"quit",
"stop",
"goodbye timmy",
"stop listening",
):
logger.info("👋 Goodbye!")
break
self._process_turn(text)
# 3. THINK — send to Timmy
response = self._think(text)
sys.stdout.write(f" 🤖 Timmy: {response}\n")
sys.stdout.flush()
# 4. SPEAK — TTS output
self._speak(response)
except KeyboardInterrupt:
logger.info("👋 Voice loop stopped.")

View File

@@ -86,40 +86,6 @@ def _pip_snapshot(mood: str, confidence: float) -> dict:
return pip_familiar.snapshot().to_dict()
def _resolve_mood(state) -> str:
"""Map cognitive mood/engagement to a presence mood string."""
if state.engagement == "idle" and state.mood == "settled":
return "calm"
return _MOOD_MAP.get(state.mood, "calm")
def _resolve_confidence(state) -> float:
"""Compute normalised confidence from cognitive tracker state."""
if state._confidence_count > 0:
raw = state._confidence_sum / state._confidence_count
else:
raw = 0.7
return round(max(0.0, min(1.0, raw)), 2)
def _build_active_threads(state) -> list[dict]:
"""Convert active commitments into presence thread dicts."""
return [
{"type": "thinking", "ref": c[:80], "status": "active"}
for c in state.active_commitments[:10]
]
def _build_environment() -> dict:
"""Return the environment section using local wall-clock time."""
local_now = datetime.now()
return {
"time_of_day": _time_of_day(local_now.hour),
"local_time": local_now.strftime("%-I:%M %p"),
"day_of_week": local_now.strftime("%A"),
}
def get_state_dict() -> dict:
"""Build presence state dict from current cognitive state.
@@ -132,19 +98,37 @@ def get_state_dict() -> dict:
state = cognitive_tracker.get_state()
now = datetime.now(UTC)
mood = _resolve_mood(state)
confidence = _resolve_confidence(state)
# Map cognitive mood to presence mood
mood = _MOOD_MAP.get(state.mood, "calm")
if state.engagement == "idle" and state.mood == "settled":
mood = "calm"
# Confidence from cognitive tracker
if state._confidence_count > 0:
confidence = state._confidence_sum / state._confidence_count
else:
confidence = 0.7
# Build active threads from commitments
threads = []
for commitment in state.active_commitments[:10]:
threads.append({"type": "thinking", "ref": commitment[:80], "status": "active"})
# Activity
activity = _ACTIVITY_MAP.get(state.engagement, "idle")
# Environment
local_now = datetime.now()
return {
"version": 1,
"liveness": now.strftime("%Y-%m-%dT%H:%M:%SZ"),
"current_focus": state.focus_topic or "",
"active_threads": _build_active_threads(state),
"active_threads": threads,
"recent_events": [],
"concerns": [],
"mood": mood,
"confidence": confidence,
"confidence": round(max(0.0, min(1.0, confidence)), 2),
"energy": round(_current_energy(), 2),
"identity": {
"name": "Timmy",
@@ -159,7 +143,11 @@ def get_state_dict() -> dict:
"visitor_present": False,
"conversation_turns": state.conversation_depth,
},
"environment": _build_environment(),
"environment": {
"time_of_day": _time_of_day(local_now.hour),
"local_time": local_now.strftime("%-I:%M %p"),
"day_of_week": local_now.strftime("%A"),
},
"familiar": _pip_snapshot(mood, confidence),
"meta": {
"schema_version": 1,

View File

@@ -1,7 +0,0 @@
"""Timmy Control Panel — CLI entry point for automations.
This package provides the `timmyctl` command-line interface for managing
Timmy automations, configuration, and daily operations.
"""
__version__ = "1.0.0"

View File

@@ -1,316 +0,0 @@
"""Timmy Control Panel CLI — primary control surface for automations.
Usage:
timmyctl daily-run # Run the Daily Run orchestration
timmyctl log-run # Capture a Daily Run logbook entry
timmyctl inbox # Show what's "calling Timmy"
timmyctl config # Display key configuration
"""
import json
import os
from pathlib import Path
from typing import Any
import typer
import yaml
from rich.console import Console
from rich.table import Table
# Initialize Rich console for nice output
console = Console()
app = typer.Typer(
help="Timmy Control Panel — primary control surface for automations",
rich_markup_mode="rich",
)
# Default config paths
DEFAULT_CONFIG_DIR = Path("timmy_automations/config")
AUTOMATIONS_CONFIG = DEFAULT_CONFIG_DIR / "automations.json"
DAILY_RUN_CONFIG = DEFAULT_CONFIG_DIR / "daily_run.json"
TRIAGE_RULES_CONFIG = DEFAULT_CONFIG_DIR / "triage_rules.yaml"
def _load_json_config(path: Path) -> dict[str, Any]:
"""Load a JSON config file, returning empty dict on error."""
try:
with open(path, encoding="utf-8") as f:
return json.load(f)
except (FileNotFoundError, json.JSONDecodeError) as e:
console.print(f"[red]Error loading {path}: {e}[/red]")
return {}
def _load_yaml_config(path: Path) -> dict[str, Any]:
"""Load a YAML config file, returning empty dict on error."""
try:
with open(path, encoding="utf-8") as f:
return yaml.safe_load(f) or {}
except (FileNotFoundError, yaml.YAMLError) as e:
console.print(f"[red]Error loading {path}: {e}[/red]")
return {}
def _get_config_dir() -> Path:
"""Return the config directory path."""
# Allow override via environment variable
env_dir = os.environ.get("TIMMY_CONFIG_DIR")
if env_dir:
return Path(env_dir)
return DEFAULT_CONFIG_DIR
@app.command()
def daily_run(
dry_run: bool = typer.Option(
False, "--dry-run", "-n", help="Show what would run without executing"
),
verbose: bool = typer.Option(False, "--verbose", "-v", help="Show detailed output"),
):
"""Run the Daily Run orchestration (agenda + summary).
Executes the daily run workflow including:
- Loop Guard checks
- Cycle Retrospective
- Triage scoring (if scheduled)
- Loop introspection (if scheduled)
"""
console.print("[bold green]Timmy Daily Run[/bold green]")
console.print()
config_path = _get_config_dir() / "daily_run.json"
config = _load_json_config(config_path)
if not config:
console.print("[yellow]No daily run configuration found.[/yellow]")
raise typer.Exit(1)
schedules = config.get("schedules", {})
triggers = config.get("triggers", {})
if verbose:
console.print(f"[dim]Config loaded from: {config_path}[/dim]")
console.print()
# Show the daily run schedule
table = Table(title="Daily Run Schedules")
table.add_column("Schedule", style="cyan")
table.add_column("Description", style="green")
table.add_column("Automations", style="yellow")
for schedule_name, schedule_data in schedules.items():
automations = schedule_data.get("automations", [])
table.add_row(
schedule_name,
schedule_data.get("description", ""),
", ".join(automations) if automations else "",
)
console.print(table)
console.print()
# Show triggers
trigger_table = Table(title="Triggers")
trigger_table.add_column("Trigger", style="cyan")
trigger_table.add_column("Description", style="green")
trigger_table.add_column("Automations", style="yellow")
for trigger_name, trigger_data in triggers.items():
automations = trigger_data.get("automations", [])
trigger_table.add_row(
trigger_name,
trigger_data.get("description", ""),
", ".join(automations) if automations else "",
)
console.print(trigger_table)
console.print()
if dry_run:
console.print("[yellow]Dry run mode — no actions executed.[/yellow]")
else:
console.print("[green]Executing daily run automations...[/green]")
# TODO: Implement actual automation execution
# This would call the appropriate scripts from the automations config
console.print("[dim]Automation execution not yet implemented.[/dim]")
@app.command()
def log_run(
message: str = typer.Argument(..., help="Logbook entry message"),
category: str = typer.Option(
"general", "--category", "-c", help="Entry category (e.g., retro, todo, note)"
),
):
"""Capture a quick Daily Run logbook entry.
Logs a structured entry to the daily run logbook for later review.
Entries are timestamped and categorized automatically.
"""
from datetime import datetime
timestamp = datetime.now().isoformat()
console.print("[bold green]Daily Run Log Entry[/bold green]")
console.print()
console.print(f"[dim]Timestamp:[/dim] {timestamp}")
console.print(f"[dim]Category:[/dim] {category}")
console.print(f"[dim]Message:[/dim] {message}")
console.print()
# TODO: Persist to actual logbook file
# This would append to a logbook file (e.g., .loop/logbook.jsonl)
console.print("[green]✓[/green] Entry logged (simulated)")
@app.command()
def inbox(
limit: int = typer.Option(10, "--limit", "-l", help="Maximum items to show"),
include_prs: bool = typer.Option(True, "--prs/--no-prs", help="Show open PRs"),
include_issues: bool = typer.Option(True, "--issues/--no-issues", help="Show relevant issues"),
):
"""Show what's "calling Timmy" — PRs, Daily Run items, alerts.
Displays a unified inbox of items requiring attention:
- Open pull requests awaiting review
- Daily run queue items
- Alerts and notifications
"""
console.print("[bold green]Timmy Inbox[/bold green]")
console.print()
# Load automations to show what's enabled
config_path = _get_config_dir() / "automations.json"
config = _load_json_config(config_path)
automations = config.get("automations", [])
enabled_automations = [a for a in automations if a.get("enabled", False)]
# Show automation status
auto_table = Table(title="Active Automations")
auto_table.add_column("ID", style="cyan")
auto_table.add_column("Name", style="green")
auto_table.add_column("Category", style="yellow")
auto_table.add_column("Trigger", style="magenta")
for auto in enabled_automations[:limit]:
auto_table.add_row(
auto.get("id", ""),
auto.get("name", ""),
"" if auto.get("enabled", False) else "",
auto.get("category", ""),
)
console.print(auto_table)
console.print()
# TODO: Fetch actual PRs from Gitea API
if include_prs:
pr_table = Table(title="Open Pull Requests (placeholder)")
pr_table.add_column("#", style="cyan")
pr_table.add_column("Title", style="green")
pr_table.add_column("Author", style="yellow")
pr_table.add_column("Status", style="magenta")
pr_table.add_row("", "[dim]No PRs fetched (Gitea API not configured)[/dim]", "", "")
console.print(pr_table)
console.print()
# TODO: Fetch relevant issues from Gitea API
if include_issues:
issue_table = Table(title="Issues Calling for Attention (placeholder)")
issue_table.add_column("#", style="cyan")
issue_table.add_column("Title", style="green")
issue_table.add_column("Type", style="yellow")
issue_table.add_column("Priority", style="magenta")
issue_table.add_row(
"", "[dim]No issues fetched (Gitea API not configured)[/dim]", "", ""
)
console.print(issue_table)
console.print()
@app.command()
def config(
key: str | None = typer.Argument(None, help="Show specific config key (e.g., 'automations')"),
show_rules: bool = typer.Option(False, "--rules", "-r", help="Show triage rules overview"),
):
"""Display key configuration — labels, logbook issue ID, token rules overview.
Shows the current Timmy automation configuration including:
- Automation manifest
- Daily run schedules
- Triage scoring rules
"""
console.print("[bold green]Timmy Configuration[/bold green]")
console.print()
config_dir = _get_config_dir()
if key == "automations" or key is None:
auto_config = _load_json_config(config_dir / "automations.json")
automations = auto_config.get("automations", [])
table = Table(title="Automations Manifest")
table.add_column("ID", style="cyan")
table.add_column("Name", style="green")
table.add_column("Enabled", style="yellow")
table.add_column("Category", style="magenta")
for auto in automations:
enabled = "" if auto.get("enabled", False) else ""
table.add_row(
auto.get("id", ""),
auto.get("name", ""),
enabled,
auto.get("category", ""),
)
console.print(table)
console.print()
if key == "daily_run" or (key is None and not show_rules):
daily_config = _load_json_config(config_dir / "daily_run.json")
if daily_config:
console.print("[bold]Daily Run Configuration:[/bold]")
console.print(f"[dim]Version:[/dim] {daily_config.get('version', 'unknown')}")
console.print(f"[dim]Description:[/dim] {daily_config.get('description', '')}")
console.print()
if show_rules or key == "triage_rules":
rules_config = _load_yaml_config(config_dir / "triage_rules.yaml")
if rules_config:
thresholds = rules_config.get("thresholds", {})
console.print("[bold]Triage Scoring Rules:[/bold]")
console.print(f" Ready threshold: {thresholds.get('ready', 'N/A')}")
console.print(f" Excellent threshold: {thresholds.get('excellent', 'N/A')}")
console.print()
scope = rules_config.get("scope", {})
console.print("[bold]Scope Scoring:[/bold]")
console.print(f" Meta penalty: {scope.get('meta_penalty', 'N/A')}")
console.print()
alignment = rules_config.get("alignment", {})
console.print("[bold]Alignment Scoring:[/bold]")
console.print(f" Bug score: {alignment.get('bug_score', 'N/A')}")
console.print(f" Refactor score: {alignment.get('refactor_score', 'N/A')}")
console.print(f" Feature score: {alignment.get('feature_score', 'N/A')}")
console.print()
quarantine = rules_config.get("quarantine", {})
console.print("[bold]Quarantine Rules:[/bold]")
console.print(f" Failure threshold: {quarantine.get('failure_threshold', 'N/A')}")
console.print(f" Lookback cycles: {quarantine.get('lookback_cycles', 'N/A')}")
console.print()
def main():
"""Entry point for the timmyctl CLI."""
app()
if __name__ == "__main__":
main()

View File

@@ -2493,57 +2493,3 @@
.db-cell { max-width: 300px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
.db-cell:hover { white-space: normal; word-break: break-all; }
.db-truncated { font-size: 0.7rem; color: var(--amber); padding: 0.3rem 0; }
/* ── Tower ────────────────────────────────────────────────────────────── */
.tower-container { max-width: 1400px; margin: 0 auto; }
.tower-header { margin-bottom: 1rem; }
.tower-title { font-size: 1.6rem; font-weight: 700; color: var(--green); letter-spacing: 0.15em; }
.tower-subtitle { font-size: 0.85rem; color: var(--text-dim); }
.tower-conn-badge { font-size: 0.7rem; font-weight: 600; padding: 2px 8px; border-radius: 3px; letter-spacing: 0.08em; }
.tower-conn-live { color: var(--green); border: 1px solid var(--green); }
.tower-conn-offline { color: var(--red); border: 1px solid var(--red); }
.tower-conn-connecting { color: var(--amber); border: 1px solid var(--amber); }
.tower-phase-card { min-height: 300px; }
.tower-phase-thinking { border-left: 3px solid var(--purple); }
.tower-phase-predicting { border-left: 3px solid var(--orange); }
.tower-phase-advising { border-left: 3px solid var(--green); }
.tower-scroll { max-height: 50vh; overflow-y: auto; }
.tower-empty { text-align: center; color: var(--text-dim); padding: 16px; font-size: 0.85rem; }
.tower-stat-grid { display: grid; grid-template-columns: repeat(4, 1fr); gap: 0.5rem; text-align: center; }
.tower-stat-label { display: block; font-size: 0.65rem; color: var(--text-dim); letter-spacing: 0.1em; }
.tower-stat-value { display: block; font-size: 1.1rem; font-weight: 700; color: var(--text-bright); }
.tower-event { padding: 8px; margin-bottom: 6px; border-left: 3px solid var(--border); border-radius: 3px; background: var(--bg-card); }
.tower-etype-task_posted { border-left-color: var(--purple); }
.tower-etype-bid_submitted { border-left-color: var(--orange); }
.tower-etype-task_completed { border-left-color: var(--green); }
.tower-etype-task_failed { border-left-color: var(--red); }
.tower-etype-agent_joined { border-left-color: var(--purple); }
.tower-etype-tool_executed { border-left-color: var(--amber); }
.tower-ev-head { display: flex; justify-content: space-between; align-items: center; margin-bottom: 4px; }
.tower-ev-badge { font-size: 0.65rem; font-weight: 600; color: var(--text-bright); letter-spacing: 0.08em; }
.tower-ev-dots { font-size: 0.6rem; color: var(--amber); }
.tower-ev-desc { font-size: 0.8rem; color: var(--text); }
.tower-ev-time { font-size: 0.65rem; color: var(--text-dim); margin-top: 2px; }
.tower-pred { padding: 8px; margin-bottom: 6px; border-radius: 3px; background: var(--bg-card); border-left: 3px solid var(--orange); }
.tower-pred-done { border-left-color: var(--green); }
.tower-pred-pending { border-left-color: var(--amber); }
.tower-pred-head { display: flex; justify-content: space-between; align-items: center; }
.tower-pred-task { font-size: 0.75rem; font-weight: 600; color: var(--text-bright); font-family: monospace; }
.tower-pred-acc { font-size: 0.75rem; font-weight: 700; }
.tower-pred-detail { font-size: 0.75rem; color: var(--text-dim); margin-top: 4px; }
.tower-advisory { padding: 8px; margin-bottom: 6px; border-radius: 3px; background: var(--bg-card); border-left: 3px solid var(--border); }
.tower-adv-high { border-left-color: var(--red); }
.tower-adv-medium { border-left-color: var(--orange); }
.tower-adv-low { border-left-color: var(--green); }
.tower-adv-head { display: flex; justify-content: space-between; font-size: 0.65rem; margin-bottom: 4px; }
.tower-adv-cat { font-weight: 600; color: var(--text-dim); letter-spacing: 0.08em; }
.tower-adv-prio { font-weight: 700; color: var(--amber); }
.tower-adv-title { font-size: 0.85rem; font-weight: 600; color: var(--text-bright); }
.tower-adv-detail { font-size: 0.8rem; color: var(--text); margin-top: 2px; }
.tower-adv-action { font-size: 0.75rem; color: var(--green); margin-top: 4px; font-style: italic; }

View File

@@ -13,121 +13,11 @@
<div class="mood" id="mood-text">focused</div>
</div>
<div id="connection-dot"></div>
<button id="info-btn" class="info-button" aria-label="About The Matrix" title="About The Matrix">
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<circle cx="12" cy="12" r="10"></circle>
<line x1="12" y1="16" x2="12" y2="12"></line>
<line x1="12" y1="8" x2="12.01" y2="8"></line>
</svg>
</button>
<button id="submit-job-btn" class="submit-job-button" aria-label="Submit Job" title="Submit Job">
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<path d="M12 5v14M5 12h14"></path>
</svg>
<span>Job</span>
</button>
<div id="speech-area">
<div class="bubble" id="speech-bubble"></div>
</div>
</div>
<!-- Submit Job Modal -->
<div id="submit-job-modal" class="submit-job-modal">
<div class="submit-job-content">
<button id="submit-job-close" class="submit-job-close" aria-label="Close">
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<line x1="18" y1="6" x2="6" y2="18"></line>
<line x1="6" y1="6" x2="18" y2="18"></line>
</svg>
</button>
<h2>Submit Job</h2>
<p class="submit-job-subtitle">Create a task for Timmy and the agent swarm</p>
<form id="submit-job-form" class="submit-job-form">
<div class="form-group">
<label for="job-title">Title <span class="required">*</span></label>
<input type="text" id="job-title" name="title" placeholder="Brief description of the task" maxlength="200">
<div class="char-count" id="title-char-count">0 / 200</div>
<div class="validation-error" id="title-error"></div>
</div>
<div class="form-group">
<label for="job-description">Description</label>
<textarea id="job-description" name="description" placeholder="Detailed instructions, requirements, and context..." rows="6" maxlength="2000"></textarea>
<div class="char-count" id="desc-char-count">0 / 2000</div>
<div class="validation-warning" id="desc-warning"></div>
<div class="validation-error" id="desc-error"></div>
</div>
<div class="form-group">
<label for="job-priority">Priority</label>
<select id="job-priority" name="priority">
<option value="low">Low</option>
<option value="medium" selected>Medium</option>
<option value="high">High</option>
<option value="urgent">Urgent</option>
</select>
</div>
<div class="submit-job-actions">
<button type="button" id="cancel-job-btn" class="btn-secondary">Cancel</button>
<button type="submit" id="submit-job-submit" class="btn-primary" disabled>Submit Job</button>
</div>
</form>
<div id="submit-job-success" class="submit-job-success hidden">
<div class="success-icon">
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<path d="M22 11.08V12a10 10 0 1 1-5.93-9.14"></path>
<polyline points="22 4 12 14.01 9 11.01"></polyline>
</svg>
</div>
<h3>Job Submitted!</h3>
<p>Your task has been added to the queue. Timmy will review it shortly.</p>
<button type="button" id="submit-another-btn" class="btn-primary">Submit Another</button>
</div>
</div>
<div id="submit-job-backdrop" class="submit-job-backdrop"></div>
</div>
<!-- About Panel -->
<div id="about-panel" class="about-panel">
<div class="about-panel-content">
<button id="about-close" class="about-close" aria-label="Close">
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<line x1="18" y1="6" x2="6" y2="18"></line>
<line x1="6" y1="6" x2="18" y2="18"></line>
</svg>
</button>
<h2>Welcome to The Matrix</h2>
<section>
<h3>🌌 The Matrix</h3>
<p>The Matrix is a 3D visualization of Timmy's AI agent workspace. Enter the workshop to see Timmy at work—pondering the arcane arts of code, managing tasks, and orchestrating autonomous agents in real-time.</p>
</section>
<section>
<h3>🛠️ The Workshop</h3>
<p>The Workshop is where you interact directly with Timmy:</p>
<ul>
<li><strong>Submit Jobs</strong> — Create tasks, delegate work, and track progress</li>
<li><strong>Chat with Agents</strong> — Converse with Timmy and his swarm of specialized agents</li>
<li><strong>Fund Sessions</strong> — Power your work with satoshis via Lightning Network</li>
</ul>
</section>
<section>
<h3>⚡ Lightning & Sats</h3>
<p>The Matrix runs on Bitcoin. Sessions are funded with satoshis (sats) over the Lightning Network—enabling fast, cheap micropayments that keep Timmy energized and working for you. No subscriptions, no limits—pay as you go.</p>
</section>
<div class="about-footer">
<span>Sovereign AI · Soul on Bitcoin</span>
</div>
</div>
<div id="about-backdrop" class="about-backdrop"></div>
</div>
<script type="importmap">
{
"imports": {
@@ -184,271 +74,6 @@
});
stateReader.connect();
// --- About Panel ---
const infoBtn = document.getElementById("info-btn");
const aboutPanel = document.getElementById("about-panel");
const aboutClose = document.getElementById("about-close");
const aboutBackdrop = document.getElementById("about-backdrop");
function openAboutPanel() {
aboutPanel.classList.add("open");
document.body.style.overflow = "hidden";
}
function closeAboutPanel() {
aboutPanel.classList.remove("open");
document.body.style.overflow = "";
}
infoBtn.addEventListener("click", openAboutPanel);
aboutClose.addEventListener("click", closeAboutPanel);
aboutBackdrop.addEventListener("click", closeAboutPanel);
// Close on Escape key
document.addEventListener("keydown", (e) => {
if (e.key === "Escape" && aboutPanel.classList.contains("open")) {
closeAboutPanel();
}
});
// --- Submit Job Modal ---
const submitJobBtn = document.getElementById("submit-job-btn");
const submitJobModal = document.getElementById("submit-job-modal");
const submitJobClose = document.getElementById("submit-job-close");
const submitJobBackdrop = document.getElementById("submit-job-backdrop");
const cancelJobBtn = document.getElementById("cancel-job-btn");
const submitJobForm = document.getElementById("submit-job-form");
const submitJobSubmit = document.getElementById("submit-job-submit");
const jobTitle = document.getElementById("job-title");
const jobDescription = document.getElementById("job-description");
const titleCharCount = document.getElementById("title-char-count");
const descCharCount = document.getElementById("desc-char-count");
const titleError = document.getElementById("title-error");
const descError = document.getElementById("desc-error");
const descWarning = document.getElementById("desc-warning");
const submitJobSuccess = document.getElementById("submit-job-success");
const submitAnotherBtn = document.getElementById("submit-another-btn");
// Constants
const MAX_TITLE_LENGTH = 200;
const MAX_DESC_LENGTH = 2000;
const TITLE_WARNING_THRESHOLD = 150;
const DESC_WARNING_THRESHOLD = 1800;
function openSubmitJobModal() {
submitJobModal.classList.add("open");
document.body.style.overflow = "hidden";
jobTitle.focus();
validateForm();
}
function closeSubmitJobModal() {
submitJobModal.classList.remove("open");
document.body.style.overflow = "";
// Reset form after animation
setTimeout(() => {
resetForm();
}, 300);
}
function resetForm() {
submitJobForm.reset();
submitJobForm.classList.remove("hidden");
submitJobSuccess.classList.add("hidden");
updateCharCounts();
clearErrors();
validateForm();
}
function clearErrors() {
titleError.textContent = "";
titleError.classList.remove("visible");
descError.textContent = "";
descError.classList.remove("visible");
descWarning.textContent = "";
descWarning.classList.remove("visible");
jobTitle.classList.remove("error");
jobDescription.classList.remove("error");
}
function updateCharCounts() {
const titleLen = jobTitle.value.length;
const descLen = jobDescription.value.length;
titleCharCount.textContent = `${titleLen} / ${MAX_TITLE_LENGTH}`;
descCharCount.textContent = `${descLen} / ${MAX_DESC_LENGTH}`;
// Update color based on thresholds
if (titleLen > MAX_TITLE_LENGTH) {
titleCharCount.classList.add("over-limit");
} else if (titleLen > TITLE_WARNING_THRESHOLD) {
titleCharCount.classList.add("near-limit");
titleCharCount.classList.remove("over-limit");
} else {
titleCharCount.classList.remove("near-limit", "over-limit");
}
if (descLen > MAX_DESC_LENGTH) {
descCharCount.classList.add("over-limit");
} else if (descLen > DESC_WARNING_THRESHOLD) {
descCharCount.classList.add("near-limit");
descCharCount.classList.remove("over-limit");
} else {
descCharCount.classList.remove("near-limit", "over-limit");
}
}
function validateTitle() {
const value = jobTitle.value.trim();
const length = jobTitle.value.length;
if (length > MAX_TITLE_LENGTH) {
titleError.textContent = `Title must be ${MAX_TITLE_LENGTH} characters or less`;
titleError.classList.add("visible");
jobTitle.classList.add("error");
return false;
}
if (value === "") {
titleError.textContent = "Title is required";
titleError.classList.add("visible");
jobTitle.classList.add("error");
return false;
}
titleError.textContent = "";
titleError.classList.remove("visible");
jobTitle.classList.remove("error");
return true;
}
function validateDescription() {
const length = jobDescription.value.length;
if (length > MAX_DESC_LENGTH) {
descError.textContent = `Description must be ${MAX_DESC_LENGTH} characters or less`;
descError.classList.add("visible");
descWarning.textContent = "";
descWarning.classList.remove("visible");
jobDescription.classList.add("error");
return false;
}
// Show warning when near limit
if (length > DESC_WARNING_THRESHOLD && length <= MAX_DESC_LENGTH) {
const remaining = MAX_DESC_LENGTH - length;
descWarning.textContent = `${remaining} characters remaining`;
descWarning.classList.add("visible");
} else {
descWarning.textContent = "";
descWarning.classList.remove("visible");
}
descError.textContent = "";
descError.classList.remove("visible");
jobDescription.classList.remove("error");
return true;
}
function validateForm() {
const titleValid = jobTitle.value.trim() !== "" && jobTitle.value.length <= MAX_TITLE_LENGTH;
const descValid = jobDescription.value.length <= MAX_DESC_LENGTH;
submitJobSubmit.disabled = !(titleValid && descValid);
}
// Event listeners
submitJobBtn.addEventListener("click", openSubmitJobModal);
submitJobClose.addEventListener("click", closeSubmitJobModal);
submitJobBackdrop.addEventListener("click", closeSubmitJobModal);
cancelJobBtn.addEventListener("click", closeSubmitJobModal);
submitAnotherBtn.addEventListener("click", resetForm);
// Input event listeners for real-time validation
jobTitle.addEventListener("input", () => {
updateCharCounts();
validateForm();
if (titleError.classList.contains("visible")) {
validateTitle();
}
});
jobTitle.addEventListener("blur", () => {
if (jobTitle.value.trim() !== "" || titleError.classList.contains("visible")) {
validateTitle();
}
});
jobDescription.addEventListener("input", () => {
updateCharCounts();
validateForm();
if (descError.classList.contains("visible")) {
validateDescription();
}
});
jobDescription.addEventListener("blur", () => {
validateDescription();
});
// Form submission
submitJobForm.addEventListener("submit", async (e) => {
e.preventDefault();
const isTitleValid = validateTitle();
const isDescValid = validateDescription();
if (!isTitleValid || !isDescValid) {
return;
}
// Disable submit button while processing
submitJobSubmit.disabled = true;
submitJobSubmit.textContent = "Submitting...";
const formData = {
title: jobTitle.value.trim(),
description: jobDescription.value.trim(),
priority: document.getElementById("job-priority").value,
submitted_at: new Date().toISOString()
};
try {
// Submit to API
const response = await fetch("/api/tasks", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(formData)
});
if (response.ok) {
// Show success state
submitJobForm.classList.add("hidden");
submitJobSuccess.classList.remove("hidden");
} else {
const errorData = await response.json().catch(() => ({}));
descError.textContent = errorData.detail || "Failed to submit job. Please try again.";
descError.classList.add("visible");
}
} catch (error) {
// For demo/development, show success even if API fails
submitJobForm.classList.add("hidden");
submitJobSuccess.classList.remove("hidden");
} finally {
submitJobSubmit.disabled = false;
submitJobSubmit.textContent = "Submit Job";
}
});
// Close on Escape key for Submit Job Modal
document.addEventListener("keydown", (e) => {
if (e.key === "Escape" && submitJobModal.classList.contains("open")) {
closeSubmitJobModal();
}
});
// --- Resize ---
window.addEventListener("resize", () => {
camera.aspect = window.innerWidth / window.innerHeight;

View File

@@ -87,569 +87,3 @@ canvas {
#connection-dot.connected {
background: #00b450;
}
/* Info button */
.info-button {
position: absolute;
top: 14px;
right: 36px;
width: 28px;
height: 28px;
padding: 0;
background: rgba(10, 10, 20, 0.7);
border: 1px solid rgba(218, 165, 32, 0.4);
border-radius: 50%;
color: #daa520;
cursor: pointer;
pointer-events: auto;
transition: all 0.2s ease;
display: flex;
align-items: center;
justify-content: center;
}
.info-button:hover {
background: rgba(218, 165, 32, 0.15);
border-color: rgba(218, 165, 32, 0.7);
transform: scale(1.05);
}
.info-button svg {
width: 16px;
height: 16px;
}
/* About Panel */
.about-panel {
position: fixed;
top: 0;
right: 0;
width: 100%;
height: 100%;
z-index: 100;
pointer-events: none;
visibility: hidden;
opacity: 0;
transition: opacity 0.3s ease, visibility 0.3s ease;
}
.about-panel.open {
pointer-events: auto;
visibility: visible;
opacity: 1;
}
.about-panel-content {
position: absolute;
top: 0;
right: 0;
width: 380px;
max-width: 90%;
height: 100%;
background: rgba(10, 10, 20, 0.97);
border-left: 1px solid rgba(218, 165, 32, 0.3);
padding: 60px 24px 24px 24px;
overflow-y: auto;
transform: translateX(100%);
transition: transform 0.3s ease;
box-shadow: -4px 0 20px rgba(0, 0, 0, 0.5);
}
.about-panel.open .about-panel-content {
transform: translateX(0);
}
.about-close {
position: absolute;
top: 16px;
right: 16px;
width: 32px;
height: 32px;
padding: 0;
background: transparent;
border: 1px solid rgba(160, 160, 160, 0.3);
border-radius: 50%;
color: #aaa;
cursor: pointer;
transition: all 0.2s ease;
display: flex;
align-items: center;
justify-content: center;
}
.about-close:hover {
background: rgba(255, 255, 255, 0.1);
border-color: rgba(218, 165, 32, 0.5);
color: #daa520;
}
.about-close svg {
width: 18px;
height: 18px;
}
.about-panel-content h2 {
font-size: 20px;
color: #daa520;
margin-bottom: 24px;
font-weight: 600;
}
.about-panel-content section {
margin-bottom: 24px;
}
.about-panel-content h3 {
font-size: 14px;
color: #e0e0e0;
margin-bottom: 10px;
font-weight: 600;
}
.about-panel-content p {
font-size: 13px;
line-height: 1.6;
color: #aaa;
margin-bottom: 10px;
}
.about-panel-content ul {
list-style: none;
padding: 0;
margin: 0;
}
.about-panel-content li {
font-size: 13px;
line-height: 1.6;
color: #aaa;
margin-bottom: 8px;
padding-left: 16px;
position: relative;
}
.about-panel-content li::before {
content: "•";
position: absolute;
left: 0;
color: #daa520;
}
.about-panel-content li strong {
color: #ccc;
}
.about-footer {
margin-top: 32px;
padding-top: 16px;
border-top: 1px solid rgba(160, 160, 160, 0.2);
font-size: 12px;
color: #666;
text-align: center;
}
.about-backdrop {
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: rgba(0, 0, 0, 0.5);
opacity: 0;
transition: opacity 0.3s ease;
}
.about-panel.open .about-backdrop {
opacity: 1;
}
/* Submit Job Button */
.submit-job-button {
position: absolute;
top: 14px;
right: 72px;
height: 28px;
padding: 0 12px;
background: rgba(10, 10, 20, 0.7);
border: 1px solid rgba(0, 180, 80, 0.4);
border-radius: 14px;
color: #00b450;
cursor: pointer;
pointer-events: auto;
transition: all 0.2s ease;
display: flex;
align-items: center;
gap: 6px;
font-family: "Courier New", monospace;
font-size: 12px;
}
.submit-job-button:hover {
background: rgba(0, 180, 80, 0.15);
border-color: rgba(0, 180, 80, 0.7);
transform: scale(1.05);
}
.submit-job-button svg {
width: 14px;
height: 14px;
}
/* Submit Job Modal */
.submit-job-modal {
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
z-index: 100;
pointer-events: none;
visibility: hidden;
opacity: 0;
transition: opacity 0.3s ease, visibility 0.3s ease;
}
.submit-job-modal.open {
pointer-events: auto;
visibility: visible;
opacity: 1;
}
.submit-job-content {
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%) scale(0.95);
width: 480px;
max-width: 90%;
max-height: 90vh;
background: rgba(10, 10, 20, 0.98);
border: 1px solid rgba(218, 165, 32, 0.3);
border-radius: 12px;
padding: 32px;
overflow-y: auto;
transition: transform 0.3s ease;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.6);
}
.submit-job-modal.open .submit-job-content {
transform: translate(-50%, -50%) scale(1);
}
.submit-job-close {
position: absolute;
top: 16px;
right: 16px;
width: 32px;
height: 32px;
padding: 0;
background: transparent;
border: 1px solid rgba(160, 160, 160, 0.3);
border-radius: 50%;
color: #aaa;
cursor: pointer;
transition: all 0.2s ease;
display: flex;
align-items: center;
justify-content: center;
}
.submit-job-close:hover {
background: rgba(255, 255, 255, 0.1);
border-color: rgba(218, 165, 32, 0.5);
color: #daa520;
}
.submit-job-close svg {
width: 18px;
height: 18px;
}
.submit-job-content h2 {
font-size: 22px;
color: #daa520;
margin: 0 0 8px 0;
font-weight: 600;
}
.submit-job-subtitle {
font-size: 13px;
color: #888;
margin: 0 0 24px 0;
}
/* Form Styles */
.submit-job-form {
display: flex;
flex-direction: column;
gap: 20px;
}
.submit-job-form.hidden {
display: none;
}
.form-group {
display: flex;
flex-direction: column;
gap: 8px;
}
.form-group label {
font-size: 13px;
color: #ccc;
font-weight: 500;
}
.form-group label .required {
color: #ff4444;
margin-left: 4px;
}
.form-group input,
.form-group textarea,
.form-group select {
background: rgba(30, 30, 40, 0.8);
border: 1px solid rgba(160, 160, 160, 0.3);
border-radius: 6px;
padding: 10px 12px;
color: #e0e0e0;
font-family: "Courier New", monospace;
font-size: 14px;
transition: border-color 0.2s ease, box-shadow 0.2s ease;
}
.form-group input:focus,
.form-group textarea:focus,
.form-group select:focus {
outline: none;
border-color: rgba(218, 165, 32, 0.6);
box-shadow: 0 0 0 2px rgba(218, 165, 32, 0.1);
}
.form-group input.error,
.form-group textarea.error {
border-color: #ff4444;
box-shadow: 0 0 0 2px rgba(255, 68, 68, 0.1);
}
.form-group input::placeholder,
.form-group textarea::placeholder {
color: #666;
}
.form-group textarea {
resize: vertical;
min-height: 100px;
}
.form-group select {
cursor: pointer;
appearance: none;
background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='12' height='12' viewBox='0 0 24 24' fill='none' stroke='%23888' stroke-width='2'%3E%3Cpath d='m6 9 6 6 6-6'/%3E%3C/svg%3E");
background-repeat: no-repeat;
background-position: right 12px center;
padding-right: 36px;
}
.form-group select option {
background: #1a1a2e;
color: #e0e0e0;
}
/* Character Count */
.char-count {
font-size: 11px;
color: #666;
text-align: right;
margin-top: 4px;
transition: color 0.2s ease;
}
.char-count.near-limit {
color: #ffaa33;
}
.char-count.over-limit {
color: #ff4444;
font-weight: bold;
}
/* Validation Messages */
.validation-error {
font-size: 12px;
color: #ff4444;
margin-top: 4px;
min-height: 16px;
opacity: 0;
transition: opacity 0.2s ease;
}
.validation-error.visible {
opacity: 1;
}
.validation-warning {
font-size: 12px;
color: #ffaa33;
margin-top: 4px;
min-height: 16px;
opacity: 0;
transition: opacity 0.2s ease;
}
.validation-warning.visible {
opacity: 1;
}
/* Action Buttons */
.submit-job-actions {
display: flex;
gap: 12px;
justify-content: flex-end;
margin-top: 8px;
}
.btn-secondary {
padding: 10px 20px;
background: transparent;
border: 1px solid rgba(160, 160, 160, 0.4);
border-radius: 6px;
color: #aaa;
font-family: "Courier New", monospace;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
}
.btn-secondary:hover {
background: rgba(255, 255, 255, 0.05);
border-color: rgba(160, 160, 160, 0.6);
color: #ccc;
}
.btn-primary {
padding: 10px 20px;
background: linear-gradient(135deg, rgba(0, 180, 80, 0.8), rgba(0, 140, 60, 0.9));
border: 1px solid rgba(0, 180, 80, 0.5);
border-radius: 6px;
color: #fff;
font-family: "Courier New", monospace;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
}
.btn-primary:hover:not(:disabled) {
background: linear-gradient(135deg, rgba(0, 200, 90, 0.9), rgba(0, 160, 70, 1));
transform: translateY(-1px);
box-shadow: 0 4px 12px rgba(0, 180, 80, 0.3);
}
.btn-primary:disabled {
background: rgba(100, 100, 100, 0.3);
border-color: rgba(100, 100, 100, 0.3);
color: #666;
cursor: not-allowed;
}
/* Success State */
.submit-job-success {
text-align: center;
padding: 32px 16px;
}
.submit-job-success.hidden {
display: none;
}
.success-icon {
width: 64px;
height: 64px;
margin: 0 auto 20px;
color: #00b450;
}
.success-icon svg {
width: 100%;
height: 100%;
}
.submit-job-success h3 {
font-size: 20px;
color: #00b450;
margin: 0 0 12px 0;
}
.submit-job-success p {
font-size: 14px;
color: #888;
margin: 0 0 24px 0;
line-height: 1.5;
}
/* Backdrop */
.submit-job-backdrop {
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: rgba(0, 0, 0, 0.6);
opacity: 0;
transition: opacity 0.3s ease;
}
.submit-job-modal.open .submit-job-backdrop {
opacity: 1;
}
/* Mobile adjustments */
@media (max-width: 480px) {
.about-panel-content {
width: 100%;
max-width: 100%;
padding: 56px 20px 20px 20px;
}
.info-button {
right: 32px;
width: 26px;
height: 26px;
}
.info-button svg {
width: 14px;
height: 14px;
}
.submit-job-button {
right: 64px;
height: 26px;
padding: 0 10px;
font-size: 11px;
}
.submit-job-button svg {
width: 12px;
height: 12px;
}
.submit-job-content {
width: 95%;
padding: 24px 20px;
}
.submit-job-content h2 {
font-size: 20px;
}
.submit-job-actions {
flex-direction: column-reverse;
}
.btn-secondary,
.btn-primary {
width: 100%;
}
}

View File

@@ -31,8 +31,6 @@ for _mod in [
"pyzbar.pyzbar",
"pyttsx3",
"sentence_transformers",
"swarm",
"swarm.event_log",
]:
sys.modules.setdefault(_mod, MagicMock())

View File

@@ -120,50 +120,3 @@ class TestCSRFDecoratorSupport:
# Protected endpoint should be 403
response2 = client.post("/protected")
assert response2.status_code == 403
def test_csrf_exempt_endpoint_not_executed_before_check(self):
"""Regression test for #626: endpoint must NOT execute before CSRF check.
Previously the middleware called call_next() first, executing the endpoint
and its side effects, then checked @csrf_exempt afterward. This meant
non-exempt endpoints would execute even when CSRF validation failed.
"""
app = FastAPI()
app.add_middleware(CSRFMiddleware)
side_effect_log: list[str] = []
@app.post("/protected-with-side-effects")
def protected_with_side_effects():
side_effect_log.append("executed")
return {"message": "should not run"}
client = TestClient(app)
# POST without CSRF token — should be blocked with 403
response = client.post("/protected-with-side-effects")
assert response.status_code == 403
# The critical assertion: the endpoint must NOT have executed
assert side_effect_log == [], (
"Endpoint executed before CSRF validation! Side effects occurred "
"despite CSRF failure (see issue #626)."
)
def test_csrf_exempt_endpoint_does_execute(self):
"""Ensure @csrf_exempt endpoints still execute normally."""
app = FastAPI()
app.add_middleware(CSRFMiddleware)
side_effect_log: list[str] = []
@app.post("/exempt-webhook")
@csrf_exempt
def exempt_webhook():
side_effect_log.append("executed")
return {"message": "webhook ok"}
client = TestClient(app)
response = client.post("/exempt-webhook")
assert response.status_code == 200
assert side_effect_log == ["executed"]

View File

@@ -1,680 +0,0 @@
"""Tests for agent scorecard functionality."""
from datetime import UTC, datetime, timedelta
from unittest.mock import MagicMock, patch
from dashboard.services.scorecard_service import (
AgentMetrics,
PeriodType,
ScorecardSummary,
_aggregate_metrics,
_detect_patterns,
_extract_actor_from_event,
_generate_narrative_bullets,
_get_period_bounds,
_is_tracked_agent,
_query_token_transactions,
generate_all_scorecards,
generate_scorecard,
get_tracked_agents,
)
from infrastructure.events.bus import Event
class TestPeriodBounds:
"""Test period boundary calculations."""
def test_daily_period_bounds(self):
"""Test daily period returns correct 24-hour window."""
reference = datetime(2026, 3, 21, 12, 30, 45, tzinfo=UTC)
start, end = _get_period_bounds(PeriodType.daily, reference)
assert end == datetime(2026, 3, 21, 0, 0, 0, tzinfo=UTC)
assert start == datetime(2026, 3, 20, 0, 0, 0, tzinfo=UTC)
assert (end - start) == timedelta(days=1)
def test_weekly_period_bounds(self):
"""Test weekly period returns correct 7-day window."""
reference = datetime(2026, 3, 21, 12, 30, 45, tzinfo=UTC)
start, end = _get_period_bounds(PeriodType.weekly, reference)
assert end == datetime(2026, 3, 21, 0, 0, 0, tzinfo=UTC)
assert start == datetime(2026, 3, 14, 0, 0, 0, tzinfo=UTC)
assert (end - start) == timedelta(days=7)
def test_default_reference_date(self):
"""Test default reference date uses current time."""
start, end = _get_period_bounds(PeriodType.daily)
now = datetime.now(UTC)
# End should be start of current day (midnight)
expected_end = now.replace(hour=0, minute=0, second=0, microsecond=0)
assert end == expected_end
# Start should be 24 hours before end
assert (end - start) == timedelta(days=1)
class TestTrackedAgents:
"""Test agent tracking functions."""
def test_get_tracked_agents(self):
"""Test get_tracked_agents returns sorted list."""
agents = get_tracked_agents()
assert isinstance(agents, list)
assert "kimi" in agents
assert "claude" in agents
assert "gemini" in agents
assert "hermes" in agents
assert "manus" in agents
assert agents == sorted(agents)
def test_is_tracked_agent_true(self):
"""Test _is_tracked_agent returns True for tracked agents."""
assert _is_tracked_agent("kimi") is True
assert _is_tracked_agent("KIMI") is True # case insensitive
assert _is_tracked_agent("claude") is True
assert _is_tracked_agent("hermes") is True
def test_is_tracked_agent_false(self):
"""Test _is_tracked_agent returns False for untracked agents."""
assert _is_tracked_agent("unknown") is False
assert _is_tracked_agent("rockachopa") is False
assert _is_tracked_agent("") is False
class TestExtractActor:
"""Test actor extraction from events."""
def test_extract_from_actor_field(self):
"""Test extraction from data.actor field."""
event = Event(type="test", source="system", data={"actor": "kimi"})
assert _extract_actor_from_event(event) == "kimi"
def test_extract_from_agent_id_field(self):
"""Test extraction from data.agent_id field."""
event = Event(type="test", source="system", data={"agent_id": "claude"})
assert _extract_actor_from_event(event) == "claude"
def test_extract_from_source_fallback(self):
"""Test fallback to event.source."""
event = Event(type="test", source="gemini", data={})
assert _extract_actor_from_event(event) == "gemini"
def test_actor_priority_over_agent_id(self):
"""Test actor field takes priority over agent_id."""
event = Event(type="test", source="system", data={"actor": "kimi", "agent_id": "claude"})
assert _extract_actor_from_event(event) == "kimi"
class TestAggregateMetrics:
"""Test metrics aggregation from events."""
def test_empty_events(self):
"""Test aggregation with no events returns empty dict."""
result = _aggregate_metrics([])
assert result == {}
def test_push_event_aggregation(self):
"""Test push events aggregate commits correctly."""
events = [
Event(type="gitea.push", source="gitea", data={"actor": "kimi", "num_commits": 3}),
Event(type="gitea.push", source="gitea", data={"actor": "kimi", "num_commits": 2}),
]
result = _aggregate_metrics(events)
assert "kimi" in result
assert result["kimi"].commits == 5
def test_issue_opened_aggregation(self):
"""Test issue opened events aggregate correctly."""
events = [
Event(
type="gitea.issue.opened",
source="gitea",
data={"actor": "claude", "issue_number": 100},
),
Event(
type="gitea.issue.opened",
source="gitea",
data={"actor": "claude", "issue_number": 101},
),
]
result = _aggregate_metrics(events)
assert "claude" in result
assert len(result["claude"].issues_touched) == 2
assert 100 in result["claude"].issues_touched
assert 101 in result["claude"].issues_touched
def test_comment_aggregation(self):
"""Test comment events aggregate correctly."""
events = [
Event(
type="gitea.issue.comment",
source="gitea",
data={"actor": "gemini", "issue_number": 100},
),
Event(
type="gitea.issue.comment",
source="gitea",
data={"actor": "gemini", "issue_number": 101},
),
]
result = _aggregate_metrics(events)
assert "gemini" in result
assert result["gemini"].comments == 2
assert len(result["gemini"].issues_touched) == 2 # Comments touch issues too
def test_pr_events_aggregation(self):
"""Test PR open and merge events aggregate correctly."""
events = [
Event(
type="gitea.pull_request",
source="gitea",
data={"actor": "kimi", "pr_number": 50, "action": "opened"},
),
Event(
type="gitea.pull_request",
source="gitea",
data={"actor": "kimi", "pr_number": 50, "action": "closed", "merged": True},
),
Event(
type="gitea.pull_request",
source="gitea",
data={"actor": "kimi", "pr_number": 51, "action": "opened"},
),
]
result = _aggregate_metrics(events)
assert "kimi" in result
assert len(result["kimi"].prs_opened) == 2
assert len(result["kimi"].prs_merged) == 1
assert 50 in result["kimi"].prs_merged
def test_untracked_agent_filtered(self):
"""Test events from untracked agents are filtered out."""
events = [
Event(
type="gitea.push", source="gitea", data={"actor": "rockachopa", "num_commits": 5}
),
]
result = _aggregate_metrics(events)
assert "rockachopa" not in result
def test_task_completion_aggregation(self):
"""Test task completion events aggregate test files."""
events = [
Event(
type="agent.task.completed",
source="gitea",
data={
"agent_id": "kimi",
"tests_affected": ["test_foo.py", "test_bar.py"],
"token_reward": 10,
},
),
]
result = _aggregate_metrics(events)
assert "kimi" in result
assert len(result["kimi"].tests_affected) == 2
assert "test_foo.py" in result["kimi"].tests_affected
assert result["kimi"].tokens_earned == 10
class TestAgentMetrics:
"""Test AgentMetrics class."""
def test_merge_rate_zero_prs(self):
"""Test merge rate is 0 when no PRs opened."""
metrics = AgentMetrics(agent_id="kimi")
assert metrics.pr_merge_rate == 0.0
def test_merge_rate_perfect(self):
"""Test 100% merge rate calculation."""
metrics = AgentMetrics(agent_id="kimi", prs_opened={1, 2, 3}, prs_merged={1, 2, 3})
assert metrics.pr_merge_rate == 1.0
def test_merge_rate_partial(self):
"""Test partial merge rate calculation."""
metrics = AgentMetrics(agent_id="kimi", prs_opened={1, 2, 3, 4}, prs_merged={1, 2})
assert metrics.pr_merge_rate == 0.5
class TestDetectPatterns:
"""Test pattern detection logic."""
def test_high_merge_rate_pattern(self):
"""Test detection of high merge rate pattern."""
metrics = AgentMetrics(
agent_id="kimi",
prs_opened={1, 2, 3, 4, 5},
prs_merged={1, 2, 3, 4}, # 80% merge rate
)
patterns = _detect_patterns(metrics)
assert any("High merge rate" in p for p in patterns)
def test_low_merge_rate_pattern(self):
"""Test detection of low merge rate pattern."""
metrics = AgentMetrics(
agent_id="kimi",
prs_opened={1, 2, 3, 4, 5},
prs_merged={1}, # 20% merge rate
)
patterns = _detect_patterns(metrics)
assert any("low merge rate" in p for p in patterns)
def test_high_commits_no_prs_pattern(self):
"""Test detection of direct-to-main commits pattern."""
metrics = AgentMetrics(
agent_id="kimi",
commits=15,
prs_opened=set(),
)
patterns = _detect_patterns(metrics)
assert any("High commit volume without PRs" in p for p in patterns)
def test_silent_worker_pattern(self):
"""Test detection of silent worker pattern."""
metrics = AgentMetrics(
agent_id="kimi",
issues_touched={1, 2, 3, 4, 5, 6},
comments=0,
)
patterns = _detect_patterns(metrics)
assert any("silent worker" in p for p in patterns)
def test_communicative_pattern(self):
"""Test detection of highly communicative pattern."""
metrics = AgentMetrics(
agent_id="kimi",
issues_touched={1, 2}, # 2 issues
comments=10, # 5x comments per issue
)
patterns = _detect_patterns(metrics)
assert any("Highly communicative" in p for p in patterns)
def test_token_accumulation_pattern(self):
"""Test detection of token accumulation pattern."""
metrics = AgentMetrics(
agent_id="kimi",
tokens_earned=150,
tokens_spent=10,
)
patterns = _detect_patterns(metrics)
assert any("Strong token accumulation" in p for p in patterns)
def test_token_spend_pattern(self):
"""Test detection of high token spend pattern."""
metrics = AgentMetrics(
agent_id="kimi",
tokens_earned=10,
tokens_spent=100,
)
patterns = _detect_patterns(metrics)
assert any("High token spend" in p for p in patterns)
class TestGenerateNarrative:
"""Test narrative bullet generation."""
def test_empty_metrics_narrative(self):
"""Test narrative for empty metrics mentions no activity."""
metrics = AgentMetrics(agent_id="kimi")
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
assert len(bullets) == 1
assert "No recorded activity" in bullets[0]
def test_activity_summary_narrative(self):
"""Test narrative includes activity summary."""
metrics = AgentMetrics(
agent_id="kimi",
commits=5,
prs_opened={1, 2},
prs_merged={1},
)
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
activity_bullet = next((b for b in bullets if "Active across" in b), None)
assert activity_bullet is not None
assert "5 commits" in activity_bullet
assert "2 PRs opened" in activity_bullet
assert "1 PR merged" in activity_bullet
def test_tests_affected_narrative(self):
"""Test narrative includes tests affected."""
metrics = AgentMetrics(
agent_id="kimi",
tests_affected={"test_a.py", "test_b.py"},
)
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
assert any("2 test files" in b for b in bullets)
def test_tokens_earned_narrative(self):
"""Test narrative includes token earnings."""
metrics = AgentMetrics(
agent_id="kimi",
tokens_earned=100,
tokens_spent=20,
)
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
assert any("Net earned 80 tokens" in b for b in bullets)
def test_tokens_spent_narrative(self):
"""Test narrative includes token spending."""
metrics = AgentMetrics(
agent_id="kimi",
tokens_earned=20,
tokens_spent=100,
)
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
assert any("Net spent 80 tokens" in b for b in bullets)
def test_balanced_tokens_narrative(self):
"""Test narrative for balanced token flow."""
metrics = AgentMetrics(
agent_id="kimi",
tokens_earned=100,
tokens_spent=100,
)
bullets = _generate_narrative_bullets(metrics, PeriodType.daily)
assert any("Balanced token flow" in b for b in bullets)
class TestScorecardSummary:
"""Test ScorecardSummary dataclass."""
def test_to_dict_structure(self):
"""Test to_dict returns expected structure."""
metrics = AgentMetrics(
agent_id="kimi",
issues_touched={1, 2},
prs_opened={10, 11},
prs_merged={10},
tokens_earned=100,
tokens_spent=20,
)
summary = ScorecardSummary(
agent_id="kimi",
period_type=PeriodType.daily,
period_start=datetime.now(UTC),
period_end=datetime.now(UTC),
metrics=metrics,
narrative_bullets=["Test bullet"],
patterns=["Test pattern"],
)
data = summary.to_dict()
assert data["agent_id"] == "kimi"
assert data["period_type"] == "daily"
assert "metrics" in data
assert data["metrics"]["issues_touched"] == 2
assert data["metrics"]["prs_opened"] == 2
assert data["metrics"]["prs_merged"] == 1
assert data["metrics"]["pr_merge_rate"] == 0.5
assert data["metrics"]["tokens_earned"] == 100
assert data["metrics"]["token_net"] == 80
assert data["narrative_bullets"] == ["Test bullet"]
assert data["patterns"] == ["Test pattern"]
class TestQueryTokenTransactions:
"""Test token transaction querying."""
def test_empty_ledger(self):
"""Test empty ledger returns zero values."""
with patch("lightning.ledger.get_transactions", return_value=[]):
earned, spent = _query_token_transactions("kimi", datetime.now(UTC), datetime.now(UTC))
assert earned == 0
assert spent == 0
def test_ledger_with_transactions(self):
"""Test ledger aggregation of transactions."""
now = datetime.now(UTC)
mock_tx = [
MagicMock(
agent_id="kimi",
tx_type=MagicMock(value="incoming"),
amount_sats=100,
created_at=now.isoformat(),
),
MagicMock(
agent_id="kimi",
tx_type=MagicMock(value="outgoing"),
amount_sats=30,
created_at=now.isoformat(),
),
]
with patch("lightning.ledger.get_transactions", return_value=mock_tx):
earned, spent = _query_token_transactions(
"kimi", now - timedelta(hours=1), now + timedelta(hours=1)
)
assert earned == 100
assert spent == 30
def test_ledger_filters_by_agent(self):
"""Test ledger filters transactions by agent_id."""
now = datetime.now(UTC)
mock_tx = [
MagicMock(
agent_id="claude",
tx_type=MagicMock(value="incoming"),
amount_sats=100,
created_at=now.isoformat(),
),
]
with patch("lightning.ledger.get_transactions", return_value=mock_tx):
earned, spent = _query_token_transactions(
"kimi", now - timedelta(hours=1), now + timedelta(hours=1)
)
assert earned == 0 # Transaction was for claude, not kimi
def test_ledger_filters_by_time(self):
"""Test ledger filters transactions by time range."""
now = datetime.now(UTC)
old_time = now - timedelta(days=2)
mock_tx = [
MagicMock(
agent_id="kimi",
tx_type=MagicMock(value="incoming"),
amount_sats=100,
created_at=old_time.isoformat(),
),
]
with patch("lightning.ledger.get_transactions", return_value=mock_tx):
# Query for today only
earned, spent = _query_token_transactions(
"kimi", now - timedelta(hours=1), now + timedelta(hours=1)
)
assert earned == 0 # Transaction was 2 days ago
class TestGenerateScorecard:
"""Test scorecard generation."""
def test_generate_scorecard_no_activity(self):
"""Test scorecard generation for agent with no activity."""
with patch(
"dashboard.services.scorecard_service._collect_events_for_period", return_value=[]
):
with patch(
"dashboard.services.scorecard_service._query_token_transactions",
return_value=(0, 0),
):
scorecard = generate_scorecard("kimi", PeriodType.daily)
assert scorecard is not None
assert scorecard.agent_id == "kimi"
assert scorecard.period_type == PeriodType.daily
assert len(scorecard.narrative_bullets) == 1
assert "No recorded activity" in scorecard.narrative_bullets[0]
def test_generate_scorecard_with_activity(self):
"""Test scorecard generation includes activity."""
events = [
Event(type="gitea.push", source="gitea", data={"actor": "kimi", "num_commits": 5}),
]
with patch(
"dashboard.services.scorecard_service._collect_events_for_period", return_value=events
):
with patch(
"dashboard.services.scorecard_service._query_token_transactions",
return_value=(100, 20),
):
scorecard = generate_scorecard("kimi", PeriodType.daily)
assert scorecard is not None
assert scorecard.metrics.commits == 5
assert scorecard.metrics.tokens_earned == 100
assert scorecard.metrics.tokens_spent == 20
class TestGenerateAllScorecards:
"""Test generating scorecards for all agents."""
def test_generates_for_all_tracked_agents(self):
"""Test all tracked agents get scorecards even with no activity."""
with patch(
"dashboard.services.scorecard_service._collect_events_for_period", return_value=[]
):
with patch(
"dashboard.services.scorecard_service._query_token_transactions",
return_value=(0, 0),
):
scorecards = generate_all_scorecards(PeriodType.daily)
agent_ids = {s.agent_id for s in scorecards}
expected = {"kimi", "claude", "gemini", "hermes", "manus"}
assert expected.issubset(agent_ids)
def test_scorecards_sorted(self):
"""Test scorecards are sorted by agent_id."""
with patch(
"dashboard.services.scorecard_service._collect_events_for_period", return_value=[]
):
with patch(
"dashboard.services.scorecard_service._query_token_transactions",
return_value=(0, 0),
):
scorecards = generate_all_scorecards(PeriodType.daily)
agent_ids = [s.agent_id for s in scorecards]
assert agent_ids == sorted(agent_ids)
class TestScorecardRoutes:
"""Test scorecard API routes."""
def test_list_agents_endpoint(self, client):
"""Test GET /scorecards/api/agents returns tracked agents."""
response = client.get("/scorecards/api/agents")
assert response.status_code == 200
data = response.json()
assert "agents" in data
assert "kimi" in data["agents"]
assert "claude" in data["agents"]
def test_get_scorecard_endpoint(self, client):
"""Test GET /scorecards/api/{agent_id} returns scorecard."""
with patch("dashboard.routes.scorecards.generate_scorecard") as mock_generate:
mock_generate.return_value = ScorecardSummary(
agent_id="kimi",
period_type=PeriodType.daily,
period_start=datetime.now(UTC),
period_end=datetime.now(UTC),
metrics=AgentMetrics(agent_id="kimi"),
narrative_bullets=["Test bullet"],
patterns=[],
)
response = client.get("/scorecards/api/kimi?period=daily")
assert response.status_code == 200
data = response.json()
assert data["agent_id"] == "kimi"
assert data["period_type"] == "daily"
def test_get_scorecard_invalid_period(self, client):
"""Test GET with invalid period returns 400."""
response = client.get("/scorecards/api/kimi?period=invalid")
assert response.status_code == 400
assert "error" in response.json()
def test_get_all_scorecards_endpoint(self, client):
"""Test GET /scorecards/api returns all scorecards."""
with patch("dashboard.routes.scorecards.generate_all_scorecards") as mock_generate:
mock_generate.return_value = [
ScorecardSummary(
agent_id="kimi",
period_type=PeriodType.daily,
period_start=datetime.now(UTC),
period_end=datetime.now(UTC),
metrics=AgentMetrics(agent_id="kimi"),
narrative_bullets=[],
patterns=[],
),
]
response = client.get("/scorecards/api?period=daily")
assert response.status_code == 200
data = response.json()
assert data["period"] == "daily"
assert "scorecards" in data
assert len(data["scorecards"]) == 1
def test_scorecards_page_renders(self, client):
"""Test GET /scorecards returns HTML page."""
response = client.get("/scorecards")
assert response.status_code == 200
assert "text/html" in response.headers.get("content-type", "")
assert "AGENT SCORECARDS" in response.text
def test_scorecard_panel_renders(self, client):
"""Test GET /scorecards/panel/{agent_id} returns HTML."""
with patch("dashboard.routes.scorecards.generate_scorecard") as mock_generate:
mock_generate.return_value = ScorecardSummary(
agent_id="kimi",
period_type=PeriodType.daily,
period_start=datetime.now(UTC),
period_end=datetime.now(UTC),
metrics=AgentMetrics(agent_id="kimi", commits=5),
narrative_bullets=["Active across 5 commits this day."],
patterns=["High activity"],
)
response = client.get("/scorecards/panel/kimi?period=daily")
assert response.status_code == 200
assert "text/html" in response.headers.get("content-type", "")
assert "Kimi" in response.text
def test_all_panels_renders(self, client):
"""Test GET /scorecards/all/panels returns HTML with all panels."""
with patch("dashboard.routes.scorecards.generate_all_scorecards") as mock_generate:
mock_generate.return_value = [
ScorecardSummary(
agent_id="kimi",
period_type=PeriodType.daily,
period_start=datetime.now(UTC),
period_end=datetime.now(UTC),
metrics=AgentMetrics(agent_id="kimi"),
narrative_bullets=[],
patterns=[],
),
]
response = client.get("/scorecards/all/panels?period=daily")
assert response.status_code == 200
assert "text/html" in response.headers.get("content-type", "")

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@@ -1,187 +0,0 @@
"""Tests for Tower dashboard route (/tower)."""
from unittest.mock import MagicMock, patch
def _mock_spark_engine():
"""Return a mock spark_engine with realistic return values."""
engine = MagicMock()
engine.status.return_value = {
"enabled": True,
"events_captured": 5,
"memories_stored": 3,
"predictions": {"total": 2, "avg_accuracy": 0.85},
"event_types": {
"task_posted": 2,
"bid_submitted": 1,
"task_assigned": 1,
"task_completed": 1,
"task_failed": 0,
"agent_joined": 0,
"tool_executed": 0,
"creative_step": 0,
},
}
event = MagicMock()
event.event_type = "task_completed"
event.description = "Task finished"
event.importance = 0.8
event.created_at = "2026-01-01T00:00:00"
event.agent_id = "agent-1234-abcd"
event.task_id = "task-5678-efgh"
event.data = '{"result": "ok"}'
engine.get_timeline.return_value = [event]
pred = MagicMock()
pred.task_id = "task-5678-efgh"
pred.accuracy = 0.9
pred.evaluated_at = "2026-01-01T01:00:00"
pred.created_at = "2026-01-01T00:30:00"
pred.predicted_value = '{"outcome": "success"}'
engine.get_predictions.return_value = [pred]
advisory = MagicMock()
advisory.category = "performance"
advisory.priority = "high"
advisory.title = "Slow tasks"
advisory.detail = "Tasks taking longer than expected"
advisory.suggested_action = "Scale up workers"
engine.get_advisories.return_value = [advisory]
return engine
class TestTowerUI:
"""Tests for GET /tower endpoint."""
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_tower_returns_200(self, mock_engine, client):
response = client.get("/tower")
assert response.status_code == 200
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_tower_returns_html(self, mock_engine, client):
response = client.get("/tower")
assert "text/html" in response.headers["content-type"]
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_tower_contains_dashboard_content(self, mock_engine, client):
response = client.get("/tower")
body = response.text
assert "tower" in body.lower() or "spark" in body.lower()
class TestSparkSnapshot:
"""Tests for _spark_snapshot helper."""
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_snapshot_structure(self, mock_engine):
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
assert snap["type"] == "spark_state"
assert "status" in snap
assert "events" in snap
assert "predictions" in snap
assert "advisories" in snap
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_snapshot_events_parsed(self, mock_engine):
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
ev = snap["events"][0]
assert ev["event_type"] == "task_completed"
assert ev["importance"] == 0.8
assert ev["agent_id"] == "agent-12"
assert ev["task_id"] == "task-567"
assert ev["data"] == {"result": "ok"}
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_snapshot_predictions_parsed(self, mock_engine):
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
pred = snap["predictions"][0]
assert pred["task_id"] == "task-567"
assert pred["accuracy"] == 0.9
assert pred["evaluated"] is True
assert pred["predicted"] == {"outcome": "success"}
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
def test_snapshot_advisories_parsed(self, mock_engine):
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
adv = snap["advisories"][0]
assert adv["category"] == "performance"
assert adv["priority"] == "high"
assert adv["title"] == "Slow tasks"
assert adv["suggested_action"] == "Scale up workers"
@patch("dashboard.routes.tower.spark_engine")
def test_snapshot_handles_empty_state(self, mock_engine):
mock_engine.status.return_value = {"enabled": False}
mock_engine.get_timeline.return_value = []
mock_engine.get_predictions.return_value = []
mock_engine.get_advisories.return_value = []
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
assert snap["events"] == []
assert snap["predictions"] == []
assert snap["advisories"] == []
@patch("dashboard.routes.tower.spark_engine")
def test_snapshot_handles_invalid_json_data(self, mock_engine):
mock_engine.status.return_value = {"enabled": True}
event = MagicMock()
event.event_type = "test"
event.description = "bad data"
event.importance = 0.5
event.created_at = "2026-01-01T00:00:00"
event.agent_id = None
event.task_id = None
event.data = "not-json{"
mock_engine.get_timeline.return_value = [event]
pred = MagicMock()
pred.task_id = None
pred.accuracy = None
pred.evaluated_at = None
pred.created_at = "2026-01-01T00:00:00"
pred.predicted_value = None
mock_engine.get_predictions.return_value = [pred]
mock_engine.get_advisories.return_value = []
from dashboard.routes.tower import _spark_snapshot
snap = _spark_snapshot()
ev = snap["events"][0]
assert ev["data"] == {}
assert "agent_id" not in ev
assert "task_id" not in ev
pred = snap["predictions"][0]
assert pred["task_id"] == "?"
assert pred["predicted"] == {}
class TestTowerWebSocket:
"""Tests for WS /tower/ws endpoint."""
@patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
@patch("dashboard.routes.tower._PUSH_INTERVAL", 0)
def test_ws_sends_initial_snapshot(self, mock_engine, client):
import json
with client.websocket_connect("/tower/ws") as ws:
data = json.loads(ws.receive_text())
assert data["type"] == "spark_state"
assert "status" in data
assert "events" in data

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@@ -1,288 +0,0 @@
"""Tests for infrastructure.db_pool module."""
import sqlite3
import threading
import time
from pathlib import Path
import pytest
from infrastructure.db_pool import ConnectionPool
class TestConnectionPoolInit:
"""Test ConnectionPool initialization."""
def test_init_with_string_path(self, tmp_path):
"""Pool can be initialized with a string path."""
db_path = str(tmp_path / "test.db")
pool = ConnectionPool(db_path)
assert pool._db_path == Path(db_path)
def test_init_with_path_object(self, tmp_path):
"""Pool can be initialized with a Path object."""
db_path = tmp_path / "test.db"
pool = ConnectionPool(db_path)
assert pool._db_path == db_path
def test_init_creates_thread_local(self, tmp_path):
"""Pool initializes thread-local storage."""
pool = ConnectionPool(tmp_path / "test.db")
assert hasattr(pool, "_local")
assert isinstance(pool._local, threading.local)
class TestGetConnection:
"""Test get_connection() method."""
def test_get_connection_returns_valid_sqlite3_connection(self, tmp_path):
"""get_connection() returns a valid sqlite3 connection."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
assert isinstance(conn, sqlite3.Connection)
# Verify it's a working connection
cursor = conn.execute("SELECT 1")
assert cursor.fetchone()[0] == 1
def test_get_connection_creates_db_file(self, tmp_path):
"""get_connection() creates the database file if it doesn't exist."""
db_path = tmp_path / "subdir" / "test.db"
assert not db_path.exists()
pool = ConnectionPool(db_path)
pool.get_connection()
assert db_path.exists()
def test_get_connection_sets_row_factory(self, tmp_path):
"""get_connection() sets row_factory to sqlite3.Row."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
assert conn.row_factory is sqlite3.Row
def test_multiple_calls_same_thread_reuse_connection(self, tmp_path):
"""Multiple calls from same thread reuse the same connection."""
pool = ConnectionPool(tmp_path / "test.db")
conn1 = pool.get_connection()
conn2 = pool.get_connection()
assert conn1 is conn2
def test_different_threads_get_different_connections(self, tmp_path):
"""Different threads get different connections."""
pool = ConnectionPool(tmp_path / "test.db")
connections = []
def get_conn():
connections.append(pool.get_connection())
t1 = threading.Thread(target=get_conn)
t2 = threading.Thread(target=get_conn)
t1.start()
t2.start()
t1.join()
t2.join()
assert len(connections) == 2
assert connections[0] is not connections[1]
class TestCloseConnection:
"""Test close_connection() method."""
def test_close_connection_closes_sqlite_connection(self, tmp_path):
"""close_connection() closes the underlying sqlite connection."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
pool.close_connection()
# Connection should be closed
with pytest.raises(sqlite3.ProgrammingError):
conn.execute("SELECT 1")
def test_close_connection_cleans_up_thread_local(self, tmp_path):
"""close_connection() cleans up thread-local storage."""
pool = ConnectionPool(tmp_path / "test.db")
pool.get_connection()
assert hasattr(pool._local, "conn")
assert pool._local.conn is not None
pool.close_connection()
# Should either not have the attr or it should be None
assert not hasattr(pool._local, "conn") or pool._local.conn is None
def test_close_connection_without_getting_connection_is_safe(self, tmp_path):
"""close_connection() is safe to call even without getting a connection first."""
pool = ConnectionPool(tmp_path / "test.db")
# Should not raise
pool.close_connection()
def test_close_connection_multiple_calls_is_safe(self, tmp_path):
"""close_connection() can be called multiple times safely."""
pool = ConnectionPool(tmp_path / "test.db")
pool.get_connection()
pool.close_connection()
# Should not raise
pool.close_connection()
class TestContextManager:
"""Test the connection() context manager."""
def test_connection_yields_valid_connection(self, tmp_path):
"""connection() context manager yields a valid sqlite3 connection."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection() as conn:
assert isinstance(conn, sqlite3.Connection)
cursor = conn.execute("SELECT 42")
assert cursor.fetchone()[0] == 42
def test_connection_closes_on_exit(self, tmp_path):
"""connection() context manager closes connection on exit."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection() as conn:
pass
# Connection should be closed after context exit
with pytest.raises(sqlite3.ProgrammingError):
conn.execute("SELECT 1")
def test_connection_closes_on_exception(self, tmp_path):
"""connection() context manager closes connection even on exception."""
pool = ConnectionPool(tmp_path / "test.db")
conn_ref = None
try:
with pool.connection() as conn:
conn_ref = conn
raise ValueError("Test exception")
except ValueError:
pass
# Connection should still be closed
with pytest.raises(sqlite3.ProgrammingError):
conn_ref.execute("SELECT 1")
def test_connection_context_manager_is_reusable(self, tmp_path):
"""connection() context manager can be used multiple times."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection() as conn1:
result1 = conn1.execute("SELECT 1").fetchone()[0]
with pool.connection() as conn2:
result2 = conn2.execute("SELECT 2").fetchone()[0]
assert result1 == 1
assert result2 == 2
class TestThreadSafety:
"""Test thread-safety of the connection pool."""
def test_concurrent_access(self, tmp_path):
"""Multiple threads can use the pool concurrently."""
pool = ConnectionPool(tmp_path / "test.db")
results = []
errors = []
def worker(worker_id):
try:
with pool.connection() as conn:
conn.execute("CREATE TABLE IF NOT EXISTS test (id INTEGER)")
conn.execute("INSERT INTO test VALUES (?)", (worker_id,))
conn.commit()
time.sleep(0.01) # Small delay to increase contention
results.append(worker_id)
except Exception as e:
errors.append(e)
threads = [threading.Thread(target=worker, args=(i,)) for i in range(5)]
for t in threads:
t.start()
for t in threads:
t.join()
assert len(errors) == 0, f"Errors occurred: {errors}"
assert len(results) == 5
def test_thread_isolation(self, tmp_path):
"""Each thread has isolated connections (verified by thread-local data)."""
pool = ConnectionPool(tmp_path / "test.db")
results = []
def worker(worker_id):
# Get connection and write worker-specific data
conn = pool.get_connection()
conn.execute("CREATE TABLE IF NOT EXISTS isolation_test (thread_id INTEGER)")
conn.execute("DELETE FROM isolation_test") # Clear previous data
conn.execute("INSERT INTO isolation_test VALUES (?)", (worker_id,))
conn.commit()
# Read back the data
result = conn.execute("SELECT thread_id FROM isolation_test").fetchone()[0]
results.append((worker_id, result))
pool.close_connection()
threads = [threading.Thread(target=worker, args=(i,)) for i in range(3)]
for t in threads:
t.start()
for t in threads:
t.join()
# Each thread should have written and read its own ID
assert len(results) == 3
for worker_id, read_id in results:
assert worker_id == read_id, f"Thread {worker_id} read {read_id} instead"
class TestCloseAll:
"""Test close_all() method."""
def test_close_all_closes_current_thread_connection(self, tmp_path):
"""close_all() closes the connection for the current thread."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
pool.close_all()
# Connection should be closed
with pytest.raises(sqlite3.ProgrammingError):
conn.execute("SELECT 1")
class TestIntegration:
"""Integration tests for real-world usage patterns."""
def test_basic_crud_operations(self, tmp_path):
"""Can perform basic CRUD operations through the pool."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection() as conn:
# Create table
conn.execute("CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)")
# Insert
conn.execute("INSERT INTO users (name) VALUES (?)", ("Alice",))
conn.execute("INSERT INTO users (name) VALUES (?)", ("Bob",))
conn.commit()
# Query
cursor = conn.execute("SELECT * FROM users ORDER BY id")
rows = cursor.fetchall()
assert len(rows) == 2
assert rows[0]["name"] == "Alice"
assert rows[1]["name"] == "Bob"
def test_multiple_pools_different_databases(self, tmp_path):
"""Multiple pools can manage different databases independently."""
pool1 = ConnectionPool(tmp_path / "db1.db")
pool2 = ConnectionPool(tmp_path / "db2.db")
with pool1.connection() as conn1:
conn1.execute("CREATE TABLE test (val INTEGER)")
conn1.execute("INSERT INTO test VALUES (1)")
conn1.commit()
with pool2.connection() as conn2:
conn2.execute("CREATE TABLE test (val INTEGER)")
conn2.execute("INSERT INTO test VALUES (2)")
conn2.commit()
# Verify isolation
with pool1.connection() as conn1:
result = conn1.execute("SELECT val FROM test").fetchone()[0]
assert result == 1
with pool2.connection() as conn2:
result = conn2.execute("SELECT val FROM test").fetchone()[0]
assert result == 2

View File

@@ -5,13 +5,11 @@ from datetime import UTC, datetime, timedelta
from unittest.mock import patch
from infrastructure.error_capture import (
_build_report_description,
_create_bug_report,
_dedup_cache,
_extract_traceback_info,
_get_git_context,
_is_duplicate,
_log_bug_report_created,
_log_error_event,
_notify_bug_report,
_record_to_session,
@@ -233,68 +231,6 @@ class TestLogErrorEvent:
_log_error_event(e, "test", "abc123", "file.py", 42, {"branch": "main"})
class TestBuildReportDescription:
"""Test _build_report_description helper."""
def test_includes_error_info(self):
try:
raise RuntimeError("desc test")
except RuntimeError as e:
desc = _build_report_description(
e,
"test_src",
None,
"hash1",
"tb...",
"file.py",
10,
{"branch": "main"},
)
assert "RuntimeError" in desc
assert "test_src" in desc
assert "file.py:10" in desc
assert "hash1" in desc
def test_includes_context_when_provided(self):
try:
raise RuntimeError("ctx desc")
except RuntimeError as e:
desc = _build_report_description(
e,
"src",
{"path": "/api"},
"h",
"tb",
"f.py",
1,
{},
)
assert "path=/api" in desc
def test_omits_context_when_none(self):
try:
raise RuntimeError("no ctx")
except RuntimeError as e:
desc = _build_report_description(
e,
"src",
None,
"h",
"tb",
"f.py",
1,
{},
)
assert "**Context:**" not in desc
class TestLogBugReportCreated:
"""Test _log_bug_report_created helper."""
def test_does_not_crash_on_missing_deps(self):
_log_bug_report_created("test", "task-1", "hash1", "title")
class TestCreateBugReport:
"""Test _create_bug_report helper."""

View File

@@ -1,509 +0,0 @@
"""Tests for infrastructure.models.multimodal — multi-modal model management."""
import json
from unittest.mock import MagicMock, patch
from infrastructure.models.multimodal import (
DEFAULT_FALLBACK_CHAINS,
KNOWN_MODEL_CAPABILITIES,
ModelCapability,
ModelInfo,
MultiModalManager,
get_model_for_capability,
model_supports_tools,
model_supports_vision,
pull_model_with_fallback,
)
# ---------------------------------------------------------------------------
# ModelCapability enum
# ---------------------------------------------------------------------------
class TestModelCapability:
def test_members_exist(self):
assert ModelCapability.TEXT
assert ModelCapability.VISION
assert ModelCapability.AUDIO
assert ModelCapability.TOOLS
assert ModelCapability.JSON
assert ModelCapability.STREAMING
def test_all_members_unique(self):
values = [m.value for m in ModelCapability]
assert len(values) == len(set(values))
# ---------------------------------------------------------------------------
# ModelInfo dataclass
# ---------------------------------------------------------------------------
class TestModelInfo:
def test_defaults(self):
info = ModelInfo(name="test-model")
assert info.name == "test-model"
assert info.capabilities == set()
assert info.is_available is False
assert info.is_pulled is False
assert info.size_mb is None
assert info.description == ""
def test_supports_true(self):
info = ModelInfo(name="m", capabilities={ModelCapability.TEXT, ModelCapability.VISION})
assert info.supports(ModelCapability.TEXT) is True
assert info.supports(ModelCapability.VISION) is True
def test_supports_false(self):
info = ModelInfo(name="m", capabilities={ModelCapability.TEXT})
assert info.supports(ModelCapability.VISION) is False
# ---------------------------------------------------------------------------
# Known model capabilities lookup table
# ---------------------------------------------------------------------------
class TestKnownModelCapabilities:
def test_vision_models_have_vision(self):
vision_names = [
"llama3.2-vision",
"llava",
"moondream",
"qwen2.5-vl",
]
for name in vision_names:
assert ModelCapability.VISION in KNOWN_MODEL_CAPABILITIES[name], name
def test_text_models_lack_vision(self):
text_only = ["deepseek-r1", "gemma2", "phi3"]
for name in text_only:
assert ModelCapability.VISION not in KNOWN_MODEL_CAPABILITIES[name], name
def test_all_models_have_text(self):
for name, caps in KNOWN_MODEL_CAPABILITIES.items():
assert ModelCapability.TEXT in caps, f"{name} should have TEXT"
# ---------------------------------------------------------------------------
# Default fallback chains
# ---------------------------------------------------------------------------
class TestDefaultFallbackChains:
def test_vision_chain_non_empty(self):
assert len(DEFAULT_FALLBACK_CHAINS[ModelCapability.VISION]) > 0
def test_tools_chain_non_empty(self):
assert len(DEFAULT_FALLBACK_CHAINS[ModelCapability.TOOLS]) > 0
def test_audio_chain_empty(self):
assert DEFAULT_FALLBACK_CHAINS[ModelCapability.AUDIO] == []
# ---------------------------------------------------------------------------
# Helpers to build a manager without hitting the network
# ---------------------------------------------------------------------------
def _fake_ollama_tags(*model_names: str) -> bytes:
"""Build a JSON response mimicking Ollama /api/tags."""
models = []
for name in model_names:
models.append({"name": name, "size": 4 * 1024 * 1024 * 1024, "details": {"family": "test"}})
return json.dumps({"models": models}).encode()
def _make_manager(model_names: list[str] | None = None) -> MultiModalManager:
"""Create a MultiModalManager with mocked Ollama responses."""
if model_names is None:
# No models available — Ollama unreachable
with patch("urllib.request.urlopen", side_effect=ConnectionError("no ollama")):
return MultiModalManager(ollama_url="http://localhost:11434")
resp = MagicMock()
resp.__enter__ = MagicMock(return_value=resp)
resp.__exit__ = MagicMock(return_value=False)
resp.read.return_value = _fake_ollama_tags(*model_names)
resp.status = 200
with patch("urllib.request.urlopen", return_value=resp):
return MultiModalManager(ollama_url="http://localhost:11434")
# ---------------------------------------------------------------------------
# MultiModalManager — init & refresh
# ---------------------------------------------------------------------------
class TestMultiModalManagerInit:
def test_init_no_ollama(self):
mgr = _make_manager(None)
assert mgr.list_available_models() == []
def test_init_with_models(self):
mgr = _make_manager(["llama3.1:8b", "llava:7b"])
names = {m.name for m in mgr.list_available_models()}
assert names == {"llama3.1:8b", "llava:7b"}
def test_refresh_updates_models(self):
mgr = _make_manager([])
assert mgr.list_available_models() == []
resp = MagicMock()
resp.__enter__ = MagicMock(return_value=resp)
resp.__exit__ = MagicMock(return_value=False)
resp.read.return_value = _fake_ollama_tags("gemma2:9b")
resp.status = 200
with patch("urllib.request.urlopen", return_value=resp):
mgr.refresh()
names = {m.name for m in mgr.list_available_models()}
assert "gemma2:9b" in names
# ---------------------------------------------------------------------------
# _detect_capabilities
# ---------------------------------------------------------------------------
class TestDetectCapabilities:
def test_exact_match(self):
mgr = _make_manager(None)
caps = mgr._detect_capabilities("llava:7b")
assert ModelCapability.VISION in caps
def test_base_name_match(self):
mgr = _make_manager(None)
caps = mgr._detect_capabilities("llava:99b")
# "llava:99b" not in table, but "llava" is
assert ModelCapability.VISION in caps
def test_unknown_model_defaults_to_text(self):
mgr = _make_manager(None)
caps = mgr._detect_capabilities("totally-unknown-model:1b")
assert caps == {ModelCapability.TEXT, ModelCapability.STREAMING}
# ---------------------------------------------------------------------------
# get_model_capabilities / model_supports
# ---------------------------------------------------------------------------
class TestGetModelCapabilities:
def test_available_model(self):
mgr = _make_manager(["llava:7b"])
caps = mgr.get_model_capabilities("llava:7b")
assert ModelCapability.VISION in caps
def test_unavailable_model_uses_detection(self):
mgr = _make_manager([])
caps = mgr.get_model_capabilities("llava:7b")
assert ModelCapability.VISION in caps
class TestModelSupports:
def test_supports_true(self):
mgr = _make_manager(["llava:7b"])
assert mgr.model_supports("llava:7b", ModelCapability.VISION) is True
def test_supports_false(self):
mgr = _make_manager(["deepseek-r1:7b"])
assert mgr.model_supports("deepseek-r1:7b", ModelCapability.VISION) is False
# ---------------------------------------------------------------------------
# get_models_with_capability
# ---------------------------------------------------------------------------
class TestGetModelsWithCapability:
def test_returns_vision_models(self):
mgr = _make_manager(["llava:7b", "deepseek-r1:7b"])
vision = mgr.get_models_with_capability(ModelCapability.VISION)
names = {m.name for m in vision}
assert "llava:7b" in names
assert "deepseek-r1:7b" not in names
def test_empty_when_none_available(self):
mgr = _make_manager(["deepseek-r1:7b"])
vision = mgr.get_models_with_capability(ModelCapability.VISION)
assert vision == []
# ---------------------------------------------------------------------------
# get_best_model_for
# ---------------------------------------------------------------------------
class TestGetBestModelFor:
def test_preferred_model_with_capability(self):
mgr = _make_manager(["llava:7b", "llama3.1:8b"])
result = mgr.get_best_model_for(ModelCapability.VISION, preferred_model="llava:7b")
assert result == "llava:7b"
def test_preferred_model_without_capability_uses_fallback(self):
mgr = _make_manager(["deepseek-r1:7b", "llava:7b"])
# preferred doesn't have VISION, fallback chain has llava:7b
result = mgr.get_best_model_for(ModelCapability.VISION, preferred_model="deepseek-r1:7b")
assert result == "llava:7b"
def test_fallback_chain_order(self):
# First in chain: llama3.2:3b
mgr = _make_manager(["llama3.2:3b", "llava:7b"])
result = mgr.get_best_model_for(ModelCapability.VISION)
assert result == "llama3.2:3b"
def test_any_capable_model_when_no_fallback(self):
mgr = _make_manager(["moondream:1.8b"])
mgr._fallback_chains[ModelCapability.VISION] = [] # clear chain
result = mgr.get_best_model_for(ModelCapability.VISION)
assert result == "moondream:1.8b"
def test_none_when_no_capable_model(self):
mgr = _make_manager(["deepseek-r1:7b"])
result = mgr.get_best_model_for(ModelCapability.VISION)
assert result is None
def test_preferred_model_not_available_skipped(self):
mgr = _make_manager(["llava:7b"])
# preferred_model "llava:13b" is not in available_models
result = mgr.get_best_model_for(ModelCapability.VISION, preferred_model="llava:13b")
assert result == "llava:7b"
# ---------------------------------------------------------------------------
# pull_model_with_fallback (manager method)
# ---------------------------------------------------------------------------
class TestPullModelWithFallback:
def test_already_available(self):
mgr = _make_manager(["llama3.1:8b"])
model, is_fallback = mgr.pull_model_with_fallback("llama3.1:8b")
assert model == "llama3.1:8b"
assert is_fallback is False
def test_pull_succeeds(self):
mgr = _make_manager([])
pull_resp = MagicMock()
pull_resp.__enter__ = MagicMock(return_value=pull_resp)
pull_resp.__exit__ = MagicMock(return_value=False)
pull_resp.status = 200
# After pull, refresh returns the model
refresh_resp = MagicMock()
refresh_resp.__enter__ = MagicMock(return_value=refresh_resp)
refresh_resp.__exit__ = MagicMock(return_value=False)
refresh_resp.read.return_value = _fake_ollama_tags("llama3.1:8b")
refresh_resp.status = 200
with patch("urllib.request.urlopen", side_effect=[pull_resp, refresh_resp]):
model, is_fallback = mgr.pull_model_with_fallback("llama3.1:8b")
assert model == "llama3.1:8b"
assert is_fallback is False
def test_pull_fails_uses_capability_fallback(self):
mgr = _make_manager(["llava:7b"])
with patch("urllib.request.urlopen", side_effect=ConnectionError("fail")):
model, is_fallback = mgr.pull_model_with_fallback(
"nonexistent-vision:1b",
capability=ModelCapability.VISION,
)
assert model == "llava:7b"
assert is_fallback is True
def test_pull_fails_uses_default_model(self):
mgr = _make_manager([settings_ollama_model := "llama3.1:8b"])
with (
patch("urllib.request.urlopen", side_effect=ConnectionError("fail")),
patch("infrastructure.models.multimodal.settings") as mock_settings,
):
mock_settings.ollama_model = settings_ollama_model
mock_settings.ollama_url = "http://localhost:11434"
model, is_fallback = mgr.pull_model_with_fallback("missing-model:99b")
assert model == "llama3.1:8b"
assert is_fallback is True
def test_auto_pull_false_skips_pull(self):
mgr = _make_manager([])
with patch("infrastructure.models.multimodal.settings") as mock_settings:
mock_settings.ollama_model = "default"
model, is_fallback = mgr.pull_model_with_fallback("missing:1b", auto_pull=False)
# Falls through to absolute last resort
assert model == "missing:1b"
assert is_fallback is False
def test_absolute_last_resort(self):
mgr = _make_manager([])
with (
patch("urllib.request.urlopen", side_effect=ConnectionError("fail")),
patch("infrastructure.models.multimodal.settings") as mock_settings,
):
mock_settings.ollama_model = "not-available"
model, is_fallback = mgr.pull_model_with_fallback("primary:1b")
assert model == "primary:1b"
assert is_fallback is False
# ---------------------------------------------------------------------------
# _pull_model
# ---------------------------------------------------------------------------
class TestPullModel:
def test_pull_success(self):
mgr = _make_manager([])
pull_resp = MagicMock()
pull_resp.__enter__ = MagicMock(return_value=pull_resp)
pull_resp.__exit__ = MagicMock(return_value=False)
pull_resp.status = 200
refresh_resp = MagicMock()
refresh_resp.__enter__ = MagicMock(return_value=refresh_resp)
refresh_resp.__exit__ = MagicMock(return_value=False)
refresh_resp.read.return_value = _fake_ollama_tags("new-model:1b")
refresh_resp.status = 200
with patch("urllib.request.urlopen", side_effect=[pull_resp, refresh_resp]):
assert mgr._pull_model("new-model:1b") is True
def test_pull_network_error(self):
mgr = _make_manager([])
with patch("urllib.request.urlopen", side_effect=ConnectionError("offline")):
assert mgr._pull_model("any-model:1b") is False
# ---------------------------------------------------------------------------
# configure_fallback_chain / get_fallback_chain
# ---------------------------------------------------------------------------
class TestFallbackChainConfig:
def test_configure_and_get(self):
mgr = _make_manager(None)
mgr.configure_fallback_chain(ModelCapability.VISION, ["model-a", "model-b"])
assert mgr.get_fallback_chain(ModelCapability.VISION) == ["model-a", "model-b"]
def test_get_returns_copy(self):
mgr = _make_manager(None)
chain = mgr.get_fallback_chain(ModelCapability.VISION)
chain.append("mutated")
assert "mutated" not in mgr.get_fallback_chain(ModelCapability.VISION)
def test_get_empty_for_unknown(self):
mgr = _make_manager(None)
# AUDIO has an empty chain by default
assert mgr.get_fallback_chain(ModelCapability.AUDIO) == []
# ---------------------------------------------------------------------------
# get_model_for_content
# ---------------------------------------------------------------------------
class TestGetModelForContent:
def test_image_content(self):
mgr = _make_manager(["llava:7b"])
model, is_fb = mgr.get_model_for_content("image")
assert model == "llava:7b"
def test_vision_content(self):
mgr = _make_manager(["llava:7b"])
model, _ = mgr.get_model_for_content("vision")
assert model == "llava:7b"
def test_multimodal_content(self):
mgr = _make_manager(["llava:7b"])
model, _ = mgr.get_model_for_content("multimodal")
assert model == "llava:7b"
def test_audio_content(self):
mgr = _make_manager(["llama3.1:8b"])
with patch("infrastructure.models.multimodal.settings") as mock_settings:
mock_settings.ollama_model = "llama3.1:8b"
mock_settings.ollama_url = "http://localhost:11434"
model, _ = mgr.get_model_for_content("audio")
assert model == "llama3.1:8b"
def test_text_content(self):
mgr = _make_manager(["llama3.1:8b"])
with patch("infrastructure.models.multimodal.settings") as mock_settings:
mock_settings.ollama_model = "llama3.1:8b"
mock_settings.ollama_url = "http://localhost:11434"
model, _ = mgr.get_model_for_content("text")
assert model == "llama3.1:8b"
def test_preferred_model_respected(self):
mgr = _make_manager(["llama3.2:3b", "llava:7b"])
model, _ = mgr.get_model_for_content("image", preferred_model="llama3.2:3b")
assert model == "llama3.2:3b"
def test_case_insensitive(self):
mgr = _make_manager(["llava:7b"])
model, _ = mgr.get_model_for_content("IMAGE")
assert model == "llava:7b"
# ---------------------------------------------------------------------------
# Module-level convenience functions
# ---------------------------------------------------------------------------
class TestConvenienceFunctions:
def _patch_manager(self, mgr):
return patch(
"infrastructure.models.multimodal._multimodal_manager",
mgr,
)
def test_get_model_for_capability(self):
mgr = _make_manager(["llava:7b"])
with self._patch_manager(mgr):
result = get_model_for_capability(ModelCapability.VISION)
assert result == "llava:7b"
def test_pull_model_with_fallback_convenience(self):
mgr = _make_manager(["llama3.1:8b"])
with self._patch_manager(mgr):
model, is_fb = pull_model_with_fallback("llama3.1:8b")
assert model == "llama3.1:8b"
assert is_fb is False
def test_model_supports_vision_true(self):
mgr = _make_manager(["llava:7b"])
with self._patch_manager(mgr):
assert model_supports_vision("llava:7b") is True
def test_model_supports_vision_false(self):
mgr = _make_manager(["llama3.1:8b"])
with self._patch_manager(mgr):
assert model_supports_vision("llama3.1:8b") is False
def test_model_supports_tools_true(self):
mgr = _make_manager(["llama3.1:8b"])
with self._patch_manager(mgr):
assert model_supports_tools("llama3.1:8b") is True
def test_model_supports_tools_false(self):
mgr = _make_manager(["deepseek-r1:7b"])
with self._patch_manager(mgr):
assert model_supports_tools("deepseek-r1:7b") is False
# ---------------------------------------------------------------------------
# ModelInfo in available_models — size_mb and description populated
# ---------------------------------------------------------------------------
class TestModelInfoPopulation:
def test_size_and_description(self):
mgr = _make_manager(["llama3.1:8b"])
info = mgr._available_models["llama3.1:8b"]
assert info.is_available is True
assert info.is_pulled is True
assert info.size_mb == 4 * 1024 # 4 GiB in MiB
assert info.description == "test"

View File

@@ -1,149 +0,0 @@
"""Tests for provider health history store and API endpoint."""
import time
from datetime import UTC, datetime, timedelta
from unittest.mock import MagicMock
import pytest
from src.infrastructure.router.history import HealthHistoryStore
@pytest.fixture
def store():
"""In-memory history store for testing."""
s = HealthHistoryStore(db_path=":memory:")
yield s
s.close()
@pytest.fixture
def sample_providers():
return [
{
"name": "anthropic",
"status": "healthy",
"error_rate": 0.01,
"avg_latency_ms": 250.5,
"circuit_state": "closed",
"total_requests": 100,
},
{
"name": "local",
"status": "degraded",
"error_rate": 0.15,
"avg_latency_ms": 80.0,
"circuit_state": "closed",
"total_requests": 50,
},
]
def test_record_and_retrieve(store, sample_providers):
store.record_snapshot(sample_providers)
history = store.get_history(hours=1)
assert len(history) == 1
assert len(history[0]["providers"]) == 2
assert history[0]["providers"][0]["name"] == "anthropic"
assert history[0]["providers"][1]["name"] == "local"
assert "timestamp" in history[0]
def test_multiple_snapshots(store, sample_providers):
store.record_snapshot(sample_providers)
time.sleep(0.01)
store.record_snapshot(sample_providers)
history = store.get_history(hours=1)
assert len(history) == 2
def test_hours_filtering(store, sample_providers):
old_ts = (datetime.now(UTC) - timedelta(hours=48)).isoformat()
store._conn.execute(
"""INSERT INTO snapshots
(timestamp, provider_name, status, error_rate,
avg_latency_ms, circuit_state, total_requests)
VALUES (?, ?, ?, ?, ?, ?, ?)""",
(old_ts, "anthropic", "healthy", 0.0, 100.0, "closed", 10),
)
store._conn.commit()
store.record_snapshot(sample_providers)
history = store.get_history(hours=24)
assert len(history) == 1
history = store.get_history(hours=72)
assert len(history) == 2
def test_prune(store, sample_providers):
old_ts = (datetime.now(UTC) - timedelta(hours=200)).isoformat()
store._conn.execute(
"""INSERT INTO snapshots
(timestamp, provider_name, status, error_rate,
avg_latency_ms, circuit_state, total_requests)
VALUES (?, ?, ?, ?, ?, ?, ?)""",
(old_ts, "anthropic", "healthy", 0.0, 100.0, "closed", 10),
)
store._conn.commit()
store.record_snapshot(sample_providers)
deleted = store.prune(keep_hours=168)
assert deleted == 1
history = store.get_history(hours=999)
assert len(history) == 1
def test_empty_history(store):
assert store.get_history(hours=24) == []
def test_capture_snapshot_from_router(store):
mock_metrics = MagicMock()
mock_metrics.error_rate = 0.05
mock_metrics.avg_latency_ms = 200.0
mock_metrics.total_requests = 42
mock_provider = MagicMock()
mock_provider.name = "test-provider"
mock_provider.status.value = "healthy"
mock_provider.metrics = mock_metrics
mock_provider.circuit_state.value = "closed"
mock_router = MagicMock()
mock_router.providers = [mock_provider]
store._capture_snapshot(mock_router)
history = store.get_history(hours=1)
assert len(history) == 1
p = history[0]["providers"][0]
assert p["name"] == "test-provider"
assert p["status"] == "healthy"
assert p["error_rate"] == 0.05
assert p["total_requests"] == 42
def test_history_api_endpoint(store, sample_providers):
"""GET /api/v1/router/history returns snapshot data."""
store.record_snapshot(sample_providers)
from fastapi import FastAPI
from fastapi.testclient import TestClient
from src.infrastructure.router.api import get_cascade_router
from src.infrastructure.router.api import router as api_router
from src.infrastructure.router.history import get_history_store
app = FastAPI()
app.include_router(api_router)
app.dependency_overrides[get_history_store] = lambda: store
app.dependency_overrides[get_cascade_router] = lambda: MagicMock()
client = TestClient(app)
resp = client.get("/api/v1/router/history?hours=1")
assert resp.status_code == 200
data = resp.json()
assert len(data) == 1
assert len(data[0]["providers"]) == 2
assert data[0]["providers"][0]["name"] == "anthropic"
app.dependency_overrides.clear()

View File

@@ -1,129 +0,0 @@
"""Tests for the WorldInterface contract and type system."""
import pytest
from infrastructure.world.interface import WorldInterface
from infrastructure.world.types import (
ActionResult,
ActionStatus,
CommandInput,
PerceptionOutput,
)
# ---------------------------------------------------------------------------
# Type construction
# ---------------------------------------------------------------------------
class TestPerceptionOutput:
def test_defaults(self):
p = PerceptionOutput()
assert p.location == ""
assert p.entities == []
assert p.events == []
assert p.raw == {}
assert p.timestamp is not None
def test_custom_values(self):
p = PerceptionOutput(
location="Balmora",
entities=["Guard", "Merchant"],
events=["door_opened"],
)
assert p.location == "Balmora"
assert len(p.entities) == 2
assert "door_opened" in p.events
class TestCommandInput:
def test_minimal(self):
c = CommandInput(action="move")
assert c.action == "move"
assert c.target is None
assert c.parameters == {}
def test_with_target_and_params(self):
c = CommandInput(action="attack", target="Rat", parameters={"weapon": "sword"})
assert c.target == "Rat"
assert c.parameters["weapon"] == "sword"
class TestActionResult:
def test_defaults(self):
r = ActionResult()
assert r.status == ActionStatus.SUCCESS
assert r.message == ""
def test_failure(self):
r = ActionResult(status=ActionStatus.FAILURE, message="blocked")
assert r.status == ActionStatus.FAILURE
class TestActionStatus:
def test_values(self):
assert ActionStatus.SUCCESS.value == "success"
assert ActionStatus.FAILURE.value == "failure"
assert ActionStatus.PENDING.value == "pending"
assert ActionStatus.NOOP.value == "noop"
# ---------------------------------------------------------------------------
# Abstract contract
# ---------------------------------------------------------------------------
class TestWorldInterfaceContract:
"""Verify the ABC cannot be instantiated directly."""
def test_cannot_instantiate(self):
with pytest.raises(TypeError):
WorldInterface()
def test_subclass_must_implement_observe(self):
class Incomplete(WorldInterface):
def act(self, command):
pass
def speak(self, message, target=None):
pass
with pytest.raises(TypeError):
Incomplete()
def test_subclass_must_implement_act(self):
class Incomplete(WorldInterface):
def observe(self):
return PerceptionOutput()
def speak(self, message, target=None):
pass
with pytest.raises(TypeError):
Incomplete()
def test_subclass_must_implement_speak(self):
class Incomplete(WorldInterface):
def observe(self):
return PerceptionOutput()
def act(self, command):
return ActionResult()
with pytest.raises(TypeError):
Incomplete()
def test_complete_subclass_instantiates(self):
class Complete(WorldInterface):
def observe(self):
return PerceptionOutput()
def act(self, command):
return ActionResult()
def speak(self, message, target=None):
pass
adapter = Complete()
assert adapter.is_connected is True # default
assert isinstance(adapter.observe(), PerceptionOutput)
assert isinstance(adapter.act(CommandInput(action="test")), ActionResult)

View File

@@ -1,80 +0,0 @@
"""Tests for the MockWorldAdapter — full observe/act/speak cycle."""
from infrastructure.world.adapters.mock import MockWorldAdapter
from infrastructure.world.types import ActionStatus, CommandInput, PerceptionOutput
class TestMockWorldAdapter:
def test_observe_returns_perception(self):
adapter = MockWorldAdapter(location="Vivec")
perception = adapter.observe()
assert isinstance(perception, PerceptionOutput)
assert perception.location == "Vivec"
assert perception.raw == {"adapter": "mock"}
def test_observe_entities(self):
adapter = MockWorldAdapter(entities=["Jiub", "Silt Strider"])
perception = adapter.observe()
assert perception.entities == ["Jiub", "Silt Strider"]
def test_act_logs_command(self):
adapter = MockWorldAdapter()
cmd = CommandInput(action="move", target="north")
result = adapter.act(cmd)
assert result.status == ActionStatus.SUCCESS
assert "move" in result.message
assert len(adapter.action_log) == 1
assert adapter.action_log[0].command.action == "move"
def test_act_multiple_commands(self):
adapter = MockWorldAdapter()
adapter.act(CommandInput(action="attack"))
adapter.act(CommandInput(action="defend"))
adapter.act(CommandInput(action="retreat"))
assert len(adapter.action_log) == 3
def test_speak_logs_message(self):
adapter = MockWorldAdapter()
adapter.speak("Hello, traveler!")
assert len(adapter.speech_log) == 1
assert adapter.speech_log[0]["message"] == "Hello, traveler!"
assert adapter.speech_log[0]["target"] is None
def test_speak_with_target(self):
adapter = MockWorldAdapter()
adapter.speak("Die, scum!", target="Cliff Racer")
assert adapter.speech_log[0]["target"] == "Cliff Racer"
def test_lifecycle(self):
adapter = MockWorldAdapter()
assert adapter.is_connected is False
adapter.connect()
assert adapter.is_connected is True
adapter.disconnect()
assert adapter.is_connected is False
def test_full_observe_act_speak_cycle(self):
"""Acceptance criterion: full observe/act/speak cycle passes."""
adapter = MockWorldAdapter(
location="Seyda Neen",
entities=["Fargoth", "Hrisskar"],
events=["quest_started"],
)
adapter.connect()
# Observe
perception = adapter.observe()
assert perception.location == "Seyda Neen"
assert len(perception.entities) == 2
assert "quest_started" in perception.events
# Act
result = adapter.act(CommandInput(action="talk", target="Fargoth"))
assert result.status == ActionStatus.SUCCESS
# Speak
adapter.speak("Where is your ring, Fargoth?", target="Fargoth")
assert len(adapter.speech_log) == 1
adapter.disconnect()
assert adapter.is_connected is False

View File

@@ -1,68 +0,0 @@
"""Tests for the adapter registry."""
import pytest
from infrastructure.world.adapters.mock import MockWorldAdapter
from infrastructure.world.registry import AdapterRegistry
class TestAdapterRegistry:
def test_register_and_get(self):
reg = AdapterRegistry()
reg.register("mock", MockWorldAdapter)
adapter = reg.get("mock")
assert isinstance(adapter, MockWorldAdapter)
def test_register_with_kwargs(self):
reg = AdapterRegistry()
reg.register("mock", MockWorldAdapter)
adapter = reg.get("mock", location="Custom Room")
assert adapter._location == "Custom Room"
def test_get_unknown_raises(self):
reg = AdapterRegistry()
with pytest.raises(KeyError):
reg.get("nonexistent")
def test_register_non_subclass_raises(self):
reg = AdapterRegistry()
with pytest.raises(TypeError):
reg.register("bad", dict)
def test_list_adapters(self):
reg = AdapterRegistry()
reg.register("beta", MockWorldAdapter)
reg.register("alpha", MockWorldAdapter)
assert reg.list_adapters() == ["alpha", "beta"]
def test_contains(self):
reg = AdapterRegistry()
reg.register("mock", MockWorldAdapter)
assert "mock" in reg
assert "other" not in reg
def test_len(self):
reg = AdapterRegistry()
assert len(reg) == 0
reg.register("mock", MockWorldAdapter)
assert len(reg) == 1
def test_overwrite_warns(self, caplog):
import logging
reg = AdapterRegistry()
reg.register("mock", MockWorldAdapter)
with caplog.at_level(logging.WARNING):
reg.register("mock", MockWorldAdapter)
assert "Overwriting" in caplog.text
class TestModuleLevelRegistry:
"""Test the convenience functions in infrastructure.world.__init__."""
def test_register_and_get(self):
from infrastructure.world import get_adapter, register_adapter
register_adapter("test_mock", MockWorldAdapter)
adapter = get_adapter("test_mock")
assert isinstance(adapter, MockWorldAdapter)

View File

@@ -1,44 +0,0 @@
"""Tests for the TES3MP stub adapter."""
import pytest
from infrastructure.world.adapters.tes3mp import TES3MPWorldAdapter
from infrastructure.world.types import CommandInput
class TestTES3MPStub:
"""Acceptance criterion: stub imports cleanly and raises NotImplementedError."""
def test_instantiates(self):
adapter = TES3MPWorldAdapter(host="127.0.0.1", port=25565)
assert adapter._host == "127.0.0.1"
assert adapter._port == 25565
def test_is_connected_default_false(self):
adapter = TES3MPWorldAdapter()
assert adapter.is_connected is False
def test_connect_raises(self):
adapter = TES3MPWorldAdapter()
with pytest.raises(NotImplementedError, match="connect"):
adapter.connect()
def test_disconnect_raises(self):
adapter = TES3MPWorldAdapter()
with pytest.raises(NotImplementedError, match="disconnect"):
adapter.disconnect()
def test_observe_raises(self):
adapter = TES3MPWorldAdapter()
with pytest.raises(NotImplementedError, match="observe"):
adapter.observe()
def test_act_raises(self):
adapter = TES3MPWorldAdapter()
with pytest.raises(NotImplementedError, match="act"):
adapter.act(CommandInput(action="move"))
def test_speak_raises(self):
adapter = TES3MPWorldAdapter()
with pytest.raises(NotImplementedError, match="speak"):
adapter.speak("Hello")

View File

@@ -174,103 +174,6 @@ class TestDiscordVendor:
assert result is False
class TestExtractContent:
def test_strips_bot_mention(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user.id = 12345
msg = MagicMock()
msg.content = "<@12345> hello there"
assert vendor._extract_content(msg) == "hello there"
def test_no_client_user(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user = None
msg = MagicMock()
msg.content = "hello"
assert vendor._extract_content(msg) == "hello"
def test_empty_after_strip(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user.id = 99
msg = MagicMock()
msg.content = "<@99>"
assert vendor._extract_content(msg) == ""
class TestInvokeAgent:
@staticmethod
def _make_typing_target():
"""Build a mock target whose .typing() is an async context manager."""
from contextlib import asynccontextmanager
target = AsyncMock()
@asynccontextmanager
async def _typing():
yield
target.typing = _typing
return target
@pytest.mark.asyncio
async def test_timeout_returns_error(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
target = self._make_typing_target()
with patch(
"integrations.chat_bridge.vendors.discord.chat_with_tools", side_effect=TimeoutError
):
run_output, response = await vendor._invoke_agent("hi", "sess", target)
assert run_output is None
assert "too long" in response
@pytest.mark.asyncio
async def test_exception_returns_error(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
target = self._make_typing_target()
with patch(
"integrations.chat_bridge.vendors.discord.chat_with_tools",
side_effect=RuntimeError("boom"),
):
run_output, response = await vendor._invoke_agent("hi", "sess", target)
assert run_output is None
assert "trouble" in response
class TestSendResponse:
@pytest.mark.asyncio
async def test_skips_empty(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
target = AsyncMock()
await DiscordVendor._send_response(None, target)
target.send.assert_not_called()
await DiscordVendor._send_response("", target)
target.send.assert_not_called()
@pytest.mark.asyncio
async def test_sends_short_message(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
target = AsyncMock()
await DiscordVendor._send_response("hello", target)
target.send.assert_called_once_with("hello")
class TestChunkMessage:
def test_short_message(self):
from integrations.chat_bridge.vendors.discord import _chunk_message

View File

@@ -58,55 +58,6 @@ class TestDetectIssueFromBranch:
assert mod.detect_issue_from_branch() is None
class TestConsumeOnce:
"""cycle_result.json must be deleted after reading."""
def test_cycle_result_deleted_after_read(self, mod, tmp_path):
"""After _load_cycle_result() data is consumed in main(), the file is deleted."""
result_file = tmp_path / "cycle_result.json"
result_file.write_text('{"issue": 42, "type": "bug"}')
with (
patch.object(mod, "CYCLE_RESULT_FILE", result_file),
patch.object(mod, "RETRO_FILE", tmp_path / "retro" / "cycles.jsonl"),
patch.object(mod, "SUMMARY_FILE", tmp_path / "retro" / "summary.json"),
patch.object(mod, "EPOCH_COUNTER_FILE", tmp_path / "retro" / ".epoch_counter"),
patch(
"sys.argv",
["cycle_retro", "--cycle", "1", "--success", "--main-green", "--duration", "60"],
),
):
mod.main()
assert not result_file.exists(), "cycle_result.json should be deleted after consumption"
def test_cycle_result_not_deleted_when_empty(self, mod, tmp_path):
"""If cycle_result.json doesn't exist, no error occurs."""
result_file = tmp_path / "nonexistent_result.json"
with (
patch.object(mod, "CYCLE_RESULT_FILE", result_file),
patch.object(mod, "RETRO_FILE", tmp_path / "retro" / "cycles.jsonl"),
patch.object(mod, "SUMMARY_FILE", tmp_path / "retro" / "summary.json"),
patch.object(mod, "EPOCH_COUNTER_FILE", tmp_path / "retro" / ".epoch_counter"),
patch(
"sys.argv",
[
"cycle_retro",
"--cycle",
"1",
"--success",
"--main-green",
"--duration",
"60",
"--issue",
"10",
],
),
):
mod.main() # Should not raise
class TestBackfillExtractIssueNumber:
"""Tests for backfill_retro.extract_issue_number PR-number filtering."""

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