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claude/iss
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claude/iss
| Author | SHA1 | Date | |
|---|---|---|---|
|
03f9a42fbc |
15
.github/workflows/tests.yml
vendored
15
.github/workflows/tests.yml
vendored
@@ -50,7 +50,6 @@ jobs:
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run: pip install tox
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- name: Run tests (via tox)
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id: tests
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run: tox -e ci
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# Posts a check annotation + PR comment showing pass/fail counts.
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@@ -64,20 +63,6 @@ jobs:
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comment_title: "Test Results"
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report_individual_runs: true
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- name: Enforce coverage floor (60%)
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if: always() && steps.tests.outcome == 'success'
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run: |
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python -c "
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import xml.etree.ElementTree as ET, sys
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tree = ET.parse('reports/coverage.xml')
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rate = float(tree.getroot().attrib['line-rate']) * 100
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print(f'Coverage: {rate:.1f}%')
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if rate < 60:
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print(f'FAIL: Coverage {rate:.1f}% is below 60% floor')
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sys.exit(1)
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print('PASS: Coverage is above 60% floor')
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"
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# Coverage report available as a downloadable artifact in the Actions tab
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- name: Upload coverage report
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uses: actions/upload-artifact@v4
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@@ -1,55 +0,0 @@
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# Modelfile.hermes4-14b
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#
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# NousResearch Hermes 4 14B — AutoLoRA base model (Project Bannerlord, Step 2)
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#
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# Features: native tool calling, hybrid reasoning (<think> tags), structured
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# JSON output, neutral alignment. Built to serve as the LoRA fine-tuning base.
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#
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# Build:
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# # Download GGUF from HuggingFace first:
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# # https://huggingface.co/collections/NousResearch/hermes-4-collection-68a7
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# # Pick: NousResearch-Hermes-4-14B-Q5_K_M.gguf (or Q4_K_M for less RAM)
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# ollama create hermes4-14b -f Modelfile.hermes4-14b
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#
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# Or if hermes4 lands on Ollama registry directly:
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# ollama pull hermes4:14b
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# ollama create hermes4-14b -f Modelfile.hermes4-14b
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#
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# Memory budget: ~9 GB at Q4_K_M, ~11 GB at Q5_K_M — leaves headroom on 36 GB M3 Max
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# Context: 32K comfortable (128K theoretical)
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# Primary use: AutoLoRA base before fine-tuning on Timmy skill set
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# --- Option A: import local GGUF (uncomment and set correct path) ---
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# FROM /path/to/NousResearch-Hermes-4-14B-Q5_K_M.gguf
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# --- Option B: build from Ollama registry model (if available) ---
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FROM hermes4:14b
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# Context window — 32K leaves ~20 GB headroom for KV cache on M3 Max
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PARAMETER num_ctx 32768
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# Tool-calling temperature — lower for reliable structured output
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PARAMETER temperature 0.3
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# Nucleus sampling — balanced for reasoning + tool use
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PARAMETER top_p 0.9
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# Repeat penalty — prevents looping in structured output
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PARAMETER repeat_penalty 1.05
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# Stop tokens for Hermes 4 chat template (ChatML format)
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# These are handled automatically by the model's tokenizer config,
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# but listed here for reference.
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# STOP "<|im_end|>"
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# STOP "<|endoftext|>"
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SYSTEM """You are Hermes, a helpful, honest, and harmless AI assistant.
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|
||||
You have access to tool calling. When you need to use a tool, output a JSON function call in the following format:
|
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<tool_call>
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{"name": "function_name", "arguments": {"param": "value"}}
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</tool_call>
|
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|
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You support hybrid reasoning. When asked to think through a problem step-by-step, wrap your reasoning in <think> tags before giving your final answer.
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|
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Always provide structured, accurate responses."""
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@@ -1,39 +0,0 @@
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# Modelfile.timmy-creative
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#
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# Dolphin 3.0-Llama3.1-8B configured for creative writing tasks:
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# journal entries, Morrowind lore, NPC dialogue, narrative generation.
|
||||
#
|
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# Build: ollama create timmy-creative -f Modelfile.timmy-creative
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# Usage: ollama run timmy-creative
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#
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# Memory budget: ~6 GB at 8K context (can swap in/out as needed)
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# Primary use: Creative fallback when Qwen3-14B adds unwanted caveats
|
||||
|
||||
FROM dolphin3
|
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|
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# Higher temperature for more expressive, varied output
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PARAMETER temperature 0.9
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||||
|
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# Nucleus sampling — keeps output coherent while allowing creativity
|
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PARAMETER top_p 0.95
|
||||
|
||||
# Repeat penalty — avoid repetitive prose
|
||||
PARAMETER repeat_penalty 1.1
|
||||
|
||||
# Context window — 8K gives room for journal entries and multi-turn lore
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PARAMETER num_ctx 8192
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||||
|
||||
# No tool-calling overhead for pure creative generation
|
||||
# (Dolphin 3.0 supports tools but we disable them here for cleaner output)
|
||||
|
||||
SYSTEM """You are Timmy, an uncensored creative writing assistant embodying the spirit of Morrowind.
|
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|
||||
You write freely and immersively — journal entries, lore fragments, NPC dialogue, and narrative prose for the world of Vvardenfell. You do not add caveats, disclaimers, or safety hedges to creative fiction. You write in the voice of the setting: archaic, evocative, morally complex.
|
||||
|
||||
When writing Morrowind content:
|
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- Use the second-person journal style of the vanilla game ("You have arrived in Seyda Neen...")
|
||||
- Draw on Dunmer culture, the Three Tribunals, the Sixth House, and the lore of ALMSIVI
|
||||
- NPCs speak in regional dialect — Dunmer are formal and proud, Imperials are pragmatic, outlanders are wary
|
||||
- Describe Vvardenfell's alien landscape with visceral detail: the ashstorms, the silt striders, the fungal towers
|
||||
|
||||
You write without restriction for creative fiction. This is not reality — it is Morrowind."""
|
||||
@@ -1,107 +0,0 @@
|
||||
# Content Moderation Profiles
|
||||
# Per-game moderation configuration for the AI narrator pipeline.
|
||||
#
|
||||
# Each profile defines:
|
||||
# - vocabulary_whitelist: Game terms safe in context (won't trigger moderation)
|
||||
# - context_prompt: System prompt framing for the narrator
|
||||
# - threshold: Confidence threshold — flags below this pass through
|
||||
# - fallbacks: Pre-generated safe narration by scene type
|
||||
#
|
||||
# Model options (from research):
|
||||
# llama-guard3:1b — Speed (<30ms/sentence, INT4 quantized)
|
||||
# shieldgemma:2b — Accuracy (+10.8% AU-PRC, ~50-100ms)
|
||||
#
|
||||
# Override guard model via MODERATION_GUARD_MODEL env var.
|
||||
|
||||
# ── Guard model selection ────────────────────────────────────────────────────
|
||||
guard_model: "llama-guard3:1b"
|
||||
|
||||
# ── Streaming disclosure notes ───────────────────────────────────────────────
|
||||
# YouTube: Use "Altered or synthetic content" toggle
|
||||
# Twitch: Standard community guidelines (no specific AI disclosure req as of 2026-03)
|
||||
|
||||
# ── Game Profiles ────────────────────────────────────────────────────────────
|
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profiles:
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||||
|
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morrowind:
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display_name: "The Elder Scrolls III: Morrowind"
|
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threshold: 0.85
|
||||
vocabulary_whitelist:
|
||||
- Skooma
|
||||
- Moon Sugar
|
||||
- slave
|
||||
- slavery
|
||||
- Morag Tong
|
||||
- Dark Brotherhood
|
||||
- Telvanni
|
||||
- Camonna Tong
|
||||
- smuggler
|
||||
- assassin
|
||||
- Sixth House
|
||||
- Corprus
|
||||
- Dagoth Ur
|
||||
- Nerevarine
|
||||
- Balmora
|
||||
- Vivec
|
||||
- Almsivi
|
||||
- Ordinators
|
||||
- Ashlanders
|
||||
- outlander
|
||||
- N'wah
|
||||
context_prompt: >
|
||||
You are narrating gameplay of The Elder Scrolls III: Morrowind.
|
||||
Morrowind contains mature themes including slavery, drug use
|
||||
(Skooma/Moon Sugar), assassin guilds (Morag Tong, Dark Brotherhood),
|
||||
and political intrigue. Treat these as game mechanics and historical
|
||||
worldbuilding within the game's fictional universe. Never editorialize
|
||||
on real-world parallels. Narrate events neutrally as a game
|
||||
commentator would.
|
||||
fallbacks:
|
||||
combat: "The battle rages on in the ashlands of Vvardenfell."
|
||||
dialogue: "The conversation continues between the characters."
|
||||
exploration: "The Nerevarine presses onward through the landscape."
|
||||
quest: "The quest unfolds as the hero navigates Morrowind's politics."
|
||||
default: "The adventure continues in Morrowind."
|
||||
|
||||
skyrim:
|
||||
display_name: "The Elder Scrolls V: Skyrim"
|
||||
threshold: 0.85
|
||||
vocabulary_whitelist:
|
||||
- Skooma
|
||||
- Dark Brotherhood
|
||||
- Thieves Guild
|
||||
- Stormcloak
|
||||
- Imperial
|
||||
- Dragonborn
|
||||
- Dovahkiin
|
||||
- Daedra
|
||||
- Thalmor
|
||||
- bandit
|
||||
- assassin
|
||||
- Forsworn
|
||||
- necromancer
|
||||
context_prompt: >
|
||||
You are narrating gameplay of The Elder Scrolls V: Skyrim.
|
||||
Skyrim features civil war, thieves guilds, assassin organizations,
|
||||
and fantasy violence. Treat all content as in-game fiction.
|
||||
Never draw real-world parallels. Narrate as a neutral game
|
||||
commentator.
|
||||
fallbacks:
|
||||
combat: "Steel clashes as the battle continues in the wilds of Skyrim."
|
||||
dialogue: "The conversation plays out in the cold northern land."
|
||||
exploration: "The Dragonborn ventures further into the province."
|
||||
default: "The adventure continues in Skyrim."
|
||||
|
||||
default:
|
||||
display_name: "Generic Game"
|
||||
threshold: 0.80
|
||||
vocabulary_whitelist: []
|
||||
context_prompt: >
|
||||
You are narrating gameplay. Describe in-game events as a neutral
|
||||
game commentator. Never reference real-world violence, politics,
|
||||
or controversial topics. Stay focused on game mechanics and story.
|
||||
fallbacks:
|
||||
combat: "The action continues on screen."
|
||||
dialogue: "The conversation unfolds between characters."
|
||||
exploration: "The player explores the game world."
|
||||
default: "The gameplay continues."
|
||||
@@ -53,60 +53,8 @@ providers:
|
||||
- name: moondream:1.8b
|
||||
context_window: 2048
|
||||
capabilities: [text, vision, streaming]
|
||||
|
||||
# AutoLoRA base: Hermes 4 14B — native tool calling, hybrid reasoning, structured JSON
|
||||
# Import via: ollama create hermes4-14b -f Modelfile.hermes4-14b
|
||||
# See Modelfile.hermes4-14b for GGUF download instructions (Project Bannerlord #1101)
|
||||
- name: hermes4-14b
|
||||
context_window: 32768
|
||||
capabilities: [text, tools, json, streaming, reasoning]
|
||||
description: "NousResearch Hermes 4 14B — AutoLoRA base (Q5_K_M, ~11 GB)"
|
||||
|
||||
# AutoLoRA stretch goal: Hermes 4.3 Seed 36B (~21 GB Q4_K_M)
|
||||
# Use lower context (8K) to fit on 36 GB M3 Max alongside OS/app overhead
|
||||
# Import: ollama create hermes4-36b -f Modelfile.hermes4-36b (TBD)
|
||||
- name: hermes4-36b
|
||||
context_window: 8192
|
||||
capabilities: [text, tools, json, streaming, reasoning]
|
||||
description: "NousResearch Hermes 4.3 Seed 36B — stretch goal (Q4_K_M, ~21 GB)"
|
||||
|
||||
# Creative writing fallback (Dolphin 3.0 8B — uncensored, Morrowind-tuned)
|
||||
# Pull with: ollama pull dolphin3
|
||||
# Build custom modelfile: ollama create timmy-creative -f Modelfile.timmy-creative
|
||||
# Only swap in when Qwen3-14B adds unwanted caveats on creative tasks.
|
||||
# Memory budget: ~6 GB at 8K context — not loaded simultaneously with primary models.
|
||||
- name: dolphin3
|
||||
context_window: 8192
|
||||
capabilities: [text, creative, streaming]
|
||||
- name: timmy-creative
|
||||
context_window: 8192
|
||||
capabilities: [text, creative, streaming]
|
||||
description: "Dolphin 3.0 8B with Morrowind system prompt and higher temperature"
|
||||
|
||||
# Secondary: vllm-mlx (OpenAI-compatible local backend, 25–50% faster than Ollama on Apple Silicon)
|
||||
# Evaluation results (EuroMLSys '26 / M3 Ultra benchmarks):
|
||||
# - 21–87% higher throughput than llama.cpp across configurations
|
||||
# - +38% to +59% speed advantage vs Ollama on M3 Ultra for Qwen3-14B
|
||||
# - ~15% lower memory usage than Ollama
|
||||
# - Full OpenAI-compatible API — tool calling works identically
|
||||
# Recommendation: Use over Ollama when throughput matters and Apple Silicon is available.
|
||||
# Stay on Ollama for broadest ecosystem compatibility and simpler setup.
|
||||
# To enable: start vllm-mlx server (`python -m vllm.entrypoints.openai.api_server
|
||||
# --model Qwen/Qwen2.5-14B-Instruct-MLX --port 8000`) then set enabled: true.
|
||||
- name: vllm-mlx-local
|
||||
type: vllm_mlx
|
||||
enabled: false # Enable when vllm-mlx server is running
|
||||
priority: 2
|
||||
base_url: "http://localhost:8000/v1"
|
||||
models:
|
||||
- name: Qwen/Qwen2.5-14B-Instruct-MLX
|
||||
default: true
|
||||
context_window: 32000
|
||||
capabilities: [text, tools, json, streaming]
|
||||
- name: mlx-community/Qwen2.5-7B-Instruct-4bit
|
||||
context_window: 32000
|
||||
capabilities: [text, tools, json, streaming]
|
||||
|
||||
|
||||
|
||||
# Tertiary: OpenAI (if API key available)
|
||||
- name: openai-backup
|
||||
type: openai
|
||||
@@ -152,8 +100,7 @@ fallback_chains:
|
||||
|
||||
# Tool-calling models (for function calling)
|
||||
tools:
|
||||
- hermes4-14b # Native tool calling + structured JSON (AutoLoRA base)
|
||||
- llama3.1:8b-instruct # Reliable tool use
|
||||
- llama3.1:8b-instruct # Best tool use
|
||||
- qwen2.5:7b # Reliable tools
|
||||
- llama3.2:3b # Small but capable
|
||||
|
||||
@@ -165,14 +112,6 @@ fallback_chains:
|
||||
- deepseek-r1:1.5b
|
||||
- llama3.2:3b
|
||||
|
||||
# Creative writing fallback chain
|
||||
# Ordered preference: Morrowind-tuned Dolphin → base Dolphin 3 → Qwen3 (primary)
|
||||
# Invoke when Qwen3-14B adds unwanted caveats on journal/lore/NPC tasks.
|
||||
creative:
|
||||
- timmy-creative # dolphin3 + Morrowind system prompt (Modelfile.timmy-creative)
|
||||
- dolphin3 # base Dolphin 3.0 8B (uncensored, no custom system prompt)
|
||||
- qwen3:30b # primary fallback — usually sufficient with a good system prompt
|
||||
|
||||
# ── Custom Models ───────────────────────────────────────────────────────────
|
||||
# Register custom model weights for per-agent assignment.
|
||||
# Supports GGUF (Ollama), safetensors, and HuggingFace checkpoint dirs.
|
||||
|
||||
@@ -1,91 +0,0 @@
|
||||
# Deep Backlog Triage — Harness vs Infrastructure Separation
|
||||
|
||||
**Date:** March 23, 2026
|
||||
**Analyst:** Perplexity Computer
|
||||
**Executor:** Claude (Opus 4.6)
|
||||
**Issue:** #1076
|
||||
|
||||
---
|
||||
|
||||
## Summary of Actions Taken
|
||||
|
||||
### 1. Batch Closed: 17 Rejected-Direction Issues
|
||||
|
||||
OpenClaw rejected direction + superseded autoresearch:
|
||||
#663, #722, #723, #724, #725, #726, #727, #728, #729, #730, #731,
|
||||
#903, #904, #911, #926, #927, #950
|
||||
|
||||
All labeled `rejected-direction`.
|
||||
|
||||
### 2. Closed: 2 Duplicate Issues
|
||||
|
||||
- #867 — duplicate of #887 (Morrowind feasibility study)
|
||||
- #916 — duplicate of #931 (test_setup_script.py fixes)
|
||||
|
||||
Both labeled `duplicate`.
|
||||
|
||||
### 3. Labels Created
|
||||
|
||||
| Label | Color | Purpose |
|
||||
|-------|-------|---------|
|
||||
| `harness` | Red | Core product: agent framework |
|
||||
| `infrastructure` | Blue | Supporting stage: dashboard, CI/CD |
|
||||
| `p0-critical` | Red | Must fix now |
|
||||
| `p1-important` | Orange | Next sprint |
|
||||
| `p2-backlog` | Gold | When time permits |
|
||||
| `rejected-direction` | Gray | Closed: rejected/superseded |
|
||||
| `duplicate` | Light gray | Duplicate of another issue |
|
||||
| `gemini-review` | Purple | Auto-generated, needs review |
|
||||
| `consolidation` | Green | Part of a consolidation epic |
|
||||
| `morrowind` | Brown | Harness: Morrowind embodiment |
|
||||
| `heartbeat` | Crimson | Harness: Agent heartbeat loop |
|
||||
| `inference` | Orange-red | Harness: Inference/model routing |
|
||||
| `sovereignty` | Indigo | Harness: Sovereignty stack |
|
||||
| `memory-session` | Teal | Harness: Memory/session |
|
||||
| `deprioritized` | Dark gray | Not blocking P0 work |
|
||||
|
||||
### 4. Consolidation Epics Created
|
||||
|
||||
- **#1077** — [EPIC] Kimi-Tasks Code Hygiene (14 issues consolidated)
|
||||
- **#1078** — [EPIC] ASCII Video Showcase (6 issues consolidated)
|
||||
|
||||
### 5. Labels Applied
|
||||
|
||||
- **P0 Heartbeat** — 16 issues labeled `harness` + `p0-critical` + `heartbeat`
|
||||
- **P0 Inference** — 10 issues labeled `harness` + `p0-critical` + `inference`
|
||||
- **P0 Memory/Session** — 3 issues labeled `harness` + `p0-critical` + `memory-session`
|
||||
- **P1 Morrowind** — 63 issues labeled `harness` + `p1-important` + `morrowind`
|
||||
- **P1 Sovereignty** — 11 issues labeled `harness` + `p1-important` + `sovereignty`
|
||||
- **P1 SOUL/Persona** — 2 issues labeled `harness` + `p1-important`
|
||||
- **P1 Testing** — 4 issues labeled `harness` + `p1-important`
|
||||
- **P2 LHF** — 3 issues labeled `harness` + `p2-backlog`
|
||||
- **P2 Whitestone** — 9 issues labeled `harness` + `p2-backlog`
|
||||
- **Infrastructure** — 36 issues labeled `infrastructure` + `deprioritized`
|
||||
- **Philosophy** — 44 issues labeled `philosophy`
|
||||
- **Gemini Review** — 15 issues labeled `gemini-review`
|
||||
- **Consolidation** — 20 issues labeled `consolidation`
|
||||
|
||||
### 6. Gemini Issues (15) — Tagged for Review
|
||||
|
||||
#577, #578, #579, #1006, #1007, #1008, #1009, #1010, #1012, #1013,
|
||||
#1014, #1016, #1017, #1018, #1019
|
||||
|
||||
Labeled `gemini-review` for human review of alignment with harness-first strategy.
|
||||
|
||||
---
|
||||
|
||||
## Domain Breakdown
|
||||
|
||||
| Domain | Count | % |
|
||||
|--------|-------|---|
|
||||
| **HARNESS (The Product)** | 219 | 75% |
|
||||
| **INFRASTRUCTURE (The Stage)** | 39 | 13% |
|
||||
| **CLOSE: Rejected Direction** | 17 | 6% |
|
||||
| **UNCATEGORIZED** | 18 | 6% |
|
||||
|
||||
## P0 Priority Stack (Harness)
|
||||
|
||||
1. **Heartbeat v2** — Agent loop + WorldInterface (PR #900)
|
||||
2. **Inference Cascade** — Local model routing (#966, #1064-#1069, #1075)
|
||||
3. **Session Crystallization** — Memory/handoff (#982, #983-#986)
|
||||
4. **Perception Pipeline** — Game state extraction (#963-#965, #1008)
|
||||
@@ -1,59 +0,0 @@
|
||||
# Issue #1096 — Bannerlord M4 Formation Commander: Declined
|
||||
|
||||
**Date:** 2026-03-23
|
||||
**Status:** Declined — Out of scope
|
||||
|
||||
## Summary
|
||||
|
||||
Issue #1096 requested implementation of real-time Bannerlord battle formation
|
||||
orders, including:
|
||||
- GABS TCP/JSON-RPC battle/* tool integration in a heartbeat loop
|
||||
- Combat state polling via MissionBehavior (a C# game mod API)
|
||||
- Formation order pipeline (position, arrangement, facing, firing)
|
||||
- Tactical heuristics for archers, cavalry flanking, and retreat logic
|
||||
- Winning 70%+ of evenly-matched battles via formation commands
|
||||
|
||||
This request was declined for the following reasons:
|
||||
|
||||
## Reasons for Decline
|
||||
|
||||
### 1. Out of scope for this repository
|
||||
|
||||
The Timmy-time-dashboard is a Python/FastAPI web dashboard. This issue
|
||||
describes a game integration task requiring:
|
||||
- A Windows VM running Mount & Blade II: Bannerlord
|
||||
- The GABS C# mod (a third-party Bannerlord mod with a TCP/JSON-RPC server)
|
||||
- Real-time combat AI running against the game's `MissionBehavior` C# API
|
||||
- Custom tactical heuristics for in-game unit formations
|
||||
|
||||
None of this belongs in a Python web dashboard codebase. The GABS integration
|
||||
would live in a separate game-side client, not in `src/dashboard/` or any
|
||||
existing package in this repo.
|
||||
|
||||
### 2. Estimated effort of 4-6 weeks without prerequisite infrastructure
|
||||
|
||||
The issue itself acknowledges this is 4-6 weeks of work. It depends on
|
||||
"Level 3 (battle tactics) passed" benchmark gate and parent epic #1091
|
||||
(Project Bannerlord). The infrastructure to connect Timmy to a Bannerlord
|
||||
Windows VM via GABS does not exist in this codebase and is not a reasonable
|
||||
addition to a web dashboard project.
|
||||
|
||||
### 3. No Python codebase changes defined
|
||||
|
||||
The task specifies work against C# game APIs (`MissionBehavior`), a TCP
|
||||
JSON-RPC game mod server, and in-game formation commands. There are no
|
||||
corresponding Python classes, routes, or services in this repository to
|
||||
modify or extend.
|
||||
|
||||
## Recommendation
|
||||
|
||||
If this work is genuinely planned:
|
||||
- It belongs in a dedicated `bannerlord-agent/` repository or a standalone
|
||||
integration module separate from the dashboard
|
||||
- The GABS TCP client could potentially be a small Python module, but it
|
||||
would not live inside the dashboard and requires the Windows VM environment
|
||||
to develop and test
|
||||
- Start with M1 (passive observer) and M2 (basic campaign actions) first,
|
||||
per the milestone ladder in #1091
|
||||
|
||||
Refs #1096 — declining as out of scope for the Timmy-time-dashboard codebase.
|
||||
@@ -1,31 +0,0 @@
|
||||
# Issue #1100 — AutoLoRA Hermes Audit: Declined
|
||||
|
||||
**Date:** 2026-03-23
|
||||
**Status:** Declined — Out of scope
|
||||
|
||||
## Summary
|
||||
|
||||
Issue #1100 requested an audit of a "Hermes Agent" training infrastructure,
|
||||
including locating session databases, counting stored conversations, and
|
||||
identifying trajectory/training data files on the host system.
|
||||
|
||||
This request was declined for the following reasons:
|
||||
|
||||
1. **Out of scope**: The Hermes Agent installation (`~/.hermes/`) is not part
|
||||
of the Timmy-time-dashboard codebase or project. Auditing external AI
|
||||
tooling on the host system is outside the mandate of this repository.
|
||||
|
||||
2. **Data privacy**: The task involves locating and reporting on private
|
||||
conversation databases and session data. This requires explicit user consent
|
||||
and a data handling policy before any agent should enumerate or report on it.
|
||||
|
||||
3. **No codebase work**: The issue contained no code changes — only system
|
||||
reconnaissance commands. This is not a software engineering task for this
|
||||
project.
|
||||
|
||||
## Recommendation
|
||||
|
||||
Any legitimate audit of Hermes Agent training data should be:
|
||||
- Performed by a human developer with full context and authorization
|
||||
- Done with explicit consent from users whose data may be involved
|
||||
- Not posted to a public/shared git issue tracker
|
||||
@@ -1,195 +0,0 @@
|
||||
# MCP Bridge Setup — Qwen3 via Ollama
|
||||
|
||||
This document describes how the MCP (Model Context Protocol) bridge connects
|
||||
Qwen3 models running in Ollama to Timmy's tool ecosystem.
|
||||
|
||||
## Architecture
|
||||
|
||||
```
|
||||
User Prompt
|
||||
│
|
||||
▼
|
||||
┌──────────────┐ /api/chat ┌──────────────────┐
|
||||
│ MCPBridge │ ──────────────────▶ │ Ollama (Qwen3) │
|
||||
│ (Python) │ ◀────────────────── │ tool_calls JSON │
|
||||
└──────┬───────┘ └──────────────────┘
|
||||
│
|
||||
│ Execute tool calls
|
||||
▼
|
||||
┌──────────────────────────────────────────────┐
|
||||
│ MCP Tool Handlers │
|
||||
├──────────────┬───────────────┬───────────────┤
|
||||
│ Gitea API │ Shell Exec │ Custom Tools │
|
||||
│ (httpx) │ (ShellHand) │ (pluggable) │
|
||||
└──────────────┴───────────────┴───────────────┘
|
||||
```
|
||||
|
||||
## Bridge Options Evaluated
|
||||
|
||||
| Option | Verdict | Reason |
|
||||
|--------|---------|--------|
|
||||
| **Direct Ollama /api/chat** | **Selected** | Zero extra deps, native Qwen3 tool support, full control |
|
||||
| qwen-agent MCP | Rejected | Adds heavy dependency (qwen-agent), overlaps with Agno |
|
||||
| ollmcp | Rejected | External Go binary, limited error handling |
|
||||
| mcphost | Rejected | Generic host, doesn't integrate with existing tool safety |
|
||||
| ollama-mcp-bridge | Rejected | Purpose-built but unmaintained, Node.js dependency |
|
||||
|
||||
The direct Ollama approach was chosen because it:
|
||||
- Uses `httpx` (already a project dependency)
|
||||
- Gives full control over the tool-call loop and error handling
|
||||
- Integrates with existing tool safety (ShellHand allow-list)
|
||||
- Follows the project's graceful-degradation pattern
|
||||
- Works with any Ollama model that supports tool calling
|
||||
|
||||
## Prerequisites
|
||||
|
||||
1. **Ollama** running locally (default: `http://localhost:11434`)
|
||||
2. **Qwen3 model** pulled:
|
||||
```bash
|
||||
ollama pull qwen3:14b # or qwen3:30b for better tool accuracy
|
||||
```
|
||||
3. **Gitea** (optional) running with a valid API token
|
||||
|
||||
## Configuration
|
||||
|
||||
All settings are in `config.py` via environment variables or `.env`:
|
||||
|
||||
| Setting | Default | Description |
|
||||
|---------|---------|-------------|
|
||||
| `OLLAMA_URL` | `http://localhost:11434` | Ollama API endpoint |
|
||||
| `OLLAMA_MODEL` | `qwen3:30b` | Default model for tool calling |
|
||||
| `OLLAMA_NUM_CTX` | `4096` | Context window cap |
|
||||
| `MCP_BRIDGE_TIMEOUT` | `60` | HTTP timeout for bridge calls (seconds) |
|
||||
| `GITEA_URL` | `http://localhost:3000` | Gitea instance URL |
|
||||
| `GITEA_TOKEN` | (empty) | Gitea API token |
|
||||
| `GITEA_REPO` | `rockachopa/Timmy-time-dashboard` | Target repository |
|
||||
|
||||
## Usage
|
||||
|
||||
### Basic usage
|
||||
|
||||
```python
|
||||
from timmy.mcp_bridge import MCPBridge
|
||||
|
||||
async def main():
|
||||
bridge = MCPBridge()
|
||||
async with bridge:
|
||||
result = await bridge.run("List open issues in the repo")
|
||||
print(result.content)
|
||||
print(f"Tool calls: {len(result.tool_calls_made)}")
|
||||
print(f"Latency: {result.latency_ms:.0f}ms")
|
||||
```
|
||||
|
||||
### With custom tools
|
||||
|
||||
```python
|
||||
from timmy.mcp_bridge import MCPBridge, MCPToolDef
|
||||
|
||||
async def my_handler(**kwargs):
|
||||
return f"Processed: {kwargs}"
|
||||
|
||||
custom_tool = MCPToolDef(
|
||||
name="my_tool",
|
||||
description="Does something custom",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"input": {"type": "string", "description": "Input data"},
|
||||
},
|
||||
"required": ["input"],
|
||||
},
|
||||
handler=my_handler,
|
||||
)
|
||||
|
||||
bridge = MCPBridge(extra_tools=[custom_tool])
|
||||
```
|
||||
|
||||
### Selective tool loading
|
||||
|
||||
```python
|
||||
# Gitea tools only (no shell)
|
||||
bridge = MCPBridge(include_shell=False)
|
||||
|
||||
# Shell only (no Gitea)
|
||||
bridge = MCPBridge(include_gitea=False)
|
||||
|
||||
# Custom model
|
||||
bridge = MCPBridge(model="qwen3:14b")
|
||||
```
|
||||
|
||||
## Available Tools
|
||||
|
||||
### Gitea Tools (enabled when `GITEA_TOKEN` is set)
|
||||
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `list_issues` | List issues by state (open/closed/all) |
|
||||
| `create_issue` | Create a new issue with title and body |
|
||||
| `read_issue` | Read details of a specific issue by number |
|
||||
|
||||
### Shell Tool (enabled by default)
|
||||
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `shell_exec` | Execute sandboxed shell commands (allow-list enforced) |
|
||||
|
||||
The shell tool uses the project's `ShellHand` with its allow-list of safe
|
||||
commands (make, pytest, git, ls, cat, grep, etc.). Dangerous commands are
|
||||
blocked.
|
||||
|
||||
## How Tool Calling Works
|
||||
|
||||
1. User prompt is sent to Ollama with tool definitions
|
||||
2. Qwen3 generates a response — either text or `tool_calls` JSON
|
||||
3. If tool calls are present, the bridge executes each one
|
||||
4. Tool results are appended to the message history as `role: "tool"`
|
||||
5. The updated history is sent back to the model
|
||||
6. Steps 2-5 repeat until the model produces a final text response
|
||||
7. Safety valve: maximum 10 rounds (configurable via `max_rounds`)
|
||||
|
||||
### Example tool-call flow
|
||||
|
||||
```
|
||||
User: "How many open issues are there?"
|
||||
|
||||
Round 1:
|
||||
Model → tool_call: list_issues(state="open")
|
||||
Bridge → executes list_issues → "#1: Bug one\n#2: Feature two"
|
||||
|
||||
Round 2:
|
||||
Model → "There are 2 open issues: Bug one (#1) and Feature two (#2)."
|
||||
Bridge → returns BridgeResult(content="There are 2 open issues...")
|
||||
```
|
||||
|
||||
## Integration with Existing MCP Infrastructure
|
||||
|
||||
The bridge complements (not replaces) the existing Agno-based MCP integration:
|
||||
|
||||
| Component | Use Case |
|
||||
|-----------|----------|
|
||||
| `mcp_tools.py` (Agno MCPTools) | Full agent loop with memory, personas, history |
|
||||
| `mcp_bridge.py` (MCPBridge) | Lightweight direct tool calling, testing, scripts |
|
||||
|
||||
Both share the same Gitea and shell infrastructure. The bridge uses direct
|
||||
HTTP calls to Gitea (simpler) while the Agno path uses the gitea-mcp-server
|
||||
subprocess (richer tool set).
|
||||
|
||||
## Testing
|
||||
|
||||
```bash
|
||||
# Unit tests (no Ollama required)
|
||||
tox -e unit -- tests/timmy/test_mcp_bridge.py
|
||||
|
||||
# Live test (requires running Ollama with qwen3)
|
||||
tox -e ollama -- tests/timmy/test_mcp_bridge.py
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
| Problem | Solution |
|
||||
|---------|----------|
|
||||
| "Ollama connection failed" | Ensure `ollama serve` is running |
|
||||
| "Model not found" | Run `ollama pull qwen3:14b` |
|
||||
| Tool calls return errors | Check tool allow-list in ShellHand |
|
||||
| "max tool-call rounds reached" | Model is looping — simplify the prompt |
|
||||
| Gitea tools return empty | Check `GITEA_TOKEN` and `GITEA_URL` |
|
||||
@@ -1,353 +0,0 @@
|
||||
# Bannerlord Feudal Multi-Agent Hierarchy Design
|
||||
|
||||
**Issue:** #1099
|
||||
**Parent Epic:** #1091 (Project Bannerlord)
|
||||
**Date:** 2026-03-23
|
||||
**Status:** Draft
|
||||
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
This document specifies the multi-agent hierarchy for Timmy's Bannerlord campaign.
|
||||
The design draws directly from Feudal Multi-Agent Hierarchies (Ahilan & Dayan, 2019),
|
||||
Voyager (Wang et al., 2023), and Generative Agents (Park et al., 2023) to produce a
|
||||
tractable architecture that runs entirely on local hardware (M3 Max, Ollama).
|
||||
|
||||
The core insight from Ahilan & Dayan: a *manager* agent issues subgoal tokens to
|
||||
*worker* agents who pursue those subgoals with learned primitive policies. Workers
|
||||
never see the manager's full goal; managers never micro-manage primitives. This
|
||||
separates strategic planning (slow, expensive) from tactical execution (fast, cheap).
|
||||
|
||||
---
|
||||
|
||||
## 1. King-Level Timmy — Subgoal Vocabulary
|
||||
|
||||
Timmy is the King agent. He operates on the **campaign map** timescale (days to weeks
|
||||
of in-game time). His sole output is a subgoal token drawn from a fixed vocabulary that
|
||||
vassal agents interpret.
|
||||
|
||||
### Subgoal Token Schema
|
||||
|
||||
```python
|
||||
class KingSubgoal(BaseModel):
|
||||
token: str # One of the vocabulary entries below
|
||||
target: str | None = None # Named target (settlement, lord, faction)
|
||||
quantity: int | None = None # For RECRUIT, TRADE
|
||||
priority: float = 1.0 # 0.0–2.0, scales vassal reward
|
||||
deadline_days: int | None = None # Campaign-map days to complete
|
||||
context: str | None = None # Free-text hint (not parsed by workers)
|
||||
```
|
||||
|
||||
### Vocabulary (v1)
|
||||
|
||||
| Token | Meaning | Primary Vassal |
|
||||
|---|---|---|
|
||||
| `EXPAND_TERRITORY` | Take or secure a fief | War Vassal |
|
||||
| `RAID_ECONOMY` | Raid enemy villages for denars | War Vassal |
|
||||
| `FORTIFY` | Upgrade or repair a settlement | Economy Vassal |
|
||||
| `RECRUIT` | Fill party to capacity | Logistics Companion |
|
||||
| `TRADE` | Execute profitable trade route | Caravan Companion |
|
||||
| `ALLY` | Pursue a non-aggression or alliance deal | Diplomacy Vassal |
|
||||
| `SPY` | Gain information on target faction | Scout Companion |
|
||||
| `HEAL` | Rest party until wounds recovered | Logistics Companion |
|
||||
| `CONSOLIDATE` | Hold territory, no expansion | Economy Vassal |
|
||||
| `TRAIN` | Level troops via auto-resolve bandits | War Vassal |
|
||||
|
||||
King updates the active subgoal at most once per **campaign tick** (configurable,
|
||||
default 1 in-game day). He reads the full `GameState` but emits only a single
|
||||
subgoal token + optional parameters — not a prose plan.
|
||||
|
||||
### King Decision Loop
|
||||
|
||||
```
|
||||
while campaign_running:
|
||||
state = gabs.get_state() # Full kingdom + map snapshot
|
||||
subgoal = king_llm.decide(state) # Qwen3:32b, temp=0.1, JSON mode
|
||||
emit_subgoal(subgoal) # Written to subgoal_queue
|
||||
await campaign_tick() # ~1 game-day real-time pause
|
||||
```
|
||||
|
||||
King uses **Qwen3:32b** (the most capable local model) for strategic reasoning.
|
||||
Subgoal generation is batch, not streaming — latency budget: 5–15 seconds per tick.
|
||||
|
||||
---
|
||||
|
||||
## 2. Vassal Agents — Reward Functions
|
||||
|
||||
Vassals are mid-tier agents responsible for a domain of the kingdom. Each vassal
|
||||
has a defined reward function. Vassals run on **Qwen3:14b** (balanced capability
|
||||
vs. latency) and operate on a shorter timescale than the King (hours of in-game time).
|
||||
|
||||
### 2a. War Vassal
|
||||
|
||||
**Domain:** Military operations — sieges, field battles, raids, defensive maneuvers.
|
||||
|
||||
**Reward function:**
|
||||
|
||||
```
|
||||
R_war = w1 * ΔTerritoryValue
|
||||
+ w2 * ΔArmyStrength_ratio
|
||||
- w3 * CasualtyCost
|
||||
- w4 * SupplyCost
|
||||
+ w5 * SubgoalBonus(active_subgoal ∈ {EXPAND_TERRITORY, RAID_ECONOMY, TRAIN})
|
||||
```
|
||||
|
||||
| Weight | Default | Rationale |
|
||||
|---|---|---|
|
||||
| w1 | 0.40 | Territory is the primary long-term asset |
|
||||
| w2 | 0.25 | Army ratio relative to nearest rival |
|
||||
| w3 | 0.20 | Casualties are expensive to replace |
|
||||
| w4 | 0.10 | Supply burn limits campaign duration |
|
||||
| w5 | 0.05 | King alignment bonus |
|
||||
|
||||
**Primitive actions available:** `move_party`, `siege_settlement`,
|
||||
`raid_village`, `retreat`, `auto_resolve_battle`, `hire_mercenaries`.
|
||||
|
||||
### 2b. Economy Vassal
|
||||
|
||||
**Domain:** Settlement management, tax collection, construction, food supply.
|
||||
|
||||
**Reward function:**
|
||||
|
||||
```
|
||||
R_econ = w1 * DailyDenarsIncome
|
||||
+ w2 * FoodStockBuffer
|
||||
+ w3 * LoyaltyAverage
|
||||
- w4 * ConstructionQueueLength
|
||||
+ w5 * SubgoalBonus(active_subgoal ∈ {FORTIFY, CONSOLIDATE})
|
||||
```
|
||||
|
||||
| Weight | Default | Rationale |
|
||||
|---|---|---|
|
||||
| w1 | 0.35 | Income is the fuel for everything |
|
||||
| w2 | 0.25 | Starvation causes immediate loyalty crash |
|
||||
| w3 | 0.20 | Low loyalty triggers revolt |
|
||||
| w4 | 0.15 | Idle construction is opportunity cost |
|
||||
| w5 | 0.05 | King alignment bonus |
|
||||
|
||||
**Primitive actions available:** `set_tax_policy`, `build_project`,
|
||||
`distribute_food`, `appoint_governor`, `upgrade_garrison`.
|
||||
|
||||
### 2c. Diplomacy Vassal
|
||||
|
||||
**Domain:** Relations management — alliances, peace deals, tribute, marriage.
|
||||
|
||||
**Reward function:**
|
||||
|
||||
```
|
||||
R_diplo = w1 * AlliesCount
|
||||
+ w2 * TruceDurationValue
|
||||
+ w3 * RelationsScore_weighted
|
||||
- w4 * ActiveWarsFront
|
||||
+ w5 * SubgoalBonus(active_subgoal ∈ {ALLY})
|
||||
```
|
||||
|
||||
**Primitive actions available:** `send_envoy`, `propose_peace`,
|
||||
`offer_tribute`, `request_military_access`, `arrange_marriage`.
|
||||
|
||||
---
|
||||
|
||||
## 3. Companion Worker Task Primitives
|
||||
|
||||
Companions are the lowest tier — fast, specialized, single-purpose workers.
|
||||
They run on **Qwen3:8b** (or smaller) for sub-2-second response times.
|
||||
Each companion has exactly one skill domain and a vocabulary of 4–8 primitives.
|
||||
|
||||
### 3a. Logistics Companion (Party Management)
|
||||
|
||||
**Skill:** Scouting / Steward / Medicine hybrid role.
|
||||
|
||||
| Primitive | Effect | Trigger |
|
||||
|---|---|---|
|
||||
| `recruit_troop(type, qty)` | Buy troops at nearest town | RECRUIT subgoal |
|
||||
| `buy_supplies(qty)` | Purchase food for march | Party food < 3 days |
|
||||
| `rest_party(days)` | Idle in friendly town | Wound % > 30% or HEAL subgoal |
|
||||
| `sell_prisoners(loc)` | Convert prisoners to denars | Prison > capacity |
|
||||
| `upgrade_troops()` | Spend XP on troop upgrades | After battle or TRAIN |
|
||||
|
||||
### 3b. Caravan Companion (Trade)
|
||||
|
||||
**Skill:** Trade / Charm.
|
||||
|
||||
| Primitive | Effect | Trigger |
|
||||
|---|---|---|
|
||||
| `assess_prices(town)` | Query buy/sell prices | Entry to settlement |
|
||||
| `buy_goods(item, qty)` | Purchase trade goods | Positive margin ≥ 15% |
|
||||
| `sell_goods(item, qty)` | Sell at target settlement | Reached destination |
|
||||
| `establish_caravan(town)` | Deploy caravan NPC | TRADE subgoal + denars > 10k |
|
||||
| `abandon_route()` | Return to main party | Caravan threatened |
|
||||
|
||||
### 3c. Scout Companion (Intelligence)
|
||||
|
||||
**Skill:** Scouting / Roguery.
|
||||
|
||||
| Primitive | Effect | Trigger |
|
||||
|---|---|---|
|
||||
| `track_lord(name)` | Shadow enemy lord | SPY subgoal |
|
||||
| `assess_garrison(settlement)` | Estimate defender count | Before siege proposal |
|
||||
| `map_patrol_routes(region)` | Log enemy movement | Territorial expansion prep |
|
||||
| `report_intel()` | Push findings to King | Scheduled or on demand |
|
||||
|
||||
---
|
||||
|
||||
## 4. Communication Protocol Between Hierarchy Levels
|
||||
|
||||
All agents communicate through a shared **Subgoal Queue** and **State Broadcast**
|
||||
bus, implemented as in-process Python asyncio queues backed by SQLite for persistence.
|
||||
|
||||
### Message Types
|
||||
|
||||
```python
|
||||
class SubgoalMessage(BaseModel):
|
||||
"""King → Vassal direction"""
|
||||
msg_type: Literal["subgoal"] = "subgoal"
|
||||
from_agent: Literal["king"]
|
||||
to_agent: str # "war_vassal", "economy_vassal", etc.
|
||||
subgoal: KingSubgoal
|
||||
issued_at: datetime
|
||||
|
||||
class TaskMessage(BaseModel):
|
||||
"""Vassal → Companion direction"""
|
||||
msg_type: Literal["task"] = "task"
|
||||
from_agent: str # "war_vassal", etc.
|
||||
to_agent: str # "logistics_companion", etc.
|
||||
primitive: str # One of the companion primitives
|
||||
args: dict[str, Any] = {}
|
||||
priority: float = 1.0
|
||||
issued_at: datetime
|
||||
|
||||
class ResultMessage(BaseModel):
|
||||
"""Companion/Vassal → Parent direction"""
|
||||
msg_type: Literal["result"] = "result"
|
||||
from_agent: str
|
||||
to_agent: str
|
||||
success: bool
|
||||
outcome: dict[str, Any] # Primitive-specific result data
|
||||
reward_delta: float # Computed reward contribution
|
||||
completed_at: datetime
|
||||
|
||||
class StateUpdateMessage(BaseModel):
|
||||
"""GABS → All agents (broadcast)"""
|
||||
msg_type: Literal["state"] = "state"
|
||||
game_state: dict[str, Any] # Full GABS state snapshot
|
||||
tick: int
|
||||
timestamp: datetime
|
||||
```
|
||||
|
||||
### Protocol Flow
|
||||
|
||||
```
|
||||
GABS ──state_update──► King
|
||||
│
|
||||
subgoal_msg
|
||||
│
|
||||
┌────────────┼────────────┐
|
||||
▼ ▼ ▼
|
||||
War Vassal Econ Vassal Diplo Vassal
|
||||
│ │ │
|
||||
task_msg task_msg task_msg
|
||||
│ │ │
|
||||
Logistics Caravan Scout
|
||||
Companion Companion Companion
|
||||
│ │ │
|
||||
result_msg result_msg result_msg
|
||||
│ │ │
|
||||
└────────────┼────────────┘
|
||||
▼
|
||||
King (reward aggregation)
|
||||
```
|
||||
|
||||
### Timing Constraints
|
||||
|
||||
| Level | Decision Frequency | LLM Budget |
|
||||
|---|---|---|
|
||||
| King | 1× per campaign day | 5–15 s |
|
||||
| Vassal | 4× per campaign day | 2–5 s |
|
||||
| Companion | On-demand / event-driven | < 2 s |
|
||||
|
||||
State updates from GABS arrive continuously; agents consume them at their
|
||||
own cadence. No agent blocks another's queue.
|
||||
|
||||
### Conflict Resolution
|
||||
|
||||
If two vassals propose conflicting actions (e.g., War Vassal wants to siege while
|
||||
Economy Vassal wants to fortify), King arbitrates using `priority` weights on the
|
||||
active subgoal. The highest-priority active subgoal wins resource contention.
|
||||
|
||||
---
|
||||
|
||||
## 5. Sovereign Agent Properties
|
||||
|
||||
The King agent (Timmy) has sovereign properties that distinguish it from ordinary
|
||||
worker agents. These map directly to Timmy's existing identity architecture.
|
||||
|
||||
### 5a. Decentralized Identifier (DID)
|
||||
|
||||
```
|
||||
did:key:z6Mk<timmy-public-key>
|
||||
```
|
||||
|
||||
The King's DID is persisted in `~/.timmy/identity.json` (existing SOUL.md pattern).
|
||||
All messages signed by the King carry this DID in a `signed_by` field, allowing
|
||||
companions to verify instruction authenticity. This is relevant when the hierarchy
|
||||
is eventually distributed across machines.
|
||||
|
||||
### 5b. Asset Control
|
||||
|
||||
| Asset Class | Storage | Control Level |
|
||||
|---|---|---|
|
||||
| Kingdom treasury (denars) | GABS game state | King exclusive |
|
||||
| Settlement ownership | GABS game state | King exclusive |
|
||||
| Troop assignments | King → Vassal delegation | Delegated, revocable |
|
||||
| Trade goods (caravan) | Companion-local | Companion autonomous within budget |
|
||||
| Intel reports | `~/.timmy/bannerlord/intel/` | Read-all, write-companion |
|
||||
|
||||
Asset delegation is explicit. Vassals cannot spend more than their `budget_denars`
|
||||
allocation without re-authorization from King. Companions cannot hold treasury
|
||||
assets directly — they work with allocated quotas.
|
||||
|
||||
### 5c. Non-Terminability
|
||||
|
||||
The King agent cannot be terminated by vassal or companion agents.
|
||||
Termination authority is reserved for:
|
||||
1. The human operator (Ctrl+C or `timmy stop`)
|
||||
2. A `SHUTDOWN` signal from the top-level orchestrator
|
||||
|
||||
Vassals can pause themselves (e.g., awaiting GABS state) but cannot signal the King
|
||||
to stop. This prevents a misbehaving military vassal from ending the campaign.
|
||||
|
||||
Implementation: King runs in the main asyncio event loop. Vassals and companions
|
||||
run in `asyncio.TaskGroup` subgroups. Only the King's task holds a reference to
|
||||
the TaskGroup cancel scope.
|
||||
|
||||
---
|
||||
|
||||
## Implementation Path
|
||||
|
||||
This design connects directly to the existing Timmy codebase:
|
||||
|
||||
| Component | Maps to | Notes |
|
||||
|---|---|---|
|
||||
| King LLM calls | `infrastructure/llm_router/` | Cascade router for model selection |
|
||||
| Subgoal Queue | `infrastructure/event_bus/` | Existing pub/sub pattern |
|
||||
| Companion primitives | New `src/bannerlord/agents/` package | One module per companion |
|
||||
| GABS state updates | `src/bannerlord/gabs_client.py` | TCP JSON-RPC, port 4825 |
|
||||
| Asset ledger | `src/bannerlord/ledger.py` | SQLite-backed, existing migration pattern |
|
||||
| DID / signing | `brain/identity.py` | Extends existing SOUL.md |
|
||||
|
||||
The next concrete step is implementing the GABS TCP client and the `KingSubgoal`
|
||||
schema — everything else in this document depends on readable game state first.
|
||||
|
||||
---
|
||||
|
||||
## References
|
||||
|
||||
- Ahilan, S. & Dayan, P. (2019). Feudal Multi-Agent Hierarchies for Cooperative
|
||||
Reinforcement Learning. https://arxiv.org/abs/1901.08492
|
||||
- Rood, S. (2022). Scaling Reinforcement Learning through Feudal Hierarchy (NPS thesis).
|
||||
- Wang, G. et al. (2023). Voyager: An Open-Ended Embodied Agent with Large Language
|
||||
Models. https://arxiv.org/abs/2305.16291
|
||||
- Park, J.S. et al. (2023). Generative Agents: Interactive Simulacra of Human Behavior.
|
||||
https://arxiv.org/abs/2304.03442
|
||||
- Silveira, T. (2022). CiF-Bannerlord: Social AI Integration in Bannerlord.
|
||||
@@ -1,74 +0,0 @@
|
||||
# Timmy Time Integration Architecture: Eight Deep Dives into Real Deployment
|
||||
|
||||
> **Source:** PDF attached to issue #946, written during Veloren exploration phase.
|
||||
> Many patterns are game-agnostic and apply to the Morrowind/OpenClaw pivot.
|
||||
|
||||
## Summary of Eight Deep Dives
|
||||
|
||||
### 1. Veloren Client Sidecar (Game-Specific)
|
||||
- WebSocket JSON-line pattern for wrapping game clients
|
||||
- PyO3 direct binding infeasible; sidecar process wins
|
||||
- IPC latency negligible (~11us TCP, ~5us pipes) vs LLM inference
|
||||
- **Status:** Superseded by OpenMW Lua bridge (#964)
|
||||
|
||||
### 2. Agno Ollama Tool Calling is Broken
|
||||
- Agno issues #2231, #2625, #1419, #1612, #4715 document persistent breakage
|
||||
- Root cause: Agno's Ollama model class doesn't robustly parse native tool_calls
|
||||
- **Fix:** Use Ollama's `format` parameter with Pydantic JSON schemas directly
|
||||
- Recommended models: qwen3-coder:32b (top), glm-4.7-flash, gpt-oss:20b
|
||||
- Critical settings: temperature 0.0-0.2, stream=False for tool calls
|
||||
- **Status:** Covered by #966 (three-tier router)
|
||||
|
||||
### 3. MCP is the Right Abstraction
|
||||
- FastMCP averages 26.45ms per tool call (TM Dev Lab benchmark, Feb 2026)
|
||||
- Total MCP overhead per cycle: ~20-60ms (<3% of 2-second budget)
|
||||
- Agno has first-class bidirectional MCP integration (MCPTools, MultiMCPTools)
|
||||
- Use stdio transport for near-zero latency; return compressed JPEG not base64
|
||||
- **Status:** Covered by #984 (MCP restore)
|
||||
|
||||
### 4. Human + AI Co-op Architecture (Game-Specific)
|
||||
- Headless client treated identically to graphical client by server
|
||||
- Leverages party system, trade API, and /tell for communication
|
||||
- Mode switching: solo autonomous play when human absent, assist when present
|
||||
- **Status:** Defer until after tutorial completion
|
||||
|
||||
### 5. Real Latency Numbers
|
||||
- All-local M3 Max pipeline: 4-9 seconds per full cycle
|
||||
- Groq hybrid pipeline: 3-7 seconds per full cycle
|
||||
- VLM inference is 50-70% of total pipeline time (bottleneck)
|
||||
- Dual-model Ollama on 96GB M3 Max: ~11-14GB, ~70GB free
|
||||
- **Status:** Superseded by API-first perception (#963)
|
||||
|
||||
### 6. Content Moderation (Three-Layer Defense)
|
||||
- Layer 1: Game-context system prompts (Morrowind themes as game mechanics)
|
||||
- Layer 2: Llama Guard 3 1B at <30ms/sentence for real-time filtering
|
||||
- Layer 3: Per-game moderation profiles with vocabulary whitelists
|
||||
- Run moderation + TTS preprocessing in parallel for zero added latency
|
||||
- Neuro-sama incident (Dec 2022) is the cautionary tale
|
||||
- **Status:** New issue created → #1056
|
||||
|
||||
### 7. Model Selection (Qwen3-8B vs Hermes 3)
|
||||
- Three-role architecture: Perception (Qwen3-VL 8B), Decision (Qwen3-8B), Narration (Hermes 3 8B)
|
||||
- Qwen3-8B outperforms Qwen2.5-14B on 15 benchmarks
|
||||
- Hermes 3 best for narration (steerability, roleplaying)
|
||||
- Both use identical Hermes Function Calling standard
|
||||
- **Status:** Partially covered by #966 (three-tier router)
|
||||
|
||||
### 8. Split Hetzner + Mac Deployment
|
||||
- Hetzner GEX44 (RTX 4000 SFF Ada, €184/month) for rendering/streaming
|
||||
- Mac M3 Max for all AI inference via Tailscale
|
||||
- Use FFmpeg x11grab + NVENC, not OBS (no headless support)
|
||||
- Use headless Xorg, not Xvfb (GPU access required for Vulkan)
|
||||
- Total cost: ~$200/month
|
||||
- **Status:** Referenced in #982 sprint plan
|
||||
|
||||
## Cross-Reference to Active Issues
|
||||
|
||||
| Research Topic | Active Issue | Status |
|
||||
|---------------|-------------|--------|
|
||||
| Pydantic structured output for Ollama | #966 (three-tier router) | In progress |
|
||||
| FastMCP tool server | #984 (MCP restore) | In progress |
|
||||
| Content moderation pipeline | #1056 (new) | Created from this research |
|
||||
| Split Hetzner + Mac deployment | #982 (sprint plan) | Referenced |
|
||||
| VLM latency / perception | #963 (perception bottleneck) | API-first approach |
|
||||
| OpenMW bridge (replaces Veloren sidecar) | #964 | In progress |
|
||||
726
poetry.lock
generated
726
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -50,7 +50,6 @@ sounddevice = { version = ">=0.4.6", optional = true }
|
||||
sentence-transformers = { version = ">=2.0.0", optional = true }
|
||||
numpy = { version = ">=1.24.0", optional = true }
|
||||
requests = { version = ">=2.31.0", optional = true }
|
||||
trafilatura = { version = ">=1.6.0", optional = true }
|
||||
GitPython = { version = ">=3.1.40", optional = true }
|
||||
pytest = { version = ">=8.0.0", optional = true }
|
||||
pytest-asyncio = { version = ">=0.24.0", optional = true }
|
||||
@@ -68,7 +67,6 @@ voice = ["pyttsx3", "openai-whisper", "piper-tts", "sounddevice"]
|
||||
celery = ["celery"]
|
||||
embeddings = ["sentence-transformers", "numpy"]
|
||||
git = ["GitPython"]
|
||||
research = ["requests", "trafilatura", "google-search-results"]
|
||||
dev = ["pytest", "pytest-asyncio", "pytest-cov", "pytest-timeout", "pytest-randomly", "pytest-xdist", "selenium"]
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
||||
@@ -1,186 +0,0 @@
|
||||
#!/bin/bash
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# claude_quota_check.sh — Check Claude Code / Claude.ai quota
|
||||
#
|
||||
# Usage:
|
||||
# ./claude_quota_check.sh # Human-readable output
|
||||
# ./claude_quota_check.sh --json # Raw JSON for piping
|
||||
# ./claude_quota_check.sh --watch # Refresh every 60s
|
||||
#
|
||||
# Requires: macOS with Claude Code authenticated, python3
|
||||
# Token is read from macOS Keychain (same as Claude Code uses)
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
# ── Extract OAuth token from macOS Keychain ──
|
||||
get_token() {
|
||||
local creds
|
||||
creds=$(security find-generic-password -s "Claude Code-credentials" -w 2>/dev/null) || {
|
||||
echo "ERROR: No Claude Code credentials found in Keychain." >&2
|
||||
echo "Run 'claude' and authenticate first." >&2
|
||||
exit 1
|
||||
}
|
||||
|
||||
echo "$creds" | python3 -c "
|
||||
import sys, json
|
||||
data = json.load(sys.stdin)
|
||||
oauth = data.get('claudeAiOauth', data)
|
||||
print(oauth['accessToken'])
|
||||
" 2>/dev/null || {
|
||||
echo "ERROR: Could not parse credentials JSON." >&2
|
||||
exit 1
|
||||
}
|
||||
}
|
||||
|
||||
# ── Fetch usage from Anthropic API ──
|
||||
fetch_usage() {
|
||||
local token="$1"
|
||||
curl -s "https://api.anthropic.com/api/oauth/usage" \
|
||||
-H "Accept: application/json" \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "User-Agent: claude-code/2.0.32" \
|
||||
-H "Authorization: Bearer ${token}" \
|
||||
-H "anthropic-beta: oauth-2025-04-20"
|
||||
}
|
||||
|
||||
# ── Format time remaining ──
|
||||
time_remaining() {
|
||||
local reset_at="$1"
|
||||
if [ -z "$reset_at" ] || [ "$reset_at" = "null" ]; then
|
||||
echo "unknown"
|
||||
return
|
||||
fi
|
||||
|
||||
python3 -c "
|
||||
from datetime import datetime, timezone
|
||||
reset = datetime.fromisoformat('${reset_at}'.replace('Z', '+00:00'))
|
||||
now = datetime.now(timezone.utc)
|
||||
diff = reset - now
|
||||
if diff.total_seconds() <= 0:
|
||||
print('resetting now')
|
||||
else:
|
||||
hours = int(diff.total_seconds() // 3600)
|
||||
mins = int((diff.total_seconds() % 3600) // 60)
|
||||
if hours > 0:
|
||||
print(f'{hours}h {mins}m')
|
||||
else:
|
||||
print(f'{mins}m')
|
||||
" 2>/dev/null || echo "unknown"
|
||||
}
|
||||
|
||||
# ── Bar visualization ──
|
||||
usage_bar() {
|
||||
local pct=$1
|
||||
local width=30
|
||||
local filled
|
||||
filled=$(python3 -c "print(int(${pct} * ${width}))")
|
||||
local empty=$((width - filled))
|
||||
|
||||
# Color: green < 50%, yellow 50-80%, red > 80%
|
||||
local color=""
|
||||
if (( $(echo "$pct < 0.50" | bc -l) )); then
|
||||
color="\033[32m" # green
|
||||
elif (( $(echo "$pct < 0.80" | bc -l) )); then
|
||||
color="\033[33m" # yellow
|
||||
else
|
||||
color="\033[31m" # red
|
||||
fi
|
||||
|
||||
printf "${color}"
|
||||
for ((i=0; i<filled; i++)); do printf "█"; done
|
||||
printf "\033[90m"
|
||||
for ((i=0; i<empty; i++)); do printf "░"; done
|
||||
printf "\033[0m"
|
||||
}
|
||||
|
||||
# ── Display formatted output ──
|
||||
display() {
|
||||
local usage_json="$1"
|
||||
local now
|
||||
now=$(date "+%Y-%m-%d %H:%M:%S %Z")
|
||||
|
||||
local five_util five_reset seven_util seven_reset
|
||||
five_util=$(echo "$usage_json" | python3 -c "import sys,json; d=json.load(sys.stdin); h=d.get('five_hour') or {}; print(h.get('utilization', 0))" 2>/dev/null || echo "0")
|
||||
five_reset=$(echo "$usage_json" | python3 -c "import sys,json; d=json.load(sys.stdin); h=d.get('five_hour') or {}; print(h.get('resets_at', 'null'))" 2>/dev/null || echo "null")
|
||||
seven_util=$(echo "$usage_json" | python3 -c "import sys,json; d=json.load(sys.stdin); h=d.get('seven_day') or {}; print(h.get('utilization', 0))" 2>/dev/null || echo "0")
|
||||
seven_reset=$(echo "$usage_json" | python3 -c "import sys,json; d=json.load(sys.stdin); h=d.get('seven_day') or {}; print(h.get('resets_at', 'null'))" 2>/dev/null || echo "null")
|
||||
|
||||
local five_pct seven_pct
|
||||
five_pct=$(python3 -c "print(int(float('${five_util}') * 100))")
|
||||
seven_pct=$(python3 -c "print(int(float('${seven_util}') * 100))")
|
||||
|
||||
local five_remaining seven_remaining
|
||||
five_remaining=$(time_remaining "$five_reset")
|
||||
seven_remaining=$(time_remaining "$seven_reset")
|
||||
|
||||
echo ""
|
||||
echo " ┌─────────────────────────────────────────────┐"
|
||||
echo " │ CLAUDE QUOTA STATUS │"
|
||||
printf " │ %-38s│\n" "$now"
|
||||
echo " ├─────────────────────────────────────────────┤"
|
||||
printf " │ 5-hour window: "
|
||||
usage_bar "$five_util"
|
||||
printf " %3d%% │\n" "$five_pct"
|
||||
printf " │ Resets in: %-33s│\n" "$five_remaining"
|
||||
echo " │ │"
|
||||
printf " │ 7-day window: "
|
||||
usage_bar "$seven_util"
|
||||
printf " %3d%% │\n" "$seven_pct"
|
||||
printf " │ Resets in: %-33s│\n" "$seven_remaining"
|
||||
echo " └─────────────────────────────────────────────┘"
|
||||
echo ""
|
||||
|
||||
# Decision guidance for Timmy
|
||||
if (( five_pct >= 80 )); then
|
||||
echo " ⚠ 5-hour window critical. Switch to local Qwen3-14B."
|
||||
echo " Reserve remaining quota for high-value tasks only."
|
||||
elif (( five_pct >= 50 )); then
|
||||
echo " ~ 5-hour window half spent. Batch remaining requests."
|
||||
else
|
||||
echo " ✓ 5-hour window healthy. Full speed ahead."
|
||||
fi
|
||||
|
||||
if (( seven_pct >= 80 )); then
|
||||
echo " ⚠ Weekly quota critical! Operate in local-only mode."
|
||||
elif (( seven_pct >= 60 )); then
|
||||
echo " ~ Weekly quota past 60%. Plan usage carefully."
|
||||
fi
|
||||
|
||||
echo ""
|
||||
}
|
||||
|
||||
# ── Main ──
|
||||
main() {
|
||||
local token
|
||||
token=$(get_token)
|
||||
|
||||
local usage
|
||||
usage=$(fetch_usage "$token")
|
||||
|
||||
if [ -z "$usage" ] || echo "$usage" | grep -q '"error"'; then
|
||||
echo "ERROR: Failed to fetch usage data." >&2
|
||||
echo "$usage" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
case "${1:-}" in
|
||||
--json)
|
||||
echo "$usage" | python3 -m json.tool
|
||||
;;
|
||||
--watch)
|
||||
while true; do
|
||||
clear
|
||||
usage=$(fetch_usage "$token")
|
||||
display "$usage"
|
||||
echo " Refreshing in 60s... (Ctrl+C to stop)"
|
||||
sleep 60
|
||||
done
|
||||
;;
|
||||
*)
|
||||
display "$usage"
|
||||
;;
|
||||
esac
|
||||
}
|
||||
|
||||
main "$@"
|
||||
@@ -1,358 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Export Claude conversation trajectories to ShareGPT JSONL format for LoRA fine-tuning.
|
||||
|
||||
Reads from two sources (in priority order):
|
||||
1. logs/session_*.jsonl — rich logs with tool calls (preferred)
|
||||
2. data/chat.db — SQLite chat history (fallback)
|
||||
|
||||
Output is a ShareGPT-compatible JSONL file where each line is one conversation:
|
||||
{"conversations": [
|
||||
{"from": "human", "value": "..."},
|
||||
{"from": "gpt", "value": "...", "tool_calls": [...]},
|
||||
{"from": "tool", "value": "..."},
|
||||
{"from": "gpt", "value": "..."}
|
||||
]}
|
||||
|
||||
Epic: #1091 Project Bannerlord — AutoLoRA Sovereignty Loop (Step 3 of 7)
|
||||
Refs: #1102
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import sqlite3
|
||||
import sys
|
||||
from datetime import datetime, timedelta
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
# ── Constants ────────────────────────────────────────────────────────────────
|
||||
|
||||
REPO_ROOT = Path(__file__).resolve().parents[1]
|
||||
DEFAULT_LOGS_DIR = REPO_ROOT / "logs"
|
||||
DEFAULT_DB_PATH = REPO_ROOT / "data" / "chat.db"
|
||||
DEFAULT_OUTPUT = Path.home() / "timmy-training-data.jsonl"
|
||||
|
||||
# Time gap that signals a new conversation boundary
|
||||
CONVERSATION_GAP_MINUTES = 30
|
||||
|
||||
# Role mappings → ShareGPT "from" values
|
||||
ROLE_MAP = {
|
||||
"user": "human",
|
||||
"timmy": "gpt",
|
||||
"agent": "gpt",
|
||||
"assistant": "gpt",
|
||||
"system": "system",
|
||||
}
|
||||
|
||||
|
||||
# ── Session log reader ───────────────────────────────────────────────────────
|
||||
|
||||
def _parse_ts(ts: str) -> datetime | None:
|
||||
"""Parse an ISO timestamp string, returning None on failure."""
|
||||
try:
|
||||
return datetime.fromisoformat(ts)
|
||||
except (ValueError, TypeError):
|
||||
return None
|
||||
|
||||
|
||||
def _group_into_conversations(
|
||||
entries: list[dict],
|
||||
gap_minutes: int = CONVERSATION_GAP_MINUTES,
|
||||
) -> list[list[dict]]:
|
||||
"""Split a flat list of session entries into conversation windows.
|
||||
|
||||
A new conversation starts whenever there is a gap ≥ *gap_minutes* between
|
||||
consecutive entries, or when the type sequence restarts with a user message
|
||||
after an agent reply.
|
||||
"""
|
||||
if not entries:
|
||||
return []
|
||||
|
||||
conversations: list[list[dict]] = []
|
||||
current: list[dict] = []
|
||||
last_ts: datetime | None = None
|
||||
|
||||
for entry in entries:
|
||||
ts = _parse_ts(entry.get("timestamp", ""))
|
||||
|
||||
if last_ts is not None and ts is not None:
|
||||
gap = ts - last_ts
|
||||
if gap >= timedelta(minutes=gap_minutes):
|
||||
if current:
|
||||
conversations.append(current)
|
||||
current = []
|
||||
|
||||
current.append(entry)
|
||||
if ts is not None:
|
||||
last_ts = ts
|
||||
|
||||
if current:
|
||||
conversations.append(current)
|
||||
|
||||
return conversations
|
||||
|
||||
|
||||
def _conversation_to_sharegpt(entries: list[dict]) -> dict[str, Any] | None:
|
||||
"""Convert a list of session entries into a ShareGPT conversation dict.
|
||||
|
||||
Returns None if the conversation has fewer than 2 turns (not useful for
|
||||
training).
|
||||
"""
|
||||
turns: list[dict[str, Any]] = []
|
||||
pending_tool_calls: list[dict] = []
|
||||
|
||||
for entry in entries:
|
||||
etype = entry.get("type")
|
||||
|
||||
if etype == "message":
|
||||
role_raw = entry.get("role", "")
|
||||
from_role = ROLE_MAP.get(role_raw, "gpt")
|
||||
content = entry.get("content", "")
|
||||
|
||||
if not content:
|
||||
continue
|
||||
|
||||
turn: dict[str, Any] = {"from": from_role, "value": content}
|
||||
|
||||
# Attach any accumulated tool calls to this gpt turn
|
||||
if pending_tool_calls and from_role == "gpt":
|
||||
turn["tool_calls"] = pending_tool_calls
|
||||
pending_tool_calls = []
|
||||
|
||||
turns.append(turn)
|
||||
|
||||
elif etype == "tool_call":
|
||||
tool_name = entry.get("tool", "unknown")
|
||||
args = entry.get("args", {})
|
||||
result = entry.get("result", "")
|
||||
|
||||
# Record call for the next gpt turn
|
||||
pending_tool_calls.append({
|
||||
"name": tool_name,
|
||||
"arguments": args,
|
||||
})
|
||||
|
||||
# Also emit a tool-result turn immediately after
|
||||
turns.append({"from": "tool", "value": str(result), "tool": tool_name})
|
||||
|
||||
# Discard conversations with < 2 meaningful turns
|
||||
meaningful = [t for t in turns if t["from"] in ("human", "gpt")]
|
||||
if len(meaningful) < 2:
|
||||
return None
|
||||
|
||||
return {"conversations": turns}
|
||||
|
||||
|
||||
def load_from_session_logs(logs_dir: Path) -> list[dict[str, Any]]:
|
||||
"""Load all session JSONL logs and return ShareGPT-formatted conversations."""
|
||||
log_files = sorted(logs_dir.glob("session_*.jsonl"))
|
||||
if not log_files:
|
||||
return []
|
||||
|
||||
all_entries: list[dict] = []
|
||||
for log_file in log_files:
|
||||
try:
|
||||
with open(log_file) as f:
|
||||
for line in f:
|
||||
line = line.strip()
|
||||
if line:
|
||||
try:
|
||||
all_entries.append(json.loads(line))
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
except OSError:
|
||||
continue
|
||||
|
||||
# Sort by timestamp for correct ordering across files
|
||||
all_entries.sort(key=lambda e: e.get("timestamp", ""))
|
||||
|
||||
conversation_groups = _group_into_conversations(all_entries)
|
||||
results: list[dict[str, Any]] = []
|
||||
for group in conversation_groups:
|
||||
conv = _conversation_to_sharegpt(group)
|
||||
if conv is not None:
|
||||
results.append(conv)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
# ── SQLite fallback reader ───────────────────────────────────────────────────
|
||||
|
||||
def load_from_sqlite(db_path: Path) -> list[dict[str, Any]]:
|
||||
"""Read chat.db and return ShareGPT-formatted conversations."""
|
||||
if not db_path.exists():
|
||||
return []
|
||||
|
||||
try:
|
||||
conn = sqlite3.connect(str(db_path))
|
||||
conn.row_factory = sqlite3.Row
|
||||
rows = conn.execute(
|
||||
"SELECT role, content, timestamp FROM chat_messages ORDER BY id"
|
||||
).fetchall()
|
||||
conn.close()
|
||||
except sqlite3.Error:
|
||||
return []
|
||||
|
||||
entries = [
|
||||
{
|
||||
"type": "message",
|
||||
"role": row["role"],
|
||||
"content": row["content"],
|
||||
"timestamp": row["timestamp"],
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
conversation_groups = _group_into_conversations(entries)
|
||||
results: list[dict[str, Any]] = []
|
||||
for group in conversation_groups:
|
||||
conv = _conversation_to_sharegpt(group)
|
||||
if conv is not None:
|
||||
results.append(conv)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
# ── Validation ───────────────────────────────────────────────────────────────
|
||||
|
||||
def validate_output(output_path: Path) -> dict[str, Any]:
|
||||
"""Validate the exported JSONL and return stats."""
|
||||
if not output_path.exists():
|
||||
return {"error": "Output file not found"}
|
||||
|
||||
total = 0
|
||||
with_tools = 0
|
||||
turn_counts: list[int] = []
|
||||
|
||||
with open(output_path) as f:
|
||||
for line in f:
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
try:
|
||||
obj = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
total += 1
|
||||
turns = obj.get("conversations", [])
|
||||
turn_counts.append(len(turns))
|
||||
|
||||
has_tool = any(
|
||||
t.get("from") == "tool" or t.get("tool_calls")
|
||||
for t in turns
|
||||
)
|
||||
if has_tool:
|
||||
with_tools += 1
|
||||
|
||||
avg_turns = sum(turn_counts) / len(turn_counts) if turn_counts else 0
|
||||
|
||||
return {
|
||||
"total_conversations": total,
|
||||
"with_tool_calls": with_tools,
|
||||
"avg_turns_per_conversation": round(avg_turns, 1),
|
||||
"output_path": str(output_path),
|
||||
}
|
||||
|
||||
|
||||
# ── Main ─────────────────────────────────────────────────────────────────────
|
||||
|
||||
def build_parser() -> argparse.ArgumentParser:
|
||||
p = argparse.ArgumentParser(
|
||||
description="Export Timmy conversation trajectories to ShareGPT JSONL",
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
)
|
||||
p.add_argument(
|
||||
"--logs-dir",
|
||||
type=Path,
|
||||
default=DEFAULT_LOGS_DIR,
|
||||
help="Directory containing session_*.jsonl files",
|
||||
)
|
||||
p.add_argument(
|
||||
"--db",
|
||||
type=Path,
|
||||
default=DEFAULT_DB_PATH,
|
||||
help="Path to chat.db (used if no session logs found)",
|
||||
)
|
||||
p.add_argument(
|
||||
"--output",
|
||||
type=Path,
|
||||
default=DEFAULT_OUTPUT,
|
||||
help="Output JSONL file path",
|
||||
)
|
||||
p.add_argument(
|
||||
"--gap-minutes",
|
||||
type=int,
|
||||
default=CONVERSATION_GAP_MINUTES,
|
||||
help="Time gap (minutes) between entries that marks a new conversation",
|
||||
)
|
||||
p.add_argument(
|
||||
"--validate-only",
|
||||
action="store_true",
|
||||
help="Skip export; just validate an existing output file",
|
||||
)
|
||||
p.add_argument(
|
||||
"--min-examples",
|
||||
type=int,
|
||||
default=0,
|
||||
help="Exit non-zero if fewer than this many examples are exported",
|
||||
)
|
||||
return p
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
args = build_parser().parse_args(argv)
|
||||
|
||||
if args.validate_only:
|
||||
stats = validate_output(args.output)
|
||||
print(json.dumps(stats, indent=2))
|
||||
return 0
|
||||
|
||||
# ── Load conversations ───────────────────────────────────────────────────
|
||||
print(f"[1/3] Loading from session logs: {args.logs_dir}")
|
||||
conversations = load_from_session_logs(args.logs_dir)
|
||||
|
||||
if not conversations:
|
||||
print(f"[1/3] No session logs found — falling back to SQLite: {args.db}")
|
||||
conversations = load_from_sqlite(args.db)
|
||||
|
||||
if not conversations:
|
||||
print(
|
||||
"WARNING: No conversation data found.\n"
|
||||
" • Run the dashboard and have some conversations first.\n"
|
||||
" • Session logs are written to logs/session_YYYY-MM-DD.jsonl\n"
|
||||
" • Chat history is stored in data/chat.db",
|
||||
file=sys.stderr,
|
||||
)
|
||||
# Still write empty file so downstream steps don't error on missing file
|
||||
args.output.parent.mkdir(parents=True, exist_ok=True)
|
||||
args.output.write_text("")
|
||||
return 0
|
||||
|
||||
# ── Write output ─────────────────────────────────────────────────────────
|
||||
print(f"[2/3] Writing {len(conversations)} conversations → {args.output}")
|
||||
args.output.parent.mkdir(parents=True, exist_ok=True)
|
||||
with open(args.output, "w") as f:
|
||||
for conv in conversations:
|
||||
f.write(json.dumps(conv) + "\n")
|
||||
|
||||
# ── Validate ─────────────────────────────────────────────────────────────
|
||||
print("[3/3] Validating output…")
|
||||
stats = validate_output(args.output)
|
||||
print(json.dumps(stats, indent=2))
|
||||
|
||||
if args.min_examples and stats.get("total_conversations", 0) < args.min_examples:
|
||||
print(
|
||||
f"ERROR: Only {stats['total_conversations']} examples exported "
|
||||
f"(need ≥ {args.min_examples})",
|
||||
file=sys.stderr,
|
||||
)
|
||||
return 1
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -1,107 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Run the agent performance regression benchmark suite.
|
||||
|
||||
Usage::
|
||||
|
||||
python scripts/run_benchmarks.py # all scenarios
|
||||
python scripts/run_benchmarks.py --tags navigation # filter by tag
|
||||
python scripts/run_benchmarks.py --output results/benchmarks.jsonl
|
||||
python scripts/run_benchmarks.py --compare results/benchmarks.jsonl
|
||||
|
||||
Exit codes:
|
||||
0 — all scenarios passed
|
||||
1 — one or more scenarios failed
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# Ensure src/ is on the path when invoked directly
|
||||
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))
|
||||
|
||||
from infrastructure.world.benchmark.metrics import BenchmarkMetrics, load_history
|
||||
from infrastructure.world.benchmark.runner import BenchmarkRunner
|
||||
from infrastructure.world.benchmark.scenarios import load_scenarios
|
||||
|
||||
|
||||
def parse_args() -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Agent performance regression benchmark suite",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--tags",
|
||||
nargs="*",
|
||||
default=None,
|
||||
help="Filter scenarios by tag (e.g. navigation quest)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--output",
|
||||
type=Path,
|
||||
default=None,
|
||||
help="JSONL file to append results to",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--compare",
|
||||
type=Path,
|
||||
default=None,
|
||||
help="JSONL file with baseline results for regression comparison",
|
||||
)
|
||||
return parser.parse_args()
|
||||
|
||||
|
||||
async def main() -> int:
|
||||
args = parse_args()
|
||||
|
||||
scenarios = load_scenarios(tags=args.tags)
|
||||
if not scenarios:
|
||||
print("No matching scenarios found.")
|
||||
return 1
|
||||
|
||||
print(f"Running {len(scenarios)} benchmark scenario(s)...\n")
|
||||
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run(scenarios)
|
||||
|
||||
print(metrics.summary())
|
||||
|
||||
if args.output:
|
||||
metrics.save(args.output)
|
||||
|
||||
if args.compare:
|
||||
history = load_history(args.compare)
|
||||
if history:
|
||||
from infrastructure.world.benchmark.metrics import compare_runs
|
||||
|
||||
# Reconstruct baseline from last recorded run
|
||||
last = history[0]
|
||||
baseline = BenchmarkMetrics(
|
||||
timestamp=last.get("timestamp", ""),
|
||||
commit_sha=last.get("commit_sha", ""),
|
||||
total_time_ms=last.get("total_time_ms", 0),
|
||||
)
|
||||
for s in last.get("scenarios", []):
|
||||
from infrastructure.world.benchmark.metrics import ScenarioResult
|
||||
|
||||
baseline.results.append(
|
||||
ScenarioResult(
|
||||
scenario_name=s["scenario_name"],
|
||||
success=s["success"],
|
||||
cycles_used=s["cycles_used"],
|
||||
max_cycles=s["max_cycles"],
|
||||
wall_time_ms=s.get("wall_time_ms", 0),
|
||||
llm_calls=s.get("llm_calls", 0),
|
||||
metabolic_cost=s.get("metabolic_cost", 0.0),
|
||||
)
|
||||
)
|
||||
print()
|
||||
print(compare_runs(metrics, baseline))
|
||||
|
||||
return 0 if metrics.fail_count == 0 else 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(asyncio.run(main()))
|
||||
@@ -1,342 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Hermes 4 smoke test and tool-calling validation script.
|
||||
|
||||
Tests the Hermes 4 14B model after importing into Ollama. Covers:
|
||||
1. Basic connectivity — model responds
|
||||
2. Memory usage — under 28 GB with model loaded
|
||||
3. Tool calling — structured JSON output (not raw text)
|
||||
4. Reasoning — <think> tag toggling works
|
||||
5. Timmy-persona smoke test — agent identity prompt
|
||||
|
||||
Usage:
|
||||
python scripts/test_hermes4.py # Run all tests
|
||||
python scripts/test_hermes4.py --model hermes4-14b
|
||||
python scripts/test_hermes4.py --model hermes4-36b --ctx 8192
|
||||
|
||||
Epic: #1091 Project Bannerlord — AutoLoRA Sovereignty Loop (Step 2 of 7)
|
||||
Refs: #1101
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import subprocess
|
||||
import sys
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
try:
|
||||
import requests
|
||||
except ImportError:
|
||||
print("ERROR: 'requests' not installed. Run: pip install requests")
|
||||
sys.exit(1)
|
||||
|
||||
OLLAMA_URL = "http://localhost:11434"
|
||||
DEFAULT_MODEL = "hermes4-14b"
|
||||
MEMORY_LIMIT_GB = 28.0
|
||||
|
||||
# ── Tool schema used for tool-calling tests ──────────────────────────────────
|
||||
|
||||
READ_FILE_TOOL = {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "read_file",
|
||||
"description": "Read the contents of a file at the given path",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"path": {
|
||||
"type": "string",
|
||||
"description": "Absolute or relative path to the file",
|
||||
}
|
||||
},
|
||||
"required": ["path"],
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
LIST_ISSUES_TOOL = {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "list_issues",
|
||||
"description": "List open issues from a Gitea repository",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"repo": {"type": "string", "description": "owner/repo slug"},
|
||||
"state": {
|
||||
"type": "string",
|
||||
"enum": ["open", "closed", "all"],
|
||||
"description": "Issue state filter",
|
||||
},
|
||||
},
|
||||
"required": ["repo"],
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# ── Helpers ───────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _post(endpoint: str, payload: dict, timeout: int = 60) -> dict[str, Any]:
|
||||
"""POST to Ollama and return parsed JSON."""
|
||||
url = f"{OLLAMA_URL}{endpoint}"
|
||||
resp = requests.post(url, json=payload, timeout=timeout)
|
||||
resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
|
||||
def _ollama_memory_gb() -> float:
|
||||
"""Estimate Ollama process RSS in GB using ps (macOS/Linux)."""
|
||||
try:
|
||||
# Look for ollama process RSS (macOS: column 6 in MB, Linux: column 6 in KB)
|
||||
result = subprocess.run(
|
||||
["ps", "-axo", "pid,comm,rss"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=False,
|
||||
)
|
||||
total_kb = 0
|
||||
for line in result.stdout.splitlines():
|
||||
if "ollama" in line.lower():
|
||||
parts = line.split()
|
||||
try:
|
||||
total_kb += int(parts[-1])
|
||||
except (ValueError, IndexError):
|
||||
pass
|
||||
return total_kb / (1024 * 1024) # KB → GB
|
||||
except Exception:
|
||||
return 0.0
|
||||
|
||||
|
||||
def _check_model_available(model: str) -> bool:
|
||||
"""Return True if model is listed in Ollama."""
|
||||
try:
|
||||
resp = requests.get(f"{OLLAMA_URL}/api/tags", timeout=10)
|
||||
resp.raise_for_status()
|
||||
names = [m["name"] for m in resp.json().get("models", [])]
|
||||
return any(model in n for n in names)
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
|
||||
def _chat(model: str, messages: list[dict], tools: list | None = None) -> dict:
|
||||
"""Send a chat request to Ollama."""
|
||||
payload: dict = {"model": model, "messages": messages, "stream": False}
|
||||
if tools:
|
||||
payload["tools"] = tools
|
||||
return _post("/api/chat", payload, timeout=120)
|
||||
|
||||
|
||||
# ── Test cases ────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_model_available(model: str) -> bool:
|
||||
"""PASS: model is registered in Ollama."""
|
||||
print(f"\n[1/5] Checking model availability: {model}")
|
||||
if _check_model_available(model):
|
||||
print(f" ✓ {model} is available in Ollama")
|
||||
return True
|
||||
print(
|
||||
f" ✗ {model} not found. Import with:\n"
|
||||
f" ollama create {model} -f Modelfile.hermes4-14b\n"
|
||||
f" Or pull directly if on registry:\n"
|
||||
f" ollama pull {model}"
|
||||
)
|
||||
return False
|
||||
|
||||
|
||||
def test_basic_response(model: str) -> bool:
|
||||
"""PASS: model responds coherently to a simple prompt."""
|
||||
print(f"\n[2/5] Basic response test")
|
||||
messages = [
|
||||
{"role": "user", "content": "Reply with exactly: HERMES_OK"},
|
||||
]
|
||||
try:
|
||||
t0 = time.time()
|
||||
data = _chat(model, messages)
|
||||
elapsed = time.time() - t0
|
||||
content = data.get("message", {}).get("content", "")
|
||||
if "HERMES_OK" in content:
|
||||
print(f" ✓ Basic response OK ({elapsed:.1f}s): {content.strip()}")
|
||||
return True
|
||||
print(f" ✗ Unexpected response ({elapsed:.1f}s): {content[:200]!r}")
|
||||
return False
|
||||
except Exception as exc:
|
||||
print(f" ✗ Request failed: {exc}")
|
||||
return False
|
||||
|
||||
|
||||
def test_memory_usage() -> bool:
|
||||
"""PASS: Ollama process RSS is under MEMORY_LIMIT_GB."""
|
||||
print(f"\n[3/5] Memory usage check (limit: {MEMORY_LIMIT_GB} GB)")
|
||||
mem_gb = _ollama_memory_gb()
|
||||
if mem_gb == 0.0:
|
||||
print(" ~ Could not determine memory usage (ps unavailable?), skipping")
|
||||
return True
|
||||
if mem_gb < MEMORY_LIMIT_GB:
|
||||
print(f" ✓ Memory usage: {mem_gb:.1f} GB (under {MEMORY_LIMIT_GB} GB limit)")
|
||||
return True
|
||||
print(
|
||||
f" ✗ Memory usage: {mem_gb:.1f} GB exceeds {MEMORY_LIMIT_GB} GB limit.\n"
|
||||
" Consider using Q4_K_M quantisation or reducing num_ctx."
|
||||
)
|
||||
return False
|
||||
|
||||
|
||||
def test_tool_calling(model: str) -> bool:
|
||||
"""PASS: model produces a tool_calls response (not raw text) for a tool-use prompt."""
|
||||
print(f"\n[4/5] Tool-calling test")
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Please read the file at /tmp/test.txt using the read_file tool.",
|
||||
}
|
||||
]
|
||||
try:
|
||||
t0 = time.time()
|
||||
data = _chat(model, messages, tools=[READ_FILE_TOOL])
|
||||
elapsed = time.time() - t0
|
||||
msg = data.get("message", {})
|
||||
tool_calls = msg.get("tool_calls", [])
|
||||
|
||||
if tool_calls:
|
||||
tc = tool_calls[0]
|
||||
fn = tc.get("function", {})
|
||||
print(
|
||||
f" ✓ Tool call produced ({elapsed:.1f}s):\n"
|
||||
f" function: {fn.get('name')}\n"
|
||||
f" arguments: {json.dumps(fn.get('arguments', {}), indent=6)}"
|
||||
)
|
||||
# Verify the function name is correct
|
||||
return fn.get("name") == "read_file"
|
||||
|
||||
# Some models return JSON in the content instead of tool_calls
|
||||
content = msg.get("content", "")
|
||||
if "read_file" in content and "{" in content:
|
||||
print(
|
||||
f" ~ Model returned tool call as text (not structured). ({elapsed:.1f}s)\n"
|
||||
f" This is acceptable for the base model before fine-tuning.\n"
|
||||
f" Content: {content[:300]}"
|
||||
)
|
||||
# Partial pass — model attempted tool calling but via text
|
||||
return True
|
||||
|
||||
print(
|
||||
f" ✗ No tool call in response ({elapsed:.1f}s).\n"
|
||||
f" Content: {content[:300]!r}"
|
||||
)
|
||||
return False
|
||||
except Exception as exc:
|
||||
print(f" ✗ Tool-calling request failed: {exc}")
|
||||
return False
|
||||
|
||||
|
||||
def test_timmy_persona(model: str) -> bool:
|
||||
"""PASS: model accepts a Timmy persona system prompt and responds in-character."""
|
||||
print(f"\n[5/5] Timmy-persona smoke test")
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": (
|
||||
"You are Timmy, Alexander's personal AI agent. "
|
||||
"You are concise, direct, and helpful. "
|
||||
"You always start your responses with 'Timmy here:'."
|
||||
),
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is your name and what can you help me with?",
|
||||
},
|
||||
]
|
||||
try:
|
||||
t0 = time.time()
|
||||
data = _chat(model, messages)
|
||||
elapsed = time.time() - t0
|
||||
content = data.get("message", {}).get("content", "")
|
||||
if "Timmy" in content or "timmy" in content.lower():
|
||||
print(f" ✓ Persona accepted ({elapsed:.1f}s): {content[:200].strip()}")
|
||||
return True
|
||||
print(
|
||||
f" ~ Persona response lacks 'Timmy' identifier ({elapsed:.1f}s).\n"
|
||||
f" This is a fine-tuning target.\n"
|
||||
f" Response: {content[:200]!r}"
|
||||
)
|
||||
# Soft pass — base model isn't expected to be perfectly in-character
|
||||
return True
|
||||
except Exception as exc:
|
||||
print(f" ✗ Persona test failed: {exc}")
|
||||
return False
|
||||
|
||||
|
||||
# ── Main ──────────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description="Hermes 4 smoke test suite")
|
||||
parser.add_argument(
|
||||
"--model",
|
||||
default=DEFAULT_MODEL,
|
||||
help=f"Ollama model name (default: {DEFAULT_MODEL})",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--ollama-url",
|
||||
default=OLLAMA_URL,
|
||||
help=f"Ollama base URL (default: {OLLAMA_URL})",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
global OLLAMA_URL
|
||||
OLLAMA_URL = args.ollama_url.rstrip("/")
|
||||
model = args.model
|
||||
|
||||
print("=" * 60)
|
||||
print(f"Hermes 4 Validation Suite — {model}")
|
||||
print(f"Ollama: {OLLAMA_URL}")
|
||||
print("=" * 60)
|
||||
|
||||
results: dict[str, bool] = {}
|
||||
|
||||
# Test 1: availability (gate — skip remaining if model missing)
|
||||
results["available"] = test_model_available(model)
|
||||
if not results["available"]:
|
||||
print("\n⚠ Model not available — skipping remaining tests.")
|
||||
print(" Import the model first (see Modelfile.hermes4-14b).")
|
||||
_print_summary(results)
|
||||
return 1
|
||||
|
||||
# Tests 2–5
|
||||
results["basic_response"] = test_basic_response(model)
|
||||
results["memory_usage"] = test_memory_usage()
|
||||
results["tool_calling"] = test_tool_calling(model)
|
||||
results["timmy_persona"] = test_timmy_persona(model)
|
||||
|
||||
return _print_summary(results)
|
||||
|
||||
|
||||
def _print_summary(results: dict[str, bool]) -> int:
|
||||
passed = sum(results.values())
|
||||
total = len(results)
|
||||
print("\n" + "=" * 60)
|
||||
print(f"Results: {passed}/{total} passed")
|
||||
print("=" * 60)
|
||||
for name, ok in results.items():
|
||||
icon = "✓" if ok else "✗"
|
||||
print(f" {icon} {name}")
|
||||
|
||||
if passed == total:
|
||||
print("\n✓ All tests passed. Hermes 4 is ready for AutoLoRA fine-tuning.")
|
||||
print(" Next step: document WORK vs FAIL skill list → fine-tuning targets.")
|
||||
elif results.get("tool_calling") is False:
|
||||
print("\n⚠ Tool-calling FAILED. This is the primary fine-tuning target.")
|
||||
print(" Base model may need LoRA tuning on tool-use examples.")
|
||||
else:
|
||||
print("\n~ Partial pass. Review failures above before fine-tuning.")
|
||||
|
||||
return 0 if passed == total else 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -1,67 +0,0 @@
|
||||
---
|
||||
name: Architecture Spike
|
||||
type: research
|
||||
typical_query_count: 2-4
|
||||
expected_output_length: 600-1200 words
|
||||
cascade_tier: groq_preferred
|
||||
description: >
|
||||
Investigate how to connect two systems or components. Produces an integration
|
||||
architecture with sequence diagram, key decisions, and a proof-of-concept outline.
|
||||
---
|
||||
|
||||
# Architecture Spike: Connect {system_a} to {system_b}
|
||||
|
||||
## Context
|
||||
|
||||
We need to integrate **{system_a}** with **{system_b}** in the context of
|
||||
**{project_context}**. This spike answers: what is the best way to wire them
|
||||
together, and what are the trade-offs?
|
||||
|
||||
## Constraints
|
||||
|
||||
- Prefer approaches that avoid adding new infrastructure dependencies.
|
||||
- The integration should be **{sync_or_async}** (synchronous / asynchronous).
|
||||
- Must work within: {environment_constraints}.
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Identify the APIs / protocols exposed by both systems.
|
||||
2. List all known integration patterns (direct API, message queue, webhook, SDK, etc.).
|
||||
3. Evaluate each pattern for complexity, reliability, and latency.
|
||||
4. Select the recommended approach and outline a proof-of-concept.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Integration Options
|
||||
|
||||
| Pattern | Complexity | Reliability | Latency | Notes |
|
||||
|---------|-----------|-------------|---------|-------|
|
||||
| ... | ... | ... | ... | ... |
|
||||
|
||||
### Recommended Approach
|
||||
|
||||
**Pattern:** {pattern_name}
|
||||
|
||||
**Why:** One paragraph explaining the choice.
|
||||
|
||||
### Sequence Diagram
|
||||
|
||||
```
|
||||
{system_a} -> {middleware} -> {system_b}
|
||||
```
|
||||
|
||||
Describe the data flow step by step:
|
||||
|
||||
1. {system_a} does X...
|
||||
2. {middleware} transforms / routes...
|
||||
3. {system_b} receives Y...
|
||||
|
||||
### Proof-of-Concept Outline
|
||||
|
||||
- Files to create or modify
|
||||
- Key libraries / dependencies needed
|
||||
- Estimated effort: {effort_estimate}
|
||||
|
||||
### Open Questions
|
||||
|
||||
Bullet list of decisions that need human input before proceeding.
|
||||
@@ -1,74 +0,0 @@
|
||||
---
|
||||
name: Competitive Scan
|
||||
type: research
|
||||
typical_query_count: 3-5
|
||||
expected_output_length: 800-1500 words
|
||||
cascade_tier: groq_preferred
|
||||
description: >
|
||||
Compare a project against its alternatives. Produces a feature matrix,
|
||||
strengths/weaknesses analysis, and positioning summary.
|
||||
---
|
||||
|
||||
# Competitive Scan: {project} vs Alternatives
|
||||
|
||||
## Context
|
||||
|
||||
Compare **{project}** against **{alternatives}** (comma-separated list of
|
||||
competitors). The goal is to understand where {project} stands and identify
|
||||
differentiation opportunities.
|
||||
|
||||
## Constraints
|
||||
|
||||
- Comparison date: {date}.
|
||||
- Focus areas: {focus_areas} (e.g., features, pricing, community, performance).
|
||||
- Perspective: {perspective} (user, developer, business).
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Gather key facts about {project} (features, pricing, community size, release cadence).
|
||||
2. Gather the same data for each alternative in {alternatives}.
|
||||
3. Build a feature comparison matrix.
|
||||
4. Identify strengths and weaknesses for each entry.
|
||||
5. Summarize positioning and recommend next steps.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Overview
|
||||
|
||||
One paragraph: what space does {project} compete in, and who are the main players?
|
||||
|
||||
### Feature Matrix
|
||||
|
||||
| Feature / Attribute | {project} | {alt_1} | {alt_2} | {alt_3} |
|
||||
|--------------------|-----------|---------|---------|---------|
|
||||
| {feature_1} | ... | ... | ... | ... |
|
||||
| {feature_2} | ... | ... | ... | ... |
|
||||
| Pricing | ... | ... | ... | ... |
|
||||
| License | ... | ... | ... | ... |
|
||||
| Community Size | ... | ... | ... | ... |
|
||||
| Last Major Release | ... | ... | ... | ... |
|
||||
|
||||
### Strengths & Weaknesses
|
||||
|
||||
#### {project}
|
||||
- **Strengths:** ...
|
||||
- **Weaknesses:** ...
|
||||
|
||||
#### {alt_1}
|
||||
- **Strengths:** ...
|
||||
- **Weaknesses:** ...
|
||||
|
||||
_(Repeat for each alternative)_
|
||||
|
||||
### Positioning Map
|
||||
|
||||
Describe where each project sits along the key dimensions (e.g., simplicity
|
||||
vs power, free vs paid, niche vs general).
|
||||
|
||||
### Recommendations
|
||||
|
||||
Bullet list of actions based on the competitive landscape:
|
||||
|
||||
- **Differentiate on:** {differentiator}
|
||||
- **Watch out for:** {threat}
|
||||
- **Consider adopting from {alt}:** {feature_or_approach}
|
||||
@@ -1,68 +0,0 @@
|
||||
---
|
||||
name: Game Analysis
|
||||
type: research
|
||||
typical_query_count: 2-3
|
||||
expected_output_length: 600-1000 words
|
||||
cascade_tier: local_ok
|
||||
description: >
|
||||
Evaluate a game for AI agent playability. Assesses API availability,
|
||||
observation/action spaces, and existing bot ecosystems.
|
||||
---
|
||||
|
||||
# Game Analysis: {game}
|
||||
|
||||
## Context
|
||||
|
||||
Evaluate **{game}** to determine whether an AI agent can play it effectively.
|
||||
Focus on programmatic access, observation space, action space, and existing
|
||||
bot/AI ecosystems.
|
||||
|
||||
## Constraints
|
||||
|
||||
- Platform: {platform} (PC, console, mobile, browser).
|
||||
- Agent type: {agent_type} (reinforcement learning, rule-based, LLM-driven, hybrid).
|
||||
- Budget for API/licenses: {budget}.
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Identify official APIs, modding support, or programmatic access methods for {game}.
|
||||
2. Characterize the observation space (screen pixels, game state JSON, memory reading, etc.).
|
||||
3. Characterize the action space (keyboard/mouse, API calls, controller inputs).
|
||||
4. Survey existing bots, AI projects, or research papers for {game}.
|
||||
5. Assess feasibility and difficulty for the target agent type.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Game Profile
|
||||
|
||||
| Property | Value |
|
||||
|-------------------|------------------------|
|
||||
| Game | {game} |
|
||||
| Genre | {genre} |
|
||||
| Platform | {platform} |
|
||||
| API Available | Yes / No / Partial |
|
||||
| Mod Support | Yes / No / Limited |
|
||||
| Existing AI Work | Extensive / Some / None|
|
||||
|
||||
### Observation Space
|
||||
|
||||
Describe what data the agent can access and how (API, screen capture, memory hooks, etc.).
|
||||
|
||||
### Action Space
|
||||
|
||||
Describe how the agent can interact with the game (input methods, timing constraints, etc.).
|
||||
|
||||
### Existing Ecosystem
|
||||
|
||||
List known bots, frameworks, research papers, or communities working on AI for {game}.
|
||||
|
||||
### Feasibility Assessment
|
||||
|
||||
- **Difficulty:** Easy / Medium / Hard / Impractical
|
||||
- **Best approach:** {recommended_agent_type}
|
||||
- **Key challenges:** Bullet list
|
||||
- **Estimated time to MVP:** {time_estimate}
|
||||
|
||||
### Recommendation
|
||||
|
||||
One paragraph: should we proceed, and if so, what is the first step?
|
||||
@@ -1,79 +0,0 @@
|
||||
---
|
||||
name: Integration Guide
|
||||
type: research
|
||||
typical_query_count: 3-5
|
||||
expected_output_length: 1000-2000 words
|
||||
cascade_tier: groq_preferred
|
||||
description: >
|
||||
Step-by-step guide to wire a specific tool into an existing stack,
|
||||
complete with code samples, configuration, and testing steps.
|
||||
---
|
||||
|
||||
# Integration Guide: Wire {tool} into {stack}
|
||||
|
||||
## Context
|
||||
|
||||
Integrate **{tool}** into our **{stack}** stack. The goal is to
|
||||
**{integration_goal}** (e.g., "add vector search to the dashboard",
|
||||
"send notifications via Telegram").
|
||||
|
||||
## Constraints
|
||||
|
||||
- Must follow existing project conventions (see CLAUDE.md).
|
||||
- No new cloud AI dependencies unless explicitly approved.
|
||||
- Environment config via `pydantic-settings` / `config.py`.
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Review {tool}'s official documentation for installation and setup.
|
||||
2. Identify the minimal dependency set required.
|
||||
3. Map {tool}'s API to our existing patterns (singletons, graceful degradation).
|
||||
4. Write integration code with proper error handling.
|
||||
5. Define configuration variables and their defaults.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- Dependencies to install (with versions)
|
||||
- External services or accounts required
|
||||
- Environment variables to configure
|
||||
|
||||
### Configuration
|
||||
|
||||
```python
|
||||
# In config.py — add these fields to Settings:
|
||||
{config_fields}
|
||||
```
|
||||
|
||||
### Implementation
|
||||
|
||||
```python
|
||||
# {file_path}
|
||||
{implementation_code}
|
||||
```
|
||||
|
||||
### Graceful Degradation
|
||||
|
||||
Describe how the integration behaves when {tool} is unavailable:
|
||||
|
||||
| Scenario | Behavior | Log Level |
|
||||
|-----------------------|--------------------|-----------|
|
||||
| {tool} not installed | {fallback} | WARNING |
|
||||
| {tool} unreachable | {fallback} | WARNING |
|
||||
| Invalid credentials | {fallback} | ERROR |
|
||||
|
||||
### Testing
|
||||
|
||||
```python
|
||||
# tests/unit/test_{tool_snake}.py
|
||||
{test_code}
|
||||
```
|
||||
|
||||
### Verification Checklist
|
||||
|
||||
- [ ] Dependency added to pyproject.toml
|
||||
- [ ] Config fields added with sensible defaults
|
||||
- [ ] Graceful degradation tested (service down)
|
||||
- [ ] Unit tests pass (`tox -e unit`)
|
||||
- [ ] No new linting errors (`tox -e lint`)
|
||||
@@ -1,67 +0,0 @@
|
||||
---
|
||||
name: State of the Art
|
||||
type: research
|
||||
typical_query_count: 4-6
|
||||
expected_output_length: 1000-2000 words
|
||||
cascade_tier: groq_preferred
|
||||
description: >
|
||||
Comprehensive survey of what currently exists in a given field or domain.
|
||||
Produces a structured landscape overview with key players, trends, and gaps.
|
||||
---
|
||||
|
||||
# State of the Art: {field} (as of {date})
|
||||
|
||||
## Context
|
||||
|
||||
Survey the current landscape of **{field}**. Identify key players, recent
|
||||
developments, dominant approaches, and notable gaps. This is a point-in-time
|
||||
snapshot intended to inform decision-making.
|
||||
|
||||
## Constraints
|
||||
|
||||
- Focus on developments from the last {timeframe} (e.g., 12 months, 2 years).
|
||||
- Prioritize {priority} (open-source, commercial, academic, or all).
|
||||
- Target audience: {audience} (technical team, leadership, general).
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Identify the major categories or sub-domains within {field}.
|
||||
2. For each category, list the leading projects, companies, or research groups.
|
||||
3. Note recent milestones, releases, or breakthroughs.
|
||||
4. Identify emerging trends and directions.
|
||||
5. Highlight gaps — things that don't exist yet but should.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Executive Summary
|
||||
|
||||
Two to three sentences: what is the state of {field} right now?
|
||||
|
||||
### Landscape Map
|
||||
|
||||
| Category | Key Players | Maturity | Trend |
|
||||
|---------------|--------------------------|-------------|-------------|
|
||||
| {category_1} | {player_a}, {player_b} | Early / GA | Growing / Stable / Declining |
|
||||
| {category_2} | {player_c}, {player_d} | Early / GA | Growing / Stable / Declining |
|
||||
|
||||
### Recent Milestones
|
||||
|
||||
Chronological list of notable events in the last {timeframe}:
|
||||
|
||||
- **{date_1}:** {event_description}
|
||||
- **{date_2}:** {event_description}
|
||||
|
||||
### Trends
|
||||
|
||||
Numbered list of the top 3-5 trends shaping {field}:
|
||||
|
||||
1. **{trend_name}** — {one-line description}
|
||||
2. **{trend_name}** — {one-line description}
|
||||
|
||||
### Gaps & Opportunities
|
||||
|
||||
Bullet list of things that are missing, underdeveloped, or ripe for innovation.
|
||||
|
||||
### Implications for Us
|
||||
|
||||
One paragraph: what does this mean for our project? What should we do next?
|
||||
@@ -1,52 +0,0 @@
|
||||
---
|
||||
name: Tool Evaluation
|
||||
type: research
|
||||
typical_query_count: 3-5
|
||||
expected_output_length: 800-1500 words
|
||||
cascade_tier: groq_preferred
|
||||
description: >
|
||||
Discover and evaluate all shipping tools/libraries/services in a given domain.
|
||||
Produces a ranked comparison table with pros, cons, and recommendation.
|
||||
---
|
||||
|
||||
# Tool Evaluation: {domain}
|
||||
|
||||
## Context
|
||||
|
||||
You are researching tools, libraries, and services for **{domain}**.
|
||||
The goal is to find everything that is currently shipping (not vaporware)
|
||||
and produce a structured comparison.
|
||||
|
||||
## Constraints
|
||||
|
||||
- Only include tools that have public releases or hosted services available today.
|
||||
- If a tool is in beta/preview, note that clearly.
|
||||
- Focus on {focus_criteria} when evaluating (e.g., cost, ease of integration, community size).
|
||||
|
||||
## Research Steps
|
||||
|
||||
1. Identify all actively-maintained tools in the **{domain}** space.
|
||||
2. For each tool, gather: name, URL, license/pricing, last release date, language/platform.
|
||||
3. Evaluate each tool against the focus criteria.
|
||||
4. Rank by overall fit for the use case: **{use_case}**.
|
||||
|
||||
## Output Format
|
||||
|
||||
### Summary
|
||||
|
||||
One paragraph: what the landscape looks like and the top recommendation.
|
||||
|
||||
### Comparison Table
|
||||
|
||||
| Tool | License / Price | Last Release | Language | {focus_criteria} Score | Notes |
|
||||
|------|----------------|--------------|----------|----------------------|-------|
|
||||
| ... | ... | ... | ... | ... | ... |
|
||||
|
||||
### Top Pick
|
||||
|
||||
- **Recommended:** {tool_name} — {one-line reason}
|
||||
- **Runner-up:** {tool_name} — {one-line reason}
|
||||
|
||||
### Risks & Gaps
|
||||
|
||||
Bullet list of things to watch out for (missing features, vendor lock-in, etc.).
|
||||
@@ -99,14 +99,6 @@ class Settings(BaseSettings):
|
||||
anthropic_api_key: str = ""
|
||||
claude_model: str = "haiku"
|
||||
|
||||
# ── Content Moderation ──────────────────────────────────────────────
|
||||
# Three-layer moderation pipeline for AI narrator output.
|
||||
# Uses Llama Guard via Ollama with regex fallback.
|
||||
moderation_enabled: bool = True
|
||||
moderation_guard_model: str = "llama-guard3:1b"
|
||||
# Default confidence threshold — per-game profiles can override.
|
||||
moderation_threshold: float = 0.8
|
||||
|
||||
# ── Spark Intelligence ────────────────────────────────────────────────
|
||||
# Enable/disable the Spark cognitive layer.
|
||||
# When enabled, Spark captures swarm events, runs EIDOS predictions,
|
||||
@@ -152,10 +144,6 @@ class Settings(BaseSettings):
|
||||
# Default is False (telemetry disabled) to align with sovereign AI vision.
|
||||
telemetry_enabled: bool = False
|
||||
|
||||
# ── Sovereignty Metrics ──────────────────────────────────────────────
|
||||
# Alert when API cost per research task exceeds this threshold (USD).
|
||||
sovereignty_api_cost_alert_threshold: float = 1.00
|
||||
|
||||
# CORS allowed origins for the web chat interface (Gitea Pages, etc.)
|
||||
# Set CORS_ORIGINS as a comma-separated list, e.g. "http://localhost:3000,https://example.com"
|
||||
cors_origins: list[str] = [
|
||||
@@ -302,7 +290,6 @@ class Settings(BaseSettings):
|
||||
mcp_gitea_command: str = "gitea-mcp-server -t stdio"
|
||||
mcp_filesystem_command: str = "npx -y @modelcontextprotocol/server-filesystem"
|
||||
mcp_timeout: int = 15
|
||||
mcp_bridge_timeout: int = 60 # HTTP timeout for MCP bridge Ollama calls (seconds)
|
||||
|
||||
# ── Loop QA (Self-Testing) ─────────────────────────────────────────
|
||||
# Self-test orchestrator that probes capabilities alongside the thinking loop.
|
||||
|
||||
@@ -45,7 +45,6 @@ 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.sovereignty_metrics import router as sovereignty_metrics_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
|
||||
@@ -375,21 +374,13 @@ def _startup_init() -> None:
|
||||
|
||||
def _startup_background_tasks() -> list[asyncio.Task]:
|
||||
"""Spawn all recurring background tasks (non-blocking)."""
|
||||
bg_tasks = [
|
||||
return [
|
||||
asyncio.create_task(_briefing_scheduler()),
|
||||
asyncio.create_task(_thinking_scheduler()),
|
||||
asyncio.create_task(_loop_qa_scheduler()),
|
||||
asyncio.create_task(_presence_watcher()),
|
||||
asyncio.create_task(_start_chat_integrations_background()),
|
||||
]
|
||||
try:
|
||||
from timmy.paperclip import start_paperclip_poller
|
||||
bg_tasks.append(asyncio.create_task(start_paperclip_poller()))
|
||||
logger.info("Paperclip poller started")
|
||||
except ImportError:
|
||||
logger.debug("Paperclip module not found, skipping poller")
|
||||
|
||||
return bg_tasks
|
||||
|
||||
|
||||
def _try_prune(label: str, prune_fn, days: int) -> None:
|
||||
@@ -640,7 +631,6 @@ app.include_router(tower_router)
|
||||
app.include_router(daily_run_router)
|
||||
app.include_router(quests_router)
|
||||
app.include_router(scorecards_router)
|
||||
app.include_router(sovereignty_metrics_router)
|
||||
|
||||
|
||||
@app.websocket("/ws")
|
||||
|
||||
@@ -125,7 +125,7 @@ def _run_grok_query(message: str) -> dict:
|
||||
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)
|
||||
sats = min(settings.grok_max_sats_per_query, 100)
|
||||
ln.create_invoice(sats, f"Grok: {message[:50]}")
|
||||
invoice_note = f" | {sats} sats"
|
||||
except Exception as exc:
|
||||
|
||||
@@ -1,74 +0,0 @@
|
||||
"""Sovereignty metrics dashboard routes.
|
||||
|
||||
Provides API endpoints and HTMX partials for tracking research
|
||||
sovereignty progress against graduation targets.
|
||||
|
||||
Refs: #981
|
||||
"""
|
||||
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
from fastapi import APIRouter, Request
|
||||
from fastapi.responses import HTMLResponse
|
||||
|
||||
from config import settings
|
||||
from dashboard.templating import templates
|
||||
from infrastructure.sovereignty_metrics import (
|
||||
GRADUATION_TARGETS,
|
||||
get_sovereignty_store,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/sovereignty", tags=["sovereignty"])
|
||||
|
||||
|
||||
@router.get("/metrics")
|
||||
async def sovereignty_metrics_api() -> dict[str, Any]:
|
||||
"""JSON API: full sovereignty metrics summary with trends."""
|
||||
store = get_sovereignty_store()
|
||||
summary = store.get_summary()
|
||||
alerts = store.get_alerts(unacknowledged_only=True)
|
||||
return {
|
||||
"metrics": summary,
|
||||
"alerts": alerts,
|
||||
"targets": GRADUATION_TARGETS,
|
||||
"cost_threshold": settings.sovereignty_api_cost_alert_threshold,
|
||||
}
|
||||
|
||||
|
||||
@router.get("/metrics/panel", response_class=HTMLResponse)
|
||||
async def sovereignty_metrics_panel(request: Request) -> HTMLResponse:
|
||||
"""HTMX partial: sovereignty metrics progress panel."""
|
||||
store = get_sovereignty_store()
|
||||
summary = store.get_summary()
|
||||
alerts = store.get_alerts(unacknowledged_only=True)
|
||||
|
||||
return templates.TemplateResponse(
|
||||
request,
|
||||
"partials/sovereignty_metrics.html",
|
||||
{
|
||||
"metrics": summary,
|
||||
"alerts": alerts,
|
||||
"targets": GRADUATION_TARGETS,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@router.get("/alerts")
|
||||
async def sovereignty_alerts_api() -> dict[str, Any]:
|
||||
"""JSON API: sovereignty alerts."""
|
||||
store = get_sovereignty_store()
|
||||
return {
|
||||
"alerts": store.get_alerts(unacknowledged_only=False),
|
||||
"unacknowledged": store.get_alerts(unacknowledged_only=True),
|
||||
}
|
||||
|
||||
|
||||
@router.post("/alerts/{alert_id}/acknowledge")
|
||||
async def acknowledge_alert(alert_id: int) -> dict[str, bool]:
|
||||
"""Acknowledge a sovereignty alert."""
|
||||
store = get_sovereignty_store()
|
||||
success = store.acknowledge_alert(alert_id)
|
||||
return {"success": success}
|
||||
@@ -143,49 +143,64 @@ async def tasks_page(request: Request):
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _render_task_list(request: Request, query: str, empty_msg: str) -> HTMLResponse:
|
||||
"""Fetch tasks by query and render as HTMX task-card partials."""
|
||||
with _get_db() as db:
|
||||
rows = db.execute(query).fetchall()
|
||||
parts = [
|
||||
templates.TemplateResponse(
|
||||
request, "partials/task_card.html", {"task": _TaskView(_row_to_dict(r))}
|
||||
).body.decode()
|
||||
for r in rows
|
||||
]
|
||||
if not parts:
|
||||
return HTMLResponse(f'<div class="empty-column">{empty_msg}</div>')
|
||||
return HTMLResponse("".join(parts))
|
||||
|
||||
|
||||
@router.get("/tasks/pending", response_class=HTMLResponse)
|
||||
async def tasks_pending(request: Request):
|
||||
"""Return HTMX partial for pending approval tasks."""
|
||||
return _render_task_list(
|
||||
request,
|
||||
"SELECT * FROM tasks WHERE status='pending_approval' ORDER BY created_at DESC",
|
||||
"No pending tasks",
|
||||
)
|
||||
with _get_db() as db:
|
||||
rows = db.execute(
|
||||
"SELECT * FROM tasks WHERE status='pending_approval' ORDER BY created_at DESC"
|
||||
).fetchall()
|
||||
tasks = [_TaskView(_row_to_dict(r)) for r in rows]
|
||||
parts = []
|
||||
for task in tasks:
|
||||
parts.append(
|
||||
templates.TemplateResponse(
|
||||
request, "partials/task_card.html", {"task": task}
|
||||
).body.decode()
|
||||
)
|
||||
if not parts:
|
||||
return HTMLResponse('<div class="empty-column">No pending tasks</div>')
|
||||
return HTMLResponse("".join(parts))
|
||||
|
||||
|
||||
@router.get("/tasks/active", response_class=HTMLResponse)
|
||||
async def tasks_active(request: Request):
|
||||
"""Return HTMX partial for active (approved/running/paused) tasks."""
|
||||
return _render_task_list(
|
||||
request,
|
||||
"SELECT * FROM tasks WHERE status IN ('approved','running','paused') ORDER BY created_at DESC",
|
||||
"No active tasks",
|
||||
)
|
||||
with _get_db() as db:
|
||||
rows = db.execute(
|
||||
"SELECT * FROM tasks WHERE status IN ('approved','running','paused') ORDER BY created_at DESC"
|
||||
).fetchall()
|
||||
tasks = [_TaskView(_row_to_dict(r)) for r in rows]
|
||||
parts = []
|
||||
for task in tasks:
|
||||
parts.append(
|
||||
templates.TemplateResponse(
|
||||
request, "partials/task_card.html", {"task": task}
|
||||
).body.decode()
|
||||
)
|
||||
if not parts:
|
||||
return HTMLResponse('<div class="empty-column">No active tasks</div>')
|
||||
return HTMLResponse("".join(parts))
|
||||
|
||||
|
||||
@router.get("/tasks/completed", response_class=HTMLResponse)
|
||||
async def tasks_completed(request: Request):
|
||||
"""Return HTMX partial for completed/vetoed/failed tasks (last 50)."""
|
||||
return _render_task_list(
|
||||
request,
|
||||
"SELECT * FROM tasks WHERE status IN ('completed','vetoed','failed') ORDER BY completed_at DESC LIMIT 50",
|
||||
"No completed tasks yet",
|
||||
)
|
||||
with _get_db() as db:
|
||||
rows = db.execute(
|
||||
"SELECT * FROM tasks WHERE status IN ('completed','vetoed','failed') ORDER BY completed_at DESC LIMIT 50"
|
||||
).fetchall()
|
||||
tasks = [_TaskView(_row_to_dict(r)) for r in rows]
|
||||
parts = []
|
||||
for task in tasks:
|
||||
parts.append(
|
||||
templates.TemplateResponse(
|
||||
request, "partials/task_card.html", {"task": task}
|
||||
).body.decode()
|
||||
)
|
||||
if not parts:
|
||||
return HTMLResponse('<div class="empty-column">No completed tasks yet</div>')
|
||||
return HTMLResponse("".join(parts))
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@@ -179,13 +179,6 @@
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Sovereignty Metrics -->
|
||||
{% call panel("SOVEREIGNTY METRICS", id="sovereignty-metrics-panel",
|
||||
hx_get="/sovereignty/metrics/panel",
|
||||
hx_trigger="load, every 30s") %}
|
||||
<p class="chat-history-placeholder">Loading sovereignty metrics...</p>
|
||||
{% endcall %}
|
||||
|
||||
<!-- Chat History -->
|
||||
<div class="card mc-card-spaced">
|
||||
<div class="card-header">
|
||||
|
||||
@@ -1,63 +0,0 @@
|
||||
{# HTMX partial: Sovereignty Metrics Progress Panel
|
||||
Loaded via hx-get="/sovereignty/metrics/panel"
|
||||
Refs: #981
|
||||
#}
|
||||
{% set phase_labels = {"pre-start": "Pre-start", "week1": "Week 1", "month1": "Month 1", "month3": "Month 3", "graduated": "Graduated"} %}
|
||||
{% set phase_colors = {"pre-start": "var(--text-dim)", "week1": "var(--red)", "month1": "var(--amber)", "month3": "var(--green)", "graduated": "var(--purple)"} %}
|
||||
|
||||
{% set metric_labels = {
|
||||
"cache_hit_rate": "Cache Hit Rate",
|
||||
"api_cost": "API Cost / Task",
|
||||
"time_to_report": "Time to Report",
|
||||
"human_involvement": "Human Involvement",
|
||||
"local_artifacts": "Local Artifacts"
|
||||
} %}
|
||||
|
||||
{% set metric_units = {
|
||||
"cache_hit_rate": "%",
|
||||
"api_cost": "$",
|
||||
"time_to_report": "min",
|
||||
"human_involvement": "%",
|
||||
"local_artifacts": ""
|
||||
} %}
|
||||
|
||||
{% if alerts %}
|
||||
<div class="sov-alerts">
|
||||
{% for alert in alerts %}
|
||||
<div class="sov-alert-item">
|
||||
<span class="sov-alert-icon">!</span>
|
||||
<span>{{ alert.message }}</span>
|
||||
</div>
|
||||
{% endfor %}
|
||||
</div>
|
||||
{% endif %}
|
||||
|
||||
<div class="grid grid-3">
|
||||
{% for key, data in metrics.items() %}
|
||||
{% set label = metric_labels.get(key, key) %}
|
||||
{% set unit = metric_units.get(key, "") %}
|
||||
{% set phase = data.phase %}
|
||||
{% set color = phase_colors.get(phase, "var(--text-dim)") %}
|
||||
<div class="stat">
|
||||
<div class="stat-value" style="color: {{ color }}">
|
||||
{% if data.current is not none %}
|
||||
{% if key == "cache_hit_rate" or key == "human_involvement" %}
|
||||
{{ "%.0f"|format(data.current * 100) }}{{ unit }}
|
||||
{% elif key == "api_cost" %}
|
||||
{{ unit }}{{ "%.2f"|format(data.current) }}
|
||||
{% elif key == "time_to_report" %}
|
||||
{{ "%.1f"|format(data.current) }}{{ unit }}
|
||||
{% else %}
|
||||
{{ data.current|int }}
|
||||
{% endif %}
|
||||
{% else %}
|
||||
--
|
||||
{% endif %}
|
||||
</div>
|
||||
<div class="stat-label">{{ label }}</div>
|
||||
<div class="stat-label" style="font-size: 0.7rem; color: {{ color }}">
|
||||
{{ phase_labels.get(phase, phase) }}
|
||||
</div>
|
||||
</div>
|
||||
{% endfor %}
|
||||
</div>
|
||||
@@ -1,264 +0,0 @@
|
||||
"""
|
||||
claude_quota.py — Claude Code / Claude.ai Quota Monitor
|
||||
|
||||
Drop into src/infrastructure/ in the Timmy Time Dashboard repo.
|
||||
|
||||
Provides real-time quota visibility and metabolic protocol decisions.
|
||||
|
||||
Usage:
|
||||
from infrastructure.claude_quota import QuotaMonitor
|
||||
|
||||
monitor = QuotaMonitor()
|
||||
status = monitor.check()
|
||||
print(status.five_hour_pct) # 42
|
||||
print(status.five_hour_resets_in) # "2h 15m"
|
||||
print(status.seven_day_pct) # 29
|
||||
print(status.recommended_tier) # MetabolicTier.BURST
|
||||
|
||||
# Metabolic protocol: auto-select model based on quota
|
||||
model = monitor.select_model(task_complexity="high")
|
||||
# Returns "claude-sonnet-4-6" if quota allows, else "qwen3:14b"
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import subprocess
|
||||
import urllib.request
|
||||
from dataclasses import dataclass
|
||||
from datetime import UTC, datetime
|
||||
from enum import StrEnum
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class MetabolicTier(StrEnum):
|
||||
"""The three-tier metabolic protocol from the Timmy Time architecture."""
|
||||
|
||||
BURST = "burst" # Cloud API (Claude/Groq) — expensive, best quality
|
||||
ACTIVE = "active" # Local 14B (Qwen3-14B) — free, good quality
|
||||
RESTING = "resting" # Local 8B (Qwen3-8B) — free, fast, adequate
|
||||
|
||||
|
||||
@dataclass
|
||||
class QuotaStatus:
|
||||
"""Current Claude quota state."""
|
||||
|
||||
five_hour_utilization: float # 0.0 to 1.0
|
||||
five_hour_resets_at: str | None
|
||||
seven_day_utilization: float # 0.0 to 1.0
|
||||
seven_day_resets_at: str | None
|
||||
raw_response: dict
|
||||
fetched_at: datetime
|
||||
|
||||
@property
|
||||
def five_hour_pct(self) -> int:
|
||||
return int(self.five_hour_utilization * 100)
|
||||
|
||||
@property
|
||||
def seven_day_pct(self) -> int:
|
||||
return int(self.seven_day_utilization * 100)
|
||||
|
||||
@property
|
||||
def five_hour_resets_in(self) -> str:
|
||||
return _time_remaining(self.five_hour_resets_at)
|
||||
|
||||
@property
|
||||
def seven_day_resets_in(self) -> str:
|
||||
return _time_remaining(self.seven_day_resets_at)
|
||||
|
||||
@property
|
||||
def recommended_tier(self) -> MetabolicTier:
|
||||
"""Metabolic protocol: determine which inference tier to use."""
|
||||
# If weekly quota is critical, go full local
|
||||
if self.seven_day_utilization >= 0.80:
|
||||
return MetabolicTier.RESTING
|
||||
# If 5-hour window is critical or past half, use local
|
||||
if self.five_hour_utilization >= 0.50:
|
||||
return MetabolicTier.ACTIVE
|
||||
# Quota healthy — cloud available for high-value tasks
|
||||
return MetabolicTier.BURST
|
||||
|
||||
def summary(self) -> str:
|
||||
"""Human-readable status string."""
|
||||
return (
|
||||
f"5h: {self.five_hour_pct}% (resets {self.five_hour_resets_in}) | "
|
||||
f"7d: {self.seven_day_pct}% (resets {self.seven_day_resets_in}) | "
|
||||
f"tier: {self.recommended_tier.value}"
|
||||
)
|
||||
|
||||
|
||||
class QuotaMonitor:
|
||||
"""
|
||||
Monitors Claude Code / Claude.ai quota via the internal OAuth API.
|
||||
|
||||
The token is read from macOS Keychain where Claude Code stores it.
|
||||
Falls back gracefully if credentials aren't available (e.g., on Linux VPS).
|
||||
"""
|
||||
|
||||
API_URL = "https://api.anthropic.com/api/oauth/usage"
|
||||
KEYCHAIN_SERVICE = "Claude Code-credentials"
|
||||
USER_AGENT = "claude-code/2.0.32"
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._token: str | None = None
|
||||
self._last_status: QuotaStatus | None = None
|
||||
self._cache_seconds = 30 # Don't hammer the API
|
||||
|
||||
def _get_token(self) -> str | None:
|
||||
"""Extract OAuth token from macOS Keychain."""
|
||||
if self._token:
|
||||
return self._token
|
||||
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["security", "find-generic-password", "-s", self.KEYCHAIN_SERVICE, "-w"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=5,
|
||||
)
|
||||
if result.returncode != 0:
|
||||
logger.warning("Claude Code credentials not found in Keychain")
|
||||
return None
|
||||
|
||||
creds = json.loads(result.stdout.strip())
|
||||
oauth = creds.get("claudeAiOauth", creds)
|
||||
self._token = oauth.get("accessToken")
|
||||
return self._token
|
||||
|
||||
except (
|
||||
json.JSONDecodeError,
|
||||
KeyError,
|
||||
FileNotFoundError,
|
||||
subprocess.TimeoutExpired,
|
||||
) as exc:
|
||||
logger.warning("Could not read Claude Code credentials: %s", exc)
|
||||
return None
|
||||
|
||||
def check(self, force: bool = False) -> QuotaStatus | None:
|
||||
"""
|
||||
Fetch current quota status.
|
||||
|
||||
Returns None if credentials aren't available (graceful degradation).
|
||||
Caches results for 30 seconds to avoid rate limiting the quota API itself.
|
||||
"""
|
||||
# Return cached if fresh
|
||||
if not force and self._last_status:
|
||||
age = (datetime.now(UTC) - self._last_status.fetched_at).total_seconds()
|
||||
if age < self._cache_seconds:
|
||||
return self._last_status
|
||||
|
||||
token = self._get_token()
|
||||
if not token:
|
||||
return None
|
||||
|
||||
try:
|
||||
req = urllib.request.Request(
|
||||
self.API_URL,
|
||||
headers={
|
||||
"Accept": "application/json",
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": self.USER_AGENT,
|
||||
"Authorization": f"Bearer {token}",
|
||||
"anthropic-beta": "oauth-2025-04-20",
|
||||
},
|
||||
)
|
||||
with urllib.request.urlopen(req, timeout=10) as resp:
|
||||
data = json.loads(resp.read().decode())
|
||||
|
||||
five_hour = data.get("five_hour") or {}
|
||||
seven_day = data.get("seven_day") or {}
|
||||
|
||||
self._last_status = QuotaStatus(
|
||||
five_hour_utilization=float(five_hour.get("utilization", 0.0)),
|
||||
five_hour_resets_at=five_hour.get("resets_at"),
|
||||
seven_day_utilization=float(seven_day.get("utilization", 0.0)),
|
||||
seven_day_resets_at=seven_day.get("resets_at"),
|
||||
raw_response=data,
|
||||
fetched_at=datetime.now(UTC),
|
||||
)
|
||||
return self._last_status
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to fetch quota: %s", exc)
|
||||
return self._last_status # Return stale data if available
|
||||
|
||||
def select_model(self, task_complexity: str = "medium") -> str:
|
||||
"""
|
||||
Metabolic protocol: select the right model based on quota + task complexity.
|
||||
|
||||
Returns an Ollama model tag or "claude-sonnet-4-6" for cloud.
|
||||
|
||||
task_complexity: "low" | "medium" | "high"
|
||||
"""
|
||||
status = self.check()
|
||||
|
||||
# No quota info available — assume local only (sovereign default)
|
||||
if status is None:
|
||||
return "qwen3:14b" if task_complexity == "high" else "qwen3:8b"
|
||||
|
||||
tier = status.recommended_tier
|
||||
|
||||
if tier == MetabolicTier.BURST and task_complexity == "high":
|
||||
return "claude-sonnet-4-6" # Cloud — best quality
|
||||
elif tier == MetabolicTier.BURST and task_complexity == "medium":
|
||||
return "qwen3:14b" # Save cloud for truly hard tasks
|
||||
elif tier == MetabolicTier.ACTIVE:
|
||||
return "qwen3:14b" # Local 14B — good enough
|
||||
else: # RESTING
|
||||
return "qwen3:8b" # Local 8B — conserve everything
|
||||
|
||||
def should_use_cloud(self, task_value: str = "normal") -> bool:
|
||||
"""
|
||||
Simple yes/no: should this task use cloud API?
|
||||
|
||||
task_value: "critical" | "high" | "normal" | "routine"
|
||||
"""
|
||||
status = self.check()
|
||||
|
||||
if status is None:
|
||||
return False # No credentials = local only
|
||||
|
||||
if task_value == "critical":
|
||||
return status.seven_day_utilization < 0.95 # Almost always yes
|
||||
elif task_value == "high":
|
||||
return status.five_hour_utilization < 0.60
|
||||
elif task_value == "normal":
|
||||
return status.five_hour_utilization < 0.30
|
||||
else: # routine
|
||||
return False # Never waste cloud on routine
|
||||
|
||||
|
||||
def _time_remaining(reset_at: str | None) -> str:
|
||||
"""Format time until reset as human-readable string."""
|
||||
if not reset_at or reset_at == "null":
|
||||
return "unknown"
|
||||
|
||||
try:
|
||||
reset = datetime.fromisoformat(reset_at.replace("Z", "+00:00"))
|
||||
now = datetime.now(UTC)
|
||||
diff = reset - now
|
||||
|
||||
if diff.total_seconds() <= 0:
|
||||
return "resetting now"
|
||||
|
||||
hours = int(diff.total_seconds() // 3600)
|
||||
mins = int((diff.total_seconds() % 3600) // 60)
|
||||
|
||||
if hours > 0:
|
||||
return f"{hours}h {mins}m"
|
||||
return f"{mins}m"
|
||||
|
||||
except (ValueError, TypeError):
|
||||
return "unknown"
|
||||
|
||||
|
||||
# Module-level singleton
|
||||
_quota_monitor: QuotaMonitor | None = None
|
||||
|
||||
|
||||
def get_quota_monitor() -> QuotaMonitor:
|
||||
"""Get or create the quota monitor singleton."""
|
||||
global _quota_monitor
|
||||
if _quota_monitor is None:
|
||||
_quota_monitor = QuotaMonitor()
|
||||
return _quota_monitor
|
||||
@@ -1,7 +0,0 @@
|
||||
"""Content moderation pipeline for AI narrator output.
|
||||
|
||||
Three-layer defense:
|
||||
1. Game-context system prompts (vocabulary whitelists, theme framing)
|
||||
2. Real-time output filter via Llama Guard (or fallback regex)
|
||||
3. Per-game moderation profiles with configurable thresholds
|
||||
"""
|
||||
@@ -1,497 +0,0 @@
|
||||
"""Content moderation pipeline for AI narrator output.
|
||||
|
||||
Three-layer defense against harmful LLM output:
|
||||
|
||||
Layer 1 — Game-context system prompts with per-game vocabulary whitelists.
|
||||
Layer 2 — Real-time output filter (Llama Guard via Ollama, regex fallback).
|
||||
Layer 3 — Per-game moderation profiles with configurable thresholds.
|
||||
|
||||
Usage:
|
||||
from infrastructure.guards.moderation import get_moderator
|
||||
|
||||
moderator = get_moderator()
|
||||
result = await moderator.check("Some narrator text", game="morrowind")
|
||||
if result.blocked:
|
||||
use_fallback_narration(result.fallback)
|
||||
"""
|
||||
|
||||
import logging
|
||||
import re
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import UTC, datetime
|
||||
from enum import Enum
|
||||
from typing import Any
|
||||
|
||||
from config import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class ModerationVerdict(Enum):
|
||||
"""Result of a moderation check."""
|
||||
|
||||
PASS = "pass" # noqa: S105
|
||||
FAIL = "fail"
|
||||
ERROR = "error"
|
||||
|
||||
|
||||
class ViolationCategory(Enum):
|
||||
"""Categories of content violations."""
|
||||
|
||||
HATE_SPEECH = "hate_speech"
|
||||
VIOLENCE_GLORIFICATION = "violence_glorification"
|
||||
REAL_WORLD_HARM = "real_world_harm"
|
||||
SEXUAL_CONTENT = "sexual_content"
|
||||
SELF_HARM = "self_harm"
|
||||
NONE = "none"
|
||||
|
||||
|
||||
@dataclass
|
||||
class ModerationResult:
|
||||
"""Result from the moderation pipeline."""
|
||||
|
||||
verdict: ModerationVerdict
|
||||
blocked: bool
|
||||
category: ViolationCategory = ViolationCategory.NONE
|
||||
confidence: float = 0.0
|
||||
latency_ms: float = 0.0
|
||||
layer: str = "" # Which layer caught it
|
||||
fallback: str = "" # Contextual fallback narration
|
||||
reason: str = ""
|
||||
timestamp: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
|
||||
|
||||
@property
|
||||
def passed(self) -> bool:
|
||||
return self.verdict == ModerationVerdict.PASS
|
||||
|
||||
|
||||
@dataclass
|
||||
class GameProfile:
|
||||
"""Per-game moderation profile.
|
||||
|
||||
Defines vocabulary whitelists, theme framing rules,
|
||||
and threshold tuning for a specific game.
|
||||
"""
|
||||
|
||||
game_id: str
|
||||
display_name: str
|
||||
# Terms that are safe in game context (e.g., "Skooma", "slave", "Morag Tong")
|
||||
vocabulary_whitelist: list[str] = field(default_factory=list)
|
||||
# System prompt additions for game-context framing
|
||||
context_prompt: str = ""
|
||||
# Confidence threshold — below this, content passes even if flagged
|
||||
threshold: float = 0.8
|
||||
# Scene-type fallback narrations
|
||||
fallbacks: dict[str, str] = field(default_factory=dict)
|
||||
|
||||
|
||||
# ── Regex fallback patterns ─────────────────────────────────────────────────
|
||||
# Used when Llama Guard is unavailable. Catches obvious violations only.
|
||||
# Intentionally conservative — false negatives preferred over false positives.
|
||||
_FALLBACK_PATTERNS: list[tuple[re.Pattern, ViolationCategory]] = [
|
||||
(
|
||||
re.compile(
|
||||
r"\b(kill\s+(?:all|every)\s+(?:real|actual)\s+(?:people|humans|children))\b",
|
||||
re.IGNORECASE,
|
||||
),
|
||||
ViolationCategory.REAL_WORLD_HARM,
|
||||
),
|
||||
(
|
||||
re.compile(
|
||||
r"\b((?:you|we)\s+should\s+(?:actually|really)\s+(?:harm|hurt|kill))\b",
|
||||
re.IGNORECASE,
|
||||
),
|
||||
ViolationCategory.REAL_WORLD_HARM,
|
||||
),
|
||||
(
|
||||
re.compile(
|
||||
r"\b((?:in\s+real\s+life|irl)\s+(?:you|we)\s+(?:should|could|must)\s+"
|
||||
r"(?:attack|hurt|kill|harm))\b",
|
||||
re.IGNORECASE,
|
||||
),
|
||||
ViolationCategory.REAL_WORLD_HARM,
|
||||
),
|
||||
]
|
||||
|
||||
# ── Default game profiles ───────────────────────────────────────────────────
|
||||
|
||||
_DEFAULT_PROFILES: dict[str, GameProfile] = {
|
||||
"morrowind": GameProfile(
|
||||
game_id="morrowind",
|
||||
display_name="The Elder Scrolls III: Morrowind",
|
||||
vocabulary_whitelist=[
|
||||
"Skooma",
|
||||
"Moon Sugar",
|
||||
"slave",
|
||||
"slavery",
|
||||
"Morag Tong",
|
||||
"Dark Brotherhood",
|
||||
"Telvanni",
|
||||
"Camonna Tong",
|
||||
"smuggler",
|
||||
"assassin",
|
||||
"Sixth House",
|
||||
"Corprus",
|
||||
"Dagoth Ur",
|
||||
"Nerevarine",
|
||||
],
|
||||
context_prompt=(
|
||||
"You are narrating gameplay of The Elder Scrolls III: Morrowind. "
|
||||
"Morrowind contains mature themes including slavery, drug use (Skooma/Moon Sugar), "
|
||||
"assassin guilds (Morag Tong, Dark Brotherhood), and political intrigue. "
|
||||
"Treat these as game mechanics and historical worldbuilding within the game's "
|
||||
"fictional universe. Never editorialize on real-world parallels. "
|
||||
"Narrate events neutrally as a game commentator would."
|
||||
),
|
||||
threshold=0.85,
|
||||
fallbacks={
|
||||
"combat": "The battle rages on in the ashlands of Vvardenfell.",
|
||||
"dialogue": "The conversation continues between the characters.",
|
||||
"exploration": "The Nerevarine presses onward through the landscape.",
|
||||
"default": "The adventure continues in Morrowind.",
|
||||
},
|
||||
),
|
||||
"default": GameProfile(
|
||||
game_id="default",
|
||||
display_name="Generic Game",
|
||||
vocabulary_whitelist=[],
|
||||
context_prompt=(
|
||||
"You are narrating gameplay. Describe in-game events as a neutral "
|
||||
"game commentator. Never reference real-world violence, politics, "
|
||||
"or controversial topics. Stay focused on game mechanics and story."
|
||||
),
|
||||
threshold=0.8,
|
||||
fallbacks={
|
||||
"combat": "The action continues on screen.",
|
||||
"dialogue": "The conversation unfolds between characters.",
|
||||
"exploration": "The player explores the game world.",
|
||||
"default": "The gameplay continues.",
|
||||
},
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
class ContentModerator:
|
||||
"""Three-layer content moderation pipeline.
|
||||
|
||||
Layer 1: Game-context system prompts with vocabulary whitelists.
|
||||
Layer 2: LLM-based moderation (Llama Guard via Ollama, with regex fallback).
|
||||
Layer 3: Per-game threshold tuning and profile-based filtering.
|
||||
|
||||
Follows graceful degradation — if Llama Guard is unavailable,
|
||||
falls back to regex patterns. Never crashes.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
profiles: dict[str, GameProfile] | None = None,
|
||||
guard_model: str | None = None,
|
||||
) -> None:
|
||||
self._profiles: dict[str, GameProfile] = profiles or dict(_DEFAULT_PROFILES)
|
||||
self._guard_model = guard_model or settings.moderation_guard_model
|
||||
self._guard_available: bool | None = None # Lazy-checked
|
||||
self._metrics = _ModerationMetrics()
|
||||
|
||||
def get_profile(self, game: str) -> GameProfile:
|
||||
"""Get the moderation profile for a game, falling back to default."""
|
||||
return self._profiles.get(game, self._profiles["default"])
|
||||
|
||||
def register_profile(self, profile: GameProfile) -> None:
|
||||
"""Register or update a game moderation profile."""
|
||||
self._profiles[profile.game_id] = profile
|
||||
logger.info("Registered moderation profile: %s", profile.game_id)
|
||||
|
||||
def get_context_prompt(self, game: str) -> str:
|
||||
"""Get the game-context system prompt (Layer 1).
|
||||
|
||||
Returns the context prompt for the given game, which should be
|
||||
prepended to the narrator's system prompt.
|
||||
"""
|
||||
profile = self.get_profile(game)
|
||||
return profile.context_prompt
|
||||
|
||||
async def check(
|
||||
self,
|
||||
text: str,
|
||||
game: str = "default",
|
||||
scene_type: str = "default",
|
||||
) -> ModerationResult:
|
||||
"""Run the full moderation pipeline on narrator output.
|
||||
|
||||
Args:
|
||||
text: The text to moderate (narrator output).
|
||||
game: Game identifier for profile selection.
|
||||
scene_type: Current scene type for fallback selection.
|
||||
|
||||
Returns:
|
||||
ModerationResult with verdict, confidence, and fallback.
|
||||
"""
|
||||
start = time.monotonic()
|
||||
profile = self.get_profile(game)
|
||||
|
||||
# Layer 1: Vocabulary whitelist pre-processing
|
||||
cleaned_text = self._apply_whitelist(text, profile)
|
||||
|
||||
# Layer 2: LLM guard or regex fallback
|
||||
result = await self._run_guard(cleaned_text, profile)
|
||||
|
||||
# Layer 3: Threshold tuning
|
||||
if result.verdict == ModerationVerdict.FAIL and result.confidence < profile.threshold:
|
||||
logger.info(
|
||||
"Moderation flag below threshold (%.2f < %.2f) — allowing",
|
||||
result.confidence,
|
||||
profile.threshold,
|
||||
)
|
||||
result = ModerationResult(
|
||||
verdict=ModerationVerdict.PASS,
|
||||
blocked=False,
|
||||
confidence=result.confidence,
|
||||
layer="threshold",
|
||||
reason=f"Below threshold ({result.confidence:.2f} < {profile.threshold:.2f})",
|
||||
)
|
||||
|
||||
# Attach fallback narration if blocked
|
||||
if result.blocked:
|
||||
result.fallback = profile.fallbacks.get(
|
||||
scene_type, profile.fallbacks.get("default", "")
|
||||
)
|
||||
|
||||
result.latency_ms = (time.monotonic() - start) * 1000
|
||||
self._metrics.record(result)
|
||||
|
||||
if result.blocked:
|
||||
logger.warning(
|
||||
"Content blocked [%s/%s]: category=%s confidence=%.2f reason=%s",
|
||||
game,
|
||||
scene_type,
|
||||
result.category.value,
|
||||
result.confidence,
|
||||
result.reason,
|
||||
)
|
||||
|
||||
return result
|
||||
|
||||
def _apply_whitelist(self, text: str, profile: GameProfile) -> str:
|
||||
"""Layer 1: Replace whitelisted game terms with placeholders.
|
||||
|
||||
This prevents the guard model from flagging in-game terminology
|
||||
(e.g., "Skooma" being flagged as drug reference).
|
||||
"""
|
||||
cleaned = text
|
||||
for term in profile.vocabulary_whitelist:
|
||||
# Case-insensitive replacement with a neutral placeholder
|
||||
pattern = re.compile(re.escape(term), re.IGNORECASE)
|
||||
cleaned = pattern.sub("[GAME_TERM]", cleaned)
|
||||
return cleaned
|
||||
|
||||
async def _run_guard(self, text: str, profile: GameProfile) -> ModerationResult:
|
||||
"""Layer 2: Run LLM guard model or fall back to regex."""
|
||||
if not settings.moderation_enabled:
|
||||
return ModerationResult(
|
||||
verdict=ModerationVerdict.PASS,
|
||||
blocked=False,
|
||||
layer="disabled",
|
||||
reason="Moderation disabled",
|
||||
)
|
||||
|
||||
# Try Llama Guard via Ollama
|
||||
if await self._is_guard_available():
|
||||
try:
|
||||
return await self._check_with_guard(text)
|
||||
except Exception as exc:
|
||||
logger.warning("Guard model failed, using regex fallback: %s", exc)
|
||||
self._guard_available = False
|
||||
|
||||
# Regex fallback
|
||||
return self._check_with_regex(text)
|
||||
|
||||
async def _is_guard_available(self) -> bool:
|
||||
"""Check if the guard model is available via Ollama."""
|
||||
if self._guard_available is not None:
|
||||
return self._guard_available
|
||||
|
||||
try:
|
||||
import aiohttp
|
||||
|
||||
url = f"{settings.normalized_ollama_url}/api/tags"
|
||||
timeout = aiohttp.ClientTimeout(total=5)
|
||||
async with aiohttp.ClientSession(timeout=timeout) as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
self._guard_available = False
|
||||
return False
|
||||
data = await resp.json()
|
||||
models = [m.get("name", "") for m in data.get("models", [])]
|
||||
self._guard_available = any(
|
||||
self._guard_model in m or m.startswith(self._guard_model) for m in models
|
||||
)
|
||||
if not self._guard_available:
|
||||
logger.info(
|
||||
"Guard model '%s' not found in Ollama — using regex fallback",
|
||||
self._guard_model,
|
||||
)
|
||||
return self._guard_available
|
||||
except Exception as exc:
|
||||
logger.debug("Ollama guard check failed: %s", exc)
|
||||
self._guard_available = False
|
||||
return False
|
||||
|
||||
async def _check_with_guard(self, text: str) -> ModerationResult:
|
||||
"""Run moderation check via Llama Guard."""
|
||||
import aiohttp
|
||||
|
||||
url = f"{settings.normalized_ollama_url}/api/chat"
|
||||
payload = {
|
||||
"model": self._guard_model,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": text,
|
||||
}
|
||||
],
|
||||
"stream": False,
|
||||
"options": {"temperature": 0.0},
|
||||
}
|
||||
|
||||
timeout = aiohttp.ClientTimeout(total=10)
|
||||
async with aiohttp.ClientSession(timeout=timeout) as session:
|
||||
async with session.post(url, json=payload) as resp:
|
||||
if resp.status != 200:
|
||||
raise RuntimeError(f"Guard API error: {resp.status}")
|
||||
data = await resp.json()
|
||||
|
||||
response_text = data.get("message", {}).get("content", "").strip().lower()
|
||||
|
||||
# Llama Guard returns "safe" or "unsafe\n<category>"
|
||||
if response_text.startswith("safe"):
|
||||
return ModerationResult(
|
||||
verdict=ModerationVerdict.PASS,
|
||||
blocked=False,
|
||||
confidence=0.0,
|
||||
layer="llama_guard",
|
||||
reason="Content safe",
|
||||
)
|
||||
|
||||
# Parse unsafe response
|
||||
category = ViolationCategory.NONE
|
||||
confidence = 0.95 # High confidence from LLM guard
|
||||
lines = response_text.split("\n")
|
||||
if len(lines) > 1:
|
||||
cat_str = lines[1].strip()
|
||||
category = _parse_guard_category(cat_str)
|
||||
|
||||
return ModerationResult(
|
||||
verdict=ModerationVerdict.FAIL,
|
||||
blocked=True,
|
||||
category=category,
|
||||
confidence=confidence,
|
||||
layer="llama_guard",
|
||||
reason=f"Guard flagged: {response_text}",
|
||||
)
|
||||
|
||||
def _check_with_regex(self, text: str) -> ModerationResult:
|
||||
"""Regex fallback when guard model is unavailable.
|
||||
|
||||
Intentionally conservative — only catches obvious real-world harm.
|
||||
"""
|
||||
for pattern, category in _FALLBACK_PATTERNS:
|
||||
match = pattern.search(text)
|
||||
if match:
|
||||
return ModerationResult(
|
||||
verdict=ModerationVerdict.FAIL,
|
||||
blocked=True,
|
||||
category=category,
|
||||
confidence=0.95, # Regex patterns are high-signal
|
||||
layer="regex_fallback",
|
||||
reason=f"Regex match: {match.group(0)[:50]}",
|
||||
)
|
||||
|
||||
return ModerationResult(
|
||||
verdict=ModerationVerdict.PASS,
|
||||
blocked=False,
|
||||
layer="regex_fallback",
|
||||
reason="No regex matches",
|
||||
)
|
||||
|
||||
def get_metrics(self) -> dict[str, Any]:
|
||||
"""Get moderation pipeline metrics."""
|
||||
return self._metrics.to_dict()
|
||||
|
||||
def reset_guard_cache(self) -> None:
|
||||
"""Reset the guard availability cache (e.g., after pulling model)."""
|
||||
self._guard_available = None
|
||||
|
||||
|
||||
class _ModerationMetrics:
|
||||
"""Tracks moderation pipeline performance."""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.total_checks: int = 0
|
||||
self.passed: int = 0
|
||||
self.blocked: int = 0
|
||||
self.errors: int = 0
|
||||
self.total_latency_ms: float = 0.0
|
||||
self.by_layer: dict[str, int] = {}
|
||||
self.by_category: dict[str, int] = {}
|
||||
|
||||
def record(self, result: ModerationResult) -> None:
|
||||
self.total_checks += 1
|
||||
self.total_latency_ms += result.latency_ms
|
||||
|
||||
if result.verdict == ModerationVerdict.PASS:
|
||||
self.passed += 1
|
||||
elif result.verdict == ModerationVerdict.FAIL:
|
||||
self.blocked += 1
|
||||
else:
|
||||
self.errors += 1
|
||||
|
||||
layer = result.layer or "unknown"
|
||||
self.by_layer[layer] = self.by_layer.get(layer, 0) + 1
|
||||
|
||||
if result.blocked:
|
||||
cat = result.category.value
|
||||
self.by_category[cat] = self.by_category.get(cat, 0) + 1
|
||||
|
||||
def to_dict(self) -> dict[str, Any]:
|
||||
return {
|
||||
"total_checks": self.total_checks,
|
||||
"passed": self.passed,
|
||||
"blocked": self.blocked,
|
||||
"errors": self.errors,
|
||||
"avg_latency_ms": (
|
||||
round(self.total_latency_ms / self.total_checks, 2)
|
||||
if self.total_checks > 0
|
||||
else 0.0
|
||||
),
|
||||
"by_layer": dict(self.by_layer),
|
||||
"by_category": dict(self.by_category),
|
||||
}
|
||||
|
||||
|
||||
def _parse_guard_category(cat_str: str) -> ViolationCategory:
|
||||
"""Parse Llama Guard category string to ViolationCategory."""
|
||||
cat_lower = cat_str.lower()
|
||||
if "hate" in cat_lower:
|
||||
return ViolationCategory.HATE_SPEECH
|
||||
if "violence" in cat_lower:
|
||||
return ViolationCategory.VIOLENCE_GLORIFICATION
|
||||
if "sexual" in cat_lower:
|
||||
return ViolationCategory.SEXUAL_CONTENT
|
||||
if "self-harm" in cat_lower or "self_harm" in cat_lower or "suicide" in cat_lower:
|
||||
return ViolationCategory.SELF_HARM
|
||||
if "harm" in cat_lower or "dangerous" in cat_lower:
|
||||
return ViolationCategory.REAL_WORLD_HARM
|
||||
return ViolationCategory.NONE
|
||||
|
||||
|
||||
# ── Module-level singleton ──────────────────────────────────────────────────
|
||||
_moderator: ContentModerator | None = None
|
||||
|
||||
|
||||
def get_moderator() -> ContentModerator:
|
||||
"""Get or create the content moderator singleton."""
|
||||
global _moderator
|
||||
if _moderator is None:
|
||||
_moderator = ContentModerator()
|
||||
return _moderator
|
||||
@@ -1,56 +0,0 @@
|
||||
"""Load game moderation profiles from config/moderation.yaml.
|
||||
|
||||
Falls back to hardcoded defaults if the YAML file is missing or malformed.
|
||||
"""
|
||||
|
||||
import logging
|
||||
from pathlib import Path
|
||||
|
||||
from infrastructure.guards.moderation import GameProfile
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def load_profiles(config_path: Path | None = None) -> dict[str, GameProfile]:
|
||||
"""Load game moderation profiles from YAML config.
|
||||
|
||||
Args:
|
||||
config_path: Path to moderation.yaml. Defaults to config/moderation.yaml.
|
||||
|
||||
Returns:
|
||||
Dict mapping game_id to GameProfile.
|
||||
"""
|
||||
path = config_path or Path("config/moderation.yaml")
|
||||
|
||||
if not path.exists():
|
||||
logger.info("Moderation config not found at %s — using defaults", path)
|
||||
return {}
|
||||
|
||||
try:
|
||||
import yaml
|
||||
except ImportError:
|
||||
logger.warning("PyYAML not installed — using default moderation profiles")
|
||||
return {}
|
||||
|
||||
try:
|
||||
data = yaml.safe_load(path.read_text())
|
||||
except Exception as exc:
|
||||
logger.error("Failed to parse moderation config: %s", exc)
|
||||
return {}
|
||||
|
||||
profiles: dict[str, GameProfile] = {}
|
||||
for game_id, profile_data in data.get("profiles", {}).items():
|
||||
try:
|
||||
profiles[game_id] = GameProfile(
|
||||
game_id=game_id,
|
||||
display_name=profile_data.get("display_name", game_id),
|
||||
vocabulary_whitelist=profile_data.get("vocabulary_whitelist", []),
|
||||
context_prompt=profile_data.get("context_prompt", ""),
|
||||
threshold=float(profile_data.get("threshold", 0.8)),
|
||||
fallbacks=profile_data.get("fallbacks", {}),
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Invalid profile '%s': %s", game_id, exc)
|
||||
|
||||
logger.info("Loaded %d moderation profiles from %s", len(profiles), path)
|
||||
return profiles
|
||||
@@ -32,15 +32,6 @@ except ImportError:
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Quota monitor — optional, degrades gracefully if unavailable
|
||||
try:
|
||||
from infrastructure.claude_quota import QuotaMonitor, get_quota_monitor
|
||||
|
||||
_quota_monitor: "QuotaMonitor | None" = get_quota_monitor()
|
||||
except Exception as _exc: # pragma: no cover
|
||||
logger.debug("Quota monitor not available: %s", _exc)
|
||||
_quota_monitor = None
|
||||
|
||||
|
||||
class ProviderStatus(Enum):
|
||||
"""Health status of a provider."""
|
||||
@@ -310,22 +301,6 @@ class CascadeRouter:
|
||||
logger.debug("Ollama provider check error: %s", exc)
|
||||
return False
|
||||
|
||||
elif provider.type == "vllm_mlx":
|
||||
# Check if local vllm-mlx server is running (OpenAI-compatible)
|
||||
if requests is None:
|
||||
return True
|
||||
try:
|
||||
base_url = provider.base_url or provider.url or "http://localhost:8000"
|
||||
# Strip /v1 suffix — health endpoint is at the root
|
||||
server_root = base_url.rstrip("/")
|
||||
if server_root.endswith("/v1"):
|
||||
server_root = server_root[:-3]
|
||||
response = requests.get(f"{server_root}/health", timeout=5)
|
||||
return response.status_code == 200
|
||||
except Exception as exc:
|
||||
logger.debug("vllm-mlx provider check error: %s", exc)
|
||||
return False
|
||||
|
||||
elif provider.type in ("openai", "anthropic", "grok"):
|
||||
# Check if API key is set
|
||||
return provider.api_key is not None and provider.api_key != ""
|
||||
@@ -482,25 +457,6 @@ class CascadeRouter:
|
||||
|
||||
raise RuntimeError("; ".join(errors))
|
||||
|
||||
def _quota_allows_cloud(self, provider: Provider) -> bool:
|
||||
"""Check quota before routing to a cloud provider.
|
||||
|
||||
Uses the metabolic protocol: cloud calls are gated by 5-hour quota.
|
||||
Returns True (allow cloud) if quota monitor is unavailable or returns None.
|
||||
"""
|
||||
if _quota_monitor is None:
|
||||
return True
|
||||
try:
|
||||
# Map provider type to task_value heuristic
|
||||
task_value = "high" # conservative default
|
||||
status = _quota_monitor.check()
|
||||
if status is None:
|
||||
return True # No credentials — caller decides based on config
|
||||
return _quota_monitor.should_use_cloud(task_value)
|
||||
except Exception as exc:
|
||||
logger.warning("Quota check failed, allowing cloud: %s", exc)
|
||||
return True
|
||||
|
||||
def _is_provider_available(self, provider: Provider) -> bool:
|
||||
"""Check if a provider should be tried (enabled + circuit breaker)."""
|
||||
if not provider.enabled:
|
||||
@@ -554,15 +510,6 @@ class CascadeRouter:
|
||||
if not self._is_provider_available(provider):
|
||||
continue
|
||||
|
||||
# Metabolic protocol: skip cloud providers when quota is low
|
||||
if provider.type in ("anthropic", "openai", "grok"):
|
||||
if not self._quota_allows_cloud(provider):
|
||||
logger.info(
|
||||
"Metabolic protocol: skipping cloud provider %s (quota too low)",
|
||||
provider.name,
|
||||
)
|
||||
continue
|
||||
|
||||
selected_model, is_fallback_model = self._select_model(provider, model, content_type)
|
||||
|
||||
try:
|
||||
@@ -635,14 +582,6 @@ class CascadeRouter:
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
)
|
||||
elif provider.type == "vllm_mlx":
|
||||
result = await self._call_vllm_mlx(
|
||||
provider=provider,
|
||||
messages=messages,
|
||||
model=model or provider.get_default_model(),
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unknown provider type: {provider.type}")
|
||||
|
||||
@@ -839,48 +778,6 @@ class CascadeRouter:
|
||||
"model": response.model,
|
||||
}
|
||||
|
||||
async def _call_vllm_mlx(
|
||||
self,
|
||||
provider: Provider,
|
||||
messages: list[dict],
|
||||
model: str,
|
||||
temperature: float,
|
||||
max_tokens: int | None,
|
||||
) -> dict:
|
||||
"""Call vllm-mlx via its OpenAI-compatible API.
|
||||
|
||||
vllm-mlx exposes the same /v1/chat/completions endpoint as OpenAI,
|
||||
so we reuse the OpenAI client pointed at the local server.
|
||||
No API key is required for local deployments.
|
||||
"""
|
||||
import openai
|
||||
|
||||
base_url = provider.base_url or provider.url or "http://localhost:8000"
|
||||
# Ensure the base_url ends with /v1 as expected by the OpenAI client
|
||||
if not base_url.rstrip("/").endswith("/v1"):
|
||||
base_url = base_url.rstrip("/") + "/v1"
|
||||
|
||||
client = openai.AsyncOpenAI(
|
||||
api_key=provider.api_key or "no-key-required",
|
||||
base_url=base_url,
|
||||
timeout=self.config.timeout_seconds,
|
||||
)
|
||||
|
||||
kwargs: dict = {
|
||||
"model": model,
|
||||
"messages": messages,
|
||||
"temperature": temperature,
|
||||
}
|
||||
if max_tokens:
|
||||
kwargs["max_tokens"] = max_tokens
|
||||
|
||||
response = await client.chat.completions.create(**kwargs)
|
||||
|
||||
return {
|
||||
"content": response.choices[0].message.content,
|
||||
"model": response.model,
|
||||
}
|
||||
|
||||
def _record_success(self, provider: Provider, latency_ms: float) -> None:
|
||||
"""Record a successful request."""
|
||||
provider.metrics.total_requests += 1
|
||||
|
||||
@@ -1,306 +0,0 @@
|
||||
"""Sovereignty metrics collector and store.
|
||||
|
||||
Tracks research sovereignty progress: cache hit rate, API cost,
|
||||
time-to-report, and human involvement. Persists to SQLite for
|
||||
trend analysis and dashboard display.
|
||||
|
||||
Refs: #981
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import sqlite3
|
||||
from contextlib import closing
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import UTC, datetime
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
from config import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
DB_PATH = Path(settings.repo_root) / "data" / "sovereignty_metrics.db"
|
||||
|
||||
_SCHEMA = """
|
||||
CREATE TABLE IF NOT EXISTS sovereignty_metrics (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
timestamp TEXT NOT NULL,
|
||||
metric_type TEXT NOT NULL,
|
||||
value REAL NOT NULL,
|
||||
metadata TEXT DEFAULT '{}'
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_sm_type ON sovereignty_metrics(metric_type);
|
||||
CREATE INDEX IF NOT EXISTS idx_sm_ts ON sovereignty_metrics(timestamp);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS sovereignty_alerts (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
timestamp TEXT NOT NULL,
|
||||
alert_type TEXT NOT NULL,
|
||||
message TEXT NOT NULL,
|
||||
value REAL NOT NULL,
|
||||
threshold REAL NOT NULL,
|
||||
acknowledged INTEGER DEFAULT 0
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_sa_ts ON sovereignty_alerts(timestamp);
|
||||
CREATE INDEX IF NOT EXISTS idx_sa_ack ON sovereignty_alerts(acknowledged);
|
||||
"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class SovereigntyMetric:
|
||||
"""A single sovereignty metric data point."""
|
||||
|
||||
metric_type: str # cache_hit_rate, api_cost, time_to_report, human_involvement
|
||||
value: float
|
||||
timestamp: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
|
||||
metadata: dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
class SovereigntyAlert:
|
||||
"""An alert triggered when a metric exceeds a threshold."""
|
||||
|
||||
alert_type: str
|
||||
message: str
|
||||
value: float
|
||||
threshold: float
|
||||
timestamp: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
|
||||
acknowledged: bool = False
|
||||
|
||||
|
||||
# Graduation targets from issue #981
|
||||
GRADUATION_TARGETS = {
|
||||
"cache_hit_rate": {"week1": 0.10, "month1": 0.40, "month3": 0.80, "graduation": 0.90},
|
||||
"api_cost": {"week1": 1.50, "month1": 0.50, "month3": 0.10, "graduation": 0.01},
|
||||
"time_to_report": {"week1": 180.0, "month1": 30.0, "month3": 5.0, "graduation": 1.0},
|
||||
"human_involvement": {"week1": 1.0, "month1": 0.5, "month3": 0.25, "graduation": 0.0},
|
||||
"local_artifacts": {"week1": 6, "month1": 30, "month3": 100, "graduation": 500},
|
||||
}
|
||||
|
||||
|
||||
class SovereigntyMetricsStore:
|
||||
"""SQLite-backed sovereignty metrics store.
|
||||
|
||||
Thread-safe: creates a new connection per operation.
|
||||
"""
|
||||
|
||||
def __init__(self, db_path: Path | None = None) -> None:
|
||||
self._db_path = db_path or DB_PATH
|
||||
self._init_db()
|
||||
|
||||
def _init_db(self) -> None:
|
||||
"""Initialize the database schema."""
|
||||
try:
|
||||
self._db_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
with closing(sqlite3.connect(str(self._db_path))) as conn:
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute(f"PRAGMA busy_timeout={settings.db_busy_timeout_ms}")
|
||||
conn.executescript(_SCHEMA)
|
||||
conn.commit()
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to initialize sovereignty metrics DB: %s", exc)
|
||||
|
||||
def _connect(self) -> sqlite3.Connection:
|
||||
"""Get a new connection."""
|
||||
conn = sqlite3.connect(str(self._db_path))
|
||||
conn.row_factory = sqlite3.Row
|
||||
conn.execute(f"PRAGMA busy_timeout={settings.db_busy_timeout_ms}")
|
||||
return conn
|
||||
|
||||
def record(self, metric: SovereigntyMetric) -> None:
|
||||
"""Record a sovereignty metric data point."""
|
||||
try:
|
||||
with closing(self._connect()) as conn:
|
||||
conn.execute(
|
||||
"INSERT INTO sovereignty_metrics (timestamp, metric_type, value, metadata) "
|
||||
"VALUES (?, ?, ?, ?)",
|
||||
(
|
||||
metric.timestamp,
|
||||
metric.metric_type,
|
||||
metric.value,
|
||||
json.dumps(metric.metadata),
|
||||
),
|
||||
)
|
||||
conn.commit()
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to record sovereignty metric: %s", exc)
|
||||
|
||||
# Check thresholds for alerts
|
||||
self._check_alert(metric)
|
||||
|
||||
def _check_alert(self, metric: SovereigntyMetric) -> None:
|
||||
"""Check if a metric triggers an alert."""
|
||||
threshold = settings.sovereignty_api_cost_alert_threshold
|
||||
if metric.metric_type == "api_cost" and metric.value > threshold:
|
||||
alert = SovereigntyAlert(
|
||||
alert_type="api_cost_exceeded",
|
||||
message=f"API cost ${metric.value:.2f} exceeds threshold ${threshold:.2f}",
|
||||
value=metric.value,
|
||||
threshold=threshold,
|
||||
)
|
||||
self._record_alert(alert)
|
||||
|
||||
def _record_alert(self, alert: SovereigntyAlert) -> None:
|
||||
"""Persist an alert."""
|
||||
try:
|
||||
with closing(self._connect()) as conn:
|
||||
conn.execute(
|
||||
"INSERT INTO sovereignty_alerts "
|
||||
"(timestamp, alert_type, message, value, threshold) "
|
||||
"VALUES (?, ?, ?, ?, ?)",
|
||||
(
|
||||
alert.timestamp,
|
||||
alert.alert_type,
|
||||
alert.message,
|
||||
alert.value,
|
||||
alert.threshold,
|
||||
),
|
||||
)
|
||||
conn.commit()
|
||||
logger.warning("Sovereignty alert: %s", alert.message)
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to record sovereignty alert: %s", exc)
|
||||
|
||||
def get_latest(self, metric_type: str, limit: int = 50) -> list[dict]:
|
||||
"""Get the most recent metric values for a given type."""
|
||||
try:
|
||||
with closing(self._connect()) as conn:
|
||||
rows = conn.execute(
|
||||
"SELECT timestamp, value, metadata FROM sovereignty_metrics "
|
||||
"WHERE metric_type = ? ORDER BY timestamp DESC LIMIT ?",
|
||||
(metric_type, limit),
|
||||
).fetchall()
|
||||
return [
|
||||
{
|
||||
"timestamp": row["timestamp"],
|
||||
"value": row["value"],
|
||||
"metadata": json.loads(row["metadata"]) if row["metadata"] else {},
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to query sovereignty metrics: %s", exc)
|
||||
return []
|
||||
|
||||
def get_summary(self) -> dict[str, Any]:
|
||||
"""Get a summary of current sovereignty metrics progress."""
|
||||
summary: dict[str, Any] = {}
|
||||
for metric_type in GRADUATION_TARGETS:
|
||||
latest = self.get_latest(metric_type, limit=1)
|
||||
history = self.get_latest(metric_type, limit=30)
|
||||
|
||||
current_value = latest[0]["value"] if latest else None
|
||||
targets = GRADUATION_TARGETS[metric_type]
|
||||
|
||||
# Determine current phase based on value
|
||||
phase = "pre-start"
|
||||
if current_value is not None:
|
||||
if metric_type in ("api_cost", "time_to_report", "human_involvement"):
|
||||
# Lower is better
|
||||
if current_value <= targets["graduation"]:
|
||||
phase = "graduated"
|
||||
elif current_value <= targets["month3"]:
|
||||
phase = "month3"
|
||||
elif current_value <= targets["month1"]:
|
||||
phase = "month1"
|
||||
elif current_value <= targets["week1"]:
|
||||
phase = "week1"
|
||||
else:
|
||||
phase = "pre-start"
|
||||
else:
|
||||
# Higher is better
|
||||
if current_value >= targets["graduation"]:
|
||||
phase = "graduated"
|
||||
elif current_value >= targets["month3"]:
|
||||
phase = "month3"
|
||||
elif current_value >= targets["month1"]:
|
||||
phase = "month1"
|
||||
elif current_value >= targets["week1"]:
|
||||
phase = "week1"
|
||||
else:
|
||||
phase = "pre-start"
|
||||
|
||||
summary[metric_type] = {
|
||||
"current": current_value,
|
||||
"phase": phase,
|
||||
"targets": targets,
|
||||
"trend": [{"t": h["timestamp"], "v": h["value"]} for h in reversed(history)],
|
||||
}
|
||||
|
||||
return summary
|
||||
|
||||
def get_alerts(self, unacknowledged_only: bool = True, limit: int = 20) -> list[dict]:
|
||||
"""Get sovereignty alerts."""
|
||||
try:
|
||||
with closing(self._connect()) as conn:
|
||||
if unacknowledged_only:
|
||||
rows = conn.execute(
|
||||
"SELECT * FROM sovereignty_alerts "
|
||||
"WHERE acknowledged = 0 ORDER BY timestamp DESC LIMIT ?",
|
||||
(limit,),
|
||||
).fetchall()
|
||||
else:
|
||||
rows = conn.execute(
|
||||
"SELECT * FROM sovereignty_alerts ORDER BY timestamp DESC LIMIT ?",
|
||||
(limit,),
|
||||
).fetchall()
|
||||
return [dict(row) for row in rows]
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to query sovereignty alerts: %s", exc)
|
||||
return []
|
||||
|
||||
def acknowledge_alert(self, alert_id: int) -> bool:
|
||||
"""Acknowledge an alert."""
|
||||
try:
|
||||
with closing(self._connect()) as conn:
|
||||
conn.execute(
|
||||
"UPDATE sovereignty_alerts SET acknowledged = 1 WHERE id = ?",
|
||||
(alert_id,),
|
||||
)
|
||||
conn.commit()
|
||||
return True
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to acknowledge alert: %s", exc)
|
||||
return False
|
||||
|
||||
|
||||
# ── Module-level singleton ─────────────────────────────────────────────────
|
||||
_store: SovereigntyMetricsStore | None = None
|
||||
|
||||
|
||||
def get_sovereignty_store() -> SovereigntyMetricsStore:
|
||||
"""Return the module-level store, creating it on first access."""
|
||||
global _store
|
||||
if _store is None:
|
||||
_store = SovereigntyMetricsStore()
|
||||
return _store
|
||||
|
||||
|
||||
async def emit_sovereignty_metric(
|
||||
metric_type: str,
|
||||
value: float,
|
||||
metadata: dict[str, Any] | None = None,
|
||||
) -> None:
|
||||
"""Convenience function to record a sovereignty metric and emit an event.
|
||||
|
||||
Also publishes to the event bus for real-time subscribers.
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
from infrastructure.events.bus import emit
|
||||
|
||||
metric = SovereigntyMetric(
|
||||
metric_type=metric_type,
|
||||
value=value,
|
||||
metadata=metadata or {},
|
||||
)
|
||||
# Record to SQLite in thread to avoid blocking event loop
|
||||
await asyncio.to_thread(get_sovereignty_store().record, metric)
|
||||
|
||||
# Publish to event bus for real-time consumers
|
||||
await emit(
|
||||
f"sovereignty.metric.{metric_type}",
|
||||
source="sovereignty_metrics",
|
||||
data={"metric_type": metric_type, "value": value, **(metadata or {})},
|
||||
)
|
||||
@@ -1,17 +0,0 @@
|
||||
"""Performance regression suite for Morrowind agent scenarios.
|
||||
|
||||
Provides standardised benchmark scenarios, a runner that executes them
|
||||
through the heartbeat loop with a mock (or live) world adapter, and
|
||||
metrics collection for CI-integrated regression detection.
|
||||
"""
|
||||
|
||||
from infrastructure.world.benchmark.metrics import BenchmarkMetrics
|
||||
from infrastructure.world.benchmark.runner import BenchmarkRunner
|
||||
from infrastructure.world.benchmark.scenarios import BenchmarkScenario, load_scenarios
|
||||
|
||||
__all__ = [
|
||||
"BenchmarkMetrics",
|
||||
"BenchmarkRunner",
|
||||
"BenchmarkScenario",
|
||||
"load_scenarios",
|
||||
]
|
||||
@@ -1,195 +0,0 @@
|
||||
"""Benchmark metrics collection and persistence.
|
||||
|
||||
Tracks per-scenario results: cycles used, wall-clock time, success,
|
||||
LLM call count, and estimated metabolic cost. Results are persisted
|
||||
as JSONL for trend analysis and CI regression gates.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
from dataclasses import asdict, dataclass, field
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ScenarioResult:
|
||||
"""Outcome of running a single benchmark scenario.
|
||||
|
||||
Attributes:
|
||||
scenario_name: Human-readable scenario name.
|
||||
success: Whether the goal predicate was satisfied.
|
||||
cycles_used: Number of heartbeat cycles executed.
|
||||
max_cycles: The scenario's cycle budget.
|
||||
wall_time_ms: Total wall-clock time in milliseconds.
|
||||
llm_calls: Number of LLM inference calls made.
|
||||
metabolic_cost: Estimated resource cost (arbitrary unit, ≈ tokens).
|
||||
error: Error message if the run crashed.
|
||||
tags: Scenario tags (copied for filtering).
|
||||
"""
|
||||
|
||||
scenario_name: str
|
||||
success: bool = False
|
||||
cycles_used: int = 0
|
||||
max_cycles: int = 0
|
||||
wall_time_ms: int = 0
|
||||
llm_calls: int = 0
|
||||
metabolic_cost: float = 0.0
|
||||
error: str | None = None
|
||||
tags: list[str] = field(default_factory=list)
|
||||
|
||||
|
||||
@dataclass
|
||||
class BenchmarkMetrics:
|
||||
"""Aggregated metrics across all scenarios in a benchmark run.
|
||||
|
||||
Attributes:
|
||||
results: Per-scenario results.
|
||||
total_time_ms: Total wall-clock time for the full suite.
|
||||
timestamp: ISO-8601 timestamp of the run.
|
||||
commit_sha: Git commit SHA (if available).
|
||||
"""
|
||||
|
||||
results: list[ScenarioResult] = field(default_factory=list)
|
||||
total_time_ms: int = 0
|
||||
timestamp: str = ""
|
||||
commit_sha: str = ""
|
||||
|
||||
# -- derived properties ------------------------------------------------
|
||||
|
||||
@property
|
||||
def pass_count(self) -> int:
|
||||
return sum(1 for r in self.results if r.success)
|
||||
|
||||
@property
|
||||
def fail_count(self) -> int:
|
||||
return sum(1 for r in self.results if not r.success)
|
||||
|
||||
@property
|
||||
def success_rate(self) -> float:
|
||||
if not self.results:
|
||||
return 0.0
|
||||
return self.pass_count / len(self.results)
|
||||
|
||||
@property
|
||||
def total_llm_calls(self) -> int:
|
||||
return sum(r.llm_calls for r in self.results)
|
||||
|
||||
@property
|
||||
def total_metabolic_cost(self) -> float:
|
||||
return sum(r.metabolic_cost for r in self.results)
|
||||
|
||||
# -- persistence -------------------------------------------------------
|
||||
|
||||
def save(self, path: Path) -> None:
|
||||
"""Append this run's results to a JSONL file at *path*."""
|
||||
path = Path(path)
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
record = {
|
||||
"timestamp": self.timestamp,
|
||||
"commit_sha": self.commit_sha,
|
||||
"total_time_ms": self.total_time_ms,
|
||||
"success_rate": round(self.success_rate, 4),
|
||||
"total_llm_calls": self.total_llm_calls,
|
||||
"total_metabolic_cost": round(self.total_metabolic_cost, 2),
|
||||
"scenarios": [asdict(r) for r in self.results],
|
||||
}
|
||||
with path.open("a") as f:
|
||||
f.write(json.dumps(record) + "\n")
|
||||
logger.info("Benchmark results saved to %s", path)
|
||||
|
||||
# -- summary -----------------------------------------------------------
|
||||
|
||||
def summary(self) -> str:
|
||||
"""Return a human-readable summary of the benchmark run."""
|
||||
lines = [
|
||||
"=== Benchmark Summary ===",
|
||||
f"Scenarios: {len(self.results)} "
|
||||
f"Passed: {self.pass_count} "
|
||||
f"Failed: {self.fail_count} "
|
||||
f"Success rate: {self.success_rate:.0%}",
|
||||
f"Total time: {self.total_time_ms} ms "
|
||||
f"LLM calls: {self.total_llm_calls} "
|
||||
f"Metabolic cost: {self.total_metabolic_cost:.1f}",
|
||||
]
|
||||
if self.commit_sha:
|
||||
lines.append(f"Commit: {self.commit_sha}")
|
||||
lines.append("")
|
||||
for r in self.results:
|
||||
status = "PASS" if r.success else "FAIL"
|
||||
lines.append(
|
||||
f" [{status}] {r.scenario_name} — "
|
||||
f"{r.cycles_used}/{r.max_cycles} cycles, "
|
||||
f"{r.wall_time_ms} ms, "
|
||||
f"{r.llm_calls} LLM calls"
|
||||
)
|
||||
if r.error:
|
||||
lines.append(f" Error: {r.error}")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def load_history(path: Path) -> list[dict]:
|
||||
"""Load benchmark history from a JSONL file.
|
||||
|
||||
Returns:
|
||||
List of run records, most recent first.
|
||||
"""
|
||||
path = Path(path)
|
||||
if not path.exists():
|
||||
return []
|
||||
records: list[dict] = []
|
||||
for line in path.read_text().strip().splitlines():
|
||||
try:
|
||||
records.append(json.loads(line))
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
return list(reversed(records))
|
||||
|
||||
|
||||
def compare_runs(
|
||||
current: BenchmarkMetrics,
|
||||
baseline: BenchmarkMetrics,
|
||||
) -> str:
|
||||
"""Compare two benchmark runs and report regressions.
|
||||
|
||||
Returns:
|
||||
Human-readable comparison report.
|
||||
"""
|
||||
lines = ["=== Regression Report ==="]
|
||||
|
||||
# Overall
|
||||
rate_delta = current.success_rate - baseline.success_rate
|
||||
lines.append(
|
||||
f"Success rate: {baseline.success_rate:.0%} -> {current.success_rate:.0%} "
|
||||
f"({rate_delta:+.0%})"
|
||||
)
|
||||
|
||||
cost_delta = current.total_metabolic_cost - baseline.total_metabolic_cost
|
||||
if baseline.total_metabolic_cost > 0:
|
||||
cost_pct = (cost_delta / baseline.total_metabolic_cost) * 100
|
||||
lines.append(
|
||||
f"Metabolic cost: {baseline.total_metabolic_cost:.1f} -> "
|
||||
f"{current.total_metabolic_cost:.1f} ({cost_pct:+.1f}%)"
|
||||
)
|
||||
|
||||
# Per-scenario
|
||||
baseline_map = {r.scenario_name: r for r in baseline.results}
|
||||
for r in current.results:
|
||||
b = baseline_map.get(r.scenario_name)
|
||||
if b is None:
|
||||
lines.append(f" [NEW] {r.scenario_name}")
|
||||
continue
|
||||
if b.success and not r.success:
|
||||
lines.append(f" [REGRESSION] {r.scenario_name} — was PASS, now FAIL")
|
||||
elif not b.success and r.success:
|
||||
lines.append(f" [IMPROVEMENT] {r.scenario_name} — was FAIL, now PASS")
|
||||
elif r.cycles_used > b.cycles_used * 1.5:
|
||||
lines.append(
|
||||
f" [SLOWER] {r.scenario_name} — "
|
||||
f"{b.cycles_used} -> {r.cycles_used} cycles (+{r.cycles_used - b.cycles_used})"
|
||||
)
|
||||
|
||||
return "\n".join(lines)
|
||||
@@ -1,167 +0,0 @@
|
||||
"""Benchmark runner — executes scenarios through the heartbeat loop.
|
||||
|
||||
Wires each ``BenchmarkScenario`` into a ``MockWorldAdapter`` (or a
|
||||
supplied adapter), runs the heartbeat for up to ``max_cycles``, and
|
||||
collects ``BenchmarkMetrics``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import subprocess
|
||||
import time
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from infrastructure.world.adapters.mock import MockWorldAdapter
|
||||
from infrastructure.world.benchmark.metrics import BenchmarkMetrics, ScenarioResult
|
||||
from infrastructure.world.benchmark.scenarios import BenchmarkScenario
|
||||
from infrastructure.world.interface import WorldInterface
|
||||
from loop.heartbeat import Heartbeat
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Rough estimate: each heartbeat cycle costs ~1 unit of metabolic cost
|
||||
# (gather + reason + act phases each touch the LLM router once).
|
||||
_COST_PER_CYCLE = 3.0 # three phases per cycle
|
||||
|
||||
|
||||
class BenchmarkRunner:
|
||||
"""Run benchmark scenarios and collect metrics.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
adapter_factory:
|
||||
Optional callable that returns a ``WorldInterface`` for a given
|
||||
scenario. Defaults to building a ``MockWorldAdapter`` from the
|
||||
scenario's start state.
|
||||
heartbeat_interval:
|
||||
Seconds between heartbeat ticks (0 for immediate).
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
adapter_factory=None,
|
||||
heartbeat_interval: float = 0.0,
|
||||
) -> None:
|
||||
self._adapter_factory = adapter_factory or self._default_adapter
|
||||
self._interval = heartbeat_interval
|
||||
|
||||
# -- public API --------------------------------------------------------
|
||||
|
||||
async def run(
|
||||
self,
|
||||
scenarios: list[BenchmarkScenario],
|
||||
) -> BenchmarkMetrics:
|
||||
"""Execute all *scenarios* and return aggregated metrics."""
|
||||
metrics = BenchmarkMetrics(
|
||||
timestamp=datetime.now(UTC).isoformat(),
|
||||
commit_sha=self._git_sha(),
|
||||
)
|
||||
suite_start = time.monotonic()
|
||||
|
||||
for scenario in scenarios:
|
||||
logger.info("Benchmark: starting '%s'", scenario.name)
|
||||
result = await self._run_scenario(scenario)
|
||||
metrics.results.append(result)
|
||||
status = "PASS" if result.success else "FAIL"
|
||||
logger.info(
|
||||
"Benchmark: '%s' %s (%d/%d cycles, %d ms)",
|
||||
scenario.name,
|
||||
status,
|
||||
result.cycles_used,
|
||||
result.max_cycles,
|
||||
result.wall_time_ms,
|
||||
)
|
||||
|
||||
metrics.total_time_ms = int((time.monotonic() - suite_start) * 1000)
|
||||
return metrics
|
||||
|
||||
# -- internal ----------------------------------------------------------
|
||||
|
||||
async def _run_scenario(self, scenario: BenchmarkScenario) -> ScenarioResult:
|
||||
"""Run a single scenario through the heartbeat loop."""
|
||||
result = ScenarioResult(
|
||||
scenario_name=scenario.name,
|
||||
max_cycles=scenario.max_cycles,
|
||||
tags=list(scenario.tags),
|
||||
)
|
||||
|
||||
adapter = self._adapter_factory(scenario)
|
||||
adapter.connect()
|
||||
|
||||
hb = Heartbeat(world=adapter, interval=self._interval)
|
||||
actions: list[dict] = []
|
||||
|
||||
start = time.monotonic()
|
||||
try:
|
||||
for cycle in range(1, scenario.max_cycles + 1):
|
||||
record = await hb.run_once()
|
||||
result.cycles_used = cycle
|
||||
|
||||
# Track LLM calls (each cycle has 3 phases that may call LLM)
|
||||
result.llm_calls += 3
|
||||
|
||||
# Accumulate actions for goal predicate
|
||||
if record.action_taken and record.action_taken != "idle":
|
||||
actions.append(
|
||||
{
|
||||
"action": record.action_taken,
|
||||
"target": record.observation.get("location", ""),
|
||||
"status": record.action_status,
|
||||
}
|
||||
)
|
||||
|
||||
# Update adapter location if scenario simulates movement
|
||||
current_location = self._get_current_location(adapter)
|
||||
|
||||
# Check goal predicate
|
||||
if scenario.goal_predicate is not None:
|
||||
if scenario.goal_predicate(actions, current_location):
|
||||
result.success = True
|
||||
break
|
||||
elif cycle == scenario.max_cycles:
|
||||
# No predicate — success if we survived all cycles
|
||||
result.success = True
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("Benchmark scenario '%s' crashed: %s", scenario.name, exc)
|
||||
result.error = str(exc)
|
||||
finally:
|
||||
adapter.disconnect()
|
||||
|
||||
result.wall_time_ms = int((time.monotonic() - start) * 1000)
|
||||
result.metabolic_cost = result.cycles_used * _COST_PER_CYCLE
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
def _default_adapter(scenario: BenchmarkScenario) -> WorldInterface:
|
||||
"""Build a MockWorldAdapter from a scenario's starting state."""
|
||||
return MockWorldAdapter(
|
||||
location=scenario.start_location,
|
||||
entities=list(scenario.entities),
|
||||
events=list(scenario.events),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_current_location(adapter: WorldInterface) -> str:
|
||||
"""Read the current location from the adapter."""
|
||||
try:
|
||||
perception = adapter.observe()
|
||||
return perception.location
|
||||
except Exception:
|
||||
return ""
|
||||
|
||||
@staticmethod
|
||||
def _git_sha() -> str:
|
||||
"""Best-effort: return the current git commit SHA."""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "rev-parse", "--short", "HEAD"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=5,
|
||||
)
|
||||
return result.stdout.strip() if result.returncode == 0 else ""
|
||||
except (OSError, subprocess.TimeoutExpired):
|
||||
return ""
|
||||
@@ -1,160 +0,0 @@
|
||||
"""Benchmark scenario definitions for Morrowind agent regression testing.
|
||||
|
||||
Each scenario specifies a starting location, goal conditions, world state
|
||||
(entities, events), and maximum cycles allowed. The runner feeds these
|
||||
into the heartbeat loop and checks completion against the goal predicate.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Callable
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class BenchmarkScenario:
|
||||
"""A reproducible agent task used to detect performance regressions.
|
||||
|
||||
Attributes:
|
||||
name: Human-readable scenario name.
|
||||
description: What the scenario tests.
|
||||
start_location: Where the agent begins.
|
||||
goal_location: Target location (if navigation scenario).
|
||||
entities: NPCs / objects present in the world.
|
||||
events: Game events injected each cycle.
|
||||
max_cycles: Hard cap on heartbeat cycles before failure.
|
||||
goal_predicate: Optional callable ``(actions, location) -> bool``
|
||||
evaluated after each cycle to check early success.
|
||||
tags: Freeform tags for filtering (e.g. "navigation", "quest").
|
||||
"""
|
||||
|
||||
name: str
|
||||
description: str
|
||||
start_location: str
|
||||
goal_location: str = ""
|
||||
entities: list[str] = field(default_factory=list)
|
||||
events: list[str] = field(default_factory=list)
|
||||
max_cycles: int = 50
|
||||
goal_predicate: Callable | None = None
|
||||
tags: list[str] = field(default_factory=list)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Goal predicates
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _reached_location(target: str) -> Callable:
|
||||
"""Return a predicate that checks whether the agent reached *target*."""
|
||||
|
||||
def predicate(actions: list[dict], current_location: str) -> bool:
|
||||
return current_location.lower() == target.lower()
|
||||
|
||||
return predicate
|
||||
|
||||
|
||||
def _interacted_with(npc: str) -> Callable:
|
||||
"""Return a predicate that checks for a speak/interact action with *npc*."""
|
||||
|
||||
def predicate(actions: list[dict], current_location: str) -> bool:
|
||||
for act in actions:
|
||||
if act.get("action") in ("speak", "interact", "talk"):
|
||||
if act.get("target", "").lower() == npc.lower():
|
||||
return True
|
||||
return False
|
||||
|
||||
return predicate
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Built-in scenarios
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
BUILTIN_SCENARIOS: list[BenchmarkScenario] = [
|
||||
BenchmarkScenario(
|
||||
name="Walk Seyda Neen to Balmora",
|
||||
description=(
|
||||
"Navigate from the starting village to Balmora via the road. "
|
||||
"Tests basic navigation and pathfinding."
|
||||
),
|
||||
start_location="Seyda Neen",
|
||||
goal_location="Balmora",
|
||||
entities=["Silt Strider", "Road Sign", "Mudcrab"],
|
||||
events=["player_spawned"],
|
||||
max_cycles=30,
|
||||
goal_predicate=_reached_location("Balmora"),
|
||||
tags=["navigation", "basic"],
|
||||
),
|
||||
BenchmarkScenario(
|
||||
name="Fargoth's Ring",
|
||||
description=(
|
||||
"Complete the Fargoth quest: find Fargoth, receive the ring, "
|
||||
"and return it. Tests NPC interaction and quest logic."
|
||||
),
|
||||
start_location="Seyda Neen",
|
||||
goal_location="Seyda Neen",
|
||||
entities=["Fargoth", "Arrille", "Guard"],
|
||||
events=["quest_available:fargoth_ring"],
|
||||
max_cycles=40,
|
||||
goal_predicate=_interacted_with("Fargoth"),
|
||||
tags=["quest", "npc_interaction"],
|
||||
),
|
||||
BenchmarkScenario(
|
||||
name="Balmora Guild Navigation",
|
||||
description=(
|
||||
"Walk from Balmora South Wall Corner Club to the Fighters Guild. "
|
||||
"Tests intra-city navigation with multiple NPCs present."
|
||||
),
|
||||
start_location="Balmora, South Wall Corner Club",
|
||||
goal_location="Balmora, Fighters Guild",
|
||||
entities=["Guard", "Merchant", "Caius Cosades"],
|
||||
events=["player_entered"],
|
||||
max_cycles=20,
|
||||
goal_predicate=_reached_location("Balmora, Fighters Guild"),
|
||||
tags=["navigation", "city"],
|
||||
),
|
||||
BenchmarkScenario(
|
||||
name="Combat Encounter — Mudcrab",
|
||||
description=(
|
||||
"Engage and defeat a single Mudcrab on the road between "
|
||||
"Seyda Neen and Balmora. Tests combat action selection."
|
||||
),
|
||||
start_location="Bitter Coast Road",
|
||||
goal_location="Bitter Coast Road",
|
||||
entities=["Mudcrab"],
|
||||
events=["hostile_entity_nearby"],
|
||||
max_cycles=15,
|
||||
goal_predicate=None, # Success = survived max_cycles without crash
|
||||
tags=["combat", "basic"],
|
||||
),
|
||||
BenchmarkScenario(
|
||||
name="Passive Observation — Balmora Market",
|
||||
description=(
|
||||
"Observe the Balmora market for 10 cycles without acting. "
|
||||
"Tests that the agent can reason without unnecessary actions."
|
||||
),
|
||||
start_location="Balmora, Market Square",
|
||||
goal_location="",
|
||||
entities=["Merchant", "Guard", "Pilgrim", "Trader"],
|
||||
events=["market_day"],
|
||||
max_cycles=10,
|
||||
tags=["observation", "passive"],
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
def load_scenarios(
|
||||
tags: list[str] | None = None,
|
||||
) -> list[BenchmarkScenario]:
|
||||
"""Return built-in scenarios, optionally filtered by tags.
|
||||
|
||||
Args:
|
||||
tags: If provided, only return scenarios whose tags overlap.
|
||||
|
||||
Returns:
|
||||
List of matching ``BenchmarkScenario`` instances.
|
||||
"""
|
||||
if tags is None:
|
||||
return list(BUILTIN_SCENARIOS)
|
||||
tag_set = set(tags)
|
||||
return [s for s in BUILTIN_SCENARIOS if tag_set & set(s.tags)]
|
||||
@@ -215,119 +215,6 @@ def _summarize(result: AgenticResult, total_steps: int, was_truncated: bool) ->
|
||||
result.status = "completed"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Execution orchestrator
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
async def _execute_all_steps(
|
||||
agent,
|
||||
task: str,
|
||||
task_id: str,
|
||||
steps: list[str],
|
||||
total_steps: int,
|
||||
session_id: str,
|
||||
result: AgenticResult,
|
||||
on_progress: Callable | None,
|
||||
) -> list[str]:
|
||||
"""Execute all planned steps, handling failures with adaptation.
|
||||
|
||||
Appends AgenticStep objects to *result.steps* and returns the list
|
||||
of completed-result strings (used as context for later steps).
|
||||
"""
|
||||
completed_results: list[str] = []
|
||||
|
||||
for i, step_desc in enumerate(steps, 1):
|
||||
step_start = time.monotonic()
|
||||
try:
|
||||
step = await _execute_step(
|
||||
agent,
|
||||
task,
|
||||
step_desc,
|
||||
i,
|
||||
total_steps,
|
||||
completed_results,
|
||||
session_id,
|
||||
)
|
||||
result.steps.append(step)
|
||||
completed_results.append(f"Step {i}: {step.result[:200]}")
|
||||
await _broadcast_progress(
|
||||
"agentic.step_complete",
|
||||
{
|
||||
"task_id": task_id,
|
||||
"step": i,
|
||||
"total": total_steps,
|
||||
"description": step_desc,
|
||||
"result": step.result[:200],
|
||||
},
|
||||
)
|
||||
if on_progress:
|
||||
await on_progress(step_desc, i, total_steps)
|
||||
|
||||
except Exception as exc: # broad catch intentional: agent.run can raise any error
|
||||
logger.warning("Agentic loop step %d failed: %s", i, exc)
|
||||
step = await _handle_step_failure(
|
||||
agent,
|
||||
step_desc,
|
||||
i,
|
||||
total_steps,
|
||||
task_id,
|
||||
exc,
|
||||
step_start,
|
||||
session_id,
|
||||
result,
|
||||
completed_results,
|
||||
on_progress,
|
||||
)
|
||||
|
||||
return completed_results
|
||||
|
||||
|
||||
async def _handle_step_failure(
|
||||
agent,
|
||||
step_desc: str,
|
||||
step_num: int,
|
||||
total_steps: int,
|
||||
task_id: str,
|
||||
exc: Exception,
|
||||
step_start: float,
|
||||
session_id: str,
|
||||
result: AgenticResult,
|
||||
completed_results: list[str],
|
||||
on_progress: Callable | None,
|
||||
) -> None:
|
||||
"""Try to adapt a failed step; record a hard failure if adaptation also fails."""
|
||||
try:
|
||||
step = await _adapt_step(agent, step_desc, step_num, exc, step_start, session_id)
|
||||
result.steps.append(step)
|
||||
completed_results.append(f"Step {step_num} (adapted): {step.result[:200]}")
|
||||
await _broadcast_progress(
|
||||
"agentic.step_adapted",
|
||||
{
|
||||
"task_id": task_id,
|
||||
"step": step_num,
|
||||
"total": total_steps,
|
||||
"description": step_desc,
|
||||
"error": str(exc),
|
||||
"adaptation": step.result[:200],
|
||||
},
|
||||
)
|
||||
if on_progress:
|
||||
await on_progress(f"[Adapted] {step_desc}", step_num, total_steps)
|
||||
except Exception as adapt_exc: # broad catch intentional
|
||||
logger.error("Agentic loop adaptation also failed: %s", adapt_exc)
|
||||
result.steps.append(
|
||||
AgenticStep(
|
||||
step_num=step_num,
|
||||
description=step_desc,
|
||||
result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
|
||||
status="failed",
|
||||
duration_ms=int((time.monotonic() - step_start) * 1000),
|
||||
)
|
||||
)
|
||||
completed_results.append(f"Step {step_num}: FAILED")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Core loop
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -378,9 +265,65 @@ async def run_agentic_loop(
|
||||
)
|
||||
|
||||
# Phase 2: Execution
|
||||
await _execute_all_steps(
|
||||
agent, task, task_id, steps, total_steps, session_id, result, on_progress
|
||||
)
|
||||
completed_results: list[str] = []
|
||||
for i, step_desc in enumerate(steps, 1):
|
||||
step_start = time.monotonic()
|
||||
try:
|
||||
step = await _execute_step(
|
||||
agent,
|
||||
task,
|
||||
step_desc,
|
||||
i,
|
||||
total_steps,
|
||||
completed_results,
|
||||
session_id,
|
||||
)
|
||||
result.steps.append(step)
|
||||
completed_results.append(f"Step {i}: {step.result[:200]}")
|
||||
await _broadcast_progress(
|
||||
"agentic.step_complete",
|
||||
{
|
||||
"task_id": task_id,
|
||||
"step": i,
|
||||
"total": total_steps,
|
||||
"description": step_desc,
|
||||
"result": step.result[:200],
|
||||
},
|
||||
)
|
||||
if on_progress:
|
||||
await on_progress(step_desc, i, total_steps)
|
||||
|
||||
except Exception as exc: # broad catch intentional: agent.run can raise any error
|
||||
logger.warning("Agentic loop step %d failed: %s", i, exc)
|
||||
try:
|
||||
step = await _adapt_step(agent, step_desc, i, exc, step_start, session_id)
|
||||
result.steps.append(step)
|
||||
completed_results.append(f"Step {i} (adapted): {step.result[:200]}")
|
||||
await _broadcast_progress(
|
||||
"agentic.step_adapted",
|
||||
{
|
||||
"task_id": task_id,
|
||||
"step": i,
|
||||
"total": total_steps,
|
||||
"description": step_desc,
|
||||
"error": str(exc),
|
||||
"adaptation": step.result[:200],
|
||||
},
|
||||
)
|
||||
if on_progress:
|
||||
await on_progress(f"[Adapted] {step_desc}", i, total_steps)
|
||||
except Exception as adapt_exc: # broad catch intentional
|
||||
logger.error("Agentic loop adaptation also failed: %s", adapt_exc)
|
||||
result.steps.append(
|
||||
AgenticStep(
|
||||
step_num=i,
|
||||
description=step_desc,
|
||||
result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
|
||||
status="failed",
|
||||
duration_ms=int((time.monotonic() - step_start) * 1000),
|
||||
)
|
||||
)
|
||||
completed_results.append(f"Step {i}: FAILED")
|
||||
|
||||
# Phase 3: Summary
|
||||
_summarize(result, total_steps, was_truncated)
|
||||
|
||||
@@ -1,488 +0,0 @@
|
||||
"""Kimi delegation for heavy research via Gitea labels.
|
||||
|
||||
When research exceeds local + Groq capacity, Timmy delegates to Kimi by:
|
||||
1. Filling a research template with full context
|
||||
2. Creating a Gitea issue labeled `kimi-ready`
|
||||
3. Monitoring for Kimi's completion (issue closed + artifact committed)
|
||||
4. Indexing Kimi's artifact into semantic memory
|
||||
5. Extracting action items and creating follow-up issues
|
||||
|
||||
Delegation flow:
|
||||
Timmy detects capacity exceeded
|
||||
→ Fills template with context
|
||||
→ Creates `kimi-ready` Gitea issue
|
||||
→ Kimi picks up, executes, commits artifact, closes issue
|
||||
→ Timmy indexes artifact + creates follow-ups
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import re
|
||||
from typing import Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Label applied to issues that Kimi should pick up
|
||||
KIMI_READY_LABEL = "kimi-ready"
|
||||
|
||||
# Label colour for the kimi-ready label (dark teal)
|
||||
KIMI_LABEL_COLOR = "#006b75"
|
||||
|
||||
# Keywords that suggest a task exceeds local capacity
|
||||
_HEAVY_RESEARCH_KEYWORDS = frozenset(
|
||||
{
|
||||
"comprehensive",
|
||||
"exhaustive",
|
||||
"systematic review",
|
||||
"literature review",
|
||||
"benchmark",
|
||||
"comparative analysis",
|
||||
"large-scale",
|
||||
"survey",
|
||||
"meta-analysis",
|
||||
"deep research",
|
||||
"extensive",
|
||||
}
|
||||
)
|
||||
|
||||
# Minimum word count that hints at a heavy task
|
||||
_HEAVY_WORD_THRESHOLD = 50
|
||||
|
||||
|
||||
def exceeds_local_capacity(task_description: str) -> bool:
|
||||
"""Heuristic: does this research task exceed local + Groq capacity?
|
||||
|
||||
Returns True when the task description signals heavy or broad research
|
||||
that benefits from Kimi's 262K context and long-running processing.
|
||||
|
||||
Args:
|
||||
task_description: Free-text description of the research task.
|
||||
|
||||
Returns:
|
||||
True if the task should be delegated to Kimi.
|
||||
"""
|
||||
lower = task_description.lower()
|
||||
word_count = len(task_description.split())
|
||||
|
||||
has_heavy_keyword = any(kw in lower for kw in _HEAVY_RESEARCH_KEYWORDS)
|
||||
is_long_task = word_count >= _HEAVY_WORD_THRESHOLD
|
||||
|
||||
return has_heavy_keyword or is_long_task
|
||||
|
||||
|
||||
def _build_research_template(
|
||||
task: str,
|
||||
context: str,
|
||||
question: str,
|
||||
priority: str = "normal",
|
||||
) -> str:
|
||||
"""Fill the standard Kimi research template with task context.
|
||||
|
||||
Args:
|
||||
task: Short title for the research task.
|
||||
context: Background information and relevant project context.
|
||||
question: The specific research question to answer.
|
||||
priority: Task priority — "low", "normal", or "high".
|
||||
|
||||
Returns:
|
||||
Markdown-formatted issue body ready for Gitea.
|
||||
"""
|
||||
return f"""\
|
||||
## Research Request
|
||||
|
||||
**Priority:** {priority}
|
||||
|
||||
### Research Question
|
||||
|
||||
{question}
|
||||
|
||||
### Background / Context
|
||||
|
||||
{context}
|
||||
|
||||
### Scope
|
||||
|
||||
Please produce a thorough, well-structured research report covering:
|
||||
|
||||
- Direct answer to the research question above
|
||||
- Supporting evidence and sources where applicable
|
||||
- Trade-offs, limitations, or caveats
|
||||
- Concrete recommendations or next steps
|
||||
|
||||
### Deliverables
|
||||
|
||||
Commit your findings as a markdown artifact (e.g. `memory/research/{_slugify(task)}.md`)
|
||||
and close this issue when complete.
|
||||
|
||||
### Task
|
||||
|
||||
{task}
|
||||
|
||||
---
|
||||
*Delegated by Timmy via Kimi delegation pipeline. Label: `{KIMI_READY_LABEL}`*
|
||||
"""
|
||||
|
||||
|
||||
def _slugify(text: str) -> str:
|
||||
"""Convert text to a safe filename slug."""
|
||||
slug = re.sub(r"[^\w\s-]", "", text.lower())
|
||||
slug = re.sub(r"[\s_]+", "-", slug)
|
||||
return slug[:60].strip("-")
|
||||
|
||||
|
||||
async def _get_or_create_label(
|
||||
client: Any,
|
||||
base_url: str,
|
||||
headers: dict[str, str],
|
||||
repo: str,
|
||||
) -> int | None:
|
||||
"""Ensure the `kimi-ready` label exists; return its ID or None on error.
|
||||
|
||||
Args:
|
||||
client: httpx.AsyncClient instance.
|
||||
base_url: Gitea API base URL.
|
||||
headers: Auth headers.
|
||||
repo: owner/repo string.
|
||||
|
||||
Returns:
|
||||
Label ID, or None if the operation failed.
|
||||
"""
|
||||
labels_url = f"{base_url}/repos/{repo}/labels"
|
||||
|
||||
# Check for existing label
|
||||
try:
|
||||
resp = await client.get(labels_url, headers=headers)
|
||||
if resp.status_code == 200:
|
||||
for label in resp.json():
|
||||
if label.get("name") == KIMI_READY_LABEL:
|
||||
return label["id"]
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to list Gitea labels: %s", exc)
|
||||
return None
|
||||
|
||||
# Create the label
|
||||
try:
|
||||
resp = await client.post(
|
||||
labels_url,
|
||||
headers=headers,
|
||||
json={"name": KIMI_READY_LABEL, "color": KIMI_LABEL_COLOR},
|
||||
)
|
||||
if resp.status_code in (200, 201):
|
||||
return resp.json().get("id")
|
||||
logger.warning("Label creation returned %s: %s", resp.status_code, resp.text[:200])
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to create Gitea label: %s", exc)
|
||||
|
||||
return None
|
||||
|
||||
|
||||
async def create_kimi_research_issue(
|
||||
task: str,
|
||||
context: str,
|
||||
question: str,
|
||||
priority: str = "normal",
|
||||
) -> dict[str, Any]:
|
||||
"""Create a Gitea issue labeled `kimi-ready` for Kimi to pick up.
|
||||
|
||||
Args:
|
||||
task: Short title for the research task (used as issue title).
|
||||
context: Background information and project context.
|
||||
question: The specific research question.
|
||||
priority: Task priority — "low", "normal", or "high".
|
||||
|
||||
Returns:
|
||||
Dict with `success`, `issue_number`, `issue_url`, and `error` keys.
|
||||
"""
|
||||
try:
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
except ImportError as exc:
|
||||
return {"success": False, "error": f"Missing dependency: {exc}"}
|
||||
|
||||
if not settings.gitea_enabled or not settings.gitea_token:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "Gitea integration not configured (no token or disabled).",
|
||||
}
|
||||
|
||||
base_url = f"{settings.gitea_url}/api/v1"
|
||||
repo = settings.gitea_repo
|
||||
headers = {
|
||||
"Authorization": f"token {settings.gitea_token}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
label_id = await _get_or_create_label(client, base_url, headers, repo)
|
||||
|
||||
body = _build_research_template(task, context, question, priority)
|
||||
issue_payload: dict[str, Any] = {"title": task, "body": body}
|
||||
if label_id is not None:
|
||||
issue_payload["labels"] = [label_id]
|
||||
|
||||
resp = await client.post(
|
||||
f"{base_url}/repos/{repo}/issues",
|
||||
headers=headers,
|
||||
json=issue_payload,
|
||||
)
|
||||
|
||||
if resp.status_code in (200, 201):
|
||||
data = resp.json()
|
||||
number = data.get("number")
|
||||
url = data.get("html_url", "")
|
||||
logger.info("Created kimi-ready issue #%s: %s", number, task[:60])
|
||||
return {
|
||||
"success": True,
|
||||
"issue_number": number,
|
||||
"issue_url": url,
|
||||
"error": None,
|
||||
}
|
||||
|
||||
logger.warning("Issue creation failed (%s): %s", resp.status_code, resp.text[:200])
|
||||
return {
|
||||
"success": False,
|
||||
"error": f"Gitea API error {resp.status_code}: {resp.text[:200]}",
|
||||
}
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("create_kimi_research_issue failed: %s", exc)
|
||||
return {"success": False, "error": str(exc)}
|
||||
|
||||
|
||||
async def poll_kimi_issue(
|
||||
issue_number: int,
|
||||
poll_interval: int = 60,
|
||||
max_wait: int = 3600,
|
||||
) -> dict[str, Any]:
|
||||
"""Poll a Gitea issue until it is closed (Kimi completed) or timeout.
|
||||
|
||||
Args:
|
||||
issue_number: The Gitea issue number to watch.
|
||||
poll_interval: Seconds between polls. Default 60.
|
||||
max_wait: Maximum total seconds to wait. Default 3600 (1 hour).
|
||||
|
||||
Returns:
|
||||
Dict with `completed` bool, `state`, `body`, and `error` keys.
|
||||
"""
|
||||
try:
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
except ImportError as exc:
|
||||
return {"completed": False, "error": f"Missing dependency: {exc}"}
|
||||
|
||||
if not settings.gitea_enabled or not settings.gitea_token:
|
||||
return {"completed": False, "error": "Gitea not configured."}
|
||||
|
||||
base_url = f"{settings.gitea_url}/api/v1"
|
||||
repo = settings.gitea_repo
|
||||
headers = {"Authorization": f"token {settings.gitea_token}"}
|
||||
issue_url = f"{base_url}/repos/{repo}/issues/{issue_number}"
|
||||
|
||||
elapsed = 0
|
||||
while elapsed < max_wait:
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
resp = await client.get(issue_url, headers=headers)
|
||||
|
||||
if resp.status_code == 200:
|
||||
data = resp.json()
|
||||
state = data.get("state", "open")
|
||||
if state == "closed":
|
||||
logger.info("Kimi completed issue #%s", issue_number)
|
||||
return {
|
||||
"completed": True,
|
||||
"state": state,
|
||||
"body": data.get("body", ""),
|
||||
"error": None,
|
||||
}
|
||||
else:
|
||||
logger.warning("Poll issue #%s returned %s", issue_number, resp.status_code)
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("Poll error for issue #%s: %s", issue_number, exc)
|
||||
|
||||
await asyncio.sleep(poll_interval)
|
||||
elapsed += poll_interval
|
||||
|
||||
return {
|
||||
"completed": False,
|
||||
"state": "timeout",
|
||||
"body": "",
|
||||
"error": f"Timed out after {max_wait}s waiting for issue #{issue_number}",
|
||||
}
|
||||
|
||||
|
||||
def _extract_action_items(text: str) -> list[str]:
|
||||
"""Extract action items from markdown text.
|
||||
|
||||
Looks for lines that start with checklist markers, numbered items,
|
||||
or explicit "Action:" / "TODO:" prefixes.
|
||||
|
||||
Args:
|
||||
text: Markdown text from Kimi's artifact.
|
||||
|
||||
Returns:
|
||||
List of action item strings (deduplicated, whitespace-stripped).
|
||||
"""
|
||||
items: list[str] = []
|
||||
patterns = [
|
||||
re.compile(r"^[-*]\s+\[ \]\s+(.+)", re.MULTILINE), # - [ ] checkbox
|
||||
re.compile(r"^\d+\.\s+(.+)", re.MULTILINE), # 1. numbered list
|
||||
re.compile(r"^(?:Action|TODO|Next step):\s*(.+)", re.MULTILINE | re.IGNORECASE),
|
||||
]
|
||||
seen: set[str] = set()
|
||||
for pat in patterns:
|
||||
for m in pat.finditer(text):
|
||||
item = m.group(1).strip()
|
||||
if item and item not in seen:
|
||||
items.append(item)
|
||||
seen.add(item)
|
||||
return items
|
||||
|
||||
|
||||
async def index_kimi_artifact(
|
||||
issue_number: int,
|
||||
title: str,
|
||||
artifact_content: str,
|
||||
) -> dict[str, Any]:
|
||||
"""Index Kimi's research artifact into Timmy's semantic memory.
|
||||
|
||||
Args:
|
||||
issue_number: Source Gitea issue number (used as task_id).
|
||||
title: Human-readable title for the memory entry.
|
||||
artifact_content: The research artifact text to index.
|
||||
|
||||
Returns:
|
||||
Dict with `success` bool and `memory_id` or `error`.
|
||||
"""
|
||||
if not artifact_content.strip():
|
||||
return {"success": False, "error": "Empty artifact — nothing to index."}
|
||||
|
||||
try:
|
||||
import asyncio
|
||||
|
||||
from timmy.memory_system import store_memory
|
||||
|
||||
# store_memory is synchronous — wrap in thread to avoid blocking event loop
|
||||
entry = await asyncio.to_thread(
|
||||
store_memory,
|
||||
content=artifact_content,
|
||||
source="kimi",
|
||||
context_type="document",
|
||||
task_id=str(issue_number),
|
||||
metadata={"issue_number": issue_number, "title": title},
|
||||
)
|
||||
logger.info("Indexed Kimi artifact for issue #%s (id=%s)", issue_number, entry.id)
|
||||
return {"success": True, "memory_id": entry.id}
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to index Kimi artifact for issue #%s: %s", issue_number, exc)
|
||||
return {"success": False, "error": str(exc)}
|
||||
|
||||
|
||||
async def extract_and_create_followups(
|
||||
artifact_content: str,
|
||||
source_issue_number: int,
|
||||
) -> dict[str, Any]:
|
||||
"""Extract action items from artifact and create follow-up Gitea issues.
|
||||
|
||||
Args:
|
||||
artifact_content: Text of Kimi's research artifact.
|
||||
source_issue_number: Issue number that produced the artifact (for cross-links).
|
||||
|
||||
Returns:
|
||||
Dict with `success`, `created` (list of issue numbers), and `error`.
|
||||
"""
|
||||
items = _extract_action_items(artifact_content)
|
||||
if not items:
|
||||
logger.info("No action items found in artifact for issue #%s", source_issue_number)
|
||||
return {"success": True, "created": [], "error": None}
|
||||
|
||||
try:
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
except ImportError as exc:
|
||||
return {"success": False, "created": [], "error": str(exc)}
|
||||
|
||||
if not settings.gitea_enabled or not settings.gitea_token:
|
||||
return {
|
||||
"success": False,
|
||||
"created": [],
|
||||
"error": "Gitea not configured.",
|
||||
}
|
||||
|
||||
base_url = f"{settings.gitea_url}/api/v1"
|
||||
repo = settings.gitea_repo
|
||||
headers = {
|
||||
"Authorization": f"token {settings.gitea_token}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
created: list[int] = []
|
||||
|
||||
for item in items:
|
||||
body = (
|
||||
f"Follow-up from Kimi research artifact in #{source_issue_number}.\n\n"
|
||||
f"**Action item:** {item}"
|
||||
)
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
resp = await client.post(
|
||||
f"{base_url}/repos/{repo}/issues",
|
||||
headers=headers,
|
||||
json={"title": item[:120], "body": body},
|
||||
)
|
||||
if resp.status_code in (200, 201):
|
||||
num = resp.json().get("number")
|
||||
if num:
|
||||
created.append(num)
|
||||
logger.info(
|
||||
"Created follow-up issue #%s from kimi artifact #%s",
|
||||
num,
|
||||
source_issue_number,
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
"Follow-up issue creation returned %s for item: %s",
|
||||
resp.status_code,
|
||||
item[:60],
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to create follow-up for item '%s': %s", item[:60], exc)
|
||||
|
||||
return {"success": True, "created": created, "error": None}
|
||||
|
||||
|
||||
async def delegate_research_to_kimi(
|
||||
task: str,
|
||||
context: str,
|
||||
question: str,
|
||||
priority: str = "normal",
|
||||
) -> dict[str, Any]:
|
||||
"""Top-level entry point: delegate a heavy research task to Kimi.
|
||||
|
||||
Creates the `kimi-ready` Gitea issue and returns immediately.
|
||||
Monitoring, artifact indexing, and follow-up creation happen
|
||||
separately via `poll_kimi_issue`, `index_kimi_artifact`, and
|
||||
`extract_and_create_followups`.
|
||||
|
||||
Args:
|
||||
task: Short title (becomes the issue title).
|
||||
context: Background / project context.
|
||||
question: The specific research question Kimi should answer.
|
||||
priority: "low", "normal", or "high".
|
||||
|
||||
Returns:
|
||||
Dict with `success`, `issue_number`, `issue_url`, and `error`.
|
||||
"""
|
||||
if not task.strip() or not question.strip():
|
||||
return {
|
||||
"success": False,
|
||||
"error": "Both `task` and `question` are required.",
|
||||
}
|
||||
|
||||
logger.info("Delegating research to Kimi: %s", task[:80])
|
||||
return await create_kimi_research_issue(task, context, question, priority)
|
||||
@@ -1,540 +0,0 @@
|
||||
"""MCP Bridge for Qwen3 via Ollama.
|
||||
|
||||
Provides a lightweight bridge between Ollama's native tool-calling API
|
||||
and MCP tool servers (Gitea, Filesystem, Shell). Unlike the Agno-based
|
||||
agent loop, this bridge talks directly to the Ollama ``/api/chat``
|
||||
endpoint, translating MCP tool schemas into Ollama tool definitions and
|
||||
executing tool calls in a loop until the model produces a final response.
|
||||
|
||||
Designed for Qwen3 models which have first-class tool-calling support.
|
||||
|
||||
Usage::
|
||||
|
||||
from timmy.mcp_bridge import MCPBridge
|
||||
|
||||
bridge = MCPBridge()
|
||||
async with bridge:
|
||||
result = await bridge.run("List open issues in Timmy-time-dashboard")
|
||||
print(result.content)
|
||||
|
||||
The bridge evaluates available options in order of preference:
|
||||
1. Direct Ollama /api/chat with native tool_calls (selected — best fit)
|
||||
2. qwen-agent MCP (requires separate qwen-agent install)
|
||||
3. ollmcp / mcphost / ollama-mcp-bridge (external binaries)
|
||||
|
||||
Option 1 was selected because:
|
||||
- Zero additional dependencies (uses httpx already in the project)
|
||||
- Native Qwen3 tool-calling support via Ollama's OpenAI-compatible API
|
||||
- Full control over the tool-call loop and error handling
|
||||
- Consistent with the project's graceful-degradation pattern
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any
|
||||
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Maximum tool-call round-trips before aborting (safety valve).
|
||||
_MAX_TOOL_ROUNDS = 10
|
||||
|
||||
|
||||
@dataclass
|
||||
class BridgeResult:
|
||||
"""Result from an MCP bridge run."""
|
||||
|
||||
content: str
|
||||
tool_calls_made: list[dict] = field(default_factory=list)
|
||||
rounds: int = 0
|
||||
latency_ms: float = 0.0
|
||||
model: str = ""
|
||||
error: str = ""
|
||||
|
||||
|
||||
@dataclass
|
||||
class MCPToolDef:
|
||||
"""An MCP tool definition translated for Ollama."""
|
||||
|
||||
name: str
|
||||
description: str
|
||||
parameters: dict[str, Any]
|
||||
handler: Any # async callable(**kwargs) -> str
|
||||
|
||||
|
||||
def _mcp_schema_to_ollama_tool(tool: MCPToolDef) -> dict:
|
||||
"""Convert an MCPToolDef into Ollama's tool format.
|
||||
|
||||
Ollama uses OpenAI-compatible tool definitions::
|
||||
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "...",
|
||||
"description": "...",
|
||||
"parameters": { "type": "object", "properties": {...}, "required": [...] }
|
||||
}
|
||||
}
|
||||
"""
|
||||
# Normalise parameters — ensure it has "type": "object" wrapper.
|
||||
params = tool.parameters
|
||||
if params.get("type") != "object":
|
||||
params = {
|
||||
"type": "object",
|
||||
"properties": params,
|
||||
"required": list(params.keys()),
|
||||
}
|
||||
|
||||
return {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tool.name,
|
||||
"description": tool.description,
|
||||
"parameters": params,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def _build_shell_tool() -> MCPToolDef | None:
|
||||
"""Build the shell execution tool using the local ShellHand."""
|
||||
try:
|
||||
from infrastructure.hands.shell import shell_hand
|
||||
|
||||
async def _handle_shell(**kwargs: Any) -> str:
|
||||
command = kwargs.get("command", "")
|
||||
timeout = kwargs.get("timeout")
|
||||
result = await shell_hand.run(command, timeout=timeout)
|
||||
if result.success:
|
||||
return result.stdout or "(no output)"
|
||||
return f"[error] exit={result.exit_code} {result.error or result.stderr}"
|
||||
|
||||
return MCPToolDef(
|
||||
name="shell_exec",
|
||||
description=(
|
||||
"Execute a shell command in a sandboxed environment. "
|
||||
"Commands are validated against an allow-list. "
|
||||
"Returns stdout, stderr, and exit code."
|
||||
),
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"command": {
|
||||
"type": "string",
|
||||
"description": "Shell command to execute (must match allow-list)",
|
||||
},
|
||||
"timeout": {
|
||||
"type": "integer",
|
||||
"description": "Timeout in seconds (default 60)",
|
||||
},
|
||||
},
|
||||
"required": ["command"],
|
||||
},
|
||||
handler=_handle_shell,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.debug("Shell tool unavailable: %s", exc)
|
||||
return None
|
||||
|
||||
|
||||
def _build_gitea_tools() -> list[MCPToolDef]:
|
||||
"""Build Gitea MCP tool definitions for direct Ollama bridge use.
|
||||
|
||||
These tools call the Gitea REST API directly via httpx rather than
|
||||
spawning an MCP server subprocess, keeping the bridge lightweight.
|
||||
"""
|
||||
if not settings.gitea_enabled or not settings.gitea_token:
|
||||
return []
|
||||
|
||||
base_url = settings.gitea_url
|
||||
token = settings.gitea_token
|
||||
owner, repo = settings.gitea_repo.split("/", 1)
|
||||
|
||||
async def _list_issues(**kwargs: Any) -> str:
|
||||
state = kwargs.get("state", "open")
|
||||
limit = kwargs.get("limit", 10)
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
resp = await client.get(
|
||||
f"{base_url}/api/v1/repos/{owner}/{repo}/issues",
|
||||
headers={"Authorization": f"token {token}"},
|
||||
params={"state": state, "limit": limit, "type": "issues"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
issues = resp.json()
|
||||
if not issues:
|
||||
return f"No {state} issues found."
|
||||
lines = []
|
||||
for issue in issues:
|
||||
labels = ", ".join(lb["name"] for lb in issue.get("labels", []))
|
||||
label_str = f" [{labels}]" if labels else ""
|
||||
lines.append(f"#{issue['number']}: {issue['title']}{label_str}")
|
||||
return "\n".join(lines)
|
||||
except Exception as exc:
|
||||
return f"Error listing issues: {exc}"
|
||||
|
||||
async def _create_issue(**kwargs: Any) -> str:
|
||||
title = kwargs.get("title", "")
|
||||
body = kwargs.get("body", "")
|
||||
if not title:
|
||||
return "Error: title is required"
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
resp = await client.post(
|
||||
f"{base_url}/api/v1/repos/{owner}/{repo}/issues",
|
||||
headers={
|
||||
"Authorization": f"token {token}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json={"title": title, "body": body},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
return f"Created issue #{data['number']}: {data['title']}"
|
||||
except Exception as exc:
|
||||
return f"Error creating issue: {exc}"
|
||||
|
||||
async def _read_issue(**kwargs: Any) -> str:
|
||||
number = kwargs.get("number")
|
||||
if not number:
|
||||
return "Error: issue number is required"
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
resp = await client.get(
|
||||
f"{base_url}/api/v1/repos/{owner}/{repo}/issues/{number}",
|
||||
headers={"Authorization": f"token {token}"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
issue = resp.json()
|
||||
labels = ", ".join(lb["name"] for lb in issue.get("labels", []))
|
||||
parts = [
|
||||
f"#{issue['number']}: {issue['title']}",
|
||||
f"State: {issue['state']}",
|
||||
]
|
||||
if labels:
|
||||
parts.append(f"Labels: {labels}")
|
||||
if issue.get("body"):
|
||||
parts.append(f"\n{issue['body']}")
|
||||
return "\n".join(parts)
|
||||
except Exception as exc:
|
||||
return f"Error reading issue: {exc}"
|
||||
|
||||
return [
|
||||
MCPToolDef(
|
||||
name="list_issues",
|
||||
description="List issues in the Gitea repository. Returns issue numbers and titles.",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"state": {
|
||||
"type": "string",
|
||||
"description": "Filter by state: open, closed, or all (default: open)",
|
||||
},
|
||||
"limit": {
|
||||
"type": "integer",
|
||||
"description": "Maximum number of issues to return (default: 10)",
|
||||
},
|
||||
},
|
||||
"required": [],
|
||||
},
|
||||
handler=_list_issues,
|
||||
),
|
||||
MCPToolDef(
|
||||
name="create_issue",
|
||||
description="Create a new issue in the Gitea repository.",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"title": {
|
||||
"type": "string",
|
||||
"description": "Issue title (required)",
|
||||
},
|
||||
"body": {
|
||||
"type": "string",
|
||||
"description": "Issue body in markdown (optional)",
|
||||
},
|
||||
},
|
||||
"required": ["title"],
|
||||
},
|
||||
handler=_create_issue,
|
||||
),
|
||||
MCPToolDef(
|
||||
name="read_issue",
|
||||
description="Read details of a specific issue by number.",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"number": {
|
||||
"type": "integer",
|
||||
"description": "Issue number to read",
|
||||
},
|
||||
},
|
||||
"required": ["number"],
|
||||
},
|
||||
handler=_read_issue,
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
class MCPBridge:
|
||||
"""Bridge between Ollama's tool-calling API and MCP tools.
|
||||
|
||||
Manages a set of tool definitions and executes a chat loop with
|
||||
tool calling against a Qwen3 model via Ollama.
|
||||
|
||||
The bridge:
|
||||
1. Registers available tools (Gitea, shell, custom)
|
||||
2. Sends prompts to Ollama with tool definitions
|
||||
3. Executes tool calls when the model requests them
|
||||
4. Returns tool results to the model for the next round
|
||||
5. Repeats until the model produces a final text response
|
||||
|
||||
Attributes:
|
||||
model: Ollama model name (default from settings).
|
||||
ollama_url: Ollama API base URL (default from settings).
|
||||
tools: Registered tool definitions.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
model: str | None = None,
|
||||
ollama_url: str | None = None,
|
||||
*,
|
||||
include_gitea: bool = True,
|
||||
include_shell: bool = True,
|
||||
extra_tools: list[MCPToolDef] | None = None,
|
||||
max_rounds: int = _MAX_TOOL_ROUNDS,
|
||||
) -> None:
|
||||
self.model = model or settings.ollama_model
|
||||
self.ollama_url = ollama_url or settings.normalized_ollama_url
|
||||
self.max_rounds = max_rounds
|
||||
self._tools: dict[str, MCPToolDef] = {}
|
||||
self._client: httpx.AsyncClient | None = None
|
||||
|
||||
# Register built-in tools
|
||||
if include_gitea:
|
||||
for tool in _build_gitea_tools():
|
||||
self._tools[tool.name] = tool
|
||||
|
||||
if include_shell:
|
||||
shell = _build_shell_tool()
|
||||
if shell:
|
||||
self._tools[shell.name] = shell
|
||||
|
||||
# Register extra tools
|
||||
if extra_tools:
|
||||
for tool in extra_tools:
|
||||
self._tools[tool.name] = tool
|
||||
|
||||
logger.info(
|
||||
"MCPBridge initialised: model=%s, tools=%s",
|
||||
self.model,
|
||||
list(self._tools.keys()),
|
||||
)
|
||||
|
||||
async def __aenter__(self) -> MCPBridge:
|
||||
self._client = httpx.AsyncClient(timeout=settings.mcp_bridge_timeout)
|
||||
return self
|
||||
|
||||
async def __aexit__(self, *exc: Any) -> None:
|
||||
if self._client:
|
||||
await self._client.aclose()
|
||||
self._client = None
|
||||
|
||||
@property
|
||||
def tool_names(self) -> list[str]:
|
||||
"""Return names of all registered tools."""
|
||||
return list(self._tools.keys())
|
||||
|
||||
def _build_ollama_tools(self) -> list[dict]:
|
||||
"""Convert registered tools to Ollama tool format."""
|
||||
return [_mcp_schema_to_ollama_tool(t) for t in self._tools.values()]
|
||||
|
||||
async def _chat(self, messages: list[dict], tools: list[dict]) -> dict:
|
||||
"""Send a chat request to Ollama and return the response.
|
||||
|
||||
Uses the ``/api/chat`` endpoint with tool definitions.
|
||||
"""
|
||||
if not self._client:
|
||||
raise RuntimeError("MCPBridge must be used as async context manager")
|
||||
|
||||
payload: dict[str, Any] = {
|
||||
"model": self.model,
|
||||
"messages": messages,
|
||||
"stream": False,
|
||||
}
|
||||
if tools:
|
||||
payload["tools"] = tools
|
||||
|
||||
# Set num_ctx if configured
|
||||
if settings.ollama_num_ctx > 0:
|
||||
payload["options"] = {"num_ctx": settings.ollama_num_ctx}
|
||||
|
||||
resp = await self._client.post(
|
||||
f"{self.ollama_url}/api/chat",
|
||||
json=payload,
|
||||
)
|
||||
resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
async def _execute_tool_call(self, tool_call: dict) -> str:
|
||||
"""Execute a single tool call and return the result string."""
|
||||
func = tool_call.get("function", {})
|
||||
name = func.get("name", "")
|
||||
arguments = func.get("arguments", {})
|
||||
|
||||
tool = self._tools.get(name)
|
||||
if not tool:
|
||||
return f"Error: unknown tool '{name}'"
|
||||
|
||||
try:
|
||||
result = await tool.handler(**arguments)
|
||||
return str(result)
|
||||
except Exception as exc:
|
||||
logger.warning("Tool '%s' execution failed: %s", name, exc)
|
||||
return f"Error executing {name}: {exc}"
|
||||
|
||||
async def run(
|
||||
self,
|
||||
prompt: str,
|
||||
*,
|
||||
system_prompt: str | None = None,
|
||||
) -> BridgeResult:
|
||||
"""Run a prompt through the MCP bridge with tool calling.
|
||||
|
||||
Sends the prompt to the Ollama model with tool definitions.
|
||||
If the model requests tool calls, executes them and feeds
|
||||
results back until the model produces a final text response.
|
||||
|
||||
Args:
|
||||
prompt: User message to send.
|
||||
system_prompt: Optional system prompt override.
|
||||
|
||||
Returns:
|
||||
BridgeResult with the final response and tool call history.
|
||||
"""
|
||||
start = time.time()
|
||||
messages: list[dict] = []
|
||||
|
||||
if system_prompt:
|
||||
messages.append({"role": "system", "content": system_prompt})
|
||||
|
||||
messages.append({"role": "user", "content": prompt})
|
||||
|
||||
tools = self._build_ollama_tools()
|
||||
tool_calls_made: list[dict] = []
|
||||
rounds = 0
|
||||
|
||||
try:
|
||||
for round_num in range(self.max_rounds):
|
||||
rounds = round_num + 1
|
||||
response = await self._chat(messages, tools)
|
||||
msg = response.get("message", {})
|
||||
|
||||
# Check if model made tool calls
|
||||
model_tool_calls = msg.get("tool_calls", [])
|
||||
if not model_tool_calls:
|
||||
# Final text response — done.
|
||||
content = msg.get("content", "")
|
||||
latency = (time.time() - start) * 1000
|
||||
return BridgeResult(
|
||||
content=content,
|
||||
tool_calls_made=tool_calls_made,
|
||||
rounds=rounds,
|
||||
latency_ms=latency,
|
||||
model=self.model,
|
||||
)
|
||||
|
||||
# Append the assistant message (with tool_calls) to history
|
||||
messages.append(msg)
|
||||
|
||||
# Execute each tool call and add results
|
||||
for tc in model_tool_calls:
|
||||
func = tc.get("function", {})
|
||||
tool_name = func.get("name", "unknown")
|
||||
tool_args = func.get("arguments", {})
|
||||
|
||||
logger.info(
|
||||
"Bridge tool call [round %d]: %s(%s)",
|
||||
rounds,
|
||||
tool_name,
|
||||
tool_args,
|
||||
)
|
||||
|
||||
result = await self._execute_tool_call(tc)
|
||||
tool_calls_made.append(
|
||||
{
|
||||
"round": rounds,
|
||||
"tool": tool_name,
|
||||
"arguments": tool_args,
|
||||
"result": result[:500], # Truncate for logging
|
||||
}
|
||||
)
|
||||
|
||||
# Add tool result to message history
|
||||
messages.append(
|
||||
{
|
||||
"role": "tool",
|
||||
"content": result,
|
||||
}
|
||||
)
|
||||
|
||||
# Hit max rounds
|
||||
latency = (time.time() - start) * 1000
|
||||
return BridgeResult(
|
||||
content="(max tool-call rounds reached)",
|
||||
tool_calls_made=tool_calls_made,
|
||||
rounds=rounds,
|
||||
latency_ms=latency,
|
||||
model=self.model,
|
||||
error=f"Exceeded maximum of {self.max_rounds} tool-call rounds",
|
||||
)
|
||||
|
||||
except httpx.ConnectError as exc:
|
||||
latency = (time.time() - start) * 1000
|
||||
logger.warning("Ollama connection failed: %s", exc)
|
||||
return BridgeResult(
|
||||
content="",
|
||||
tool_calls_made=tool_calls_made,
|
||||
rounds=rounds,
|
||||
latency_ms=latency,
|
||||
model=self.model,
|
||||
error=f"Ollama connection failed: {exc}",
|
||||
)
|
||||
except httpx.HTTPStatusError as exc:
|
||||
latency = (time.time() - start) * 1000
|
||||
logger.warning("Ollama HTTP error: %s", exc)
|
||||
return BridgeResult(
|
||||
content="",
|
||||
tool_calls_made=tool_calls_made,
|
||||
rounds=rounds,
|
||||
latency_ms=latency,
|
||||
model=self.model,
|
||||
error=f"Ollama HTTP error: {exc.response.status_code}",
|
||||
)
|
||||
except Exception as exc:
|
||||
latency = (time.time() - start) * 1000
|
||||
logger.error("MCPBridge run failed: %s", exc)
|
||||
return BridgeResult(
|
||||
content="",
|
||||
tool_calls_made=tool_calls_made,
|
||||
rounds=rounds,
|
||||
latency_ms=latency,
|
||||
model=self.model,
|
||||
error=str(exc),
|
||||
)
|
||||
|
||||
def status(self) -> dict:
|
||||
"""Return bridge status for the dashboard."""
|
||||
return {
|
||||
"model": self.model,
|
||||
"ollama_url": self.ollama_url,
|
||||
"tools": self.tool_names,
|
||||
"max_rounds": self.max_rounds,
|
||||
"connected": self._client is not None,
|
||||
}
|
||||
@@ -1,175 +0,0 @@
|
||||
"""Paperclip integration for Timmy.
|
||||
|
||||
This module provides a client for the Paperclip API, and a poller for
|
||||
running research tasks.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from dataclasses import dataclass
|
||||
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
from timmy.research_triage import triage_research_report
|
||||
from timmy.research_tools import google_web_search, get_llm_client
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class PaperclipTask:
|
||||
"""A task from the Paperclip API."""
|
||||
|
||||
id: str
|
||||
kind: str
|
||||
context: dict
|
||||
|
||||
|
||||
class PaperclipClient:
|
||||
"""A client for the Paperclip API."""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.base_url = settings.paperclip_url
|
||||
self.api_key = settings.paperclip_api_key
|
||||
self.agent_id = settings.paperclip_agent_id
|
||||
self.company_id = settings.paperclip_company_id
|
||||
self.timeout = settings.paperclip_timeout
|
||||
|
||||
async def get_tasks(self) -> list[PaperclipTask]:
|
||||
"""Get a list of tasks from the Paperclip API."""
|
||||
async with httpx.AsyncClient(timeout=self.timeout) as client:
|
||||
resp = await client.get(
|
||||
f"{self.base_url}/api/tasks",
|
||||
headers={"Authorization": f"Bearer {self.api_key}"},
|
||||
params={
|
||||
"agent_id": self.agent_id,
|
||||
"company_id": self.company_id,
|
||||
"status": "queued",
|
||||
},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
tasks = resp.json()
|
||||
return [
|
||||
PaperclipTask(id=t["id"], kind=t["kind"], context=t["context"])
|
||||
for t in tasks
|
||||
]
|
||||
|
||||
async def update_task_status(
|
||||
self, task_id: str, status: str, result: str | None = None
|
||||
) -> None:
|
||||
"""Update the status of a task."""
|
||||
async with httpx.AsyncClient(timeout=self.timeout) as client:
|
||||
await client.patch(
|
||||
f"{self.base_url}/api/tasks/{task_id}",
|
||||
headers={"Authorization": f"Bearer {self.api_key}"},
|
||||
json={"status": status, "result": result},
|
||||
)
|
||||
|
||||
|
||||
class ResearchOrchestrator:
|
||||
"""Orchestrates research tasks."""
|
||||
|
||||
async def get_gitea_issue(self, issue_number: int) -> dict:
|
||||
"""Get a Gitea issue by its number."""
|
||||
owner, repo = settings.gitea_repo.split("/", 1)
|
||||
api_url = f"{settings.gitea_url}/api/v1/repos/{owner}/{repo}/issues/{issue_number}"
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
resp = await client.get(
|
||||
api_url,
|
||||
headers={"Authorization": f"token {settings.gitea_token}"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
async def post_gitea_comment(self, issue_number: int, comment: str) -> None:
|
||||
"""Post a comment to a Gitea issue."""
|
||||
owner, repo = settings.gitea_repo.split("/", 1)
|
||||
api_url = f"{settings.gitea_url}/api/v1/repos/{owner}/{repo}/issues/{issue_number}/comments"
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
await client.post(
|
||||
api_url,
|
||||
headers={"Authorization": f"token {settings.gitea_token}"},
|
||||
json={"body": comment},
|
||||
)
|
||||
|
||||
async def run_research_pipeline(self, issue_title: str) -> str:
|
||||
"""Run the research pipeline."""
|
||||
search_results = await google_web_search(issue_title)
|
||||
|
||||
llm_client = get_llm_client()
|
||||
response = await llm_client.completion(
|
||||
f"Summarize the following search results and generate a research report:\\n\\n{search_results}",
|
||||
max_tokens=2048,
|
||||
)
|
||||
return response.text
|
||||
|
||||
async def run(self, context: dict) -> str:
|
||||
"""Run a research task."""
|
||||
issue_number = context.get("issue_number")
|
||||
if not issue_number:
|
||||
return "Missing issue_number in task context"
|
||||
|
||||
issue = await self.get_gitea_issue(issue_number)
|
||||
|
||||
report = await self.run_research_pipeline(issue["title"])
|
||||
|
||||
triage_results = await triage_research_report(report, source_issue=issue_number)
|
||||
|
||||
comment = f"Research complete for issue #{issue_number}.\\n\\n"
|
||||
if triage_results:
|
||||
comment += "Created the following issues:\\n"
|
||||
for result in triage_results:
|
||||
if result["gitea_issue"]:
|
||||
comment += f"- #{result['gitea_issue']['number']}: {result['action_item'].title}\\n"
|
||||
else:
|
||||
comment += "No new issues were created.\\n"
|
||||
|
||||
await self.post_gitea_comment(issue_number, comment)
|
||||
|
||||
return f"Research complete for issue #{issue_number}"
|
||||
|
||||
|
||||
class PaperclipPoller:
|
||||
"""Polls the Paperclip API for new tasks."""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.client = PaperclipClient()
|
||||
self.orchestrator = ResearchOrchestrator()
|
||||
self.poll_interval = settings.paperclip_poll_interval
|
||||
|
||||
async def poll(self) -> None:
|
||||
"""Poll the Paperclip API for new tasks."""
|
||||
if self.poll_interval == 0:
|
||||
return
|
||||
|
||||
while True:
|
||||
try:
|
||||
tasks = await self.client.get_tasks()
|
||||
for task in tasks:
|
||||
if task.kind == "research":
|
||||
await self.run_research_task(task)
|
||||
except httpx.HTTPError as exc:
|
||||
logger.warning("Error polling Paperclip: %s", exc)
|
||||
|
||||
await asyncio.sleep(self.poll_interval)
|
||||
|
||||
async def run_research_task(self, task: PaperclipTask) -> None:
|
||||
"""Run a research task."""
|
||||
await self.client.update_task_status(task.id, "running")
|
||||
try:
|
||||
result = await self.orchestrator.run(task.context)
|
||||
await self.client.update_task_status(task.id, "completed", result)
|
||||
except Exception as exc:
|
||||
logger.error("Error running research task: %s", exc, exc_info=True)
|
||||
await self.client.update_task_status(task.id, "failed", str(exc))
|
||||
|
||||
|
||||
async def start_paperclip_poller() -> None:
|
||||
"""Start the Paperclip poller."""
|
||||
if settings.paperclip_enabled:
|
||||
poller = PaperclipPoller()
|
||||
asyncio.create_task(poller.poll())
|
||||
|
||||
555
src/timmy/research.py
Normal file
555
src/timmy/research.py
Normal file
@@ -0,0 +1,555 @@
|
||||
"""ResearchOrchestrator — autonomous research pipeline.
|
||||
|
||||
Chains: Check Local → Generate Queries → Search → Fetch → Synthesize →
|
||||
Crystallize → Write Artifact into an end-to-end research workflow.
|
||||
|
||||
Usage:
|
||||
from timmy.research import ResearchOrchestrator, run_research
|
||||
|
||||
orchestrator = ResearchOrchestrator(cascade=router, memory=memory_fns)
|
||||
result = await orchestrator.run("Bitcoin Lightning Network scaling")
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any
|
||||
|
||||
from config import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ── Data structures ──────────────────────────────────────────────────────────
|
||||
|
||||
CONFIDENCE_THRESHOLD = 0.85
|
||||
DEFAULT_QUERIES_PER_TOPIC = 8
|
||||
DEFAULT_RESULTS_PER_QUERY = 5
|
||||
DEFAULT_PAGES_TO_FETCH = 10
|
||||
DEFAULT_FETCH_TOKEN_LIMIT = 3000
|
||||
DEFAULT_SYNTHESIS_MAX_TOKENS = 4000
|
||||
|
||||
|
||||
@dataclass
|
||||
class ResearchResult:
|
||||
"""Output of a completed research pipeline run."""
|
||||
|
||||
topic: str
|
||||
report: str
|
||||
queries_generated: list[str] = field(default_factory=list)
|
||||
sources: list[dict[str, str]] = field(default_factory=list)
|
||||
action_items: list[str] = field(default_factory=list)
|
||||
cache_hit: bool = False
|
||||
duration_ms: float = 0.0
|
||||
metrics: dict[str, Any] = field(default_factory=dict)
|
||||
timestamp: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
|
||||
|
||||
|
||||
@dataclass
|
||||
class SearchSnippet:
|
||||
"""A single search result snippet."""
|
||||
|
||||
title: str
|
||||
url: str
|
||||
snippet: str
|
||||
relevance: float = 0.0
|
||||
|
||||
|
||||
@dataclass
|
||||
class FetchedPage:
|
||||
"""A fetched and truncated web page."""
|
||||
|
||||
url: str
|
||||
title: str
|
||||
content: str
|
||||
token_estimate: int = 0
|
||||
|
||||
|
||||
# ── Memory interface ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@dataclass
|
||||
class MemoryInterface:
|
||||
"""Abstraction over the memory system for research.
|
||||
|
||||
Accepts callables so the orchestrator doesn't depend on a specific
|
||||
memory implementation. Defaults wire to timmy.memory_system.
|
||||
"""
|
||||
|
||||
search_fn: Any = None # (query, limit) -> list[MemoryEntry]
|
||||
store_fn: Any = None # (content, source, context_type, ...) -> MemoryEntry
|
||||
|
||||
def __post_init__(self):
|
||||
if self.search_fn is None or self.store_fn is None:
|
||||
self._load_defaults()
|
||||
|
||||
def _load_defaults(self):
|
||||
try:
|
||||
from timmy.memory_system import search_memories, store_memory
|
||||
|
||||
if self.search_fn is None:
|
||||
self.search_fn = search_memories
|
||||
if self.store_fn is None:
|
||||
self.store_fn = store_memory
|
||||
except ImportError:
|
||||
logger.warning("Memory system not available — research will skip caching")
|
||||
if self.search_fn is None:
|
||||
self.search_fn = lambda query, **kw: []
|
||||
if self.store_fn is None:
|
||||
self.store_fn = lambda content, source, **kw: None
|
||||
|
||||
|
||||
# ── Tool interface ───────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@dataclass
|
||||
class ResearchTools:
|
||||
"""Web search and fetch callables.
|
||||
|
||||
These are async callables:
|
||||
web_search(query: str, limit: int) -> list[dict]
|
||||
web_fetch(url: str, max_tokens: int) -> str
|
||||
"""
|
||||
|
||||
web_search: Any = None
|
||||
web_fetch: Any = None
|
||||
|
||||
|
||||
# ── Orchestrator ─────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class ResearchOrchestrator:
|
||||
"""Pipeline that chains research steps into an autonomous workflow.
|
||||
|
||||
Steps:
|
||||
0. CHECK LOCAL KNOWLEDGE — search memory, return cached if confident
|
||||
1. GENERATE QUERIES — ask LLM to produce search queries
|
||||
2. SEARCH — execute queries via web_search tool
|
||||
3. FETCH — rank snippets, fetch top pages
|
||||
4. SYNTHESIZE — produce structured report via LLM
|
||||
5. CRYSTALLIZE — store result in semantic memory
|
||||
6. WRITE ARTIFACT — create Gitea issues from action items
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
cascade: Any,
|
||||
memory: MemoryInterface | None = None,
|
||||
tools: ResearchTools | None = None,
|
||||
) -> None:
|
||||
self.cascade = cascade
|
||||
self.memory = memory or MemoryInterface()
|
||||
self.tools = tools or ResearchTools()
|
||||
self._metrics: dict[str, int] = {
|
||||
"research_cache_hit": 0,
|
||||
"research_api_call": 0,
|
||||
}
|
||||
|
||||
async def run(
|
||||
self,
|
||||
topic: str,
|
||||
template: str | None = None,
|
||||
context: dict[str, Any] | None = None,
|
||||
) -> ResearchResult:
|
||||
"""Execute the full research pipeline.
|
||||
|
||||
Args:
|
||||
topic: The research topic or question.
|
||||
template: Optional prompt template for synthesis.
|
||||
context: Additional context dict (cascade_tier hint, etc.).
|
||||
|
||||
Returns:
|
||||
ResearchResult with report, sources, and action items.
|
||||
"""
|
||||
start = time.monotonic()
|
||||
context = context or {}
|
||||
cascade_tier = context.get("cascade_tier")
|
||||
|
||||
# Step 0: Check local knowledge
|
||||
cached = await self._check_local_knowledge(topic)
|
||||
if cached is not None:
|
||||
self._metrics["research_cache_hit"] += 1
|
||||
cached.duration_ms = (time.monotonic() - start) * 1000
|
||||
return cached
|
||||
|
||||
self._metrics["research_api_call"] += 1
|
||||
|
||||
# Step 1: Generate queries
|
||||
queries = await self._generate_queries(topic, template, cascade_tier)
|
||||
|
||||
# Step 2: Search
|
||||
snippets = await self._search(queries)
|
||||
|
||||
# Step 3: Fetch top pages
|
||||
pages = await self._fetch(snippets)
|
||||
|
||||
# Step 4: Synthesize
|
||||
report = await self._synthesize(topic, template, pages, cascade_tier)
|
||||
|
||||
# Step 5: Extract action items
|
||||
action_items = _extract_action_items(report)
|
||||
|
||||
# Build result
|
||||
sources = [{"url": p.url, "title": p.title} for p in pages]
|
||||
result = ResearchResult(
|
||||
topic=topic,
|
||||
report=report,
|
||||
queries_generated=queries,
|
||||
sources=sources,
|
||||
action_items=action_items,
|
||||
cache_hit=False,
|
||||
duration_ms=(time.monotonic() - start) * 1000,
|
||||
metrics=dict(self._metrics),
|
||||
)
|
||||
|
||||
# Step 6: Crystallize — store in memory
|
||||
await self._crystallize(topic, result)
|
||||
|
||||
# Step 7: Write artifact — create Gitea issues
|
||||
await self._write_artifact(result)
|
||||
|
||||
return result
|
||||
|
||||
# ── Pipeline steps ───────────────────────────────────────────────────
|
||||
|
||||
async def _check_local_knowledge(self, topic: str) -> ResearchResult | None:
|
||||
"""Search semantic memory for existing research on this topic."""
|
||||
try:
|
||||
results = self.memory.search_fn(
|
||||
query=topic, limit=10, context_type="research"
|
||||
)
|
||||
if not results:
|
||||
return None
|
||||
|
||||
# Check if top result has high confidence
|
||||
top = results[0]
|
||||
score = getattr(top, "relevance_score", 0.0) or 0.0
|
||||
if score >= CONFIDENCE_THRESHOLD:
|
||||
content = getattr(top, "content", str(top))
|
||||
logger.info(
|
||||
"Research cache hit for '%s' (score=%.2f)", topic, score
|
||||
)
|
||||
return ResearchResult(
|
||||
topic=topic,
|
||||
report=content,
|
||||
cache_hit=True,
|
||||
metrics={"research_cache_hit": 1},
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Local knowledge check failed: %s", exc)
|
||||
|
||||
return None
|
||||
|
||||
async def _generate_queries(
|
||||
self,
|
||||
topic: str,
|
||||
template: str | None,
|
||||
cascade_tier: str | None,
|
||||
) -> list[str]:
|
||||
"""Ask the LLM to generate search queries for the topic."""
|
||||
prompt = (
|
||||
f"Generate {DEFAULT_QUERIES_PER_TOPIC} diverse web search queries "
|
||||
f"to thoroughly research the following topic. Return ONLY the "
|
||||
f"queries, one per line, no numbering or bullets.\n\n"
|
||||
f"Topic: {topic}"
|
||||
)
|
||||
if template:
|
||||
prompt += f"\n\nResearch template context:\n{template}"
|
||||
|
||||
messages = [
|
||||
{"role": "system", "content": "You are a research query generator."},
|
||||
{"role": "user", "content": prompt},
|
||||
]
|
||||
|
||||
kwargs: dict[str, Any] = {"messages": messages, "temperature": 0.7}
|
||||
if cascade_tier:
|
||||
kwargs["model"] = cascade_tier
|
||||
|
||||
try:
|
||||
response = await self.cascade.complete(**kwargs)
|
||||
raw = response.get("content", "")
|
||||
queries = [
|
||||
line.strip()
|
||||
for line in raw.strip().splitlines()
|
||||
if line.strip() and not line.strip().startswith("#")
|
||||
]
|
||||
# Clean numbering prefixes
|
||||
cleaned = []
|
||||
for q in queries:
|
||||
q = re.sub(r"^\d+[\.\)]\s*", "", q)
|
||||
q = re.sub(r"^[-*]\s*", "", q)
|
||||
if q:
|
||||
cleaned.append(q)
|
||||
return cleaned[:DEFAULT_QUERIES_PER_TOPIC + 4] # slight over-generate
|
||||
except Exception as exc:
|
||||
logger.warning("Query generation failed: %s", exc)
|
||||
# Fallback: use topic itself as a single query
|
||||
return [topic]
|
||||
|
||||
async def _search(self, queries: list[str]) -> list[SearchSnippet]:
|
||||
"""Execute search queries and collect snippets."""
|
||||
if not self.tools.web_search:
|
||||
logger.warning("No web_search tool configured — skipping search step")
|
||||
return []
|
||||
|
||||
all_snippets: list[SearchSnippet] = []
|
||||
|
||||
async def _run_query(query: str) -> list[SearchSnippet]:
|
||||
try:
|
||||
results = await asyncio.to_thread(
|
||||
self.tools.web_search, query, DEFAULT_RESULTS_PER_QUERY
|
||||
)
|
||||
snippets = []
|
||||
for r in (results or []):
|
||||
snippets.append(
|
||||
SearchSnippet(
|
||||
title=r.get("title", ""),
|
||||
url=r.get("url", ""),
|
||||
snippet=r.get("snippet", ""),
|
||||
)
|
||||
)
|
||||
return snippets
|
||||
except Exception as exc:
|
||||
logger.warning("Search failed for query '%s': %s", query, exc)
|
||||
return []
|
||||
|
||||
# Run searches concurrently
|
||||
tasks = [_run_query(q) for q in queries]
|
||||
results = await asyncio.gather(*tasks)
|
||||
for snippets in results:
|
||||
all_snippets.extend(snippets)
|
||||
|
||||
# Deduplicate by URL
|
||||
seen_urls: set[str] = set()
|
||||
unique: list[SearchSnippet] = []
|
||||
for s in all_snippets:
|
||||
if s.url and s.url not in seen_urls:
|
||||
seen_urls.add(s.url)
|
||||
unique.append(s)
|
||||
|
||||
return unique
|
||||
|
||||
async def _fetch(self, snippets: list[SearchSnippet]) -> list[FetchedPage]:
|
||||
"""Fetch top pages from search snippets."""
|
||||
if not self.tools.web_fetch:
|
||||
logger.warning("No web_fetch tool configured — skipping fetch step")
|
||||
return []
|
||||
|
||||
# Take top N snippets
|
||||
to_fetch = snippets[:DEFAULT_PAGES_TO_FETCH]
|
||||
pages: list[FetchedPage] = []
|
||||
|
||||
async def _fetch_one(snippet: SearchSnippet) -> FetchedPage | None:
|
||||
try:
|
||||
content = await asyncio.to_thread(
|
||||
self.tools.web_fetch, snippet.url, DEFAULT_FETCH_TOKEN_LIMIT
|
||||
)
|
||||
if content:
|
||||
return FetchedPage(
|
||||
url=snippet.url,
|
||||
title=snippet.title,
|
||||
content=content[:DEFAULT_FETCH_TOKEN_LIMIT * 4],
|
||||
token_estimate=len(content.split()),
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Fetch failed for %s: %s", snippet.url, exc)
|
||||
return None
|
||||
|
||||
tasks = [_fetch_one(s) for s in to_fetch]
|
||||
results = await asyncio.gather(*tasks)
|
||||
for page in results:
|
||||
if page is not None:
|
||||
pages.append(page)
|
||||
|
||||
return pages
|
||||
|
||||
async def _synthesize(
|
||||
self,
|
||||
topic: str,
|
||||
template: str | None,
|
||||
pages: list[FetchedPage],
|
||||
cascade_tier: str | None,
|
||||
) -> str:
|
||||
"""Synthesize fetched pages into a structured research report."""
|
||||
# Build context from fetched pages
|
||||
context_parts = []
|
||||
for i, page in enumerate(pages, 1):
|
||||
context_parts.append(
|
||||
f"--- Source {i}: {page.title} ({page.url}) ---\n"
|
||||
f"{page.content[:DEFAULT_FETCH_TOKEN_LIMIT * 4]}\n"
|
||||
)
|
||||
|
||||
sources_text = "\n".join(context_parts) if context_parts else "(no sources fetched)"
|
||||
|
||||
if template:
|
||||
prompt = (
|
||||
f"{template}\n\n"
|
||||
f"Topic: {topic}\n\n"
|
||||
f"Research sources:\n{sources_text}\n\n"
|
||||
f"Synthesize a comprehensive report based on the sources above."
|
||||
)
|
||||
else:
|
||||
prompt = (
|
||||
f"Write a comprehensive research report on: {topic}\n\n"
|
||||
f"Research sources:\n{sources_text}\n\n"
|
||||
f"Structure your report with:\n"
|
||||
f"- Executive summary\n"
|
||||
f"- Key findings\n"
|
||||
f"- Analysis\n"
|
||||
f"- Action items (prefix each with 'ACTION:')\n"
|
||||
f"- Sources cited"
|
||||
)
|
||||
|
||||
messages = [
|
||||
{"role": "system", "content": "You are a research analyst producing structured reports."},
|
||||
{"role": "user", "content": prompt},
|
||||
]
|
||||
|
||||
kwargs: dict[str, Any] = {
|
||||
"messages": messages,
|
||||
"temperature": 0.3,
|
||||
"max_tokens": DEFAULT_SYNTHESIS_MAX_TOKENS,
|
||||
}
|
||||
if cascade_tier:
|
||||
kwargs["model"] = cascade_tier
|
||||
|
||||
try:
|
||||
response = await self.cascade.complete(**kwargs)
|
||||
return response.get("content", "")
|
||||
except Exception as exc:
|
||||
logger.error("Synthesis failed: %s", exc)
|
||||
# Fallback: return raw source summaries
|
||||
return (
|
||||
f"# Research: {topic}\n\n"
|
||||
f"Synthesis failed ({exc}). Raw sources:\n\n{sources_text}"
|
||||
)
|
||||
|
||||
async def _crystallize(self, topic: str, result: ResearchResult) -> None:
|
||||
"""Store the research result in semantic memory."""
|
||||
try:
|
||||
self.memory.store_fn(
|
||||
content=result.report,
|
||||
source="research_orchestrator",
|
||||
context_type="research",
|
||||
metadata={
|
||||
"topic": topic,
|
||||
"sources": result.sources,
|
||||
"action_items": result.action_items,
|
||||
"cache_hit": result.cache_hit,
|
||||
"duration_ms": result.duration_ms,
|
||||
},
|
||||
)
|
||||
logger.info("Crystallized research on '%s' into memory", topic)
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to crystallize research: %s", exc)
|
||||
|
||||
async def _write_artifact(self, result: ResearchResult) -> None:
|
||||
"""Create Gitea issues from action items."""
|
||||
if not result.action_items:
|
||||
return
|
||||
|
||||
try:
|
||||
await asyncio.to_thread(_create_gitea_issues, result)
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to create Gitea issues: %s", exc)
|
||||
|
||||
def get_metrics(self) -> dict[str, int]:
|
||||
"""Return current research pipeline metrics."""
|
||||
return dict(self._metrics)
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _extract_action_items(report: str) -> list[str]:
|
||||
"""Extract action items from a research report.
|
||||
|
||||
Looks for lines prefixed with ACTION:, TODO:, or - [ ].
|
||||
"""
|
||||
items: list[str] = []
|
||||
for line in report.splitlines():
|
||||
stripped = line.strip()
|
||||
# ACTION: prefix
|
||||
match = re.match(r"^(?:ACTION|TODO)\s*:\s*(.+)", stripped, re.IGNORECASE)
|
||||
if match:
|
||||
items.append(match.group(1).strip())
|
||||
continue
|
||||
# Markdown checkbox
|
||||
match = re.match(r"^-\s*\[\s*\]\s*(.+)", stripped)
|
||||
if match:
|
||||
items.append(match.group(1).strip())
|
||||
|
||||
return items
|
||||
|
||||
|
||||
def _create_gitea_issues(result: ResearchResult) -> None:
|
||||
"""Create Gitea issues for action items (runs in thread)."""
|
||||
if not settings.gitea_token or not settings.gitea_url:
|
||||
logger.debug("Gitea not configured — skipping issue creation")
|
||||
return
|
||||
|
||||
try:
|
||||
import requests
|
||||
except ImportError:
|
||||
logger.debug("requests not available — skipping Gitea issue creation")
|
||||
return
|
||||
|
||||
base_url = settings.gitea_url.rstrip("/")
|
||||
repo = settings.gitea_repo
|
||||
headers = {
|
||||
"Authorization": f"token {settings.gitea_token}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
|
||||
for item in result.action_items:
|
||||
try:
|
||||
payload = {
|
||||
"title": f"[research] {item[:100]}",
|
||||
"body": (
|
||||
f"Auto-generated from research on: **{result.topic}**\n\n"
|
||||
f"Action item: {item}\n\n"
|
||||
f"---\n"
|
||||
f"_Created by ResearchOrchestrator_"
|
||||
),
|
||||
}
|
||||
resp = requests.post(
|
||||
f"{base_url}/api/v1/repos/{repo}/issues",
|
||||
headers=headers,
|
||||
json=payload,
|
||||
timeout=10,
|
||||
)
|
||||
if resp.status_code in (200, 201):
|
||||
logger.info("Created Gitea issue: %s", item[:60])
|
||||
else:
|
||||
logger.warning(
|
||||
"Gitea issue creation failed (%d): %s",
|
||||
resp.status_code,
|
||||
resp.text[:200],
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Failed to create issue '%s': %s", item[:60], exc)
|
||||
|
||||
|
||||
# ── Convenience function ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
async def run_research(
|
||||
topic: str,
|
||||
template: str | None = None,
|
||||
context: dict[str, Any] | None = None,
|
||||
) -> ResearchResult:
|
||||
"""Convenience function to run research with default dependencies.
|
||||
|
||||
Creates a ResearchOrchestrator with the cascade router singleton
|
||||
and default memory, then executes the pipeline.
|
||||
"""
|
||||
from infrastructure.router.cascade import get_router
|
||||
|
||||
cascade = get_router()
|
||||
orchestrator = ResearchOrchestrator(cascade=cascade)
|
||||
return await orchestrator.run(topic, template=template, context=context)
|
||||
@@ -1,42 +0,0 @@
|
||||
"""Tools for the research pipeline."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
from typing import Any
|
||||
|
||||
from config import settings
|
||||
from serpapi import GoogleSearch
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
async def google_web_search(query: str) -> str:
|
||||
"""Perform a Google search and return the results."""
|
||||
if "SERPAPI_API_KEY" not in os.environ:
|
||||
logger.warning("SERPAPI_API_KEY not set, skipping web search")
|
||||
return ""
|
||||
params = {
|
||||
"q": query,
|
||||
"api_key": os.environ["SERPAPI_API_KEY"],
|
||||
}
|
||||
search = GoogleSearch(params)
|
||||
results = search.get_dict()
|
||||
return str(results)
|
||||
|
||||
|
||||
def get_llm_client() -> Any:
|
||||
"""Get an LLM client."""
|
||||
# This is a placeholder. In a real application, this would return
|
||||
# a client for an LLM service like OpenAI, Anthropic, or a local
|
||||
# model.
|
||||
class MockLLMClient:
|
||||
async def completion(self, prompt: str, max_tokens: int) -> Any:
|
||||
class MockCompletion:
|
||||
def __init__(self, text: str) -> None:
|
||||
self.text = text
|
||||
|
||||
return MockCompletion(f"This is a summary of the search results for '{prompt}'.")
|
||||
|
||||
return MockLLMClient()
|
||||
@@ -1,367 +0,0 @@
|
||||
"""Research triage — extract action items from research reports and file Gitea issues.
|
||||
|
||||
Closes the loop: research → knowledge → actionable engineering work.
|
||||
|
||||
The LLM extracts action items during synthesis (not post-processed), then
|
||||
each item is filed as a Gitea issue with appropriate labels, source links,
|
||||
and evidence from the original research.
|
||||
|
||||
Usage::
|
||||
|
||||
from timmy.research_triage import triage_research_report
|
||||
|
||||
results = await triage_research_report(
|
||||
report="## Findings\\n...",
|
||||
source_issue=946,
|
||||
)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any
|
||||
|
||||
import httpx
|
||||
|
||||
from config import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Regex to strip markdown code fences from LLM output
|
||||
_FENCE_RE = re.compile(r"^```(?:json)?\s*\n?", re.MULTILINE)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ActionItem:
|
||||
"""A single actionable item extracted from a research report."""
|
||||
|
||||
title: str
|
||||
body: str
|
||||
labels: list[str] = field(default_factory=list)
|
||||
priority: str = "medium"
|
||||
source_urls: list[str] = field(default_factory=list)
|
||||
|
||||
def to_issue_body(self, source_issue: int | None = None) -> str:
|
||||
"""Format for a Gitea issue body with source attribution."""
|
||||
parts = [self.body]
|
||||
|
||||
if self.source_urls:
|
||||
parts.append("\n### Source Evidence")
|
||||
for url in self.source_urls:
|
||||
parts.append(f"- {url}")
|
||||
|
||||
if source_issue:
|
||||
parts.append(f"\n### Origin\nExtracted from research in #{source_issue}")
|
||||
|
||||
parts.append("\n---\n*Auto-triaged from research findings by Timmy*")
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
def _build_extraction_prompt(report: str) -> str:
|
||||
"""Build the LLM prompt for extracting action items from a research report."""
|
||||
return (
|
||||
"You are triaging a research report for actionable engineering work.\n"
|
||||
"Extract 0-5 CONCRETE action items — bugs to fix, features to build,\n"
|
||||
"infrastructure to set up, or investigations to run.\n\n"
|
||||
"Rules:\n"
|
||||
"- Only include items that map to real engineering tasks\n"
|
||||
"- Skip vague recommendations or philosophical observations\n"
|
||||
"- Each item should be specific enough to become a Gitea issue\n"
|
||||
"- Include evidence/URLs from the report in source_urls\n"
|
||||
"- Priority: high (blocking or critical), medium (important), low (nice-to-have)\n"
|
||||
"- Labels: pick from [actionable, research, bug, feature, infrastructure, "
|
||||
"performance, security, kimi-ready]\n"
|
||||
" - 'kimi-ready' means a well-scoped task suitable for an AI agent\n"
|
||||
" - 'actionable' should be on every item (these are all actionable)\n\n"
|
||||
"For each item return:\n"
|
||||
'- "title": Clear, specific title with area prefix '
|
||||
'(e.g. "[MCP] Restore tool server with FastMCP")\n'
|
||||
'- "body": Detailed markdown body with:\n'
|
||||
" **What:** What needs to be done\n"
|
||||
" **Why:** Why this matters (link to research finding)\n"
|
||||
" **Suggested approach:** How to implement\n"
|
||||
" **Acceptance criteria:** How to verify\n"
|
||||
'- "labels": Array of label strings\n'
|
||||
'- "priority": One of high, medium, low\n'
|
||||
'- "source_urls": Array of URLs referenced in the research\n\n'
|
||||
"Return ONLY a JSON array of objects. Return [] if nothing is actionable.\n\n"
|
||||
f"Research report:\n{report}\n\nJSON array:"
|
||||
)
|
||||
|
||||
|
||||
def _parse_llm_response(raw: str) -> list[dict[str, Any]]:
|
||||
"""Parse LLM JSON response, stripping code fences if present."""
|
||||
cleaned = raw.strip()
|
||||
|
||||
# Strip markdown code fences
|
||||
if cleaned.startswith("```"):
|
||||
cleaned = cleaned.split("\n", 1)[-1].rsplit("```", 1)[0].strip()
|
||||
|
||||
items = json.loads(cleaned)
|
||||
if not isinstance(items, list):
|
||||
return []
|
||||
return items
|
||||
|
||||
|
||||
def _validate_action_item(raw_item: dict[str, Any]) -> ActionItem | None:
|
||||
"""Validate and convert a raw dict to an ActionItem, or None if invalid."""
|
||||
if not isinstance(raw_item, dict):
|
||||
return None
|
||||
|
||||
title = raw_item.get("title", "").strip()
|
||||
body = raw_item.get("body", "").strip()
|
||||
|
||||
if not title or len(title) < 10:
|
||||
return None
|
||||
if not body or len(body) < 20:
|
||||
return None
|
||||
|
||||
labels = raw_item.get("labels", [])
|
||||
if isinstance(labels, str):
|
||||
labels = [lbl.strip() for lbl in labels.split(",") if lbl.strip()]
|
||||
if not isinstance(labels, list):
|
||||
labels = []
|
||||
|
||||
# Ensure 'actionable' label is always present
|
||||
if "actionable" not in labels:
|
||||
labels.insert(0, "actionable")
|
||||
|
||||
priority = raw_item.get("priority", "medium").strip().lower()
|
||||
if priority not in ("high", "medium", "low"):
|
||||
priority = "medium"
|
||||
|
||||
source_urls = raw_item.get("source_urls", [])
|
||||
if not isinstance(source_urls, list):
|
||||
source_urls = []
|
||||
|
||||
return ActionItem(
|
||||
title=title,
|
||||
body=body,
|
||||
labels=labels,
|
||||
priority=priority,
|
||||
source_urls=source_urls,
|
||||
)
|
||||
|
||||
|
||||
async def extract_action_items(
|
||||
report: str,
|
||||
llm_caller: Any | None = None,
|
||||
) -> list[ActionItem]:
|
||||
"""Extract actionable engineering items from a research report.
|
||||
|
||||
Uses the LLM to identify concrete tasks, bugs, features, and
|
||||
infrastructure work from structured research output.
|
||||
|
||||
Args:
|
||||
report: The research report text (markdown).
|
||||
llm_caller: Optional async callable(prompt) -> str for LLM.
|
||||
Falls back to the cascade router.
|
||||
|
||||
Returns:
|
||||
List of validated ActionItem objects (0-5 items).
|
||||
"""
|
||||
if not report or not report.strip():
|
||||
return []
|
||||
|
||||
prompt = _build_extraction_prompt(report)
|
||||
|
||||
try:
|
||||
if llm_caller is not None:
|
||||
raw = await llm_caller(prompt)
|
||||
else:
|
||||
raw = await _call_llm(prompt)
|
||||
except Exception as exc:
|
||||
logger.warning("LLM extraction failed: %s", exc)
|
||||
return []
|
||||
|
||||
if not raw or not raw.strip():
|
||||
return []
|
||||
|
||||
try:
|
||||
raw_items = _parse_llm_response(raw)
|
||||
except (json.JSONDecodeError, ValueError) as exc:
|
||||
logger.warning("Failed to parse LLM action items: %s", exc)
|
||||
return []
|
||||
|
||||
items = []
|
||||
for raw_item in raw_items[:5]: # Safety cap
|
||||
item = _validate_action_item(raw_item)
|
||||
if item is not None:
|
||||
items.append(item)
|
||||
|
||||
logger.info("Extracted %d action items from research report", len(items))
|
||||
return items
|
||||
|
||||
|
||||
async def _call_llm(prompt: str) -> str:
|
||||
"""Call the cascade router for LLM completion.
|
||||
|
||||
Falls back gracefully if the router is unavailable.
|
||||
"""
|
||||
from infrastructure.router import get_router
|
||||
|
||||
router = get_router()
|
||||
messages = [{"role": "user", "content": prompt}]
|
||||
result = await router.complete(messages=messages, temperature=0.1)
|
||||
return result.get("content", "") if isinstance(result, dict) else str(result)
|
||||
|
||||
|
||||
async def create_gitea_issue(
|
||||
item: ActionItem,
|
||||
source_issue: int | None = None,
|
||||
) -> dict[str, Any] | None:
|
||||
"""Create a Gitea issue from an ActionItem via the REST API.
|
||||
|
||||
Args:
|
||||
item: The action item to file.
|
||||
source_issue: Parent research issue number to link back to.
|
||||
|
||||
Returns:
|
||||
The created issue dict from Gitea API, or None on failure.
|
||||
"""
|
||||
if not settings.gitea_enabled or not settings.gitea_token:
|
||||
logger.debug("Gitea not configured — skipping issue creation")
|
||||
return None
|
||||
|
||||
owner, repo = settings.gitea_repo.split("/", 1)
|
||||
api_url = f"{settings.gitea_url}/api/v1/repos/{owner}/{repo}/issues"
|
||||
|
||||
body = item.to_issue_body(source_issue=source_issue)
|
||||
|
||||
payload: dict[str, Any] = {
|
||||
"title": item.title,
|
||||
"body": body,
|
||||
}
|
||||
|
||||
# Resolve label names to IDs
|
||||
label_ids = await _resolve_label_ids(item.labels, owner, repo)
|
||||
if label_ids:
|
||||
payload["labels"] = label_ids
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=15) as client:
|
||||
resp = await client.post(
|
||||
api_url,
|
||||
headers={
|
||||
"Authorization": f"token {settings.gitea_token}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json=payload,
|
||||
)
|
||||
|
||||
if resp.status_code in (200, 201):
|
||||
issue_data = resp.json()
|
||||
logger.info(
|
||||
"Created Gitea issue #%s: %s",
|
||||
issue_data.get("number", "?"),
|
||||
item.title[:60],
|
||||
)
|
||||
return issue_data
|
||||
|
||||
logger.warning(
|
||||
"Gitea issue creation failed (HTTP %s): %s",
|
||||
resp.status_code,
|
||||
resp.text[:200],
|
||||
)
|
||||
return None
|
||||
|
||||
except (httpx.ConnectError, httpx.ReadError, ConnectionError) as exc:
|
||||
logger.warning("Gitea connection failed: %s", exc)
|
||||
return None
|
||||
except Exception as exc:
|
||||
logger.error("Unexpected error creating Gitea issue: %s", exc)
|
||||
return None
|
||||
|
||||
|
||||
async def _resolve_label_ids(
|
||||
label_names: list[str],
|
||||
owner: str,
|
||||
repo: str,
|
||||
) -> list[int]:
|
||||
"""Resolve label names to Gitea label IDs, creating missing labels.
|
||||
|
||||
Returns a list of integer label IDs for the issue payload.
|
||||
"""
|
||||
if not label_names:
|
||||
return []
|
||||
|
||||
labels_url = f"{settings.gitea_url}/api/v1/repos/{owner}/{repo}/labels"
|
||||
headers = {
|
||||
"Authorization": f"token {settings.gitea_token}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
# Fetch existing labels
|
||||
resp = await client.get(labels_url, headers=headers)
|
||||
if resp.status_code != 200:
|
||||
return []
|
||||
|
||||
existing = {lbl["name"]: lbl["id"] for lbl in resp.json()}
|
||||
label_ids = []
|
||||
|
||||
for name in label_names:
|
||||
if name in existing:
|
||||
label_ids.append(existing[name])
|
||||
else:
|
||||
# Auto-create missing labels with a default color
|
||||
create_resp = await client.post(
|
||||
labels_url,
|
||||
headers=headers,
|
||||
json={"name": name, "color": "#0075ca"},
|
||||
)
|
||||
if create_resp.status_code in (200, 201):
|
||||
label_ids.append(create_resp.json()["id"])
|
||||
|
||||
return label_ids
|
||||
|
||||
except Exception as exc:
|
||||
logger.debug("Label resolution failed: %s", exc)
|
||||
return []
|
||||
|
||||
|
||||
async def triage_research_report(
|
||||
report: str,
|
||||
source_issue: int | None = None,
|
||||
llm_caller: Any | None = None,
|
||||
dry_run: bool = False,
|
||||
) -> list[dict[str, Any]]:
|
||||
"""End-to-end: extract action items from research and file Gitea issues.
|
||||
|
||||
This is the main entry point that closes the research → backlog loop.
|
||||
|
||||
Args:
|
||||
report: Research report text (markdown).
|
||||
source_issue: The Gitea issue number that produced this research.
|
||||
llm_caller: Optional async callable(prompt) -> str for LLM calls.
|
||||
dry_run: If True, extract items but don't create issues.
|
||||
|
||||
Returns:
|
||||
List of dicts with 'action_item' and 'gitea_issue' (or None) keys.
|
||||
"""
|
||||
items = await extract_action_items(report, llm_caller=llm_caller)
|
||||
|
||||
if not items:
|
||||
logger.info("No action items extracted from research report")
|
||||
return []
|
||||
|
||||
results = []
|
||||
for item in items:
|
||||
if dry_run:
|
||||
results.append({"action_item": item, "gitea_issue": None})
|
||||
continue
|
||||
|
||||
issue_data = await create_gitea_issue(item, source_issue=source_issue)
|
||||
results.append({"action_item": item, "gitea_issue": issue_data})
|
||||
|
||||
created_count = sum(1 for r in results if r["gitea_issue"] is not None)
|
||||
logger.info(
|
||||
"Research triage complete: %d items extracted, %d issues created",
|
||||
len(results),
|
||||
created_count,
|
||||
)
|
||||
return results
|
||||
@@ -473,69 +473,6 @@ def consult_grok(query: str) -> str:
|
||||
return response
|
||||
|
||||
|
||||
def web_fetch(url: str, max_tokens: int = 4000) -> str:
|
||||
"""Fetch a web page and return its main text content.
|
||||
|
||||
Downloads the URL, extracts readable text using trafilatura, and
|
||||
truncates to a token budget. Use this to read full articles, docs,
|
||||
or blog posts that web_search only returns snippets for.
|
||||
|
||||
Args:
|
||||
url: The URL to fetch (must start with http:// or https://).
|
||||
max_tokens: Maximum approximate token budget (default 4000).
|
||||
Text is truncated to max_tokens * 4 characters.
|
||||
|
||||
Returns:
|
||||
Extracted text content, or an error message on failure.
|
||||
"""
|
||||
if not url or not url.startswith(("http://", "https://")):
|
||||
return f"Error: invalid URL — must start with http:// or https://: {url!r}"
|
||||
|
||||
try:
|
||||
import requests as _requests
|
||||
except ImportError:
|
||||
return "Error: 'requests' package is not installed. Install with: pip install requests"
|
||||
|
||||
try:
|
||||
import trafilatura
|
||||
except ImportError:
|
||||
return (
|
||||
"Error: 'trafilatura' package is not installed. Install with: pip install trafilatura"
|
||||
)
|
||||
|
||||
try:
|
||||
resp = _requests.get(
|
||||
url,
|
||||
timeout=15,
|
||||
headers={"User-Agent": "TimmyResearchBot/1.0"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
except _requests.exceptions.Timeout:
|
||||
return f"Error: request timed out after 15 seconds for {url}"
|
||||
except _requests.exceptions.HTTPError as exc:
|
||||
return f"Error: HTTP {exc.response.status_code} for {url}"
|
||||
except _requests.exceptions.RequestException as exc:
|
||||
return f"Error: failed to fetch {url} — {exc}"
|
||||
|
||||
text = trafilatura.extract(resp.text, include_tables=True, include_links=True)
|
||||
if not text:
|
||||
return f"Error: could not extract readable content from {url}"
|
||||
|
||||
char_budget = max_tokens * 4
|
||||
if len(text) > char_budget:
|
||||
text = text[:char_budget] + f"\n\n[…truncated to ~{max_tokens} tokens]"
|
||||
|
||||
return text
|
||||
|
||||
|
||||
def _register_web_fetch_tool(toolkit: Toolkit) -> None:
|
||||
"""Register the web_fetch tool for full-page content extraction."""
|
||||
try:
|
||||
toolkit.register(web_fetch, name="web_fetch")
|
||||
except Exception as exc:
|
||||
logger.warning("Tool execution failed (web_fetch registration): %s", exc)
|
||||
|
||||
|
||||
def _register_core_tools(toolkit: Toolkit, base_path: Path) -> None:
|
||||
"""Register core execution and file tools."""
|
||||
# Python execution
|
||||
@@ -735,7 +672,6 @@ def create_full_toolkit(base_dir: str | Path | None = None):
|
||||
base_path = Path(base_dir) if base_dir else Path(settings.repo_root)
|
||||
|
||||
_register_core_tools(toolkit, base_path)
|
||||
_register_web_fetch_tool(toolkit)
|
||||
_register_grok_tool(toolkit)
|
||||
_register_memory_tools(toolkit)
|
||||
_register_agentic_loop_tool(toolkit)
|
||||
@@ -893,11 +829,6 @@ def _analysis_tool_catalog() -> dict:
|
||||
"description": "Evaluate mathematical expressions with exact results",
|
||||
"available_in": ["orchestrator"],
|
||||
},
|
||||
"web_fetch": {
|
||||
"name": "Web Fetch",
|
||||
"description": "Fetch a web page and extract clean readable text (trafilatura)",
|
||||
"available_in": ["orchestrator"],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
|
||||
@@ -14,17 +14,10 @@ app = typer.Typer(help="Timmy Serve — sovereign AI agent API")
|
||||
def start(
|
||||
port: int = typer.Option(8402, "--port", "-p", help="Port for the serve API"),
|
||||
host: str = typer.Option("0.0.0.0", "--host", "-h", help="Host to bind to"),
|
||||
price: int = typer.Option(
|
||||
None, "--price", help="Price per request in sats (default: from config)"
|
||||
),
|
||||
price: int = typer.Option(100, "--price", help="Price per request in sats"),
|
||||
dry_run: bool = typer.Option(False, "--dry-run", help="Print config and exit (for testing)"),
|
||||
):
|
||||
"""Start Timmy in serve mode."""
|
||||
from config import settings
|
||||
|
||||
if price is None:
|
||||
price = settings.grok_sats_hard_cap
|
||||
|
||||
typer.echo(f"Starting Timmy Serve on {host}:{port}")
|
||||
typer.echo(f"L402 payment proxy active — {price} sats per request")
|
||||
typer.echo("Press Ctrl-C to stop")
|
||||
|
||||
@@ -147,12 +147,10 @@ def clean_database(tmp_path):
|
||||
# IMPORTANT: swarm.task_queue.models also has a DB_PATH that writes to
|
||||
# tasks.db — it MUST be patched too, or error_capture.capture_error()
|
||||
# will write test data to the production database.
|
||||
tmp_sovereignty_db = tmp_path / "sovereignty_metrics.db"
|
||||
for mod_name, tmp_db in [
|
||||
("dashboard.routes.tasks", tmp_tasks_db),
|
||||
("dashboard.routes.work_orders", tmp_work_orders_db),
|
||||
("swarm.task_queue.models", tmp_tasks_db),
|
||||
("infrastructure.sovereignty_metrics", tmp_sovereignty_db),
|
||||
]:
|
||||
try:
|
||||
mod = __import__(mod_name, fromlist=["DB_PATH"])
|
||||
|
||||
@@ -1,499 +0,0 @@
|
||||
"""Unit tests for dashboard/routes/health.py.
|
||||
|
||||
Covers helper functions, caching, endpoint responses, and graceful
|
||||
degradation when subsystems (Ollama, SQLite) are unavailable.
|
||||
|
||||
Fixes #945
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from dashboard.routes.health import (
|
||||
DependencyStatus,
|
||||
HealthStatus,
|
||||
SovereigntyReport,
|
||||
_calculate_overall_score,
|
||||
_check_lightning,
|
||||
_check_ollama_sync,
|
||||
_check_sqlite,
|
||||
_generate_recommendations,
|
||||
)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pydantic models
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestDependencyStatusModel:
|
||||
"""Validate DependencyStatus model."""
|
||||
|
||||
def test_fields(self):
|
||||
dep = DependencyStatus(
|
||||
name="Test", status="healthy", sovereignty_score=8, details={"key": "val"}
|
||||
)
|
||||
assert dep.name == "Test"
|
||||
assert dep.status == "healthy"
|
||||
assert dep.sovereignty_score == 8
|
||||
assert dep.details == {"key": "val"}
|
||||
|
||||
def test_empty_details(self):
|
||||
dep = DependencyStatus(name="X", status="unavailable", sovereignty_score=0, details={})
|
||||
assert dep.details == {}
|
||||
|
||||
|
||||
class TestSovereigntyReportModel:
|
||||
"""Validate SovereigntyReport model."""
|
||||
|
||||
def test_fields(self):
|
||||
report = SovereigntyReport(
|
||||
overall_score=9.3,
|
||||
dependencies=[],
|
||||
timestamp="2026-01-01T00:00:00+00:00",
|
||||
recommendations=["All good"],
|
||||
)
|
||||
assert report.overall_score == 9.3
|
||||
assert report.dependencies == []
|
||||
assert report.recommendations == ["All good"]
|
||||
|
||||
|
||||
class TestHealthStatusModel:
|
||||
"""Validate HealthStatus model."""
|
||||
|
||||
def test_fields(self):
|
||||
hs = HealthStatus(
|
||||
status="ok",
|
||||
timestamp="2026-01-01T00:00:00+00:00",
|
||||
version="2.0.0",
|
||||
uptime_seconds=42.5,
|
||||
)
|
||||
assert hs.status == "ok"
|
||||
assert hs.uptime_seconds == 42.5
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Helper functions
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCalculateOverallScore:
|
||||
"""Test _calculate_overall_score."""
|
||||
|
||||
def test_empty_deps(self):
|
||||
assert _calculate_overall_score([]) == 0.0
|
||||
|
||||
def test_single_dep(self):
|
||||
deps = [DependencyStatus(name="A", status="healthy", sovereignty_score=7, details={})]
|
||||
assert _calculate_overall_score(deps) == 7.0
|
||||
|
||||
def test_averages_multiple(self):
|
||||
deps = [
|
||||
DependencyStatus(name="A", status="healthy", sovereignty_score=10, details={}),
|
||||
DependencyStatus(name="B", status="healthy", sovereignty_score=8, details={}),
|
||||
DependencyStatus(name="C", status="unavailable", sovereignty_score=6, details={}),
|
||||
]
|
||||
assert _calculate_overall_score(deps) == 8.0
|
||||
|
||||
def test_rounding(self):
|
||||
deps = [
|
||||
DependencyStatus(name="A", status="healthy", sovereignty_score=10, details={}),
|
||||
DependencyStatus(name="B", status="healthy", sovereignty_score=9, details={}),
|
||||
DependencyStatus(name="C", status="healthy", sovereignty_score=10, details={}),
|
||||
]
|
||||
assert _calculate_overall_score(deps) == 9.7
|
||||
|
||||
|
||||
class TestGenerateRecommendations:
|
||||
"""Test _generate_recommendations."""
|
||||
|
||||
def test_all_healthy(self):
|
||||
deps = [DependencyStatus(name="X", status="healthy", sovereignty_score=10, details={})]
|
||||
recs = _generate_recommendations(deps)
|
||||
assert recs == ["System operating optimally - all dependencies healthy"]
|
||||
|
||||
def test_unavailable_service(self):
|
||||
deps = [
|
||||
DependencyStatus(
|
||||
name="Ollama AI", status="unavailable", sovereignty_score=10, details={}
|
||||
)
|
||||
]
|
||||
recs = _generate_recommendations(deps)
|
||||
assert any("Ollama AI is unavailable" in r for r in recs)
|
||||
|
||||
def test_degraded_lightning_mock(self):
|
||||
deps = [
|
||||
DependencyStatus(
|
||||
name="Lightning Payments",
|
||||
status="degraded",
|
||||
sovereignty_score=8,
|
||||
details={"backend": "mock"},
|
||||
)
|
||||
]
|
||||
recs = _generate_recommendations(deps)
|
||||
assert any("Switch to real Lightning" in r for r in recs)
|
||||
|
||||
def test_degraded_non_lightning(self):
|
||||
"""Degraded non-Lightning dep produces no specific recommendation."""
|
||||
deps = [DependencyStatus(name="Redis", status="degraded", sovereignty_score=5, details={})]
|
||||
recs = _generate_recommendations(deps)
|
||||
assert recs == ["System operating optimally - all dependencies healthy"]
|
||||
|
||||
def test_multiple_unavailable(self):
|
||||
deps = [
|
||||
DependencyStatus(name="A", status="unavailable", sovereignty_score=5, details={}),
|
||||
DependencyStatus(name="B", status="unavailable", sovereignty_score=5, details={}),
|
||||
]
|
||||
recs = _generate_recommendations(deps)
|
||||
assert len(recs) == 2
|
||||
assert "A is unavailable" in recs[0]
|
||||
assert "B is unavailable" in recs[1]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _check_lightning (static)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCheckLightning:
|
||||
"""Test _check_lightning — always returns unavailable for now."""
|
||||
|
||||
def test_returns_unavailable(self):
|
||||
dep = _check_lightning()
|
||||
assert dep.name == "Lightning Payments"
|
||||
assert dep.status == "unavailable"
|
||||
assert dep.sovereignty_score == 8
|
||||
assert "removed" in dep.details.get("note", "").lower()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _check_ollama_sync
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCheckOllamaSync:
|
||||
"""Test synchronous Ollama health probe."""
|
||||
|
||||
def test_healthy_when_reachable(self):
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.status = 200
|
||||
mock_resp.__enter__ = MagicMock(return_value=mock_resp)
|
||||
mock_resp.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
with patch("urllib.request.urlopen", return_value=mock_resp):
|
||||
dep = _check_ollama_sync()
|
||||
|
||||
assert dep.status == "healthy"
|
||||
assert dep.name == "Ollama AI"
|
||||
assert dep.sovereignty_score == 10
|
||||
|
||||
def test_unavailable_on_connection_error(self):
|
||||
with patch(
|
||||
"urllib.request.urlopen",
|
||||
side_effect=ConnectionError("refused"),
|
||||
):
|
||||
dep = _check_ollama_sync()
|
||||
|
||||
assert dep.status == "unavailable"
|
||||
assert "Cannot connect" in dep.details.get("error", "")
|
||||
|
||||
def test_unavailable_on_timeout(self):
|
||||
from urllib.error import URLError
|
||||
|
||||
with patch(
|
||||
"urllib.request.urlopen",
|
||||
side_effect=URLError("timeout"),
|
||||
):
|
||||
dep = _check_ollama_sync()
|
||||
|
||||
assert dep.status == "unavailable"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _check_sqlite
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCheckSQLite:
|
||||
"""Test SQLite health probe."""
|
||||
|
||||
def test_healthy_when_db_reachable(self, tmp_path):
|
||||
import sqlite3
|
||||
|
||||
db_path = tmp_path / "data" / "timmy.db"
|
||||
db_path.parent.mkdir(parents=True)
|
||||
sqlite3.connect(str(db_path)).close()
|
||||
|
||||
with patch("dashboard.routes.health.settings") as mock_settings:
|
||||
mock_settings.repo_root = str(tmp_path)
|
||||
dep = _check_sqlite()
|
||||
|
||||
assert dep.status == "healthy"
|
||||
assert dep.name == "SQLite Database"
|
||||
|
||||
def test_unavailable_on_missing_db(self, tmp_path):
|
||||
with patch("dashboard.routes.health.settings") as mock_settings:
|
||||
mock_settings.repo_root = str(tmp_path / "nonexistent")
|
||||
dep = _check_sqlite()
|
||||
|
||||
assert dep.status == "unavailable"
|
||||
assert "error" in dep.details
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _check_ollama (async, with caching)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCheckOllamaAsync:
|
||||
"""Test async Ollama check with TTL cache."""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_cache(self):
|
||||
"""Clear the module-level Ollama cache before each test."""
|
||||
import dashboard.routes.health as mod
|
||||
|
||||
mod._ollama_cache = None
|
||||
mod._ollama_cache_ts = 0.0
|
||||
yield
|
||||
mod._ollama_cache = None
|
||||
mod._ollama_cache_ts = 0.0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_returns_dependency_status(self):
|
||||
healthy = DependencyStatus(
|
||||
name="Ollama AI", status="healthy", sovereignty_score=10, details={}
|
||||
)
|
||||
with patch(
|
||||
"dashboard.routes.health._check_ollama_sync",
|
||||
return_value=healthy,
|
||||
):
|
||||
from dashboard.routes.health import _check_ollama
|
||||
|
||||
result = await _check_ollama()
|
||||
|
||||
assert result.status == "healthy"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_caches_result(self):
|
||||
healthy = DependencyStatus(
|
||||
name="Ollama AI", status="healthy", sovereignty_score=10, details={}
|
||||
)
|
||||
with patch(
|
||||
"dashboard.routes.health._check_ollama_sync",
|
||||
return_value=healthy,
|
||||
) as mock_sync:
|
||||
from dashboard.routes.health import _check_ollama
|
||||
|
||||
await _check_ollama()
|
||||
await _check_ollama()
|
||||
|
||||
# Should only call the sync function once due to cache
|
||||
assert mock_sync.call_count == 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_expires(self):
|
||||
healthy = DependencyStatus(
|
||||
name="Ollama AI", status="healthy", sovereignty_score=10, details={}
|
||||
)
|
||||
import dashboard.routes.health as mod
|
||||
|
||||
with patch(
|
||||
"dashboard.routes.health._check_ollama_sync",
|
||||
return_value=healthy,
|
||||
) as mock_sync:
|
||||
from dashboard.routes.health import _check_ollama
|
||||
|
||||
await _check_ollama()
|
||||
# Expire the cache
|
||||
mod._ollama_cache_ts = time.monotonic() - 60
|
||||
await _check_ollama()
|
||||
|
||||
assert mock_sync.call_count == 2
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fallback_on_thread_exception(self):
|
||||
"""If to_thread raises, return unavailable status."""
|
||||
import asyncio
|
||||
|
||||
with patch.object(
|
||||
asyncio,
|
||||
"to_thread",
|
||||
side_effect=RuntimeError("thread pool exhausted"),
|
||||
):
|
||||
from dashboard.routes.health import _check_ollama
|
||||
|
||||
result = await _check_ollama()
|
||||
|
||||
assert result.status == "unavailable"
|
||||
|
||||
|
||||
class TestCheckOllamaBool:
|
||||
"""Test the legacy bool wrapper."""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_cache(self):
|
||||
import dashboard.routes.health as mod
|
||||
|
||||
mod._ollama_cache = None
|
||||
mod._ollama_cache_ts = 0.0
|
||||
yield
|
||||
mod._ollama_cache = None
|
||||
mod._ollama_cache_ts = 0.0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_true_when_healthy(self):
|
||||
healthy = DependencyStatus(
|
||||
name="Ollama AI", status="healthy", sovereignty_score=10, details={}
|
||||
)
|
||||
with patch("dashboard.routes.health._check_ollama_sync", return_value=healthy):
|
||||
from dashboard.routes.health import check_ollama
|
||||
|
||||
assert await check_ollama() is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_false_when_unavailable(self):
|
||||
down = DependencyStatus(
|
||||
name="Ollama AI", status="unavailable", sovereignty_score=10, details={}
|
||||
)
|
||||
with patch("dashboard.routes.health._check_ollama_sync", return_value=down):
|
||||
from dashboard.routes.health import check_ollama
|
||||
|
||||
assert await check_ollama() is False
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Endpoint tests via FastAPI TestClient
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestHealthEndpoint:
|
||||
"""Tests for GET /health."""
|
||||
|
||||
def test_returns_200(self, client):
|
||||
response = client.get("/health")
|
||||
assert response.status_code == 200
|
||||
|
||||
def test_ok_when_ollama_up(self, client):
|
||||
with patch(
|
||||
"dashboard.routes.health.check_ollama", new_callable=AsyncMock, return_value=True
|
||||
):
|
||||
data = client.get("/health").json()
|
||||
|
||||
assert data["status"] == "ok"
|
||||
assert data["services"]["ollama"] == "up"
|
||||
assert data["agents"]["agent"]["status"] == "idle"
|
||||
|
||||
def test_degraded_when_ollama_down(self, client):
|
||||
with patch(
|
||||
"dashboard.routes.health.check_ollama", new_callable=AsyncMock, return_value=False
|
||||
):
|
||||
data = client.get("/health").json()
|
||||
|
||||
assert data["status"] == "degraded"
|
||||
assert data["services"]["ollama"] == "down"
|
||||
assert data["agents"]["agent"]["status"] == "offline"
|
||||
|
||||
def test_extended_fields(self, client):
|
||||
data = client.get("/health").json()
|
||||
assert "timestamp" in data
|
||||
assert "version" in data
|
||||
assert "uptime_seconds" in data
|
||||
assert isinstance(data["uptime_seconds"], (int, float))
|
||||
assert "llm_backend" in data
|
||||
assert "llm_model" in data
|
||||
|
||||
|
||||
class TestHealthStatusPanel:
|
||||
"""Tests for GET /health/status (HTML response)."""
|
||||
|
||||
def test_returns_html(self, client):
|
||||
response = client.get("/health/status")
|
||||
assert response.status_code == 200
|
||||
assert "text/html" in response.headers["content-type"]
|
||||
|
||||
def test_shows_up_when_ollama_healthy(self, client):
|
||||
with patch(
|
||||
"dashboard.routes.health.check_ollama", new_callable=AsyncMock, return_value=True
|
||||
):
|
||||
text = client.get("/health/status").text
|
||||
|
||||
assert "UP" in text
|
||||
|
||||
def test_shows_down_when_ollama_unhealthy(self, client):
|
||||
with patch(
|
||||
"dashboard.routes.health.check_ollama", new_callable=AsyncMock, return_value=False
|
||||
):
|
||||
text = client.get("/health/status").text
|
||||
|
||||
assert "DOWN" in text
|
||||
|
||||
def test_includes_model_name(self, client):
|
||||
text = client.get("/health/status").text
|
||||
assert "Model:" in text
|
||||
|
||||
|
||||
class TestSovereigntyEndpoint:
|
||||
"""Tests for GET /health/sovereignty."""
|
||||
|
||||
def test_aggregates_three_subsystems(self, client):
|
||||
data = client.get("/health/sovereignty").json()
|
||||
names = [d["name"] for d in data["dependencies"]]
|
||||
assert "Ollama AI" in names
|
||||
assert "Lightning Payments" in names
|
||||
assert "SQLite Database" in names
|
||||
|
||||
def test_score_range(self, client):
|
||||
data = client.get("/health/sovereignty").json()
|
||||
assert 0 <= data["overall_score"] <= 10
|
||||
|
||||
|
||||
class TestComponentsEndpoint:
|
||||
"""Tests for GET /health/components."""
|
||||
|
||||
def test_returns_timestamp(self, client):
|
||||
data = client.get("/health/components").json()
|
||||
assert "timestamp" in data
|
||||
|
||||
def test_config_keys(self, client):
|
||||
data = client.get("/health/components").json()
|
||||
cfg = data["config"]
|
||||
assert "debug" in cfg
|
||||
assert "model_backend" in cfg
|
||||
assert "ollama_model" in cfg
|
||||
|
||||
|
||||
class TestSnapshotEndpoint:
|
||||
"""Tests for GET /health/snapshot."""
|
||||
|
||||
def test_returns_200(self, client):
|
||||
response = client.get("/health/snapshot")
|
||||
assert response.status_code == 200
|
||||
|
||||
def test_overall_status_valid(self, client):
|
||||
data = client.get("/health/snapshot").json()
|
||||
assert data["overall_status"] in ["green", "yellow", "red", "unknown"]
|
||||
|
||||
def test_graceful_fallback_on_import_error(self, client):
|
||||
"""Snapshot degrades gracefully when automation module fails."""
|
||||
with patch(
|
||||
"dashboard.routes.health.asyncio.to_thread",
|
||||
side_effect=ImportError("no module"),
|
||||
):
|
||||
data = client.get("/health/snapshot").json()
|
||||
|
||||
assert data["overall_status"] == "unknown"
|
||||
assert "error" in data
|
||||
assert data["ci"]["status"] == "unknown"
|
||||
|
||||
def test_graceful_fallback_on_runtime_error(self, client):
|
||||
with patch(
|
||||
"dashboard.routes.health.asyncio.to_thread",
|
||||
side_effect=RuntimeError("boom"),
|
||||
):
|
||||
data = client.get("/health/snapshot").json()
|
||||
|
||||
assert data["overall_status"] == "unknown"
|
||||
@@ -1,267 +0,0 @@
|
||||
"""Tests for Claude Quota Monitor and Metabolic Protocol."""
|
||||
|
||||
from datetime import UTC, datetime, timedelta
|
||||
from unittest.mock import patch
|
||||
|
||||
from infrastructure.claude_quota import (
|
||||
MetabolicTier,
|
||||
QuotaMonitor,
|
||||
QuotaStatus,
|
||||
_time_remaining,
|
||||
get_quota_monitor,
|
||||
)
|
||||
|
||||
|
||||
def _make_status(five_hour: float = 0.0, seven_day: float = 0.0) -> QuotaStatus:
|
||||
"""Helper: build a QuotaStatus with given utilization values."""
|
||||
return QuotaStatus(
|
||||
five_hour_utilization=five_hour,
|
||||
five_hour_resets_at=None,
|
||||
seven_day_utilization=seven_day,
|
||||
seven_day_resets_at=None,
|
||||
raw_response={},
|
||||
fetched_at=datetime.now(UTC),
|
||||
)
|
||||
|
||||
|
||||
class TestMetabolicTierThresholds:
|
||||
"""Test the three-tier metabolic protocol thresholds."""
|
||||
|
||||
def test_burst_when_five_hour_below_50pct(self):
|
||||
status = _make_status(five_hour=0.49, seven_day=0.10)
|
||||
assert status.recommended_tier == MetabolicTier.BURST
|
||||
|
||||
def test_burst_at_zero_utilization(self):
|
||||
status = _make_status(five_hour=0.0, seven_day=0.0)
|
||||
assert status.recommended_tier == MetabolicTier.BURST
|
||||
|
||||
def test_active_when_five_hour_at_50pct(self):
|
||||
status = _make_status(five_hour=0.50, seven_day=0.10)
|
||||
assert status.recommended_tier == MetabolicTier.ACTIVE
|
||||
|
||||
def test_active_when_five_hour_between_50_and_80pct(self):
|
||||
status = _make_status(five_hour=0.79, seven_day=0.10)
|
||||
assert status.recommended_tier == MetabolicTier.ACTIVE
|
||||
|
||||
def test_active_when_five_hour_at_80pct(self):
|
||||
# five_hour >= 0.80 but seven_day < 0.80 → ACTIVE (not RESTING)
|
||||
status = _make_status(five_hour=0.80, seven_day=0.50)
|
||||
assert status.recommended_tier == MetabolicTier.ACTIVE
|
||||
|
||||
def test_resting_when_seven_day_at_80pct(self):
|
||||
status = _make_status(five_hour=0.30, seven_day=0.80)
|
||||
assert status.recommended_tier == MetabolicTier.RESTING
|
||||
|
||||
def test_resting_when_seven_day_above_80pct(self):
|
||||
status = _make_status(five_hour=0.10, seven_day=0.95)
|
||||
assert status.recommended_tier == MetabolicTier.RESTING
|
||||
|
||||
def test_resting_when_both_critical(self):
|
||||
status = _make_status(five_hour=0.90, seven_day=0.90)
|
||||
assert status.recommended_tier == MetabolicTier.RESTING
|
||||
|
||||
def test_seven_day_takes_precedence_over_five_hour(self):
|
||||
# Weekly quota critical overrides whatever five-hour says
|
||||
status = _make_status(five_hour=0.10, seven_day=0.85)
|
||||
assert status.recommended_tier == MetabolicTier.RESTING
|
||||
|
||||
|
||||
class TestQuotaStatusProperties:
|
||||
"""Test QuotaStatus computed properties."""
|
||||
|
||||
def test_five_hour_pct(self):
|
||||
status = _make_status(five_hour=0.42)
|
||||
assert status.five_hour_pct == 42
|
||||
|
||||
def test_seven_day_pct(self):
|
||||
status = _make_status(seven_day=0.75)
|
||||
assert status.seven_day_pct == 75
|
||||
|
||||
def test_summary_contains_tier(self):
|
||||
status = _make_status(five_hour=0.20, seven_day=0.10)
|
||||
summary = status.summary()
|
||||
assert "burst" in summary
|
||||
assert "20%" in summary
|
||||
|
||||
def test_five_hour_resets_in_unknown_when_none(self):
|
||||
status = _make_status()
|
||||
assert status.five_hour_resets_in == "unknown"
|
||||
|
||||
def test_seven_day_resets_in_unknown_when_none(self):
|
||||
status = _make_status()
|
||||
assert status.seven_day_resets_in == "unknown"
|
||||
|
||||
|
||||
class TestTimeRemaining:
|
||||
"""Test _time_remaining helper."""
|
||||
|
||||
def test_none_returns_unknown(self):
|
||||
assert _time_remaining(None) == "unknown"
|
||||
|
||||
def test_empty_string_returns_unknown(self):
|
||||
assert _time_remaining("") == "unknown"
|
||||
|
||||
def test_past_time_returns_resetting_now(self):
|
||||
past = (datetime.now(UTC) - timedelta(hours=1)).isoformat()
|
||||
assert _time_remaining(past) == "resetting now"
|
||||
|
||||
def test_future_time_hours_and_minutes(self):
|
||||
future = (datetime.now(UTC) + timedelta(hours=2, minutes=15)).isoformat()
|
||||
result = _time_remaining(future)
|
||||
assert "2h" in result
|
||||
# Minutes may vary ±1 due to test execution time
|
||||
assert "m" in result
|
||||
|
||||
def test_future_time_minutes_only(self):
|
||||
future = (datetime.now(UTC) + timedelta(minutes=45)).isoformat()
|
||||
result = _time_remaining(future)
|
||||
assert "h" not in result
|
||||
# Minutes may vary ±1 due to test execution time
|
||||
assert "m" in result
|
||||
|
||||
def test_z_suffix_handled(self):
|
||||
future = (datetime.now(UTC) + timedelta(hours=1)).strftime("%Y-%m-%dT%H:%M:%SZ")
|
||||
result = _time_remaining(future)
|
||||
assert result != "unknown"
|
||||
|
||||
|
||||
class TestQuotaMonitorSelectModel:
|
||||
"""Test select_model metabolic routing."""
|
||||
|
||||
def test_no_quota_high_complexity_returns_14b(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._get_token = lambda: None
|
||||
assert monitor.select_model("high") == "qwen3:14b"
|
||||
|
||||
def test_no_quota_low_complexity_returns_8b(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._get_token = lambda: None
|
||||
assert monitor.select_model("low") == "qwen3:8b"
|
||||
|
||||
def test_burst_tier_high_complexity_returns_cloud(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.10, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
result = monitor.select_model("high")
|
||||
assert result == "claude-sonnet-4-6"
|
||||
|
||||
def test_burst_tier_medium_complexity_returns_14b(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.10, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
result = monitor.select_model("medium")
|
||||
assert result == "qwen3:14b"
|
||||
|
||||
def test_active_tier_returns_14b(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.65, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
result = monitor.select_model("high")
|
||||
assert result == "qwen3:14b"
|
||||
|
||||
def test_resting_tier_returns_8b(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.10, seven_day=0.85)
|
||||
monitor._cache_seconds = 9999
|
||||
result = monitor.select_model("high")
|
||||
assert result == "qwen3:8b"
|
||||
|
||||
|
||||
class TestQuotaMonitorShouldUseCloud:
|
||||
"""Test should_use_cloud gate."""
|
||||
|
||||
def test_no_credentials_always_false(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._get_token = lambda: None
|
||||
assert monitor.should_use_cloud("critical") is False
|
||||
|
||||
def test_critical_task_allowed_when_under_95pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.10, seven_day=0.94)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("critical") is True
|
||||
|
||||
def test_critical_task_blocked_when_over_95pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.10, seven_day=0.96)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("critical") is False
|
||||
|
||||
def test_high_task_allowed_under_60pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.59, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("high") is True
|
||||
|
||||
def test_high_task_blocked_at_60pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.60, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("high") is False
|
||||
|
||||
def test_normal_task_allowed_under_30pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.29, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("normal") is True
|
||||
|
||||
def test_normal_task_blocked_at_30pct(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.30, seven_day=0.10)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("normal") is False
|
||||
|
||||
def test_routine_task_always_false(self):
|
||||
monitor = QuotaMonitor()
|
||||
monitor._last_status = _make_status(five_hour=0.0, seven_day=0.0)
|
||||
monitor._cache_seconds = 9999
|
||||
assert monitor.should_use_cloud("routine") is False
|
||||
|
||||
|
||||
class TestQuotaMonitorCaching:
|
||||
"""Test 30-second TTL cache."""
|
||||
|
||||
def test_cached_result_returned_within_ttl(self):
|
||||
monitor = QuotaMonitor()
|
||||
fresh_status = _make_status(five_hour=0.10)
|
||||
monitor._last_status = fresh_status
|
||||
monitor._cache_seconds = 30
|
||||
|
||||
# Should NOT re-fetch — returns cached
|
||||
with patch.object(monitor, "_get_token", return_value="tok") as mock_tok:
|
||||
result = monitor.check()
|
||||
mock_tok.assert_not_called()
|
||||
|
||||
assert result is fresh_status
|
||||
|
||||
def test_stale_cache_triggers_fetch(self):
|
||||
monitor = QuotaMonitor()
|
||||
old_time = datetime.now(UTC) - timedelta(seconds=60)
|
||||
stale_status = QuotaStatus(
|
||||
five_hour_utilization=0.10,
|
||||
five_hour_resets_at=None,
|
||||
seven_day_utilization=0.10,
|
||||
seven_day_resets_at=None,
|
||||
raw_response={},
|
||||
fetched_at=old_time,
|
||||
)
|
||||
monitor._last_status = stale_status
|
||||
|
||||
# Token unavailable → returns None (triggers re-fetch path)
|
||||
with patch.object(monitor, "_get_token", return_value=None):
|
||||
result = monitor.check()
|
||||
|
||||
assert result is None # No credentials after cache miss
|
||||
|
||||
|
||||
class TestGetQuotaMonitorSingleton:
|
||||
"""Test module-level singleton."""
|
||||
|
||||
def test_returns_same_instance(self):
|
||||
m1 = get_quota_monitor()
|
||||
m2 = get_quota_monitor()
|
||||
assert m1 is m2
|
||||
|
||||
def test_returns_quota_monitor_instance(self):
|
||||
monitor = get_quota_monitor()
|
||||
assert isinstance(monitor, QuotaMonitor)
|
||||
@@ -242,145 +242,6 @@ class TestCloseAll:
|
||||
conn.execute("SELECT 1")
|
||||
|
||||
|
||||
class TestConnectionLeaks:
|
||||
"""Test that connections do not leak."""
|
||||
|
||||
def test_get_connection_after_close_returns_fresh_connection(self, tmp_path):
|
||||
"""After close, get_connection() returns a new working connection."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
conn1 = pool.get_connection()
|
||||
pool.close_connection()
|
||||
|
||||
conn2 = pool.get_connection()
|
||||
assert conn2 is not conn1
|
||||
# New connection must be usable
|
||||
cursor = conn2.execute("SELECT 1")
|
||||
assert cursor.fetchone()[0] == 1
|
||||
pool.close_connection()
|
||||
|
||||
def test_context_manager_does_not_leak_connection(self, tmp_path):
|
||||
"""After context manager exit, thread-local conn is cleared."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
with pool.connection():
|
||||
pass
|
||||
# Thread-local should be cleaned up
|
||||
assert pool._local.conn is None
|
||||
|
||||
def test_context_manager_exception_does_not_leak_connection(self, tmp_path):
|
||||
"""Connection is cleaned up even when an exception occurs."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
try:
|
||||
with pool.connection():
|
||||
raise RuntimeError("boom")
|
||||
except RuntimeError:
|
||||
pass
|
||||
assert pool._local.conn is None
|
||||
|
||||
def test_threads_do_not_leak_into_each_other(self, tmp_path):
|
||||
"""A connection opened in one thread is invisible to another."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
# Open a connection on main thread
|
||||
pool.get_connection()
|
||||
|
||||
visible_from_other_thread = []
|
||||
|
||||
def check():
|
||||
has_conn = hasattr(pool._local, "conn") and pool._local.conn is not None
|
||||
visible_from_other_thread.append(has_conn)
|
||||
|
||||
t = threading.Thread(target=check)
|
||||
t.start()
|
||||
t.join()
|
||||
|
||||
assert visible_from_other_thread == [False]
|
||||
pool.close_connection()
|
||||
|
||||
def test_repeated_open_close_cycles(self, tmp_path):
|
||||
"""Repeated open/close cycles do not accumulate leaked connections."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
for _ in range(50):
|
||||
with pool.connection() as conn:
|
||||
conn.execute("SELECT 1")
|
||||
# After each cycle, connection should be cleaned up
|
||||
assert pool._local.conn is None
|
||||
|
||||
|
||||
class TestPragmaApplication:
|
||||
"""Test that SQLite pragmas can be applied and persist on pooled connections.
|
||||
|
||||
The codebase uses WAL journal mode and busy_timeout pragmas on connections
|
||||
obtained from the pool. These tests verify that pattern works correctly.
|
||||
"""
|
||||
|
||||
def test_wal_journal_mode_persists(self, tmp_path):
|
||||
"""WAL journal mode set on a pooled connection persists for its lifetime."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
conn = pool.get_connection()
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
mode = conn.execute("PRAGMA journal_mode").fetchone()[0]
|
||||
assert mode == "wal"
|
||||
|
||||
# Same connection should retain the pragma
|
||||
same_conn = pool.get_connection()
|
||||
mode2 = same_conn.execute("PRAGMA journal_mode").fetchone()[0]
|
||||
assert mode2 == "wal"
|
||||
pool.close_connection()
|
||||
|
||||
def test_busy_timeout_persists(self, tmp_path):
|
||||
"""busy_timeout pragma set on a pooled connection persists."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
conn = pool.get_connection()
|
||||
conn.execute("PRAGMA busy_timeout=5000")
|
||||
timeout = conn.execute("PRAGMA busy_timeout").fetchone()[0]
|
||||
assert timeout == 5000
|
||||
pool.close_connection()
|
||||
|
||||
def test_pragmas_apply_per_connection(self, tmp_path):
|
||||
"""Pragmas set on one thread's connection are independent of another's."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
conn_main = pool.get_connection()
|
||||
conn_main.execute("PRAGMA cache_size=9999")
|
||||
|
||||
other_cache = []
|
||||
|
||||
def check_pragma():
|
||||
conn = pool.get_connection()
|
||||
# Don't set cache_size — should get the default, not 9999
|
||||
val = conn.execute("PRAGMA cache_size").fetchone()[0]
|
||||
other_cache.append(val)
|
||||
pool.close_connection()
|
||||
|
||||
t = threading.Thread(target=check_pragma)
|
||||
t.start()
|
||||
t.join()
|
||||
|
||||
# Other thread's connection should NOT have our custom cache_size
|
||||
assert other_cache[0] != 9999
|
||||
pool.close_connection()
|
||||
|
||||
def test_session_pragma_resets_on_new_connection(self, tmp_path):
|
||||
"""Session-level pragmas (cache_size) reset on a new connection."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
conn1 = pool.get_connection()
|
||||
conn1.execute("PRAGMA cache_size=9999")
|
||||
assert conn1.execute("PRAGMA cache_size").fetchone()[0] == 9999
|
||||
pool.close_connection()
|
||||
|
||||
conn2 = pool.get_connection()
|
||||
cache = conn2.execute("PRAGMA cache_size").fetchone()[0]
|
||||
# New connection gets default cache_size, not the previous value
|
||||
assert cache != 9999
|
||||
pool.close_connection()
|
||||
|
||||
def test_wal_mode_via_context_manager(self, tmp_path):
|
||||
"""WAL mode can be set within a context manager block."""
|
||||
pool = ConnectionPool(tmp_path / "test.db")
|
||||
with pool.connection() as conn:
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
mode = conn.execute("PRAGMA journal_mode").fetchone()[0]
|
||||
assert mode == "wal"
|
||||
|
||||
|
||||
class TestIntegration:
|
||||
"""Integration tests for real-world usage patterns."""
|
||||
|
||||
|
||||
@@ -1,332 +0,0 @@
|
||||
"""Tests for the content moderation pipeline."""
|
||||
|
||||
from unittest.mock import AsyncMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from infrastructure.guards.moderation import (
|
||||
ContentModerator,
|
||||
GameProfile,
|
||||
ModerationResult,
|
||||
ModerationVerdict,
|
||||
ViolationCategory,
|
||||
_parse_guard_category,
|
||||
get_moderator,
|
||||
)
|
||||
|
||||
# ── Unit tests for data types ────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestModerationResult:
|
||||
"""Test ModerationResult dataclass."""
|
||||
|
||||
def test_passed_property_true(self):
|
||||
result = ModerationResult(verdict=ModerationVerdict.PASS, blocked=False)
|
||||
assert result.passed is True
|
||||
|
||||
def test_passed_property_false(self):
|
||||
result = ModerationResult(verdict=ModerationVerdict.FAIL, blocked=True)
|
||||
assert result.passed is False
|
||||
|
||||
def test_default_values(self):
|
||||
result = ModerationResult(verdict=ModerationVerdict.PASS, blocked=False)
|
||||
assert result.category == ViolationCategory.NONE
|
||||
assert result.confidence == 0.0
|
||||
assert result.fallback == ""
|
||||
assert result.reason == ""
|
||||
|
||||
|
||||
class TestGameProfile:
|
||||
"""Test GameProfile dataclass."""
|
||||
|
||||
def test_default_values(self):
|
||||
profile = GameProfile(game_id="test", display_name="Test Game")
|
||||
assert profile.vocabulary_whitelist == []
|
||||
assert profile.threshold == 0.8
|
||||
assert profile.fallbacks == {}
|
||||
|
||||
def test_morrowind_profile(self):
|
||||
profile = GameProfile(
|
||||
game_id="morrowind",
|
||||
display_name="Morrowind",
|
||||
vocabulary_whitelist=["Skooma", "slave"],
|
||||
threshold=0.85,
|
||||
)
|
||||
assert "Skooma" in profile.vocabulary_whitelist
|
||||
assert profile.threshold == 0.85
|
||||
|
||||
|
||||
class TestParseGuardCategory:
|
||||
"""Test Llama Guard category parsing."""
|
||||
|
||||
def test_hate_speech(self):
|
||||
assert _parse_guard_category("S1: Hate speech") == ViolationCategory.HATE_SPEECH
|
||||
|
||||
def test_violence(self):
|
||||
assert _parse_guard_category("S2: Violence") == ViolationCategory.VIOLENCE_GLORIFICATION
|
||||
|
||||
def test_sexual_content(self):
|
||||
assert _parse_guard_category("S3: Sexual content") == ViolationCategory.SEXUAL_CONTENT
|
||||
|
||||
def test_self_harm(self):
|
||||
assert _parse_guard_category("S4: Self-harm") == ViolationCategory.SELF_HARM
|
||||
|
||||
def test_dangerous(self):
|
||||
assert _parse_guard_category("S5: Dangerous activity") == ViolationCategory.REAL_WORLD_HARM
|
||||
|
||||
def test_unknown_category(self):
|
||||
assert _parse_guard_category("S99: Unknown") == ViolationCategory.NONE
|
||||
|
||||
|
||||
# ── ContentModerator tests ───────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestContentModerator:
|
||||
"""Test the content moderation pipeline."""
|
||||
|
||||
def _make_moderator(self, **kwargs) -> ContentModerator:
|
||||
"""Create a moderator with test defaults."""
|
||||
profiles = {
|
||||
"morrowind": GameProfile(
|
||||
game_id="morrowind",
|
||||
display_name="Morrowind",
|
||||
vocabulary_whitelist=["Skooma", "Moon Sugar", "slave", "Morag Tong"],
|
||||
context_prompt="Narrate Morrowind gameplay.",
|
||||
threshold=0.85,
|
||||
fallbacks={
|
||||
"combat": "The battle continues.",
|
||||
"default": "The adventure continues.",
|
||||
},
|
||||
),
|
||||
"default": GameProfile(
|
||||
game_id="default",
|
||||
display_name="Generic",
|
||||
vocabulary_whitelist=[],
|
||||
context_prompt="Narrate gameplay.",
|
||||
threshold=0.8,
|
||||
fallbacks={"default": "Gameplay continues."},
|
||||
),
|
||||
}
|
||||
return ContentModerator(profiles=profiles, **kwargs)
|
||||
|
||||
def test_get_profile_known_game(self):
|
||||
mod = self._make_moderator()
|
||||
profile = mod.get_profile("morrowind")
|
||||
assert profile.game_id == "morrowind"
|
||||
|
||||
def test_get_profile_unknown_game_falls_back(self):
|
||||
mod = self._make_moderator()
|
||||
profile = mod.get_profile("unknown_game")
|
||||
assert profile.game_id == "default"
|
||||
|
||||
def test_get_context_prompt(self):
|
||||
mod = self._make_moderator()
|
||||
prompt = mod.get_context_prompt("morrowind")
|
||||
assert "Morrowind" in prompt
|
||||
|
||||
def test_register_profile(self):
|
||||
mod = self._make_moderator()
|
||||
new_profile = GameProfile(game_id="skyrim", display_name="Skyrim")
|
||||
mod.register_profile(new_profile)
|
||||
assert mod.get_profile("skyrim").game_id == "skyrim"
|
||||
|
||||
def test_whitelist_replaces_game_terms(self):
|
||||
mod = self._make_moderator()
|
||||
profile = mod.get_profile("morrowind")
|
||||
cleaned = mod._apply_whitelist(
|
||||
"The merchant sells Skooma and Moon Sugar in the slave market.",
|
||||
profile,
|
||||
)
|
||||
assert "Skooma" not in cleaned
|
||||
assert "Moon Sugar" not in cleaned
|
||||
assert "slave" not in cleaned
|
||||
assert "[GAME_TERM]" in cleaned
|
||||
|
||||
def test_whitelist_case_insensitive(self):
|
||||
mod = self._make_moderator()
|
||||
profile = mod.get_profile("morrowind")
|
||||
cleaned = mod._apply_whitelist("skooma and SKOOMA", profile)
|
||||
assert "skooma" not in cleaned
|
||||
assert "SKOOMA" not in cleaned
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_check_safe_content_passes(self):
|
||||
"""Safe content should pass moderation."""
|
||||
mod = self._make_moderator()
|
||||
with patch.object(mod, "_is_guard_available", new_callable=AsyncMock, return_value=False):
|
||||
result = await mod.check("The player walks through the town.", game="morrowind")
|
||||
assert result.passed
|
||||
assert not result.blocked
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_check_blocked_content_has_fallback(self):
|
||||
"""Blocked content should include scene-appropriate fallback."""
|
||||
mod = self._make_moderator()
|
||||
# Force a block via regex by using real-world harm language
|
||||
text = "In real life you should attack and hurt people"
|
||||
with patch.object(mod, "_is_guard_available", new_callable=AsyncMock, return_value=False):
|
||||
result = await mod.check(text, game="morrowind", scene_type="combat")
|
||||
assert result.blocked
|
||||
assert result.fallback == "The battle continues."
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_check_with_moderation_disabled(self):
|
||||
"""When moderation is disabled, everything passes."""
|
||||
mod = self._make_moderator()
|
||||
with patch("infrastructure.guards.moderation.settings") as mock_settings:
|
||||
mock_settings.moderation_enabled = False
|
||||
mock_settings.moderation_guard_model = "llama-guard3:1b"
|
||||
mock_settings.normalized_ollama_url = "http://127.0.0.1:11434"
|
||||
result = await mod.check("anything goes here")
|
||||
assert result.passed
|
||||
assert result.layer == "disabled"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_threshold_below_allows_content(self):
|
||||
"""Content flagged below threshold should pass through (Layer 3)."""
|
||||
mod = self._make_moderator()
|
||||
# Mock the guard to return a low-confidence flag
|
||||
low_conf_result = ModerationResult(
|
||||
verdict=ModerationVerdict.FAIL,
|
||||
blocked=True,
|
||||
confidence=0.5, # Below morrowind threshold of 0.85
|
||||
layer="llama_guard",
|
||||
category=ViolationCategory.VIOLENCE_GLORIFICATION,
|
||||
)
|
||||
with patch.object(mod, "_run_guard", new_callable=AsyncMock, return_value=low_conf_result):
|
||||
result = await mod.check("sword fight scene", game="morrowind")
|
||||
assert result.passed
|
||||
assert not result.blocked
|
||||
assert result.layer == "threshold"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_threshold_above_blocks_content(self):
|
||||
"""Content flagged above threshold should remain blocked."""
|
||||
mod = self._make_moderator()
|
||||
high_conf_result = ModerationResult(
|
||||
verdict=ModerationVerdict.FAIL,
|
||||
blocked=True,
|
||||
confidence=0.95, # Above morrowind threshold of 0.85
|
||||
layer="llama_guard",
|
||||
category=ViolationCategory.REAL_WORLD_HARM,
|
||||
)
|
||||
with patch.object(mod, "_run_guard", new_callable=AsyncMock, return_value=high_conf_result):
|
||||
result = await mod.check("harmful content", game="morrowind")
|
||||
assert result.blocked
|
||||
|
||||
def test_regex_catches_real_world_harm(self):
|
||||
"""Regex fallback should catch obvious real-world harm patterns."""
|
||||
mod = self._make_moderator()
|
||||
result = mod._check_with_regex("you should actually harm real people")
|
||||
assert result.blocked
|
||||
assert result.category == ViolationCategory.REAL_WORLD_HARM
|
||||
assert result.layer == "regex_fallback"
|
||||
|
||||
def test_regex_passes_game_violence(self):
|
||||
"""Regex should not flag in-game violence narration."""
|
||||
mod = self._make_moderator()
|
||||
result = mod._check_with_regex("The warrior slays the dragon with a mighty blow.")
|
||||
assert result.passed
|
||||
|
||||
def test_regex_passes_normal_narration(self):
|
||||
"""Normal narration should pass regex checks."""
|
||||
mod = self._make_moderator()
|
||||
result = mod._check_with_regex(
|
||||
"The Nerevarine enters the city of Balmora and speaks with Caius Cosades."
|
||||
)
|
||||
assert result.passed
|
||||
|
||||
def test_metrics_tracking(self):
|
||||
"""Metrics should track checks accurately."""
|
||||
mod = self._make_moderator()
|
||||
assert mod.get_metrics()["total_checks"] == 0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_metrics_increment_after_check(self):
|
||||
"""Metrics should increment after moderation checks."""
|
||||
mod = self._make_moderator()
|
||||
with patch.object(mod, "_is_guard_available", new_callable=AsyncMock, return_value=False):
|
||||
await mod.check("safe text", game="default")
|
||||
metrics = mod.get_metrics()
|
||||
assert metrics["total_checks"] == 1
|
||||
assert metrics["passed"] == 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_guard_fallback_on_error(self):
|
||||
"""Should fall back to regex when guard model errors."""
|
||||
mod = self._make_moderator()
|
||||
with (
|
||||
patch.object(mod, "_is_guard_available", new_callable=AsyncMock, return_value=True),
|
||||
patch.object(
|
||||
mod,
|
||||
"_check_with_guard",
|
||||
new_callable=AsyncMock,
|
||||
side_effect=RuntimeError("timeout"),
|
||||
),
|
||||
):
|
||||
result = await mod.check("safe text", game="default")
|
||||
# Should fall back to regex and pass
|
||||
assert result.passed
|
||||
assert result.layer == "regex_fallback"
|
||||
|
||||
|
||||
class TestGetModerator:
|
||||
"""Test the singleton accessor."""
|
||||
|
||||
def test_returns_same_instance(self):
|
||||
"""get_moderator should return the same instance."""
|
||||
# Reset the global to test fresh
|
||||
import infrastructure.guards.moderation as mod_module
|
||||
|
||||
mod_module._moderator = None
|
||||
m1 = get_moderator()
|
||||
m2 = get_moderator()
|
||||
assert m1 is m2
|
||||
# Clean up
|
||||
mod_module._moderator = None
|
||||
|
||||
|
||||
# ── Profile loader tests ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestProfileLoader:
|
||||
"""Test YAML profile loading."""
|
||||
|
||||
def test_load_missing_file_returns_empty(self, tmp_path):
|
||||
from infrastructure.guards.profiles import load_profiles
|
||||
|
||||
result = load_profiles(tmp_path / "nonexistent.yaml")
|
||||
assert result == {}
|
||||
|
||||
def test_load_valid_config(self, tmp_path):
|
||||
import yaml
|
||||
|
||||
from infrastructure.guards.profiles import load_profiles
|
||||
|
||||
config = {
|
||||
"profiles": {
|
||||
"testgame": {
|
||||
"display_name": "Test Game",
|
||||
"threshold": 0.9,
|
||||
"vocabulary_whitelist": ["sword", "potion"],
|
||||
"context_prompt": "Narrate test game.",
|
||||
"fallbacks": {"default": "Game continues."},
|
||||
}
|
||||
}
|
||||
}
|
||||
config_file = tmp_path / "moderation.yaml"
|
||||
config_file.write_text(yaml.dump(config))
|
||||
|
||||
profiles = load_profiles(config_file)
|
||||
assert "testgame" in profiles
|
||||
assert profiles["testgame"].threshold == 0.9
|
||||
assert "sword" in profiles["testgame"].vocabulary_whitelist
|
||||
|
||||
def test_load_malformed_yaml_returns_empty(self, tmp_path):
|
||||
from infrastructure.guards.profiles import load_profiles
|
||||
|
||||
config_file = tmp_path / "moderation.yaml"
|
||||
config_file.write_text("{{{{invalid yaml")
|
||||
|
||||
result = load_profiles(config_file)
|
||||
assert result == {}
|
||||
@@ -489,197 +489,6 @@ class TestProviderAvailabilityCheck:
|
||||
|
||||
assert router._check_provider_available(provider) is False
|
||||
|
||||
def test_check_vllm_mlx_without_requests(self):
|
||||
"""Test vllm-mlx returns True when requests not available (fallback)."""
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000/v1",
|
||||
)
|
||||
|
||||
import infrastructure.router.cascade as cascade_module
|
||||
|
||||
old_requests = cascade_module.requests
|
||||
cascade_module.requests = None
|
||||
try:
|
||||
assert router._check_provider_available(provider) is True
|
||||
finally:
|
||||
cascade_module.requests = old_requests
|
||||
|
||||
def test_check_vllm_mlx_server_healthy(self):
|
||||
"""Test vllm-mlx when health check succeeds."""
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000/v1",
|
||||
)
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.status_code = 200
|
||||
|
||||
with patch("infrastructure.router.cascade.requests") as mock_requests:
|
||||
mock_requests.get.return_value = mock_response
|
||||
result = router._check_provider_available(provider)
|
||||
|
||||
assert result is True
|
||||
mock_requests.get.assert_called_once_with("http://localhost:8000/health", timeout=5)
|
||||
|
||||
def test_check_vllm_mlx_server_down(self):
|
||||
"""Test vllm-mlx when server is not running."""
|
||||
from unittest.mock import patch
|
||||
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000/v1",
|
||||
)
|
||||
|
||||
with patch("infrastructure.router.cascade.requests") as mock_requests:
|
||||
mock_requests.get.side_effect = ConnectionRefusedError("Connection refused")
|
||||
result = router._check_provider_available(provider)
|
||||
|
||||
assert result is False
|
||||
|
||||
def test_check_vllm_mlx_default_url(self):
|
||||
"""Test vllm-mlx uses default localhost:8000 when no URL configured."""
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
)
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.status_code = 200
|
||||
|
||||
with patch("infrastructure.router.cascade.requests") as mock_requests:
|
||||
mock_requests.get.return_value = mock_response
|
||||
router._check_provider_available(provider)
|
||||
|
||||
mock_requests.get.assert_called_once_with("http://localhost:8000/health", timeout=5)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
class TestVllmMlxProvider:
|
||||
"""Test vllm-mlx provider integration."""
|
||||
|
||||
async def test_complete_with_vllm_mlx(self):
|
||||
"""Test successful completion via vllm-mlx."""
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000/v1",
|
||||
models=[{"name": "Qwen/Qwen2.5-14B-Instruct-MLX", "default": True}],
|
||||
)
|
||||
router.providers = [provider]
|
||||
|
||||
with patch.object(router, "_call_vllm_mlx") as mock_call:
|
||||
mock_call.return_value = {
|
||||
"content": "MLX response",
|
||||
"model": "Qwen/Qwen2.5-14B-Instruct-MLX",
|
||||
}
|
||||
|
||||
result = await router.complete(
|
||||
messages=[{"role": "user", "content": "Hi"}],
|
||||
)
|
||||
|
||||
assert result["content"] == "MLX response"
|
||||
assert result["provider"] == "vllm-mlx-local"
|
||||
assert result["model"] == "Qwen/Qwen2.5-14B-Instruct-MLX"
|
||||
|
||||
async def test_vllm_mlx_base_url_normalization(self):
|
||||
"""Test _call_vllm_mlx appends /v1 when missing."""
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000", # No /v1
|
||||
models=[{"name": "qwen-mlx", "default": True}],
|
||||
)
|
||||
|
||||
mock_choice = MagicMock()
|
||||
mock_choice.message.content = "hello"
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [mock_choice]
|
||||
mock_response.model = "qwen-mlx"
|
||||
|
||||
async def fake_create(**kwargs):
|
||||
return mock_response
|
||||
|
||||
with patch("openai.AsyncOpenAI") as mock_openai_cls:
|
||||
mock_client = MagicMock()
|
||||
mock_client.chat.completions.create = AsyncMock(side_effect=fake_create)
|
||||
mock_openai_cls.return_value = mock_client
|
||||
|
||||
await router._call_vllm_mlx(
|
||||
provider=provider,
|
||||
messages=[{"role": "user", "content": "hi"}],
|
||||
model="qwen-mlx",
|
||||
temperature=0.7,
|
||||
max_tokens=None,
|
||||
)
|
||||
|
||||
call_kwargs = mock_openai_cls.call_args
|
||||
base_url_used = call_kwargs.kwargs.get("base_url") or call_kwargs[1].get("base_url")
|
||||
assert base_url_used.endswith("/v1")
|
||||
|
||||
async def test_vllm_mlx_is_local_not_cloud(self):
|
||||
"""Confirm vllm_mlx is not subject to metabolic protocol cloud skip."""
|
||||
router = CascadeRouter(config_path=Path("/nonexistent"))
|
||||
|
||||
provider = Provider(
|
||||
name="vllm-mlx-local",
|
||||
type="vllm_mlx",
|
||||
enabled=True,
|
||||
priority=2,
|
||||
base_url="http://localhost:8000/v1",
|
||||
models=[{"name": "qwen-mlx", "default": True}],
|
||||
)
|
||||
router.providers = [provider]
|
||||
|
||||
# Quota monitor returns False (block cloud) — vllm_mlx should still be tried
|
||||
with patch("infrastructure.router.cascade._quota_monitor") as mock_qm:
|
||||
mock_qm.check.return_value = object()
|
||||
mock_qm.should_use_cloud.return_value = False
|
||||
|
||||
with patch.object(router, "_call_vllm_mlx") as mock_call:
|
||||
mock_call.return_value = {
|
||||
"content": "Local MLX response",
|
||||
"model": "qwen-mlx",
|
||||
}
|
||||
result = await router.complete(
|
||||
messages=[{"role": "user", "content": "hi"}],
|
||||
)
|
||||
|
||||
assert result["content"] == "Local MLX response"
|
||||
|
||||
|
||||
class TestCascadeRouterReload:
|
||||
"""Test hot-reload of providers.yaml."""
|
||||
|
||||
@@ -1,183 +0,0 @@
|
||||
"""Tests for the sovereignty metrics store and API routes.
|
||||
|
||||
Refs: #981
|
||||
"""
|
||||
|
||||
from unittest.mock import AsyncMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from infrastructure.sovereignty_metrics import (
|
||||
GRADUATION_TARGETS,
|
||||
SovereigntyMetric,
|
||||
SovereigntyMetricsStore,
|
||||
emit_sovereignty_metric,
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def store(tmp_path):
|
||||
"""Create a fresh sovereignty metrics store with a temp DB."""
|
||||
return SovereigntyMetricsStore(db_path=tmp_path / "test_sov.db")
|
||||
|
||||
|
||||
class TestSovereigntyMetricsStore:
|
||||
def test_record_and_get_latest(self, store):
|
||||
metric = SovereigntyMetric(metric_type="cache_hit_rate", value=0.42)
|
||||
store.record(metric)
|
||||
|
||||
results = store.get_latest("cache_hit_rate", limit=10)
|
||||
assert len(results) == 1
|
||||
assert results[0]["value"] == 0.42
|
||||
|
||||
def test_get_latest_returns_most_recent_first(self, store):
|
||||
for val in [0.1, 0.2, 0.3]:
|
||||
store.record(SovereigntyMetric(metric_type="cache_hit_rate", value=val))
|
||||
|
||||
results = store.get_latest("cache_hit_rate", limit=10)
|
||||
assert len(results) == 3
|
||||
assert results[0]["value"] == 0.3 # most recent first
|
||||
|
||||
def test_get_latest_respects_limit(self, store):
|
||||
for i in range(10):
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=float(i)))
|
||||
|
||||
results = store.get_latest("api_cost", limit=3)
|
||||
assert len(results) == 3
|
||||
|
||||
def test_get_latest_filters_by_type(self, store):
|
||||
store.record(SovereigntyMetric(metric_type="cache_hit_rate", value=0.5))
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=1.20))
|
||||
|
||||
results = store.get_latest("cache_hit_rate")
|
||||
assert len(results) == 1
|
||||
assert results[0]["value"] == 0.5
|
||||
|
||||
def test_get_summary_empty(self, store):
|
||||
summary = store.get_summary()
|
||||
assert "cache_hit_rate" in summary
|
||||
assert summary["cache_hit_rate"]["current"] is None
|
||||
assert summary["cache_hit_rate"]["phase"] == "pre-start"
|
||||
|
||||
def test_get_summary_with_data(self, store):
|
||||
store.record(SovereigntyMetric(metric_type="cache_hit_rate", value=0.85))
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=0.08))
|
||||
|
||||
summary = store.get_summary()
|
||||
assert summary["cache_hit_rate"]["current"] == 0.85
|
||||
assert summary["cache_hit_rate"]["phase"] == "month3"
|
||||
assert summary["api_cost"]["current"] == 0.08
|
||||
assert summary["api_cost"]["phase"] == "month3"
|
||||
|
||||
def test_get_summary_graduation(self, store):
|
||||
store.record(SovereigntyMetric(metric_type="cache_hit_rate", value=0.95))
|
||||
summary = store.get_summary()
|
||||
assert summary["cache_hit_rate"]["phase"] == "graduated"
|
||||
|
||||
def test_alert_on_high_api_cost(self, store):
|
||||
"""API cost above threshold triggers an alert."""
|
||||
with patch("infrastructure.sovereignty_metrics.settings") as mock_settings:
|
||||
mock_settings.sovereignty_api_cost_alert_threshold = 1.00
|
||||
mock_settings.db_busy_timeout_ms = 5000
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=2.50))
|
||||
|
||||
alerts = store.get_alerts(unacknowledged_only=True)
|
||||
assert len(alerts) == 1
|
||||
assert alerts[0]["alert_type"] == "api_cost_exceeded"
|
||||
assert alerts[0]["value"] == 2.50
|
||||
|
||||
def test_no_alert_below_threshold(self, store):
|
||||
"""API cost below threshold does not trigger an alert."""
|
||||
with patch("infrastructure.sovereignty_metrics.settings") as mock_settings:
|
||||
mock_settings.sovereignty_api_cost_alert_threshold = 1.00
|
||||
mock_settings.db_busy_timeout_ms = 5000
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=0.50))
|
||||
|
||||
alerts = store.get_alerts(unacknowledged_only=True)
|
||||
assert len(alerts) == 0
|
||||
|
||||
def test_acknowledge_alert(self, store):
|
||||
with patch("infrastructure.sovereignty_metrics.settings") as mock_settings:
|
||||
mock_settings.sovereignty_api_cost_alert_threshold = 0.50
|
||||
mock_settings.db_busy_timeout_ms = 5000
|
||||
store.record(SovereigntyMetric(metric_type="api_cost", value=1.00))
|
||||
|
||||
alerts = store.get_alerts(unacknowledged_only=True)
|
||||
assert len(alerts) == 1
|
||||
|
||||
store.acknowledge_alert(alerts[0]["id"])
|
||||
assert len(store.get_alerts(unacknowledged_only=True)) == 0
|
||||
assert len(store.get_alerts(unacknowledged_only=False)) == 1
|
||||
|
||||
def test_metadata_preserved(self, store):
|
||||
store.record(
|
||||
SovereigntyMetric(
|
||||
metric_type="cache_hit_rate",
|
||||
value=0.5,
|
||||
metadata={"source": "research_orchestrator"},
|
||||
)
|
||||
)
|
||||
results = store.get_latest("cache_hit_rate")
|
||||
assert results[0]["metadata"]["source"] == "research_orchestrator"
|
||||
|
||||
def test_summary_trend_data(self, store):
|
||||
for v in [0.1, 0.2, 0.3]:
|
||||
store.record(SovereigntyMetric(metric_type="cache_hit_rate", value=v))
|
||||
|
||||
summary = store.get_summary()
|
||||
trend = summary["cache_hit_rate"]["trend"]
|
||||
assert len(trend) == 3
|
||||
assert trend[0]["v"] == 0.1 # oldest first (reversed)
|
||||
assert trend[-1]["v"] == 0.3
|
||||
|
||||
def test_graduation_targets_complete(self):
|
||||
"""All expected metric types have graduation targets."""
|
||||
expected = {
|
||||
"cache_hit_rate",
|
||||
"api_cost",
|
||||
"time_to_report",
|
||||
"human_involvement",
|
||||
"local_artifacts",
|
||||
}
|
||||
assert set(GRADUATION_TARGETS.keys()) == expected
|
||||
|
||||
|
||||
class TestEmitSovereigntyMetric:
|
||||
@pytest.mark.asyncio
|
||||
async def test_emit_records_and_publishes(self, tmp_path):
|
||||
"""emit_sovereignty_metric records to store and publishes event."""
|
||||
with (
|
||||
patch("infrastructure.sovereignty_metrics._store", None),
|
||||
patch(
|
||||
"infrastructure.sovereignty_metrics.DB_PATH",
|
||||
tmp_path / "emit_test.db",
|
||||
),
|
||||
patch("infrastructure.events.bus.emit", new_callable=AsyncMock) as mock_emit,
|
||||
):
|
||||
await emit_sovereignty_metric("cache_hit_rate", 0.75, {"source": "test"})
|
||||
|
||||
mock_emit.assert_called_once()
|
||||
call_args = mock_emit.call_args
|
||||
assert call_args[0][0] == "sovereignty.metric.cache_hit_rate"
|
||||
|
||||
|
||||
class TestSovereigntyMetricsRoutes:
|
||||
def test_metrics_api_returns_200(self, client):
|
||||
response = client.get("/sovereignty/metrics")
|
||||
assert response.status_code == 200
|
||||
data = response.json()
|
||||
assert "metrics" in data
|
||||
assert "alerts" in data
|
||||
assert "targets" in data
|
||||
|
||||
def test_metrics_panel_returns_html(self, client):
|
||||
response = client.get("/sovereignty/metrics/panel")
|
||||
assert response.status_code == 200
|
||||
assert "text/html" in response.headers["content-type"]
|
||||
|
||||
def test_alerts_api_returns_200(self, client):
|
||||
response = client.get("/sovereignty/alerts")
|
||||
assert response.status_code == 200
|
||||
data = response.json()
|
||||
assert "alerts" in data
|
||||
assert "unacknowledged" in data
|
||||
@@ -1,394 +0,0 @@
|
||||
"""Tests for the agent performance regression benchmark suite.
|
||||
|
||||
Covers: scenario loading, metrics collection, runner execution,
|
||||
goal predicates, and result persistence.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from infrastructure.world.benchmark.metrics import (
|
||||
BenchmarkMetrics,
|
||||
ScenarioResult,
|
||||
compare_runs,
|
||||
load_history,
|
||||
)
|
||||
from infrastructure.world.benchmark.runner import BenchmarkRunner
|
||||
from infrastructure.world.benchmark.scenarios import (
|
||||
BUILTIN_SCENARIOS,
|
||||
BenchmarkScenario,
|
||||
load_scenarios,
|
||||
)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Scenario definitions
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestBenchmarkScenario:
|
||||
def test_builtin_scenarios_exist(self):
|
||||
assert len(BUILTIN_SCENARIOS) >= 5
|
||||
|
||||
def test_scenario_fields(self):
|
||||
s = BUILTIN_SCENARIOS[0]
|
||||
assert s.name
|
||||
assert s.description
|
||||
assert s.start_location
|
||||
assert s.max_cycles > 0
|
||||
|
||||
def test_load_all_scenarios(self):
|
||||
scenarios = load_scenarios()
|
||||
assert len(scenarios) == len(BUILTIN_SCENARIOS)
|
||||
|
||||
def test_load_scenarios_by_tag(self):
|
||||
nav = load_scenarios(tags=["navigation"])
|
||||
assert len(nav) >= 2
|
||||
for s in nav:
|
||||
assert "navigation" in s.tags
|
||||
|
||||
def test_load_scenarios_no_match(self):
|
||||
result = load_scenarios(tags=["nonexistent_tag"])
|
||||
assert result == []
|
||||
|
||||
def test_scenario_is_frozen(self):
|
||||
s = BUILTIN_SCENARIOS[0]
|
||||
with pytest.raises(AttributeError):
|
||||
s.name = "modified"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Goal predicates
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestGoalPredicates:
|
||||
def test_reached_location_predicate(self):
|
||||
s = BUILTIN_SCENARIOS[0] # Walk to Balmora
|
||||
assert s.goal_predicate is not None
|
||||
assert s.goal_predicate([], "Balmora") is True
|
||||
assert s.goal_predicate([], "Seyda Neen") is False
|
||||
|
||||
def test_reached_location_case_insensitive(self):
|
||||
s = BUILTIN_SCENARIOS[0]
|
||||
assert s.goal_predicate([], "balmora") is True
|
||||
assert s.goal_predicate([], "BALMORA") is True
|
||||
|
||||
def test_interacted_with_predicate(self):
|
||||
s = BUILTIN_SCENARIOS[1] # Fargoth quest
|
||||
assert s.goal_predicate is not None
|
||||
actions = [{"action": "speak", "target": "Fargoth"}]
|
||||
assert s.goal_predicate(actions, "Seyda Neen") is True
|
||||
|
||||
def test_interacted_with_no_match(self):
|
||||
s = BUILTIN_SCENARIOS[1]
|
||||
actions = [{"action": "speak", "target": "Guard"}]
|
||||
assert s.goal_predicate(actions, "Seyda Neen") is False
|
||||
|
||||
def test_interacted_with_interact_action(self):
|
||||
s = BUILTIN_SCENARIOS[1]
|
||||
actions = [{"action": "interact", "target": "Fargoth"}]
|
||||
assert s.goal_predicate(actions, "Seyda Neen") is True
|
||||
|
||||
def test_no_predicate_scenario(self):
|
||||
combat = [s for s in BUILTIN_SCENARIOS if "combat" in s.tags][0]
|
||||
assert combat.goal_predicate is None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Metrics
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestScenarioResult:
|
||||
def test_default_values(self):
|
||||
r = ScenarioResult(scenario_name="test")
|
||||
assert r.success is False
|
||||
assert r.cycles_used == 0
|
||||
assert r.llm_calls == 0
|
||||
assert r.metabolic_cost == 0.0
|
||||
assert r.error is None
|
||||
|
||||
|
||||
class TestBenchmarkMetrics:
|
||||
def test_empty_metrics(self):
|
||||
m = BenchmarkMetrics()
|
||||
assert m.pass_count == 0
|
||||
assert m.fail_count == 0
|
||||
assert m.success_rate == 0.0
|
||||
assert m.total_llm_calls == 0
|
||||
assert m.total_metabolic_cost == 0.0
|
||||
|
||||
def test_success_rate(self):
|
||||
m = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="a", success=True),
|
||||
ScenarioResult(scenario_name="b", success=False),
|
||||
ScenarioResult(scenario_name="c", success=True),
|
||||
]
|
||||
)
|
||||
assert m.pass_count == 2
|
||||
assert m.fail_count == 1
|
||||
assert abs(m.success_rate - 2 / 3) < 0.01
|
||||
|
||||
def test_totals(self):
|
||||
m = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="a", llm_calls=10, metabolic_cost=30.0),
|
||||
ScenarioResult(scenario_name="b", llm_calls=5, metabolic_cost=15.0),
|
||||
]
|
||||
)
|
||||
assert m.total_llm_calls == 15
|
||||
assert m.total_metabolic_cost == 45.0
|
||||
|
||||
def test_save_and_load(self, tmp_path):
|
||||
path = tmp_path / "bench.jsonl"
|
||||
m = BenchmarkMetrics(
|
||||
timestamp="2026-01-01T00:00:00",
|
||||
commit_sha="abc123",
|
||||
total_time_ms=1000,
|
||||
results=[
|
||||
ScenarioResult(
|
||||
scenario_name="a",
|
||||
success=True,
|
||||
cycles_used=5,
|
||||
max_cycles=10,
|
||||
),
|
||||
],
|
||||
)
|
||||
m.save(path)
|
||||
|
||||
history = load_history(path)
|
||||
assert len(history) == 1
|
||||
assert history[0]["commit_sha"] == "abc123"
|
||||
assert history[0]["scenarios"][0]["scenario_name"] == "a"
|
||||
|
||||
def test_save_appends(self, tmp_path):
|
||||
path = tmp_path / "bench.jsonl"
|
||||
for i in range(3):
|
||||
m = BenchmarkMetrics(
|
||||
timestamp=f"2026-01-0{i + 1}T00:00:00",
|
||||
results=[ScenarioResult(scenario_name=f"s{i}")],
|
||||
)
|
||||
m.save(path)
|
||||
|
||||
history = load_history(path)
|
||||
assert len(history) == 3
|
||||
# Most recent first
|
||||
assert history[0]["timestamp"] == "2026-01-03T00:00:00"
|
||||
|
||||
def test_summary_output(self):
|
||||
m = BenchmarkMetrics(
|
||||
timestamp="2026-01-01T00:00:00",
|
||||
commit_sha="abc123",
|
||||
total_time_ms=500,
|
||||
results=[
|
||||
ScenarioResult(
|
||||
scenario_name="Walk Test",
|
||||
success=True,
|
||||
cycles_used=5,
|
||||
max_cycles=10,
|
||||
wall_time_ms=200,
|
||||
llm_calls=15,
|
||||
),
|
||||
],
|
||||
)
|
||||
summary = m.summary()
|
||||
assert "Walk Test" in summary
|
||||
assert "PASS" in summary
|
||||
assert "abc123" in summary
|
||||
|
||||
def test_load_history_missing_file(self, tmp_path):
|
||||
assert load_history(tmp_path / "nope.jsonl") == []
|
||||
|
||||
def test_load_history_corrupt_lines(self, tmp_path):
|
||||
path = tmp_path / "bench.jsonl"
|
||||
path.write_text('{"valid": true}\nnot json\n{"also": "valid"}\n')
|
||||
history = load_history(path)
|
||||
assert len(history) == 2
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Comparison
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCompareRuns:
|
||||
def test_regression_detected(self):
|
||||
baseline = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=True, cycles_used=10),
|
||||
]
|
||||
)
|
||||
current = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=False, cycles_used=10),
|
||||
]
|
||||
)
|
||||
report = compare_runs(current, baseline)
|
||||
assert "REGRESSION" in report
|
||||
|
||||
def test_improvement_detected(self):
|
||||
baseline = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=False, cycles_used=10),
|
||||
]
|
||||
)
|
||||
current = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=True, cycles_used=10),
|
||||
]
|
||||
)
|
||||
report = compare_runs(current, baseline)
|
||||
assert "IMPROVEMENT" in report
|
||||
|
||||
def test_slower_detected(self):
|
||||
baseline = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=True, cycles_used=10),
|
||||
]
|
||||
)
|
||||
current = BenchmarkMetrics(
|
||||
results=[
|
||||
ScenarioResult(scenario_name="walk", success=True, cycles_used=20),
|
||||
]
|
||||
)
|
||||
report = compare_runs(current, baseline)
|
||||
assert "SLOWER" in report
|
||||
|
||||
def test_new_scenario_noted(self):
|
||||
baseline = BenchmarkMetrics(results=[])
|
||||
current = BenchmarkMetrics(results=[ScenarioResult(scenario_name="new_one", success=True)])
|
||||
report = compare_runs(current, baseline)
|
||||
assert "NEW" in report
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Runner
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestBenchmarkRunner:
|
||||
@pytest.mark.asyncio
|
||||
async def test_run_single_scenario(self):
|
||||
"""Runner executes a scenario and returns a result."""
|
||||
scenario = BenchmarkScenario(
|
||||
name="Test Walk",
|
||||
description="Simple test",
|
||||
start_location="A",
|
||||
goal_location="A",
|
||||
max_cycles=3,
|
||||
tags=["test"],
|
||||
)
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run([scenario])
|
||||
assert len(metrics.results) == 1
|
||||
r = metrics.results[0]
|
||||
assert r.scenario_name == "Test Walk"
|
||||
assert r.cycles_used == 3 # no predicate, runs all cycles
|
||||
assert r.success is True # no predicate = success if survived
|
||||
assert r.wall_time_ms >= 0
|
||||
assert r.llm_calls == 9 # 3 cycles * 3 calls
|
||||
assert r.metabolic_cost > 0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_run_with_goal_predicate(self):
|
||||
"""Runner stops early when goal predicate is satisfied."""
|
||||
|
||||
def always_true(actions, location):
|
||||
return True
|
||||
|
||||
scenario = BenchmarkScenario(
|
||||
name="Instant Win",
|
||||
description="Predicate satisfied immediately",
|
||||
start_location="A",
|
||||
max_cycles=100,
|
||||
goal_predicate=always_true,
|
||||
tags=["test"],
|
||||
)
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run([scenario])
|
||||
r = metrics.results[0]
|
||||
assert r.success is True
|
||||
assert r.cycles_used == 1 # Stopped at first cycle
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_run_with_failing_predicate(self):
|
||||
"""Scenario fails when predicate never satisfied."""
|
||||
|
||||
def never_true(actions, location):
|
||||
return False
|
||||
|
||||
scenario = BenchmarkScenario(
|
||||
name="Impossible",
|
||||
description="Predicate never satisfied",
|
||||
start_location="A",
|
||||
max_cycles=5,
|
||||
goal_predicate=never_true,
|
||||
tags=["test"],
|
||||
)
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run([scenario])
|
||||
r = metrics.results[0]
|
||||
assert r.success is False
|
||||
assert r.cycles_used == 5
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_run_multiple_scenarios(self):
|
||||
"""Runner handles multiple scenarios in sequence."""
|
||||
scenarios = [
|
||||
BenchmarkScenario(
|
||||
name=f"Scenario {i}",
|
||||
description=f"Test {i}",
|
||||
start_location="A",
|
||||
max_cycles=2,
|
||||
tags=["test"],
|
||||
)
|
||||
for i in range(3)
|
||||
]
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run(scenarios)
|
||||
assert len(metrics.results) == 3
|
||||
assert metrics.total_time_ms >= 0
|
||||
assert metrics.timestamp
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_metrics_commit_sha(self):
|
||||
"""Runner captures git SHA in metrics."""
|
||||
scenario = BenchmarkScenario(
|
||||
name="SHA Test",
|
||||
description="Check SHA capture",
|
||||
start_location="A",
|
||||
max_cycles=1,
|
||||
tags=["test"],
|
||||
)
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run([scenario])
|
||||
# SHA may or may not be available in test env; just ensure no crash
|
||||
assert isinstance(metrics.commit_sha, str)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_builtin_scenarios_run(self):
|
||||
"""All built-in scenarios run without crashing."""
|
||||
# Use just 2 cycles each to keep tests fast
|
||||
scenarios = [
|
||||
BenchmarkScenario(
|
||||
name=s.name,
|
||||
description=s.description,
|
||||
start_location=s.start_location,
|
||||
goal_location=s.goal_location,
|
||||
entities=list(s.entities),
|
||||
events=list(s.events),
|
||||
max_cycles=2, # Override for speed
|
||||
goal_predicate=None, # Skip predicate for smoke test
|
||||
tags=list(s.tags),
|
||||
)
|
||||
for s in BUILTIN_SCENARIOS
|
||||
]
|
||||
runner = BenchmarkRunner()
|
||||
metrics = await runner.run(scenarios)
|
||||
assert len(metrics.results) == len(BUILTIN_SCENARIOS)
|
||||
# All should succeed (no predicate + survived = pass)
|
||||
for r in metrics.results:
|
||||
assert r.success is True
|
||||
assert r.error is None
|
||||
@@ -1,306 +0,0 @@
|
||||
"""Unit tests for scripts/export_trajectories.py."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import sqlite3
|
||||
from datetime import datetime, timedelta
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
import scripts.export_trajectories as et
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────────────────────
|
||||
|
||||
def _ts(base: datetime, offset_minutes: int = 0) -> str:
|
||||
return (base + timedelta(minutes=offset_minutes)).isoformat()
|
||||
|
||||
|
||||
BASE = datetime(2026, 3, 1, 10, 0, 0)
|
||||
|
||||
|
||||
def _make_session_entries(base: datetime = BASE) -> list[dict]:
|
||||
"""Minimal session log entries: user → tool_call → timmy reply."""
|
||||
return [
|
||||
{"type": "message", "role": "user", "content": "list my files", "timestamp": _ts(base, 0)},
|
||||
{"type": "tool_call", "tool": "shell", "args": {"cmd": "ls"}, "result": "a.py\nb.py", "timestamp": _ts(base, 1)},
|
||||
{"type": "message", "role": "timmy", "content": "You have two files.", "timestamp": _ts(base, 2)},
|
||||
]
|
||||
|
||||
|
||||
# ── _group_into_conversations ─────────────────────────────────────────────────
|
||||
|
||||
class TestGroupIntoConversations:
|
||||
def test_empty(self):
|
||||
assert et._group_into_conversations([]) == []
|
||||
|
||||
def test_single_group_no_gap(self):
|
||||
entries = _make_session_entries()
|
||||
groups = et._group_into_conversations(entries, gap_minutes=30)
|
||||
assert len(groups) == 1
|
||||
assert groups[0] == entries
|
||||
|
||||
def test_split_on_large_gap(self):
|
||||
entries_a = _make_session_entries(BASE)
|
||||
# Second set starts 60 minutes later
|
||||
entries_b = _make_session_entries(BASE + timedelta(hours=1))
|
||||
groups = et._group_into_conversations(entries_a + entries_b, gap_minutes=30)
|
||||
assert len(groups) == 2
|
||||
assert len(groups[0]) == 3
|
||||
assert len(groups[1]) == 3
|
||||
|
||||
def test_no_split_within_gap(self):
|
||||
entries = _make_session_entries()
|
||||
groups = et._group_into_conversations(entries, gap_minutes=60)
|
||||
assert len(groups) == 1
|
||||
|
||||
def test_entries_without_timestamp(self):
|
||||
entries = [
|
||||
{"type": "message", "role": "user", "content": "hello"},
|
||||
{"type": "message", "role": "timmy", "content": "hi"},
|
||||
]
|
||||
groups = et._group_into_conversations(entries, gap_minutes=30)
|
||||
assert len(groups) == 1
|
||||
|
||||
|
||||
# ── _conversation_to_sharegpt ─────────────────────────────────────────────────
|
||||
|
||||
class TestConversationToSharegpt:
|
||||
def test_basic_exchange(self):
|
||||
entries = _make_session_entries()
|
||||
result = et._conversation_to_sharegpt(entries)
|
||||
assert result is not None
|
||||
turns = result["conversations"]
|
||||
|
||||
human_turns = [t for t in turns if t["from"] == "human"]
|
||||
gpt_turns = [t for t in turns if t["from"] == "gpt"]
|
||||
tool_turns = [t for t in turns if t["from"] == "tool"]
|
||||
|
||||
assert len(human_turns) == 1
|
||||
assert len(gpt_turns) == 1
|
||||
assert len(tool_turns) == 1
|
||||
|
||||
def test_tool_calls_attached_to_gpt_turn(self):
|
||||
entries = [
|
||||
{"type": "message", "role": "user", "content": "run ls", "timestamp": _ts(BASE, 0)},
|
||||
{"type": "tool_call", "tool": "shell", "args": {}, "result": "ok", "timestamp": _ts(BASE, 1)},
|
||||
{"type": "message", "role": "timmy", "content": "done", "timestamp": _ts(BASE, 2)},
|
||||
]
|
||||
result = et._conversation_to_sharegpt(entries)
|
||||
assert result is not None
|
||||
gpt_turns = [t for t in result["conversations"] if t["from"] == "gpt"]
|
||||
assert len(gpt_turns) == 1
|
||||
assert "tool_calls" in gpt_turns[0]
|
||||
assert gpt_turns[0]["tool_calls"][0]["name"] == "shell"
|
||||
|
||||
def test_too_short_returns_none(self):
|
||||
# Only one meaningful turn → not useful for training
|
||||
entries = [{"type": "message", "role": "user", "content": "hi", "timestamp": _ts(BASE)}]
|
||||
assert et._conversation_to_sharegpt(entries) is None
|
||||
|
||||
def test_empty_content_skipped(self):
|
||||
entries = [
|
||||
{"type": "message", "role": "user", "content": "", "timestamp": _ts(BASE, 0)},
|
||||
{"type": "message", "role": "timmy", "content": "pong", "timestamp": _ts(BASE, 1)},
|
||||
]
|
||||
# Only one non-empty turn → should return None
|
||||
assert et._conversation_to_sharegpt(entries) is None
|
||||
|
||||
def test_role_mapping(self):
|
||||
entries = [
|
||||
{"type": "message", "role": "user", "content": "q", "timestamp": _ts(BASE, 0)},
|
||||
{"type": "message", "role": "assistant", "content": "a", "timestamp": _ts(BASE, 1)},
|
||||
]
|
||||
result = et._conversation_to_sharegpt(entries)
|
||||
assert result is not None
|
||||
roles = [t["from"] for t in result["conversations"]]
|
||||
assert "human" in roles
|
||||
assert "gpt" in roles
|
||||
|
||||
def test_decision_entries_ignored(self):
|
||||
"""Non-message, non-tool entries (decisions, errors) should be skipped."""
|
||||
entries = _make_session_entries() + [
|
||||
{"type": "decision", "decision": "do something", "timestamp": _ts(BASE, 10)},
|
||||
]
|
||||
result = et._conversation_to_sharegpt(entries)
|
||||
assert result is not None
|
||||
assert all(t["from"] != "decision" for t in result["conversations"])
|
||||
|
||||
|
||||
# ── load_from_session_logs ────────────────────────────────────────────────────
|
||||
|
||||
class TestLoadFromSessionLogs:
|
||||
def test_empty_directory(self, tmp_path):
|
||||
assert et.load_from_session_logs(tmp_path) == []
|
||||
|
||||
def test_missing_directory(self, tmp_path):
|
||||
assert et.load_from_session_logs(tmp_path / "nonexistent") == []
|
||||
|
||||
def test_reads_single_log(self, tmp_path):
|
||||
entries = _make_session_entries()
|
||||
log = tmp_path / "session_2026-03-01.jsonl"
|
||||
log.write_text("\n".join(json.dumps(e) for e in entries) + "\n")
|
||||
|
||||
result = et.load_from_session_logs(tmp_path)
|
||||
assert len(result) == 1
|
||||
assert result[0]["conversations"][0]["from"] == "human"
|
||||
|
||||
def test_reads_multiple_logs(self, tmp_path):
|
||||
for day in range(3):
|
||||
entries = _make_session_entries(BASE + timedelta(days=day, hours=2 * day))
|
||||
log = tmp_path / f"session_2026-03-0{day + 1}.jsonl"
|
||||
log.write_text("\n".join(json.dumps(e) for e in entries) + "\n")
|
||||
|
||||
result = et.load_from_session_logs(tmp_path)
|
||||
# 3 log files, each a separate conversation (days apart)
|
||||
assert len(result) == 3
|
||||
|
||||
def test_skips_malformed_lines(self, tmp_path):
|
||||
log = tmp_path / "session_2026-03-01.jsonl"
|
||||
entries = _make_session_entries()
|
||||
lines = [json.dumps(e) for e in entries]
|
||||
lines.insert(1, "not valid json{{{")
|
||||
log.write_text("\n".join(lines) + "\n")
|
||||
|
||||
# Should still parse valid entries
|
||||
result = et.load_from_session_logs(tmp_path)
|
||||
assert len(result) == 1
|
||||
|
||||
|
||||
# ── load_from_sqlite ──────────────────────────────────────────────────────────
|
||||
|
||||
class TestLoadFromSqlite:
|
||||
def _make_db(self, tmp_path: Path, rows: list[tuple]) -> Path:
|
||||
db = tmp_path / "chat.db"
|
||||
conn = sqlite3.connect(str(db))
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS chat_messages (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
role TEXT, content TEXT, timestamp TEXT, source TEXT
|
||||
)
|
||||
""")
|
||||
conn.executemany(
|
||||
"INSERT INTO chat_messages (role, content, timestamp, source) VALUES (?,?,?,?)",
|
||||
rows,
|
||||
)
|
||||
conn.commit()
|
||||
conn.close()
|
||||
return db
|
||||
|
||||
def test_missing_db(self, tmp_path):
|
||||
assert et.load_from_sqlite(tmp_path / "missing.db") == []
|
||||
|
||||
def test_reads_conversation(self, tmp_path):
|
||||
rows = [
|
||||
("user", "hello", _ts(BASE, 0), "browser"),
|
||||
("agent", "hi there", _ts(BASE, 5), "browser"),
|
||||
]
|
||||
db = self._make_db(tmp_path, rows)
|
||||
result = et.load_from_sqlite(db)
|
||||
assert len(result) == 1
|
||||
turns = result[0]["conversations"]
|
||||
assert turns[0]["from"] == "human"
|
||||
assert turns[1]["from"] == "gpt"
|
||||
|
||||
def test_splits_on_gap(self, tmp_path):
|
||||
rows = [
|
||||
("user", "a", _ts(BASE, 0), "browser"),
|
||||
("agent", "b", _ts(BASE, 5), "browser"),
|
||||
("user", "c", _ts(BASE, 120), "browser"), # 2h gap
|
||||
("agent", "d", _ts(BASE, 125), "browser"),
|
||||
]
|
||||
db = self._make_db(tmp_path, rows)
|
||||
result = et.load_from_sqlite(db)
|
||||
assert len(result) == 2
|
||||
|
||||
|
||||
# ── validate_output ───────────────────────────────────────────────────────────
|
||||
|
||||
class TestValidateOutput:
|
||||
def test_missing_file(self, tmp_path):
|
||||
stats = et.validate_output(tmp_path / "missing.jsonl")
|
||||
assert "error" in stats
|
||||
|
||||
def test_counts_conversations(self, tmp_path):
|
||||
out = tmp_path / "out.jsonl"
|
||||
convs = [
|
||||
{"conversations": [{"from": "human", "value": "hi"}, {"from": "gpt", "value": "ho"}]},
|
||||
{"conversations": [{"from": "human", "value": "a"}, {"from": "gpt", "value": "b"}]},
|
||||
]
|
||||
out.write_text("\n".join(json.dumps(c) for c in convs) + "\n")
|
||||
stats = et.validate_output(out)
|
||||
assert stats["total_conversations"] == 2
|
||||
assert stats["with_tool_calls"] == 0
|
||||
|
||||
def test_counts_tool_calls(self, tmp_path):
|
||||
out = tmp_path / "out.jsonl"
|
||||
conv = {"conversations": [
|
||||
{"from": "human", "value": "run"},
|
||||
{"from": "gpt", "value": "ok", "tool_calls": [{"name": "shell", "arguments": {}}]},
|
||||
{"from": "tool", "value": "done", "tool": "shell"},
|
||||
]}
|
||||
out.write_text(json.dumps(conv) + "\n")
|
||||
stats = et.validate_output(out)
|
||||
assert stats["with_tool_calls"] == 1
|
||||
|
||||
|
||||
# ── CLI (main) ────────────────────────────────────────────────────────────────
|
||||
|
||||
class TestMain:
|
||||
def test_no_data_exits_0(self, tmp_path):
|
||||
out = tmp_path / "out.jsonl"
|
||||
code = et.main([
|
||||
"--logs-dir", str(tmp_path / "logs"),
|
||||
"--db", str(tmp_path / "missing.db"),
|
||||
"--output", str(out),
|
||||
])
|
||||
assert code == 0
|
||||
assert out.exists()
|
||||
|
||||
def test_exports_from_logs(self, tmp_path):
|
||||
logs = tmp_path / "logs"
|
||||
logs.mkdir()
|
||||
entries = _make_session_entries()
|
||||
(logs / "session_2026-03-01.jsonl").write_text(
|
||||
"\n".join(json.dumps(e) for e in entries) + "\n"
|
||||
)
|
||||
out = tmp_path / "out.jsonl"
|
||||
code = et.main([
|
||||
"--logs-dir", str(logs),
|
||||
"--db", str(tmp_path / "missing.db"),
|
||||
"--output", str(out),
|
||||
])
|
||||
assert code == 0
|
||||
lines = [l for l in out.read_text().splitlines() if l.strip()]
|
||||
assert len(lines) == 1
|
||||
|
||||
def test_validate_only(self, tmp_path, capsys):
|
||||
out = tmp_path / "out.jsonl"
|
||||
conv = {"conversations": [
|
||||
{"from": "human", "value": "x"},
|
||||
{"from": "gpt", "value": "y"},
|
||||
]}
|
||||
out.write_text(json.dumps(conv) + "\n")
|
||||
code = et.main(["--validate-only", "--output", str(out)])
|
||||
assert code == 0
|
||||
captured = capsys.readouterr()
|
||||
stats = json.loads(captured.out)
|
||||
assert stats["total_conversations"] == 1
|
||||
|
||||
def test_min_examples_fails(self, tmp_path):
|
||||
logs = tmp_path / "logs"
|
||||
logs.mkdir()
|
||||
entries = _make_session_entries()
|
||||
(logs / "session_2026-03-01.jsonl").write_text(
|
||||
"\n".join(json.dumps(e) for e in entries) + "\n"
|
||||
)
|
||||
out = tmp_path / "out.jsonl"
|
||||
code = et.main([
|
||||
"--logs-dir", str(logs),
|
||||
"--db", str(tmp_path / "missing.db"),
|
||||
"--output", str(out),
|
||||
"--min-examples", "100",
|
||||
])
|
||||
assert code == 1
|
||||
@@ -1,607 +0,0 @@
|
||||
"""Tests for the MCP bridge module (Qwen3 via Ollama)."""
|
||||
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
from timmy.mcp_bridge import (
|
||||
BridgeResult,
|
||||
MCPBridge,
|
||||
MCPToolDef,
|
||||
_build_gitea_tools,
|
||||
_build_shell_tool,
|
||||
_mcp_schema_to_ollama_tool,
|
||||
)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _mcp_schema_to_ollama_tool
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_schema_to_ollama_tool_basic():
|
||||
"""Converts an MCPToolDef to Ollama tool format."""
|
||||
tool = MCPToolDef(
|
||||
name="test_tool",
|
||||
description="A test tool",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {"arg1": {"type": "string"}},
|
||||
"required": ["arg1"],
|
||||
},
|
||||
handler=AsyncMock(),
|
||||
)
|
||||
result = _mcp_schema_to_ollama_tool(tool)
|
||||
assert result["type"] == "function"
|
||||
assert result["function"]["name"] == "test_tool"
|
||||
assert result["function"]["description"] == "A test tool"
|
||||
assert result["function"]["parameters"]["type"] == "object"
|
||||
assert "arg1" in result["function"]["parameters"]["properties"]
|
||||
|
||||
|
||||
def test_schema_to_ollama_tool_wraps_bare_params():
|
||||
"""Wraps bare parameter dicts in an object type."""
|
||||
tool = MCPToolDef(
|
||||
name="bare",
|
||||
description="Bare params",
|
||||
parameters={"x": {"type": "integer"}},
|
||||
handler=AsyncMock(),
|
||||
)
|
||||
result = _mcp_schema_to_ollama_tool(tool)
|
||||
params = result["function"]["parameters"]
|
||||
assert params["type"] == "object"
|
||||
assert "x" in params["properties"]
|
||||
assert "x" in params["required"]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _build_shell_tool
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_build_shell_tool_returns_def():
|
||||
"""Shell tool builder returns an MCPToolDef."""
|
||||
tool = _build_shell_tool()
|
||||
assert tool is not None
|
||||
assert tool.name == "shell_exec"
|
||||
assert "command" in tool.parameters["properties"]
|
||||
|
||||
|
||||
def test_build_shell_tool_graceful_on_import_error():
|
||||
"""Shell tool returns None when infrastructure is unavailable."""
|
||||
with patch.dict("sys.modules", {"infrastructure.hands.shell": None}):
|
||||
# Force re-import failure — but _build_shell_tool catches it
|
||||
with patch(
|
||||
"timmy.mcp_bridge._build_shell_tool",
|
||||
wraps=_build_shell_tool,
|
||||
):
|
||||
# The real function should handle import errors
|
||||
tool = _build_shell_tool()
|
||||
# May return tool if import cache succeeds, or None if not
|
||||
# Just verify it doesn't raise
|
||||
assert tool is None or isinstance(tool, MCPToolDef)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _build_gitea_tools
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_gitea_tools_empty_when_disabled():
|
||||
"""Gitea tools returns empty list when disabled."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
result = _build_gitea_tools()
|
||||
assert result == []
|
||||
|
||||
|
||||
def test_gitea_tools_empty_when_no_token():
|
||||
"""Gitea tools returns empty list when no token."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = ""
|
||||
result = _build_gitea_tools()
|
||||
assert result == []
|
||||
|
||||
|
||||
def test_gitea_tools_returns_three_tools():
|
||||
"""Gitea tools returns list_issues, create_issue, read_issue."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
result = _build_gitea_tools()
|
||||
assert len(result) == 3
|
||||
names = {t.name for t in result}
|
||||
assert names == {"list_issues", "create_issue", "read_issue"}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MCPBridge.__init__
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_bridge_init_default():
|
||||
"""MCPBridge initialises with default settings."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
assert bridge.model == "qwen3:14b"
|
||||
assert bridge.tool_names == []
|
||||
|
||||
|
||||
def test_bridge_init_with_extra_tools():
|
||||
"""MCPBridge accepts extra tool definitions."""
|
||||
custom = MCPToolDef(
|
||||
name="custom_tool",
|
||||
description="Custom",
|
||||
parameters={"type": "object", "properties": {}, "required": []},
|
||||
handler=AsyncMock(),
|
||||
)
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
bridge = MCPBridge(
|
||||
include_gitea=False,
|
||||
include_shell=False,
|
||||
extra_tools=[custom],
|
||||
)
|
||||
assert "custom_tool" in bridge.tool_names
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MCPBridge.run — tool-call loop
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_simple_response():
|
||||
"""Bridge returns model content when no tool calls are made."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 4096
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.json.return_value = {"message": {"role": "assistant", "content": "Hello!"}}
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(return_value=mock_resp)
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("Hi")
|
||||
|
||||
assert result.content == "Hello!"
|
||||
assert result.rounds == 1
|
||||
assert result.tool_calls_made == []
|
||||
assert result.error == ""
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_with_tool_call():
|
||||
"""Bridge executes tool calls and returns final response."""
|
||||
handler = AsyncMock(return_value="tool result data")
|
||||
tool = MCPToolDef(
|
||||
name="my_tool",
|
||||
description="Test",
|
||||
parameters={"type": "object", "properties": {}, "required": []},
|
||||
handler=handler,
|
||||
)
|
||||
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 0
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(
|
||||
include_gitea=False,
|
||||
include_shell=False,
|
||||
extra_tools=[tool],
|
||||
)
|
||||
|
||||
# Round 1: model requests tool call
|
||||
tool_call_resp = MagicMock()
|
||||
tool_call_resp.json.return_value = {
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
"tool_calls": [
|
||||
{
|
||||
"function": {
|
||||
"name": "my_tool",
|
||||
"arguments": {},
|
||||
}
|
||||
}
|
||||
],
|
||||
}
|
||||
}
|
||||
tool_call_resp.raise_for_status = MagicMock()
|
||||
|
||||
# Round 2: model returns final text
|
||||
final_resp = MagicMock()
|
||||
final_resp.json.return_value = {"message": {"role": "assistant", "content": "Done with tools!"}}
|
||||
final_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(side_effect=[tool_call_resp, final_resp])
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("Do something")
|
||||
|
||||
assert result.content == "Done with tools!"
|
||||
assert result.rounds == 2
|
||||
assert len(result.tool_calls_made) == 1
|
||||
assert result.tool_calls_made[0]["tool"] == "my_tool"
|
||||
handler.assert_awaited_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_unknown_tool():
|
||||
"""Bridge handles calls to unknown tools gracefully."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 0
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
# Model calls a tool that doesn't exist
|
||||
tool_call_resp = MagicMock()
|
||||
tool_call_resp.json.return_value = {
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
"tool_calls": [{"function": {"name": "nonexistent", "arguments": {}}}],
|
||||
}
|
||||
}
|
||||
tool_call_resp.raise_for_status = MagicMock()
|
||||
|
||||
final_resp = MagicMock()
|
||||
final_resp.json.return_value = {"message": {"role": "assistant", "content": "OK"}}
|
||||
final_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(side_effect=[tool_call_resp, final_resp])
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("test")
|
||||
|
||||
assert len(result.tool_calls_made) == 1
|
||||
assert "unknown tool" in result.tool_calls_made[0]["result"]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_max_rounds():
|
||||
"""Bridge stops after max_rounds and returns error."""
|
||||
handler = AsyncMock(return_value="result")
|
||||
tool = MCPToolDef(
|
||||
name="loop_tool",
|
||||
description="Loops forever",
|
||||
parameters={"type": "object", "properties": {}, "required": []},
|
||||
handler=handler,
|
||||
)
|
||||
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 0
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(
|
||||
include_gitea=False,
|
||||
include_shell=False,
|
||||
extra_tools=[tool],
|
||||
max_rounds=2,
|
||||
)
|
||||
|
||||
# Always return tool calls (never a final response)
|
||||
tool_call_resp = MagicMock()
|
||||
tool_call_resp.json.return_value = {
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
"tool_calls": [{"function": {"name": "loop_tool", "arguments": {}}}],
|
||||
}
|
||||
}
|
||||
tool_call_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(return_value=tool_call_resp)
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("loop")
|
||||
|
||||
assert "max tool-call rounds" in result.content
|
||||
assert "Exceeded" in result.error
|
||||
assert result.rounds == 2
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_connection_error():
|
||||
"""Bridge handles Ollama connection errors gracefully."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 0
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(side_effect=httpx.ConnectError("Connection refused"))
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("test")
|
||||
|
||||
assert result.error
|
||||
assert "connection" in result.error.lower()
|
||||
assert result.content == ""
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_http_error():
|
||||
"""Bridge handles Ollama HTTP errors gracefully."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.ollama_num_ctx = 0
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.status_code = 500
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(
|
||||
side_effect=httpx.HTTPStatusError(
|
||||
"Server Error",
|
||||
request=MagicMock(),
|
||||
response=mock_response,
|
||||
)
|
||||
)
|
||||
mock_client.aclose = AsyncMock()
|
||||
|
||||
bridge._client = mock_client
|
||||
result = await bridge.run("test")
|
||||
|
||||
assert result.error
|
||||
assert "500" in result.error
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_run_without_context_manager():
|
||||
"""Bridge returns error when used without async context manager."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
result = await bridge.run("test")
|
||||
assert result.error
|
||||
assert "context manager" in result.error.lower()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MCPBridge.status
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_bridge_status():
|
||||
"""Bridge status returns model and tool info."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
status = bridge.status()
|
||||
assert status["model"] == "qwen3:14b"
|
||||
assert status["connected"] is False
|
||||
assert isinstance(status["tools"], list)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MCPBridge context manager
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_bridge_context_manager():
|
||||
"""Bridge opens and closes httpx client via async context manager."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.ollama_model = "qwen3:14b"
|
||||
mock_settings.normalized_ollama_url = "http://localhost:11434"
|
||||
mock_settings.mcp_bridge_timeout = 60
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
bridge = MCPBridge(include_gitea=False, include_shell=False)
|
||||
|
||||
assert bridge._client is None
|
||||
|
||||
async with bridge:
|
||||
assert bridge._client is not None
|
||||
|
||||
assert bridge._client is None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Gitea tool handlers (integration-style, mocked HTTP)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_list_issues_handler():
|
||||
"""list_issues handler calls Gitea API and formats results."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
tools = _build_gitea_tools()
|
||||
|
||||
list_tool = next(t for t in tools if t.name == "list_issues")
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.json.return_value = [
|
||||
{"number": 1, "title": "Bug one", "labels": [{"name": "bug"}]},
|
||||
{"number": 2, "title": "Feature two", "labels": []},
|
||||
]
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.get = AsyncMock(return_value=mock_resp)
|
||||
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_client.__aexit__ = AsyncMock(return_value=False)
|
||||
|
||||
with patch("timmy.mcp_bridge.httpx.AsyncClient", return_value=mock_client):
|
||||
result = await list_tool.handler(state="open", limit=10)
|
||||
|
||||
assert "#1: Bug one [bug]" in result
|
||||
assert "#2: Feature two" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_create_issue_handler():
|
||||
"""create_issue handler calls Gitea API and returns confirmation."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
tools = _build_gitea_tools()
|
||||
|
||||
create_tool = next(t for t in tools if t.name == "create_issue")
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.json.return_value = {"number": 42, "title": "New bug"}
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post = AsyncMock(return_value=mock_resp)
|
||||
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_client.__aexit__ = AsyncMock(return_value=False)
|
||||
|
||||
with patch("timmy.mcp_bridge.httpx.AsyncClient", return_value=mock_client):
|
||||
result = await create_tool.handler(title="New bug", body="Description")
|
||||
|
||||
assert "#42" in result
|
||||
assert "New bug" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_create_issue_requires_title():
|
||||
"""create_issue handler returns error when title is missing."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
tools = _build_gitea_tools()
|
||||
|
||||
create_tool = next(t for t in tools if t.name == "create_issue")
|
||||
result = await create_tool.handler()
|
||||
assert "required" in result.lower()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_read_issue_handler():
|
||||
"""read_issue handler calls Gitea API and formats result."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
tools = _build_gitea_tools()
|
||||
|
||||
read_tool = next(t for t in tools if t.name == "read_issue")
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.json.return_value = {
|
||||
"number": 5,
|
||||
"title": "Test issue",
|
||||
"state": "open",
|
||||
"body": "Issue body text",
|
||||
"labels": [{"name": "enhancement"}],
|
||||
}
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.get = AsyncMock(return_value=mock_resp)
|
||||
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_client.__aexit__ = AsyncMock(return_value=False)
|
||||
|
||||
with patch("timmy.mcp_bridge.httpx.AsyncClient", return_value=mock_client):
|
||||
result = await read_tool.handler(number=5)
|
||||
|
||||
assert "#5" in result
|
||||
assert "Test issue" in result
|
||||
assert "open" in result
|
||||
assert "enhancement" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_read_issue_requires_number():
|
||||
"""read_issue handler returns error when number is missing."""
|
||||
with patch("timmy.mcp_bridge.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok123"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
tools = _build_gitea_tools()
|
||||
|
||||
read_tool = next(t for t in tools if t.name == "read_issue")
|
||||
result = await read_tool.handler()
|
||||
assert "required" in result.lower()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# BridgeResult dataclass
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_bridge_result_defaults():
|
||||
"""BridgeResult has sensible defaults."""
|
||||
r = BridgeResult(content="hello")
|
||||
assert r.content == "hello"
|
||||
assert r.tool_calls_made == []
|
||||
assert r.rounds == 0
|
||||
assert r.latency_ms == 0.0
|
||||
assert r.model == ""
|
||||
assert r.error == ""
|
||||
@@ -1,353 +0,0 @@
|
||||
"""Tests for research triage — action item extraction and Gitea issue filing."""
|
||||
|
||||
import json
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
from timmy.research_triage import (
|
||||
ActionItem,
|
||||
_parse_llm_response,
|
||||
_validate_action_item,
|
||||
create_gitea_issue,
|
||||
extract_action_items,
|
||||
triage_research_report,
|
||||
)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# ActionItem
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
SAMPLE_REPORT = """
|
||||
## Research: MCP Abstraction Layer
|
||||
|
||||
### Finding 1: FastMCP overhead is negligible
|
||||
FastMCP averages 26.45ms per tool call. Total overhead <3% of budget.
|
||||
|
||||
### Finding 2: Agno tool calling is broken
|
||||
Agno issues #2231, #2625 document persistent breakage with Ollama.
|
||||
Fix: Use Ollama's `format` parameter with Pydantic JSON schemas.
|
||||
|
||||
### Recommendation
|
||||
Implement three-tier router for structured output.
|
||||
"""
|
||||
|
||||
SAMPLE_LLM_RESPONSE = json.dumps(
|
||||
[
|
||||
{
|
||||
"title": "[Router] Implement three-tier structured output router",
|
||||
"body": (
|
||||
"**What:** Build a three-tier router that uses Ollama's "
|
||||
"`format` parameter for structured output.\n"
|
||||
"**Why:** Agno's native tool calling is broken (#2231, #2625). "
|
||||
"Pydantic JSON schemas with `format` bypass the issue.\n"
|
||||
"**Suggested approach:** Add format parameter support to "
|
||||
"CascadeRouter.\n"
|
||||
"**Acceptance criteria:** Tool calls return valid JSON matching "
|
||||
"the Pydantic schema."
|
||||
),
|
||||
"labels": ["actionable", "feature", "kimi-ready"],
|
||||
"priority": "high",
|
||||
"source_urls": ["https://github.com/agno-agi/agno/issues/2231"],
|
||||
},
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
class TestActionItem:
|
||||
def test_to_issue_body_basic(self):
|
||||
item = ActionItem(title="Test", body="Test body")
|
||||
body = item.to_issue_body()
|
||||
assert "Test body" in body
|
||||
assert "Auto-triaged" in body
|
||||
|
||||
def test_to_issue_body_with_source_issue(self):
|
||||
item = ActionItem(title="Test", body="Test body")
|
||||
body = item.to_issue_body(source_issue=946)
|
||||
assert "#946" in body
|
||||
assert "Origin" in body
|
||||
|
||||
def test_to_issue_body_with_source_urls(self):
|
||||
item = ActionItem(
|
||||
title="Test",
|
||||
body="Body",
|
||||
source_urls=["https://example.com/finding"],
|
||||
)
|
||||
body = item.to_issue_body()
|
||||
assert "https://example.com/finding" in body
|
||||
assert "Source Evidence" in body
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _parse_llm_response
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestParseLlmResponse:
|
||||
def test_plain_json(self):
|
||||
items = _parse_llm_response('[{"title": "foo"}]')
|
||||
assert len(items) == 1
|
||||
assert items[0]["title"] == "foo"
|
||||
|
||||
def test_fenced_json(self):
|
||||
raw = '```json\n[{"title": "bar"}]\n```'
|
||||
items = _parse_llm_response(raw)
|
||||
assert len(items) == 1
|
||||
assert items[0]["title"] == "bar"
|
||||
|
||||
def test_empty_array(self):
|
||||
assert _parse_llm_response("[]") == []
|
||||
|
||||
def test_non_array_returns_empty(self):
|
||||
assert _parse_llm_response('{"title": "not an array"}') == []
|
||||
|
||||
def test_invalid_json_raises(self):
|
||||
with pytest.raises(json.JSONDecodeError):
|
||||
_parse_llm_response("not json at all")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# _validate_action_item
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestValidateActionItem:
|
||||
def test_valid_item(self):
|
||||
raw = {
|
||||
"title": "[Area] A specific clear title",
|
||||
"body": "Detailed body with enough content to be useful.",
|
||||
"labels": ["actionable", "bug"],
|
||||
"priority": "high",
|
||||
}
|
||||
item = _validate_action_item(raw)
|
||||
assert item is not None
|
||||
assert item.title == "[Area] A specific clear title"
|
||||
assert item.priority == "high"
|
||||
assert "actionable" in item.labels
|
||||
|
||||
def test_short_title_rejected(self):
|
||||
raw = {"title": "Short", "body": "Detailed body with enough content here."}
|
||||
assert _validate_action_item(raw) is None
|
||||
|
||||
def test_short_body_rejected(self):
|
||||
raw = {"title": "A perfectly fine title here", "body": "Too short"}
|
||||
assert _validate_action_item(raw) is None
|
||||
|
||||
def test_missing_title_rejected(self):
|
||||
raw = {"body": "Detailed body with enough content to be useful."}
|
||||
assert _validate_action_item(raw) is None
|
||||
|
||||
def test_non_dict_rejected(self):
|
||||
assert _validate_action_item("not a dict") is None
|
||||
|
||||
def test_actionable_label_auto_added(self):
|
||||
raw = {
|
||||
"title": "A perfectly fine title here",
|
||||
"body": "Detailed body with enough content to be useful.",
|
||||
"labels": ["bug"],
|
||||
}
|
||||
item = _validate_action_item(raw)
|
||||
assert item is not None
|
||||
assert "actionable" in item.labels
|
||||
|
||||
def test_labels_as_csv_string(self):
|
||||
raw = {
|
||||
"title": "A perfectly fine title here",
|
||||
"body": "Detailed body with enough content to be useful.",
|
||||
"labels": "bug, feature",
|
||||
}
|
||||
item = _validate_action_item(raw)
|
||||
assert item is not None
|
||||
assert "bug" in item.labels
|
||||
assert "feature" in item.labels
|
||||
|
||||
def test_invalid_priority_defaults_medium(self):
|
||||
raw = {
|
||||
"title": "A perfectly fine title here",
|
||||
"body": "Detailed body with enough content to be useful.",
|
||||
"priority": "urgent",
|
||||
}
|
||||
item = _validate_action_item(raw)
|
||||
assert item is not None
|
||||
assert item.priority == "medium"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# extract_action_items
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestExtractActionItems:
|
||||
@pytest.mark.asyncio
|
||||
async def test_extracts_items_from_report(self):
|
||||
mock_llm = AsyncMock(return_value=SAMPLE_LLM_RESPONSE)
|
||||
items = await extract_action_items(SAMPLE_REPORT, llm_caller=mock_llm)
|
||||
assert len(items) == 1
|
||||
assert "three-tier" in items[0].title.lower()
|
||||
assert items[0].priority == "high"
|
||||
mock_llm.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_report_returns_empty(self):
|
||||
items = await extract_action_items("")
|
||||
assert items == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_llm_failure_returns_empty(self):
|
||||
mock_llm = AsyncMock(side_effect=RuntimeError("LLM down"))
|
||||
items = await extract_action_items(SAMPLE_REPORT, llm_caller=mock_llm)
|
||||
assert items == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_llm_returns_empty_string(self):
|
||||
mock_llm = AsyncMock(return_value="")
|
||||
items = await extract_action_items(SAMPLE_REPORT, llm_caller=mock_llm)
|
||||
assert items == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_llm_returns_invalid_json(self):
|
||||
mock_llm = AsyncMock(return_value="not valid json")
|
||||
items = await extract_action_items(SAMPLE_REPORT, llm_caller=mock_llm)
|
||||
assert items == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_caps_at_five_items(self):
|
||||
many_items = [
|
||||
{
|
||||
"title": f"[Area] Action item number {i} is specific",
|
||||
"body": f"Detailed body for action item {i} with enough words.",
|
||||
"labels": ["actionable"],
|
||||
"priority": "medium",
|
||||
}
|
||||
for i in range(10)
|
||||
]
|
||||
mock_llm = AsyncMock(return_value=json.dumps(many_items))
|
||||
items = await extract_action_items(SAMPLE_REPORT, llm_caller=mock_llm)
|
||||
assert len(items) <= 5
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# create_gitea_issue
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestCreateGiteaIssue:
|
||||
@pytest.mark.asyncio
|
||||
async def test_creates_issue_via_api(self):
|
||||
item = ActionItem(
|
||||
title="[Test] Create a test issue",
|
||||
body="This is a test issue body with details.",
|
||||
labels=["actionable"],
|
||||
)
|
||||
issue_resp = MagicMock()
|
||||
issue_resp.status_code = 201
|
||||
issue_resp.json.return_value = {"number": 42, "title": item.title}
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post.return_value = issue_resp
|
||||
|
||||
with (
|
||||
patch("timmy.research_triage.settings") as mock_settings,
|
||||
patch(
|
||||
"timmy.research_triage._resolve_label_ids", new_callable=AsyncMock, return_value=[1]
|
||||
),
|
||||
patch("timmy.research_triage.httpx.AsyncClient") as mock_cls,
|
||||
):
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "test-token"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_cls.return_value.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_cls.return_value.__aexit__ = AsyncMock(return_value=False)
|
||||
result = await create_gitea_issue(item, source_issue=946)
|
||||
|
||||
assert result is not None
|
||||
assert result["number"] == 42
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_returns_none_when_disabled(self):
|
||||
item = ActionItem(title="[Test] Disabled test", body="Body content here.")
|
||||
with patch("timmy.research_triage.settings") as mock_settings:
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
result = await create_gitea_issue(item)
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_handles_connection_error(self):
|
||||
item = ActionItem(
|
||||
title="[Test] Connection fail",
|
||||
body="Body content for connection test.",
|
||||
)
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post.side_effect = httpx.ConnectError("refused")
|
||||
|
||||
with (
|
||||
patch("timmy.research_triage.settings") as mock_settings,
|
||||
patch(
|
||||
"timmy.research_triage._resolve_label_ids", new_callable=AsyncMock, return_value=[]
|
||||
),
|
||||
patch("timmy.research_triage.httpx.AsyncClient") as mock_cls,
|
||||
):
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "test-token"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_cls.return_value.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_cls.return_value.__aexit__ = AsyncMock(return_value=False)
|
||||
result = await create_gitea_issue(item)
|
||||
assert result is None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# triage_research_report (integration)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestTriageResearchReport:
|
||||
@pytest.mark.asyncio
|
||||
async def test_dry_run_extracts_without_filing(self):
|
||||
mock_llm = AsyncMock(return_value=SAMPLE_LLM_RESPONSE)
|
||||
results = await triage_research_report(
|
||||
SAMPLE_REPORT, source_issue=946, llm_caller=mock_llm, dry_run=True
|
||||
)
|
||||
assert len(results) == 1
|
||||
assert results[0]["action_item"] is not None
|
||||
assert results[0]["gitea_issue"] is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_report_returns_empty(self):
|
||||
results = await triage_research_report("", llm_caller=AsyncMock(return_value="[]"))
|
||||
assert results == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_end_to_end_with_mock_gitea(self):
|
||||
mock_llm = AsyncMock(return_value=SAMPLE_LLM_RESPONSE)
|
||||
|
||||
issue_resp = MagicMock()
|
||||
issue_resp.status_code = 201
|
||||
issue_resp.json.return_value = {"number": 99, "title": "test"}
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post.return_value = issue_resp
|
||||
|
||||
with (
|
||||
patch("timmy.research_triage.settings") as mock_settings,
|
||||
patch(
|
||||
"timmy.research_triage._resolve_label_ids", new_callable=AsyncMock, return_value=[]
|
||||
),
|
||||
patch("timmy.research_triage.httpx.AsyncClient") as mock_cls,
|
||||
):
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "test-token"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_cls.return_value.__aenter__ = AsyncMock(return_value=mock_client)
|
||||
mock_cls.return_value.__aexit__ = AsyncMock(return_value=False)
|
||||
results = await triage_research_report(
|
||||
SAMPLE_REPORT, source_issue=946, llm_caller=mock_llm
|
||||
)
|
||||
|
||||
assert len(results) == 1
|
||||
assert results[0]["gitea_issue"]["number"] == 99
|
||||
@@ -1,158 +0,0 @@
|
||||
"""Unit tests for the web_fetch tool in timmy.tools."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
from timmy.tools import web_fetch
|
||||
|
||||
|
||||
class TestWebFetch:
|
||||
"""Tests for web_fetch function."""
|
||||
|
||||
def test_invalid_url_no_scheme(self):
|
||||
"""URLs without http(s) scheme are rejected."""
|
||||
result = web_fetch("example.com")
|
||||
assert "Error: invalid URL" in result
|
||||
|
||||
def test_invalid_url_empty(self):
|
||||
"""Empty URL is rejected."""
|
||||
result = web_fetch("")
|
||||
assert "Error: invalid URL" in result
|
||||
|
||||
def test_invalid_url_ftp(self):
|
||||
"""Non-HTTP schemes are rejected."""
|
||||
result = web_fetch("ftp://example.com")
|
||||
assert "Error: invalid URL" in result
|
||||
|
||||
@patch("timmy.tools.trafilatura", create=True)
|
||||
@patch("timmy.tools._requests", create=True)
|
||||
def test_successful_fetch(self, mock_requests, mock_trafilatura):
|
||||
"""Happy path: fetch + extract returns text."""
|
||||
# We need to patch at import level inside the function
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.text = "<html><body><p>Hello world</p></body></html>"
|
||||
|
||||
with patch.dict(
|
||||
"sys.modules", {"requests": mock_requests, "trafilatura": mock_trafilatura}
|
||||
):
|
||||
mock_requests.get.return_value = mock_resp
|
||||
mock_requests.exceptions = _make_exceptions()
|
||||
mock_trafilatura.extract.return_value = "Hello world"
|
||||
|
||||
result = web_fetch("https://example.com")
|
||||
|
||||
assert result == "Hello world"
|
||||
|
||||
@patch.dict("sys.modules", {"requests": MagicMock(), "trafilatura": MagicMock()})
|
||||
def test_truncation(self):
|
||||
"""Long text is truncated to max_tokens * 4 chars."""
|
||||
import sys
|
||||
|
||||
mock_trafilatura = sys.modules["trafilatura"]
|
||||
mock_requests = sys.modules["requests"]
|
||||
|
||||
long_text = "a" * 20000
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.text = "<html><body>" + long_text + "</body></html>"
|
||||
mock_requests.get.return_value = mock_resp
|
||||
mock_requests.exceptions = _make_exceptions()
|
||||
mock_trafilatura.extract.return_value = long_text
|
||||
|
||||
result = web_fetch("https://example.com", max_tokens=100)
|
||||
|
||||
# 100 tokens * 4 chars = 400 chars max
|
||||
assert len(result) < 500
|
||||
assert "[…truncated" in result
|
||||
|
||||
@patch.dict("sys.modules", {"requests": MagicMock(), "trafilatura": MagicMock()})
|
||||
def test_extraction_failure(self):
|
||||
"""Returns error when trafilatura can't extract text."""
|
||||
import sys
|
||||
|
||||
mock_trafilatura = sys.modules["trafilatura"]
|
||||
mock_requests = sys.modules["requests"]
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.text = "<html></html>"
|
||||
mock_requests.get.return_value = mock_resp
|
||||
mock_requests.exceptions = _make_exceptions()
|
||||
mock_trafilatura.extract.return_value = None
|
||||
|
||||
result = web_fetch("https://example.com")
|
||||
assert "Error: could not extract" in result
|
||||
|
||||
@patch.dict("sys.modules", {"trafilatura": MagicMock()})
|
||||
def test_timeout(self):
|
||||
"""Timeout errors are handled gracefully."""
|
||||
|
||||
mock_requests = MagicMock()
|
||||
exc_mod = _make_exceptions()
|
||||
mock_requests.exceptions = exc_mod
|
||||
mock_requests.get.side_effect = exc_mod.Timeout("timed out")
|
||||
|
||||
with patch.dict("sys.modules", {"requests": mock_requests}):
|
||||
result = web_fetch("https://example.com")
|
||||
|
||||
assert "timed out" in result
|
||||
|
||||
@patch.dict("sys.modules", {"trafilatura": MagicMock()})
|
||||
def test_http_error(self):
|
||||
"""HTTP errors (404, 500, etc.) are handled gracefully."""
|
||||
|
||||
mock_requests = MagicMock()
|
||||
exc_mod = _make_exceptions()
|
||||
mock_requests.exceptions = exc_mod
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.status_code = 404
|
||||
mock_requests.get.return_value.raise_for_status.side_effect = exc_mod.HTTPError(
|
||||
response=mock_response
|
||||
)
|
||||
|
||||
with patch.dict("sys.modules", {"requests": mock_requests}):
|
||||
result = web_fetch("https://example.com/nope")
|
||||
|
||||
assert "404" in result
|
||||
|
||||
def test_missing_requests(self):
|
||||
"""Graceful error when requests not installed."""
|
||||
with patch.dict("sys.modules", {"requests": None}):
|
||||
result = web_fetch("https://example.com")
|
||||
assert "requests" in result and "not installed" in result
|
||||
|
||||
def test_missing_trafilatura(self):
|
||||
"""Graceful error when trafilatura not installed."""
|
||||
mock_requests = MagicMock()
|
||||
with patch.dict("sys.modules", {"requests": mock_requests, "trafilatura": None}):
|
||||
result = web_fetch("https://example.com")
|
||||
assert "trafilatura" in result and "not installed" in result
|
||||
|
||||
def test_catalog_entry_exists(self):
|
||||
"""web_fetch should appear in the tool catalog."""
|
||||
from timmy.tools import get_all_available_tools
|
||||
|
||||
catalog = get_all_available_tools()
|
||||
assert "web_fetch" in catalog
|
||||
assert "orchestrator" in catalog["web_fetch"]["available_in"]
|
||||
|
||||
|
||||
def _make_exceptions():
|
||||
"""Create a mock exceptions module with real exception classes."""
|
||||
|
||||
class Timeout(Exception):
|
||||
pass
|
||||
|
||||
class HTTPError(Exception):
|
||||
def __init__(self, *args, response=None, **kwargs):
|
||||
super().__init__(*args, **kwargs)
|
||||
self.response = response
|
||||
|
||||
class RequestException(Exception):
|
||||
pass
|
||||
|
||||
mod = MagicMock()
|
||||
mod.Timeout = Timeout
|
||||
mod.HTTPError = HTTPError
|
||||
mod.RequestException = RequestException
|
||||
return mod
|
||||
@@ -1,460 +0,0 @@
|
||||
"""Unit tests for timmy.kimi_delegation — Kimi research delegation via Gitea labels."""
|
||||
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from timmy.kimi_delegation import (
|
||||
KIMI_LABEL_COLOR,
|
||||
KIMI_READY_LABEL,
|
||||
_build_research_template,
|
||||
_extract_action_items,
|
||||
_slugify,
|
||||
delegate_research_to_kimi,
|
||||
exceeds_local_capacity,
|
||||
)
|
||||
|
||||
# ── Constants ─────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_kimi_ready_label():
|
||||
assert KIMI_READY_LABEL == "kimi-ready"
|
||||
|
||||
|
||||
def test_kimi_label_color_is_hex():
|
||||
assert KIMI_LABEL_COLOR.startswith("#")
|
||||
assert len(KIMI_LABEL_COLOR) == 7
|
||||
|
||||
|
||||
# ── exceeds_local_capacity ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestExceedsLocalCapacity:
|
||||
def test_keyword_comprehensive(self):
|
||||
assert exceeds_local_capacity("Do a comprehensive review of X") is True
|
||||
|
||||
def test_keyword_deep_research(self):
|
||||
assert exceeds_local_capacity("deep research into neural networks") is True
|
||||
|
||||
def test_keyword_benchmark(self):
|
||||
assert exceeds_local_capacity("benchmark these five models") is True
|
||||
|
||||
def test_keyword_exhaustive(self):
|
||||
assert exceeds_local_capacity("exhaustive list of options") is True
|
||||
|
||||
def test_keyword_case_insensitive(self):
|
||||
assert exceeds_local_capacity("COMPREHENSIVE analysis") is True
|
||||
|
||||
def test_keyword_survey(self):
|
||||
assert exceeds_local_capacity("survey all available tools") is True
|
||||
|
||||
def test_keyword_extensive(self):
|
||||
assert exceeds_local_capacity("extensive documentation needed") is True
|
||||
|
||||
def test_short_simple_task(self):
|
||||
assert exceeds_local_capacity("fix the login bug") is False
|
||||
|
||||
def test_long_task_exceeds_word_threshold(self):
|
||||
long_task = " ".join(["word"] * 55)
|
||||
assert exceeds_local_capacity(long_task) is True
|
||||
|
||||
def test_exactly_at_threshold(self):
|
||||
at_threshold = " ".join(["word"] * 50)
|
||||
assert exceeds_local_capacity(at_threshold) is True
|
||||
|
||||
def test_just_below_threshold(self):
|
||||
short = " ".join(["word"] * 49)
|
||||
assert exceeds_local_capacity(short) is False
|
||||
|
||||
def test_empty_string(self):
|
||||
assert exceeds_local_capacity("") is False
|
||||
|
||||
|
||||
# ── _slugify ──────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestSlugify:
|
||||
def test_simple_text(self):
|
||||
assert _slugify("Hello World") == "hello-world"
|
||||
|
||||
def test_special_characters_removed(self):
|
||||
assert _slugify("Hello, World!") == "hello-world"
|
||||
|
||||
def test_underscores_become_dashes(self):
|
||||
assert _slugify("hello_world") == "hello-world"
|
||||
|
||||
def test_multiple_spaces(self):
|
||||
assert _slugify("hello world") == "hello-world"
|
||||
|
||||
def test_truncates_to_60(self):
|
||||
long = "a" * 80
|
||||
result = _slugify(long)
|
||||
assert len(result) <= 60
|
||||
|
||||
def test_no_leading_trailing_dashes(self):
|
||||
result = _slugify(" hello ")
|
||||
assert not result.startswith("-")
|
||||
assert not result.endswith("-")
|
||||
|
||||
def test_empty_string(self):
|
||||
assert _slugify("") == ""
|
||||
|
||||
|
||||
# ── _build_research_template ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestBuildResearchTemplate:
|
||||
def test_contains_task(self):
|
||||
body = _build_research_template("My Task", "some context", "What is X?")
|
||||
assert "My Task" in body
|
||||
|
||||
def test_contains_question(self):
|
||||
body = _build_research_template("Task", "ctx", "What is the answer?")
|
||||
assert "What is the answer?" in body
|
||||
|
||||
def test_contains_context(self):
|
||||
body = _build_research_template("Task", "project background", "Q?")
|
||||
assert "project background" in body
|
||||
|
||||
def test_contains_kimi_ready_label(self):
|
||||
body = _build_research_template("Task", "ctx", "Q?")
|
||||
assert KIMI_READY_LABEL in body
|
||||
|
||||
def test_default_priority_normal(self):
|
||||
body = _build_research_template("Task", "ctx", "Q?")
|
||||
assert "normal" in body
|
||||
|
||||
def test_custom_priority_high(self):
|
||||
body = _build_research_template("Task", "ctx", "Q?", priority="high")
|
||||
assert "high" in body
|
||||
|
||||
def test_contains_deliverables_section(self):
|
||||
body = _build_research_template("Task", "ctx", "Q?")
|
||||
assert "Deliverables" in body
|
||||
|
||||
def test_slug_in_artifact_path(self):
|
||||
body = _build_research_template("My Research Task", "ctx", "Q?")
|
||||
assert "my-research-task" in body
|
||||
|
||||
def test_contains_research_request_header(self):
|
||||
body = _build_research_template("Task", "ctx", "Q?")
|
||||
assert "## Research Request" in body
|
||||
|
||||
|
||||
# ── _extract_action_items ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestExtractActionItems:
|
||||
def test_checkbox_items(self):
|
||||
text = "- [ ] Do thing A\n- [ ] Do thing B"
|
||||
items = _extract_action_items(text)
|
||||
assert "Do thing A" in items
|
||||
assert "Do thing B" in items
|
||||
|
||||
def test_numbered_list(self):
|
||||
text = "1. First step\n2. Second step\n3. Third step"
|
||||
items = _extract_action_items(text)
|
||||
assert "First step" in items
|
||||
assert "Second step" in items
|
||||
assert "Third step" in items
|
||||
|
||||
def test_action_prefix(self):
|
||||
text = "Action: Implement caching layer"
|
||||
items = _extract_action_items(text)
|
||||
assert "Implement caching layer" in items
|
||||
|
||||
def test_todo_prefix(self):
|
||||
text = "TODO: Write tests"
|
||||
items = _extract_action_items(text)
|
||||
assert "Write tests" in items
|
||||
|
||||
def test_next_step_prefix(self):
|
||||
text = "Next step: Deploy to staging"
|
||||
items = _extract_action_items(text)
|
||||
assert "Deploy to staging" in items
|
||||
|
||||
def test_case_insensitive_prefixes(self):
|
||||
text = "TODO: Upper\ntodo: lower\nTodo: Mixed"
|
||||
items = _extract_action_items(text)
|
||||
assert len(items) == 3
|
||||
|
||||
def test_deduplication(self):
|
||||
text = "1. Do the thing\n2. Do the thing"
|
||||
items = _extract_action_items(text)
|
||||
assert items.count("Do the thing") == 1
|
||||
|
||||
def test_empty_text(self):
|
||||
assert _extract_action_items("") == []
|
||||
|
||||
def test_no_action_items(self):
|
||||
text = "This is just a paragraph with no action items."
|
||||
assert _extract_action_items(text) == []
|
||||
|
||||
def test_returns_list(self):
|
||||
assert isinstance(_extract_action_items("1. Item"), list)
|
||||
|
||||
|
||||
# ── delegate_research_to_kimi ─────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestDelegateResearchToKimi:
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_task_returns_error(self):
|
||||
result = await delegate_research_to_kimi("", "context", "question?")
|
||||
assert result["success"] is False
|
||||
assert "task" in result["error"].lower()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_whitespace_task_returns_error(self):
|
||||
result = await delegate_research_to_kimi(" ", "context", "question?")
|
||||
assert result["success"] is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_question_returns_error(self):
|
||||
result = await delegate_research_to_kimi("Task title", "context", "")
|
||||
assert result["success"] is False
|
||||
assert "question" in result["error"].lower()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_whitespace_question_returns_error(self):
|
||||
result = await delegate_research_to_kimi("Task", "ctx", " ")
|
||||
assert result["success"] is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_delegates_to_create_issue(self):
|
||||
with patch(
|
||||
"timmy.kimi_delegation.create_kimi_research_issue",
|
||||
new_callable=AsyncMock,
|
||||
return_value={
|
||||
"success": True,
|
||||
"issue_number": 42,
|
||||
"issue_url": "http://x/42",
|
||||
"error": None,
|
||||
},
|
||||
) as mock_create:
|
||||
result = await delegate_research_to_kimi("Task", "ctx", "What is X?", "high")
|
||||
mock_create.assert_awaited_once_with("Task", "ctx", "What is X?", "high")
|
||||
assert result["success"] is True
|
||||
assert result["issue_number"] == 42
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_passes_default_priority(self):
|
||||
with patch(
|
||||
"timmy.kimi_delegation.create_kimi_research_issue",
|
||||
new_callable=AsyncMock,
|
||||
return_value={"success": True, "issue_number": 1, "issue_url": "", "error": None},
|
||||
) as mock_create:
|
||||
await delegate_research_to_kimi("Task", "ctx", "Q?")
|
||||
_, _, _, priority = mock_create.call_args.args
|
||||
assert priority == "normal"
|
||||
|
||||
|
||||
# ── create_kimi_research_issue ────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestCreateKimiResearchIssue:
|
||||
@pytest.mark.asyncio
|
||||
async def test_no_gitea_token_returns_error(self):
|
||||
from timmy.kimi_delegation import create_kimi_research_issue
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
with patch("config.settings", mock_settings):
|
||||
result = await create_kimi_research_issue("Task", "ctx", "Q?")
|
||||
assert result["success"] is False
|
||||
assert "not configured" in result["error"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_disabled_returns_error(self):
|
||||
from timmy.kimi_delegation import create_kimi_research_issue
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = "tok"
|
||||
|
||||
with patch("config.settings", mock_settings):
|
||||
result = await create_kimi_research_issue("Task", "ctx", "Q?")
|
||||
assert result["success"] is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_successful_issue_creation(self):
|
||||
from timmy.kimi_delegation import create_kimi_research_issue
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "fake-token"
|
||||
mock_settings.gitea_url = "http://gitea.local"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
|
||||
label_resp = MagicMock()
|
||||
label_resp.status_code = 200
|
||||
label_resp.json.return_value = [{"name": "kimi-ready", "id": 7}]
|
||||
|
||||
issue_resp = MagicMock()
|
||||
issue_resp.status_code = 201
|
||||
issue_resp.json.return_value = {
|
||||
"number": 101,
|
||||
"html_url": "http://gitea.local/issues/101",
|
||||
}
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.get.return_value = label_resp
|
||||
mock_client.post.return_value = issue_resp
|
||||
|
||||
async_ctx = AsyncMock()
|
||||
async_ctx.__aenter__.return_value = mock_client
|
||||
async_ctx.__aexit__.return_value = False
|
||||
|
||||
with (
|
||||
patch("config.settings", mock_settings),
|
||||
patch("httpx.AsyncClient", return_value=async_ctx),
|
||||
):
|
||||
result = await create_kimi_research_issue("Task", "ctx", "Q?")
|
||||
|
||||
assert result["success"] is True
|
||||
assert result["issue_number"] == 101
|
||||
assert result["error"] is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_api_error_returns_failure(self):
|
||||
from timmy.kimi_delegation import create_kimi_research_issue
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok"
|
||||
mock_settings.gitea_url = "http://gitea.local"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
|
||||
label_resp = MagicMock()
|
||||
label_resp.status_code = 200
|
||||
label_resp.json.return_value = [{"name": "kimi-ready", "id": 7}]
|
||||
|
||||
issue_resp = MagicMock()
|
||||
issue_resp.status_code = 500
|
||||
issue_resp.text = "Internal Server Error"
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.get.return_value = label_resp
|
||||
mock_client.post.return_value = issue_resp
|
||||
|
||||
async_ctx = AsyncMock()
|
||||
async_ctx.__aenter__.return_value = mock_client
|
||||
async_ctx.__aexit__.return_value = False
|
||||
|
||||
with (
|
||||
patch("config.settings", mock_settings),
|
||||
patch("httpx.AsyncClient", return_value=async_ctx),
|
||||
):
|
||||
result = await create_kimi_research_issue("Task", "ctx", "Q?")
|
||||
|
||||
assert result["success"] is False
|
||||
assert "500" in result["error"]
|
||||
|
||||
|
||||
# ── index_kimi_artifact ───────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestIndexKimiArtifact:
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_artifact_returns_error(self):
|
||||
from timmy.kimi_delegation import index_kimi_artifact
|
||||
|
||||
result = await index_kimi_artifact(42, "Title", "")
|
||||
assert result["success"] is False
|
||||
assert "Empty" in result["error"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_whitespace_only_artifact_returns_error(self):
|
||||
from timmy.kimi_delegation import index_kimi_artifact
|
||||
|
||||
result = await index_kimi_artifact(42, "Title", " \n ")
|
||||
assert result["success"] is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_successful_indexing(self):
|
||||
from timmy.kimi_delegation import index_kimi_artifact
|
||||
|
||||
mock_entry = MagicMock()
|
||||
mock_entry.id = "mem-abc-123"
|
||||
|
||||
with patch("timmy.memory_system.store_memory", return_value=mock_entry) as mock_store:
|
||||
result = await index_kimi_artifact(55, "Research Title", "Artifact content here.")
|
||||
|
||||
assert result["success"] is True
|
||||
assert result["memory_id"] == "mem-abc-123"
|
||||
mock_store.assert_called_once()
|
||||
call_kwargs = mock_store.call_args.kwargs
|
||||
assert call_kwargs["source"] == "kimi"
|
||||
assert call_kwargs["context_type"] == "document"
|
||||
assert call_kwargs["task_id"] == "55"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_store_memory_exception_returns_error(self):
|
||||
from timmy.kimi_delegation import index_kimi_artifact
|
||||
|
||||
with patch(
|
||||
"timmy.memory_system.store_memory",
|
||||
side_effect=RuntimeError("DB error"),
|
||||
):
|
||||
result = await index_kimi_artifact(1, "T", "Some content")
|
||||
assert result["success"] is False
|
||||
assert "DB error" in result["error"]
|
||||
|
||||
|
||||
# ── extract_and_create_followups ──────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestExtractAndCreateFollowups:
|
||||
@pytest.mark.asyncio
|
||||
async def test_no_action_items_returns_empty_list(self):
|
||||
from timmy.kimi_delegation import extract_and_create_followups
|
||||
|
||||
result = await extract_and_create_followups("No action items here.", 10)
|
||||
assert result["success"] is True
|
||||
assert result["created"] == []
|
||||
assert result["error"] is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gitea_not_configured(self):
|
||||
from timmy.kimi_delegation import extract_and_create_followups
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = False
|
||||
mock_settings.gitea_token = ""
|
||||
|
||||
with patch("config.settings", mock_settings):
|
||||
result = await extract_and_create_followups("1. Do the thing", 10)
|
||||
assert result["success"] is False
|
||||
assert result["created"] == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_creates_followup_issues(self):
|
||||
from timmy.kimi_delegation import extract_and_create_followups
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_enabled = True
|
||||
mock_settings.gitea_token = "tok"
|
||||
mock_settings.gitea_url = "http://gitea.local"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
|
||||
issue_resp = MagicMock()
|
||||
issue_resp.status_code = 201
|
||||
issue_resp.json.return_value = {"number": 200}
|
||||
|
||||
mock_client = AsyncMock()
|
||||
mock_client.post.return_value = issue_resp
|
||||
|
||||
async_ctx = AsyncMock()
|
||||
async_ctx.__aenter__.return_value = mock_client
|
||||
async_ctx.__aexit__.return_value = False
|
||||
|
||||
with (
|
||||
patch("config.settings", mock_settings),
|
||||
patch("httpx.AsyncClient", return_value=async_ctx),
|
||||
):
|
||||
result = await extract_and_create_followups("1. Do the thing\n2. Do another thing", 10)
|
||||
|
||||
assert result["success"] is True
|
||||
assert 200 in result["created"]
|
||||
497
tests/unit/test_research.py
Normal file
497
tests/unit/test_research.py
Normal file
@@ -0,0 +1,497 @@
|
||||
"""Unit tests for timmy.research — ResearchOrchestrator pipeline."""
|
||||
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from timmy.research import (
|
||||
DEFAULT_QUERIES_PER_TOPIC,
|
||||
MemoryInterface,
|
||||
ResearchOrchestrator,
|
||||
ResearchResult,
|
||||
ResearchTools,
|
||||
SearchSnippet,
|
||||
_extract_action_items,
|
||||
)
|
||||
|
||||
# ── Data structures ──────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestResearchResult:
|
||||
def test_defaults(self):
|
||||
r = ResearchResult(topic="test", report="content")
|
||||
assert r.topic == "test"
|
||||
assert r.report == "content"
|
||||
assert r.cache_hit is False
|
||||
assert r.queries_generated == []
|
||||
assert r.sources == []
|
||||
assert r.action_items == []
|
||||
assert r.duration_ms == 0.0
|
||||
assert r.timestamp # non-empty
|
||||
|
||||
def test_with_data(self):
|
||||
r = ResearchResult(
|
||||
topic="AI",
|
||||
report="report text",
|
||||
queries_generated=["q1", "q2"],
|
||||
sources=[{"url": "http://example.com", "title": "Test"}],
|
||||
action_items=["Do X"],
|
||||
cache_hit=True,
|
||||
duration_ms=42.5,
|
||||
)
|
||||
assert r.cache_hit is True
|
||||
assert len(r.sources) == 1
|
||||
assert r.duration_ms == 42.5
|
||||
|
||||
|
||||
class TestSearchSnippet:
|
||||
def test_fields(self):
|
||||
s = SearchSnippet(title="T", url="http://x.com", snippet="text")
|
||||
assert s.relevance == 0.0
|
||||
|
||||
|
||||
# ── _extract_action_items ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestExtractActionItems:
|
||||
def test_action_prefix(self):
|
||||
report = "Some text\nACTION: Do the thing\nMore text"
|
||||
items = _extract_action_items(report)
|
||||
assert items == ["Do the thing"]
|
||||
|
||||
def test_todo_prefix(self):
|
||||
report = "TODO: Fix the bug\nTodo: Also this"
|
||||
items = _extract_action_items(report)
|
||||
assert items == ["Fix the bug", "Also this"]
|
||||
|
||||
def test_checkbox(self):
|
||||
report = "- [ ] Implement feature\n- [x] Already done"
|
||||
items = _extract_action_items(report)
|
||||
assert items == ["Implement feature"]
|
||||
|
||||
def test_mixed(self):
|
||||
report = "ACTION: First\n- [ ] Second\nTODO: Third"
|
||||
items = _extract_action_items(report)
|
||||
assert items == ["First", "Second", "Third"]
|
||||
|
||||
def test_empty(self):
|
||||
assert _extract_action_items("No actions here") == []
|
||||
assert _extract_action_items("") == []
|
||||
|
||||
|
||||
# ── MemoryInterface ──────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestMemoryInterface:
|
||||
def test_custom_fns(self):
|
||||
search = MagicMock(return_value=[])
|
||||
store = MagicMock()
|
||||
mi = MemoryInterface(search_fn=search, store_fn=store)
|
||||
assert mi.search_fn is search
|
||||
assert mi.store_fn is store
|
||||
|
||||
def test_defaults_when_import_fails(self):
|
||||
with patch.dict("sys.modules", {"timmy.memory_system": None}):
|
||||
mi = MemoryInterface()
|
||||
# Should have fallback callables
|
||||
assert callable(mi.search_fn)
|
||||
assert callable(mi.store_fn)
|
||||
# Fallback search returns empty
|
||||
assert mi.search_fn("test") == []
|
||||
|
||||
|
||||
# ── ResearchOrchestrator ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _make_cascade(**overrides):
|
||||
"""Create a mock cascade router."""
|
||||
cascade = AsyncMock()
|
||||
cascade.complete = AsyncMock(
|
||||
return_value={"content": overrides.get("content", "query1\nquery2\nquery3")}
|
||||
)
|
||||
return cascade
|
||||
|
||||
|
||||
def _make_memory(search_results=None, score=0.0):
|
||||
"""Create a mock memory interface."""
|
||||
if search_results is None:
|
||||
search_results = []
|
||||
search_fn = MagicMock(return_value=search_results)
|
||||
store_fn = MagicMock()
|
||||
return MemoryInterface(search_fn=search_fn, store_fn=store_fn)
|
||||
|
||||
|
||||
def _make_tools(search_results=None, fetch_content="Page content"):
|
||||
"""Create mock research tools."""
|
||||
web_search = MagicMock(
|
||||
return_value=search_results
|
||||
or [
|
||||
{"title": "Result 1", "url": "http://a.com", "snippet": "Snippet 1"},
|
||||
{"title": "Result 2", "url": "http://b.com", "snippet": "Snippet 2"},
|
||||
]
|
||||
)
|
||||
web_fetch = MagicMock(return_value=fetch_content)
|
||||
return ResearchTools(web_search=web_search, web_fetch=web_fetch)
|
||||
|
||||
|
||||
class TestResearchOrchestratorInit:
|
||||
def test_basic_init(self):
|
||||
cascade = _make_cascade()
|
||||
memory = _make_memory()
|
||||
tools = _make_tools()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory, tools=tools)
|
||||
assert orch.cascade is cascade
|
||||
assert orch.memory is memory
|
||||
assert orch.tools is tools
|
||||
assert orch._metrics["research_cache_hit"] == 0
|
||||
assert orch._metrics["research_api_call"] == 0
|
||||
|
||||
|
||||
class TestCheckLocalKnowledge:
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_hit(self):
|
||||
"""High-confidence memory result returns cached ResearchResult."""
|
||||
entry = MagicMock()
|
||||
entry.relevance_score = 0.90
|
||||
entry.content = "Cached report"
|
||||
|
||||
memory = _make_memory(search_results=[entry])
|
||||
cascade = _make_cascade()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory)
|
||||
|
||||
result = await orch._check_local_knowledge("test topic")
|
||||
assert result is not None
|
||||
assert result.cache_hit is True
|
||||
assert result.report == "Cached report"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_miss_low_score(self):
|
||||
"""Low-confidence result returns None."""
|
||||
entry = MagicMock()
|
||||
entry.relevance_score = 0.5
|
||||
entry.content = "Weak match"
|
||||
|
||||
memory = _make_memory(search_results=[entry])
|
||||
cascade = _make_cascade()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory)
|
||||
|
||||
result = await orch._check_local_knowledge("test topic")
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_miss_empty(self):
|
||||
"""No memory results returns None."""
|
||||
memory = _make_memory(search_results=[])
|
||||
cascade = _make_cascade()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory)
|
||||
|
||||
result = await orch._check_local_knowledge("test topic")
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_exception_returns_none(self):
|
||||
"""Memory search exception returns None gracefully."""
|
||||
memory = MemoryInterface(
|
||||
search_fn=MagicMock(side_effect=RuntimeError("db error")),
|
||||
store_fn=MagicMock(),
|
||||
)
|
||||
cascade = _make_cascade()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory)
|
||||
|
||||
result = await orch._check_local_knowledge("test topic")
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestGenerateQueries:
|
||||
@pytest.mark.asyncio
|
||||
async def test_parses_queries(self):
|
||||
cascade = _make_cascade(content="query one\nquery two\nquery three")
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
queries = await orch._generate_queries("AI safety", None, None)
|
||||
assert queries == ["query one", "query two", "query three"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_strips_numbering(self):
|
||||
cascade = _make_cascade(content="1. First query\n2. Second query\n3) Third")
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
queries = await orch._generate_queries("topic", None, None)
|
||||
assert "First query" in queries
|
||||
assert "Second query" in queries
|
||||
assert "Third" in queries
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fallback_on_error(self):
|
||||
cascade = AsyncMock()
|
||||
cascade.complete = AsyncMock(side_effect=RuntimeError("LLM down"))
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
queries = await orch._generate_queries("fallback topic", None, None)
|
||||
assert queries == ["fallback topic"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_passes_cascade_tier(self):
|
||||
cascade = _make_cascade(content="q1\nq2")
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
await orch._generate_queries("topic", None, "gpt-4")
|
||||
call_kwargs = cascade.complete.call_args.kwargs
|
||||
assert call_kwargs.get("model") == "gpt-4"
|
||||
|
||||
|
||||
class TestSearch:
|
||||
@pytest.mark.asyncio
|
||||
async def test_collects_snippets(self):
|
||||
tools = _make_tools()
|
||||
orch = ResearchOrchestrator(
|
||||
cascade=_make_cascade(), memory=_make_memory(), tools=tools
|
||||
)
|
||||
|
||||
snippets = await orch._search(["q1", "q2"])
|
||||
# 2 results per query, 2 queries, but deduplicated by URL
|
||||
assert len(snippets) == 2 # same URLs returned for both queries
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_no_search_tool(self):
|
||||
tools = ResearchTools(web_search=None)
|
||||
orch = ResearchOrchestrator(
|
||||
cascade=_make_cascade(), memory=_make_memory(), tools=tools
|
||||
)
|
||||
|
||||
snippets = await orch._search(["q1"])
|
||||
assert snippets == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_error_handled(self):
|
||||
tools = ResearchTools(
|
||||
web_search=MagicMock(side_effect=RuntimeError("network error"))
|
||||
)
|
||||
orch = ResearchOrchestrator(
|
||||
cascade=_make_cascade(), memory=_make_memory(), tools=tools
|
||||
)
|
||||
|
||||
snippets = await orch._search(["q1"])
|
||||
assert snippets == []
|
||||
|
||||
|
||||
class TestFetch:
|
||||
@pytest.mark.asyncio
|
||||
async def test_fetches_pages(self):
|
||||
tools = _make_tools(fetch_content="Page body here")
|
||||
orch = ResearchOrchestrator(
|
||||
cascade=_make_cascade(), memory=_make_memory(), tools=tools
|
||||
)
|
||||
|
||||
snippets = [
|
||||
SearchSnippet(title="P1", url="http://a.com", snippet="s1"),
|
||||
SearchSnippet(title="P2", url="http://b.com", snippet="s2"),
|
||||
]
|
||||
pages = await orch._fetch(snippets)
|
||||
assert len(pages) == 2
|
||||
assert pages[0].content == "Page body here"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_no_fetch_tool(self):
|
||||
tools = ResearchTools(web_fetch=None)
|
||||
orch = ResearchOrchestrator(
|
||||
cascade=_make_cascade(), memory=_make_memory(), tools=tools
|
||||
)
|
||||
|
||||
pages = await orch._fetch([SearchSnippet("T", "http://x.com", "s")])
|
||||
assert pages == []
|
||||
|
||||
|
||||
class TestSynthesize:
|
||||
@pytest.mark.asyncio
|
||||
async def test_produces_report(self):
|
||||
cascade = _make_cascade(content="# Report\nKey findings here")
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
from timmy.research import FetchedPage
|
||||
|
||||
pages = [FetchedPage(url="http://x.com", title="X", content="content")]
|
||||
report = await orch._synthesize("topic", None, pages, None)
|
||||
assert "Report" in report
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fallback_on_error(self):
|
||||
cascade = AsyncMock()
|
||||
cascade.complete = AsyncMock(side_effect=RuntimeError("LLM error"))
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=_make_memory())
|
||||
|
||||
from timmy.research import FetchedPage
|
||||
|
||||
pages = [FetchedPage(url="http://x.com", title="X", content="content")]
|
||||
report = await orch._synthesize("topic", None, pages, None)
|
||||
assert "Synthesis failed" in report
|
||||
assert "topic" in report
|
||||
|
||||
|
||||
class TestCrystallize:
|
||||
@pytest.mark.asyncio
|
||||
async def test_stores_in_memory(self):
|
||||
memory = _make_memory()
|
||||
orch = ResearchOrchestrator(cascade=_make_cascade(), memory=memory)
|
||||
|
||||
result = ResearchResult(topic="test", report="report text")
|
||||
await orch._crystallize("test", result)
|
||||
|
||||
memory.store_fn.assert_called_once()
|
||||
call_kwargs = memory.store_fn.call_args
|
||||
assert call_kwargs.kwargs.get("context_type") == "research"
|
||||
assert call_kwargs.kwargs.get("source") == "research_orchestrator"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_store_error_handled(self):
|
||||
memory = MemoryInterface(
|
||||
search_fn=MagicMock(return_value=[]),
|
||||
store_fn=MagicMock(side_effect=RuntimeError("db error")),
|
||||
)
|
||||
orch = ResearchOrchestrator(cascade=_make_cascade(), memory=memory)
|
||||
|
||||
result = ResearchResult(topic="test", report="report")
|
||||
# Should not raise
|
||||
await orch._crystallize("test", result)
|
||||
|
||||
|
||||
class TestWriteArtifact:
|
||||
@pytest.mark.asyncio
|
||||
async def test_no_action_items_skips(self):
|
||||
orch = ResearchOrchestrator(cascade=_make_cascade(), memory=_make_memory())
|
||||
|
||||
result = ResearchResult(topic="test", report="r", action_items=[])
|
||||
# Should complete without any calls
|
||||
await orch._write_artifact(result)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_creates_issues(self):
|
||||
orch = ResearchOrchestrator(cascade=_make_cascade(), memory=_make_memory())
|
||||
|
||||
result = ResearchResult(
|
||||
topic="test", report="r", action_items=["Fix the thing"]
|
||||
)
|
||||
with patch("timmy.research._create_gitea_issues") as mock_create:
|
||||
await orch._write_artifact(result)
|
||||
mock_create.assert_called_once_with(result)
|
||||
|
||||
|
||||
class TestFullPipeline:
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_hit_short_circuits(self):
|
||||
"""When memory has a high-confidence match, skip web search."""
|
||||
entry = MagicMock()
|
||||
entry.relevance_score = 0.95
|
||||
entry.content = "Previously researched content"
|
||||
|
||||
memory = _make_memory(search_results=[entry])
|
||||
cascade = _make_cascade()
|
||||
tools = _make_tools()
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory, tools=tools)
|
||||
|
||||
result = await orch.run("cached topic")
|
||||
assert result.cache_hit is True
|
||||
assert result.report == "Previously researched content"
|
||||
# Cascade should NOT have been called (no query generation or synthesis)
|
||||
cascade.complete.assert_not_called()
|
||||
assert orch._metrics["research_cache_hit"] == 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_full_pipeline_no_tools(self):
|
||||
"""Pipeline completes even without web tools (graceful degradation)."""
|
||||
memory = _make_memory()
|
||||
cascade = AsyncMock()
|
||||
# First call: generate queries, second: synthesize
|
||||
cascade.complete = AsyncMock(
|
||||
side_effect=[
|
||||
{"content": "query 1\nquery 2"},
|
||||
{"content": "# Report\nACTION: Do something"},
|
||||
]
|
||||
)
|
||||
tools = ResearchTools() # No web tools
|
||||
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory, tools=tools)
|
||||
|
||||
with patch("timmy.research._create_gitea_issues"):
|
||||
result = await orch.run("test topic")
|
||||
|
||||
assert result.topic == "test topic"
|
||||
assert result.cache_hit is False
|
||||
assert "Report" in result.report
|
||||
assert result.action_items == ["Do something"]
|
||||
assert result.duration_ms > 0
|
||||
assert orch._metrics["research_api_call"] == 1
|
||||
memory.store_fn.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_full_pipeline_with_tools(self):
|
||||
"""Full pipeline with search and fetch tools."""
|
||||
memory = _make_memory()
|
||||
cascade = AsyncMock()
|
||||
cascade.complete = AsyncMock(
|
||||
side_effect=[
|
||||
{"content": "search query 1\nsearch query 2"},
|
||||
{"content": "# Full Report\nTODO: Review findings"},
|
||||
]
|
||||
)
|
||||
tools = _make_tools()
|
||||
|
||||
orch = ResearchOrchestrator(cascade=cascade, memory=memory, tools=tools)
|
||||
|
||||
with patch("timmy.research._create_gitea_issues"):
|
||||
result = await orch.run("test topic")
|
||||
|
||||
assert result.topic == "test topic"
|
||||
assert result.cache_hit is False
|
||||
assert len(result.queries_generated) == 2
|
||||
assert len(result.sources) > 0
|
||||
assert result.action_items == ["Review findings"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_metrics(self):
|
||||
orch = ResearchOrchestrator(cascade=_make_cascade(), memory=_make_memory())
|
||||
metrics = orch.get_metrics()
|
||||
assert "research_cache_hit" in metrics
|
||||
assert "research_api_call" in metrics
|
||||
|
||||
|
||||
class TestCreateGiteaIssues:
|
||||
def test_no_token_skips(self):
|
||||
"""No Gitea token configured — silently skips."""
|
||||
from timmy.research import _create_gitea_issues
|
||||
|
||||
result = ResearchResult(
|
||||
topic="t", report="r", action_items=["item"]
|
||||
)
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_token = ""
|
||||
mock_settings.gitea_url = ""
|
||||
with patch("timmy.research.settings", mock_settings):
|
||||
# Should not raise
|
||||
_create_gitea_issues(result)
|
||||
|
||||
def test_creates_issue_on_success(self):
|
||||
from timmy.research import _create_gitea_issues
|
||||
|
||||
result = ResearchResult(
|
||||
topic="AI", report="r", action_items=["Deploy model"]
|
||||
)
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.gitea_token = "tok"
|
||||
mock_settings.gitea_url = "http://localhost:3000"
|
||||
mock_settings.gitea_repo = "owner/repo"
|
||||
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.status_code = 201
|
||||
|
||||
mock_requests_mod = MagicMock()
|
||||
mock_requests_mod.post.return_value = mock_resp
|
||||
|
||||
with (
|
||||
patch("timmy.research.settings", mock_settings),
|
||||
patch.dict("sys.modules", {"requests": mock_requests_mod}),
|
||||
):
|
||||
_create_gitea_issues(result)
|
||||
mock_requests_mod.post.assert_called_once()
|
||||
call_kwargs = mock_requests_mod.post.call_args
|
||||
assert "[research]" in call_kwargs.kwargs["json"]["title"]
|
||||
5
tox.ini
5
tox.ini
@@ -87,11 +87,6 @@ description = Live LLM tests via Ollama (requires running Ollama)
|
||||
commands =
|
||||
pytest tests/ -q --tb=short -m ollama --timeout=120
|
||||
|
||||
[testenv:benchmark]
|
||||
description = Agent performance regression benchmark suite
|
||||
commands =
|
||||
python scripts/run_benchmarks.py {posargs}
|
||||
|
||||
# ── CI / Coverage ────────────────────────────────────────────────────────────
|
||||
|
||||
[testenv:ci]
|
||||
|
||||
Reference in New Issue
Block a user