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Author SHA1 Message Date
Alexander Whitestone
1a4653570e fix: fix test patching in campaign_loop and malformed entry filtering in campaign_state
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- Remove redundant local GabsClient import inside run() that bypassed
  unittest.mock patches in TestCampaignLoopRun tests
- Skip nearby_party entries missing a valid 'id' field in parse_campaign_state
  so malformed dicts like {"bad": "data"} are dropped rather than creating
  empty NearbyParty objects

Fixes #1094

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-23 21:34:18 -04:00
Alexander Whitestone
46ef9d3aba WIP: Claude Code progress on #1094
Automated salvage commit — agent session ended (exit 124).
Work in progress, may need continuation.
2026-03-23 14:26:15 -04:00
852fec3681 [gemini] feat: Integrate ResearchOrchestrator with Paperclip (#978) (#1111)
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Co-authored-by: Google Gemini <gemini@hermes.local>
Co-committed-by: Google Gemini <gemini@hermes.local>
2026-03-23 18:09:29 +00:00
19dbdec314 [claude] Add Hermes 4 14B Modelfile, providers config, and smoke test (#1101) (#1110)
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2026-03-23 17:59:45 +00:00
3c6a1659d2 [claude] Decline out-of-scope Bannerlord M4 formation commander (#1096) (#1109)
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2026-03-23 17:59:18 +00:00
62e7cfeffb [claude] Feudal multi-agent hierarchy design for Bannerlord (#1099) (#1108)
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2026-03-23 17:57:32 +00:00
efb09932ce [claude] Decline out-of-scope Hermes Agent audit (#1100) (#1107)
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2026-03-23 17:56:16 +00:00
f2a277f7b5 [claude] Add vllm-mlx as high-performance local inference backend (#1069) (#1089)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:34:13 +00:00
7fdd532260 [claude] Configure Dolphin 3.0 8B as creative writing fallback (#1068) (#1088)
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2026-03-23 15:25:06 +00:00
48f667c76b [claude] Integrate Claude Quota Monitor + Metabolic Protocol into cascade router (#1075) (#1086)
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2026-03-23 15:18:11 +00:00
e482337e50 [claude] Implement Kimi delegation for heavy research via Gitea labels (#979) (#1085)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:14:53 +00:00
b5a65b9d10 [claude] Add unit tests for health.py (#945) (#1002)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:10:53 +00:00
43030b7db2 [claude] DRY up tasks_pending/active/completed in tasks.py (#942) (#1020)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:10:05 +00:00
ab36149fa5 [claude] Auto-create Gitea issues from research findings (#977) (#1060)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:09:18 +00:00
6a674bf9e0 [claude] Set up MCP bridge for Qwen3 via Ollama (#1067) (#1081)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:09:11 +00:00
df7358b383 [claude] Extract hardcoded sats limit in consult_grok() (#937) (#1058)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 15:07:40 +00:00
af0963a8c7 [loop-cycle-1] refactor: break up run_agentic_loop (#531) (#1084)
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2026-03-23 15:06:59 +00:00
dd65586b5e [claude] Execute deep backlog triage — harness vs infrastructure separation (#1076) (#1082)
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Co-authored-by: Claude (Opus 4.6) <claude@hermes.local>
Co-committed-by: Claude (Opus 4.6) <claude@hermes.local>
2026-03-23 14:59:09 +00:00
7f875398fc [claude] Add sovereignty metrics tracking + dashboard panel (#981) (#1083)
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2026-03-23 14:09:03 +00:00
fc53a33361 [claude] Enforce coverage threshold in CI workflow (#935) (#1061)
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2026-03-23 02:19:26 +00:00
1697e55cdb [claude] Add content moderation pipeline (Llama Guard + game-context prompts) (#1056) (#1059)
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2026-03-23 02:14:42 +00:00
092c982341 [claude] Ingest integration architecture research and triage work (#946) (#1057)
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2026-03-23 01:40:39 +00:00
45bde4df58 [claude] Add agent performance regression benchmark suite (#1015) (#1053)
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2026-03-22 23:55:27 +00:00
c0f6ca9fc2 [claude] Add web_fetch tool (trafilatura) for full-page content extraction (#973) (#1004)
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2026-03-22 23:03:38 +00:00
9656a5e0d0 [claude] Add connection leak and pragma unit tests for db_pool.py (#944) (#1001)
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2026-03-22 22:56:58 +00:00
Alexander Whitestone
e35a23cefa [claude] Add research prompt template library (#974) (#999)
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Co-authored-by: Alexander Whitestone <alexpaynex@gmail.com>
Co-committed-by: Alexander Whitestone <alexpaynex@gmail.com>
2026-03-22 22:44:02 +00:00
Alexander Whitestone
3ab180b8a7 [claude] Add Gitea backup script (#990) (#996)
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Co-authored-by: Alexander Whitestone <alexpaynex@gmail.com>
Co-committed-by: Alexander Whitestone <alexpaynex@gmail.com>
2026-03-22 22:36:51 +00:00
76 changed files with 12461 additions and 331 deletions

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@@ -50,6 +50,7 @@ jobs:
run: pip install tox
- name: Run tests (via tox)
id: tests
run: tox -e ci
# Posts a check annotation + PR comment showing pass/fail counts.
@@ -63,6 +64,20 @@ jobs:
comment_title: "Test Results"
report_individual_runs: true
- name: Enforce coverage floor (60%)
if: always() && steps.tests.outcome == 'success'
run: |
python -c "
import xml.etree.ElementTree as ET, sys
tree = ET.parse('reports/coverage.xml')
rate = float(tree.getroot().attrib['line-rate']) * 100
print(f'Coverage: {rate:.1f}%')
if rate < 60:
print(f'FAIL: Coverage {rate:.1f}% is below 60% floor')
sys.exit(1)
print('PASS: Coverage is above 60% floor')
"
# Coverage report available as a downloadable artifact in the Actions tab
- name: Upload coverage report
uses: actions/upload-artifact@v4

55
Modelfile.hermes4-14b Normal file
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@@ -0,0 +1,55 @@
# Modelfile.hermes4-14b
#
# NousResearch Hermes 4 14B — AutoLoRA base model (Project Bannerlord, Step 2)
#
# Features: native tool calling, hybrid reasoning (<think> tags), structured
# JSON output, neutral alignment. Built to serve as the LoRA fine-tuning base.
#
# Build:
# # Download GGUF from HuggingFace first:
# # https://huggingface.co/collections/NousResearch/hermes-4-collection-68a7
# # Pick: NousResearch-Hermes-4-14B-Q5_K_M.gguf (or Q4_K_M for less RAM)
# ollama create hermes4-14b -f Modelfile.hermes4-14b
#
# Or if hermes4 lands on Ollama registry directly:
# ollama pull hermes4:14b
# ollama create hermes4-14b -f Modelfile.hermes4-14b
#
# Memory budget: ~9 GB at Q4_K_M, ~11 GB at Q5_K_M — leaves headroom on 36 GB M3 Max
# Context: 32K comfortable (128K theoretical)
# Primary use: AutoLoRA base before fine-tuning on Timmy skill set
# --- Option A: import local GGUF (uncomment and set correct path) ---
# FROM /path/to/NousResearch-Hermes-4-14B-Q5_K_M.gguf
# --- Option B: build from Ollama registry model (if available) ---
FROM hermes4:14b
# Context window — 32K leaves ~20 GB headroom for KV cache on M3 Max
PARAMETER num_ctx 32768
# Tool-calling temperature — lower for reliable structured output
PARAMETER temperature 0.3
# Nucleus sampling — balanced for reasoning + tool use
PARAMETER top_p 0.9
# Repeat penalty — prevents looping in structured output
PARAMETER repeat_penalty 1.05
# Stop tokens for Hermes 4 chat template (ChatML format)
# These are handled automatically by the model's tokenizer config,
# but listed here for reference.
# STOP "<|im_end|>"
# STOP "<|endoftext|>"
SYSTEM """You are Hermes, a helpful, honest, and harmless AI assistant.
You have access to tool calling. When you need to use a tool, output a JSON function call in the following format:
<tool_call>
{"name": "function_name", "arguments": {"param": "value"}}
</tool_call>
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.
Always provide structured, accurate responses."""

39
Modelfile.timmy-creative Normal file
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@@ -0,0 +1,39 @@
# Modelfile.timmy-creative
#
# Dolphin 3.0-Llama3.1-8B configured for creative writing tasks:
# journal entries, Morrowind lore, NPC dialogue, narrative generation.
#
# Build: ollama create timmy-creative -f Modelfile.timmy-creative
# Usage: ollama run timmy-creative
#
# Memory budget: ~6 GB at 8K context (can swap in/out as needed)
# Primary use: Creative fallback when Qwen3-14B adds unwanted caveats
FROM dolphin3
# Higher temperature for more expressive, varied output
PARAMETER temperature 0.9
# Nucleus sampling — keeps output coherent while allowing creativity
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
PARAMETER num_ctx 8192
# 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.
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:
- 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."""

107
config/moderation.yaml Normal file
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@@ -0,0 +1,107 @@
# 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 ────────────────────────────────────────────────────────────
profiles:
morrowind:
display_name: "The Elder Scrolls III: Morrowind"
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."

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@@ -53,8 +53,60 @@ 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, 2550% faster than Ollama on Apple Silicon)
# Evaluation results (EuroMLSys '26 / M3 Ultra benchmarks):
# - 2187% 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
@@ -100,7 +152,8 @@ fallback_chains:
# Tool-calling models (for function calling)
tools:
- llama3.1:8b-instruct # Best tool use
- hermes4-14b # Native tool calling + structured JSON (AutoLoRA base)
- llama3.1:8b-instruct # Reliable tool use
- qwen2.5:7b # Reliable tools
- llama3.2:3b # Small but capable
@@ -112,6 +165,14 @@ 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.

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@@ -1,21 +0,0 @@
; ── Gitea Hardening — Security Overrides ─────────────────────────────────────
;
; Merge these settings into your Gitea custom/conf/app.ini.
;
; On a default Gitea install (Docker or bare-metal):
; /path/to/gitea/custom/conf/app.ini
;
; After editing, restart Gitea:
; systemctl restart gitea # bare-metal
; docker restart <gitea-container> # Docker
;
; See also: scripts/harden_gitea.sh (automated version)
[service]
; Disable public registration — only admins can create accounts
DISABLE_REGISTRATION = true
ALLOW_ONLY_EXTERNAL_REGISTRATION = false
SHOW_REGISTRATION_BUTTON = false
; Require sign-in to view any content (repos, explore, etc.)
REQUIRE_SIGNIN_VIEW = true

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@@ -0,0 +1,91 @@
# 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)

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# 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.

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# 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

195
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# 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` |

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# 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 # 0.02.0, 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: 515 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 48 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 | 515 s |
| Vassal | 4× per campaign day | 25 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.

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# 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 |

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@@ -50,6 +50,7 @@ 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 }
@@ -67,6 +68,7 @@ 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]

186
scripts/claude_quota_check.sh Executable file
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@@ -0,0 +1,186 @@
#!/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 "$usage"
;;
esac
}
main "$@"

83
scripts/gitea_backup.sh Executable file
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@@ -0,0 +1,83 @@
#!/bin/bash
# Gitea backup script — run on the VPS before any hardening changes.
# Usage: sudo bash scripts/gitea_backup.sh [off-site-dest]
#
# off-site-dest: optional rsync/scp destination for off-site copy
# e.g. user@backup-host:/backups/gitea/
#
# Refs: #971, #990
set -euo pipefail
BACKUP_DIR="/opt/gitea/backups"
TIMESTAMP=$(date +"%Y%m%d_%H%M%S")
GITEA_CONF="/etc/gitea/app.ini"
GITEA_WORK_DIR="/var/lib/gitea"
OFFSITE_DEST="${1:-}"
echo "=== Gitea Backup — $TIMESTAMP ==="
# Ensure backup directory exists
mkdir -p "$BACKUP_DIR"
cd "$BACKUP_DIR"
# Run the dump
echo "[1/4] Running gitea dump..."
gitea dump -c "$GITEA_CONF"
# Find the newest zip (gitea dump names it gitea-dump-*.zip)
BACKUP_FILE=$(ls -t "$BACKUP_DIR"/gitea-dump-*.zip 2>/dev/null | head -1)
if [ -z "$BACKUP_FILE" ]; then
echo "ERROR: No backup zip found in $BACKUP_DIR"
exit 1
fi
BACKUP_SIZE=$(stat -c%s "$BACKUP_FILE" 2>/dev/null || stat -f%z "$BACKUP_FILE")
echo "[2/4] Backup created: $BACKUP_FILE ($BACKUP_SIZE bytes)"
if [ "$BACKUP_SIZE" -eq 0 ]; then
echo "ERROR: Backup file is 0 bytes"
exit 1
fi
# Lock down permissions
chmod 600 "$BACKUP_FILE"
# Verify contents
echo "[3/4] Verifying backup contents..."
CONTENTS=$(unzip -l "$BACKUP_FILE" 2>/dev/null || true)
check_component() {
if echo "$CONTENTS" | grep -q "$1"; then
echo " OK: $2"
else
echo " WARN: $2 not found in backup"
fi
}
check_component "gitea-db.sql" "Database dump"
check_component "gitea-repo" "Repositories"
check_component "custom" "Custom config"
check_component "app.ini" "app.ini"
# Off-site copy
if [ -n "$OFFSITE_DEST" ]; then
echo "[4/4] Copying to off-site: $OFFSITE_DEST"
rsync -avz "$BACKUP_FILE" "$OFFSITE_DEST"
echo " Off-site copy complete."
else
echo "[4/4] No off-site destination provided. Skipping."
echo " To copy later: scp $BACKUP_FILE user@backup-host:/backups/gitea/"
fi
echo ""
echo "=== Backup complete ==="
echo "File: $BACKUP_FILE"
echo "Size: $BACKUP_SIZE bytes"
echo ""
echo "To verify restore on a clean instance:"
echo " 1. Copy zip to test machine"
echo " 2. unzip $BACKUP_FILE"
echo " 3. gitea restore --from <extracted-dir> -c /etc/gitea/app.ini"
echo " 4. Verify repos and DB are intact"

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@@ -1,169 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
# ── Gitea Hardening Script ──────────────────────────────────────────────────
#
# Disables public registration and requires sign-in to view content.
# Refs: Issue #988
#
# Usage (on the Gitea server):
# sudo bash scripts/harden_gitea.sh
# sudo bash scripts/harden_gitea.sh --config /path/to/custom/conf/app.ini
# sudo bash scripts/harden_gitea.sh --docker gitea # restart via docker
#
# What it does:
# 1. Patches [service] section in app.ini
# 2. Restarts Gitea so changes take effect
# 3. Verifies the changes are active
BOLD='\033[1m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
RED='\033[0;31m'
NC='\033[0m'
info() { echo -e "${GREEN}[+]${NC} $1"; }
warn() { echo -e "${YELLOW}[!]${NC} $1"; }
error() { echo -e "${RED}[x]${NC} $1"; }
# ── Defaults ────────────────────────────────────────────────────────────────
# Common Gitea config paths (checked in order)
SEARCH_PATHS=(
"/etc/gitea/app.ini"
"/opt/gitea/custom/conf/app.ini"
"/data/gitea/conf/app.ini"
"/app/gitea/conf/app.ini"
)
CONFIG_PATH=""
DOCKER_CONTAINER=""
SYSTEMD_SERVICE="gitea"
# ── Parse arguments ─────────────────────────────────────────────────────────
while [[ $# -gt 0 ]]; do
case $1 in
--config) CONFIG_PATH="$2"; shift 2 ;;
--docker) DOCKER_CONTAINER="$2"; shift 2 ;;
--service) SYSTEMD_SERVICE="$2"; shift 2 ;;
-h|--help)
echo "Usage: $0 [--config /path/to/app.ini] [--docker container] [--service name]"
exit 0
;;
*) error "Unknown option: $1"; exit 1 ;;
esac
done
# ── Find config ─────────────────────────────────────────────────────────────
if [ -z "$CONFIG_PATH" ]; then
for path in "${SEARCH_PATHS[@]}"; do
if [ -f "$path" ]; then
CONFIG_PATH="$path"
break
fi
done
fi
# If using Docker, try to find config inside the container
if [ -z "$CONFIG_PATH" ] && [ -n "$DOCKER_CONTAINER" ]; then
for path in "${SEARCH_PATHS[@]}"; do
if docker exec "$DOCKER_CONTAINER" test -f "$path" 2>/dev/null; then
CONFIG_PATH="$path"
info "Found config inside container at $path"
break
fi
done
fi
if [ -z "$CONFIG_PATH" ]; then
error "Could not find Gitea app.ini. Use --config to specify the path."
exit 1
fi
info "Using config: $CONFIG_PATH"
# ── Backup ──────────────────────────────────────────────────────────────────
BACKUP="${CONFIG_PATH}.bak.$(date +%Y%m%d%H%M%S)"
if [ -n "$DOCKER_CONTAINER" ]; then
docker exec "$DOCKER_CONTAINER" cp "$CONFIG_PATH" "$BACKUP"
else
cp "$CONFIG_PATH" "$BACKUP"
fi
info "Backup saved to $BACKUP"
# ── Apply settings ──────────────────────────────────────────────────────────
apply_setting() {
local key="$1"
local value="$2"
local file="$3"
if [ -n "$DOCKER_CONTAINER" ]; then
# Check if key exists (commented or not) and update, otherwise append to [service]
if docker exec "$DOCKER_CONTAINER" grep -qE "^;?\s*${key}\s*=" "$file" 2>/dev/null; then
docker exec "$DOCKER_CONTAINER" sed -i "s|^;*\s*${key}\s*=.*|${key} = ${value}|" "$file"
else
# Append after [service] section header
docker exec "$DOCKER_CONTAINER" sed -i "/^\[service\]/a ${key} = ${value}" "$file"
fi
else
if grep -qE "^;?\s*${key}\s*=" "$file" 2>/dev/null; then
sed -i "s|^;*\s*${key}\s*=.*|${key} = ${value}|" "$file"
else
# Ensure [service] section exists, then append
if ! grep -q '^\[service\]' "$file"; then
printf '\n[service]\n' >> "$file"
fi
sed -i "/^\[service\]/a ${key} = ${value}" "$file"
fi
fi
}
info "Applying hardening settings..."
apply_setting "DISABLE_REGISTRATION" "true" "$CONFIG_PATH"
apply_setting "ALLOW_ONLY_EXTERNAL_REGISTRATION" "false" "$CONFIG_PATH"
apply_setting "SHOW_REGISTRATION_BUTTON" "false" "$CONFIG_PATH"
apply_setting "REQUIRE_SIGNIN_VIEW" "true" "$CONFIG_PATH"
info "Settings applied:"
info " DISABLE_REGISTRATION = true"
info " ALLOW_ONLY_EXTERNAL_REGISTRATION = false"
info " SHOW_REGISTRATION_BUTTON = false"
info " REQUIRE_SIGNIN_VIEW = true"
# ── Restart Gitea ───────────────────────────────────────────────────────────
echo ""
if [ -n "$DOCKER_CONTAINER" ]; then
info "Restarting Gitea container: $DOCKER_CONTAINER"
docker restart "$DOCKER_CONTAINER"
elif systemctl is-active --quiet "$SYSTEMD_SERVICE" 2>/dev/null; then
info "Restarting Gitea via systemd: $SYSTEMD_SERVICE"
systemctl restart "$SYSTEMD_SERVICE"
else
warn "Could not detect Gitea service. Restart Gitea manually to apply changes."
fi
# ── Verify ──────────────────────────────────────────────────────────────────
echo ""
info "Verification — current [service] settings:"
if [ -n "$DOCKER_CONTAINER" ]; then
docker exec "$DOCKER_CONTAINER" grep -A 20 '^\[service\]' "$CONFIG_PATH" | head -25
else
grep -A 20 '^\[service\]' "$CONFIG_PATH" | head -25
fi
echo ""
echo -e "${GREEN}${BOLD} Gitea hardening complete.${NC}"
echo ""
echo " Registration: DISABLED"
echo " Sign-in required to view: YES"
echo ""
echo " Backup: $BACKUP"
echo ""

107
scripts/run_benchmarks.py Normal file
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@@ -0,0 +1,107 @@
#!/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()))

342
scripts/test_hermes4.py Normal file
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#!/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 25
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())

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---
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.

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---
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}

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---
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?

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---
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`)

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---
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?

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---
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.).

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"""Bannerlord campaign agent — M2: Basic Campaign Actions.
Provides GABS integration (TCP JSON-RPC, port 4825) and the observe →
decide → act loop for autonomous campaign play: move, trade, recruit,
and engage bandits.
Key GABS tools: party/move_to_settlement, inventory/buy_item,
party/recruit_all, party/engage_party.
Done-condition: party grows from 20 → 100 troops, gold reaches 10 000 denars.
"""

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"""Bannerlord M2 campaign action primitives.
Wraps the four key GABS tools for the M2 milestone:
- party/move_to_settlement → move the party to a named settlement
- inventory/buy_item → purchase trade goods
- party/recruit_all → hire all available recruits
- party/engage_party → engage a nearby bandit party
All functions are async and return an ``ActionResult`` that is compatible
with the ``WorldInterface`` contract.
Error handling follows Pattern 3 (Feature Disable): if GABS rejects an
action, log a warning and return a FAILURE result — never raise.
"""
from __future__ import annotations
import logging
from enum import StrEnum
from typing import TYPE_CHECKING
from infrastructure.world.types import ActionResult, ActionStatus
if TYPE_CHECKING:
from bannerlord.gabs_client import GabsClient
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# GABS method names — canonical reference
# ---------------------------------------------------------------------------
class GabsTool(StrEnum):
"""GABS JSON-RPC method names for the M2 action set."""
MOVE_TO_SETTLEMENT = "party/move_to_settlement"
BUY_ITEM = "inventory/buy_item"
RECRUIT_ALL = "party/recruit_all"
ENGAGE_PARTY = "party/engage_party"
# ---------------------------------------------------------------------------
# Action functions
# ---------------------------------------------------------------------------
async def move_to_settlement(
client: "GabsClient",
settlement_id: str,
*,
settlement_name: str = "",
) -> ActionResult:
"""Move the party to a target settlement.
Parameters
----------
client:
Connected ``GabsClient`` instance.
settlement_id:
GABS settlement identifier (e.g. ``"town_A1"``).
settlement_name:
Human-readable name for logging only.
"""
label = settlement_name or settlement_id
try:
result = await client.call(
GabsTool.MOVE_TO_SETTLEMENT,
{"settlement_id": settlement_id},
)
logger.info("MOVE → %s: %s", label, result)
return ActionResult(
status=ActionStatus.SUCCESS,
message=f"Moving to {label}",
data=result or {},
)
except Exception as exc: # noqa: BLE001
logger.warning("MOVE → %s failed: %s", label, exc)
return ActionResult(
status=ActionStatus.FAILURE,
message=f"Move to {label} failed: {exc}",
data={},
)
async def buy_item(
client: "GabsClient",
item_id: str,
quantity: int,
*,
settlement_id: str = "",
) -> ActionResult:
"""Purchase trade goods from the current or specified settlement.
Parameters
----------
client:
Connected ``GabsClient`` instance.
item_id:
Item identifier (e.g. ``"grain"``, ``"iron"``, ``"wool"``).
quantity:
Number of units to purchase.
settlement_id:
Optional target settlement; empty means current location.
"""
try:
params: dict = {"item_id": item_id, "quantity": quantity}
if settlement_id:
params["settlement_id"] = settlement_id
result = await client.call(GabsTool.BUY_ITEM, params)
logger.info("BUY %dx %s: %s", quantity, item_id, result)
return ActionResult(
status=ActionStatus.SUCCESS,
message=f"Purchased {quantity}x {item_id}",
data=result or {},
)
except Exception as exc: # noqa: BLE001
logger.warning("BUY %dx %s failed: %s", quantity, item_id, exc)
return ActionResult(
status=ActionStatus.FAILURE,
message=f"Buy {item_id} failed: {exc}",
data={},
)
async def recruit_all(
client: "GabsClient",
*,
settlement_id: str = "",
) -> ActionResult:
"""Recruit all available troops at the current or specified settlement.
Parameters
----------
client:
Connected ``GabsClient`` instance.
settlement_id:
Optional settlement to recruit from; empty means current.
"""
try:
params: dict = {}
if settlement_id:
params["settlement_id"] = settlement_id
result = await client.call(GabsTool.RECRUIT_ALL, params)
recruited = (result or {}).get("recruited", "?")
logger.info("RECRUIT_ALL: recruited %s troops", recruited)
return ActionResult(
status=ActionStatus.SUCCESS,
message=f"Recruited {recruited} troops",
data=result or {},
)
except Exception as exc: # noqa: BLE001
logger.warning("RECRUIT_ALL failed: %s", exc)
return ActionResult(
status=ActionStatus.FAILURE,
message=f"Recruit all failed: {exc}",
data={},
)
async def engage_party(
client: "GabsClient",
party_id: str,
*,
party_name: str = "",
) -> ActionResult:
"""Engage a nearby party (typically a bandit gang) in combat.
Auto-resolve is expected at high Tactics skill — the agent relies
on GABS to handle the battle outcome.
Parameters
----------
client:
Connected ``GabsClient`` instance.
party_id:
GABS party identifier of the target.
party_name:
Human-readable name for logging only.
"""
label = party_name or party_id
try:
result = await client.call(GabsTool.ENGAGE_PARTY, {"party_id": party_id})
outcome = (result or {}).get("outcome", "unknown")
logger.info("ENGAGE %s: %s", label, outcome)
return ActionResult(
status=ActionStatus.SUCCESS,
message=f"Engaged {label}: {outcome}",
data=result or {},
)
except Exception as exc: # noqa: BLE001
logger.warning("ENGAGE %s failed: %s", label, exc)
return ActionResult(
status=ActionStatus.FAILURE,
message=f"Engage {label} failed: {exc}",
data={},
)

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"""Bannerlord M2 campaign action loop.
Implements the observe → decide → act → wait pipeline described in
issue #1094. The loop runs until the M2 victory conditions are met
(100 troops + 10 000 gold) or until stopped externally.
Architecture:
CampaignLoop.run()
while not m2_complete:
state = gabs.get_game_state() # observe
decision = decide(state) # decide (local Qwen3)
result = dispatch(decision, gabs) # act (GABS)
await asyncio.sleep(tick_seconds) # wait
Error handling:
- GABS connection failures → log + retry with backoff (max 3 attempts)
- LLM failures → WAIT action (graceful degradation)
- Action failures → log + continue to next tick
Progress tracking:
Loop publishes heartbeat events via the event bus so the dashboard
can display live party size and gold.
"""
from __future__ import annotations
import asyncio
import logging
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime
from bannerlord.campaign_actions import buy_item, engage_party, move_to_settlement, recruit_all
from bannerlord.campaign_state import parse_campaign_state
from bannerlord.decision import M2Action, decide
from bannerlord.gabs_client import GabsClient
from config import settings
from infrastructure.world.types import ActionResult, ActionStatus
logger = logging.getLogger(__name__)
_MAX_RECONNECT_ATTEMPTS = 3
_RECONNECT_DELAY = 5.0 # seconds
# ---------------------------------------------------------------------------
# Progress snapshot (emitted each tick)
# ---------------------------------------------------------------------------
@dataclass
class TickResult:
"""Summary of one campaign tick."""
tick: int
timestamp: str
party_size: int
gold: int
action: str
action_status: str
reasoning: str
duration_ms: int
m2_complete: bool = False
error: str = ""
# ---------------------------------------------------------------------------
# Campaign loop
# ---------------------------------------------------------------------------
class CampaignLoop:
"""Runs the Bannerlord M2 autonomous campaign.
Parameters
----------
gabs_host:
Override GABS server host.
gabs_port:
Override GABS server port.
tick_seconds:
Real-time pause between in-game ticks.
on_tick:
Optional async callback invoked after each tick with the
``TickResult``. Used by the dashboard for live updates.
max_ticks:
Hard cap for testing / benchmarking. 0 = unlimited.
"""
def __init__(
self,
*,
gabs_host: str | None = None,
gabs_port: int | None = None,
tick_seconds: float | None = None,
on_tick=None,
max_ticks: int = 0,
) -> None:
self._host = gabs_host or settings.gabs_host
self._port = gabs_port or settings.gabs_port
self._tick_seconds = tick_seconds if tick_seconds is not None else settings.bannerlord_tick_seconds
self._on_tick = on_tick
self._max_ticks = max_ticks
self._running = False
self.history: list[TickResult] = []
# -- public API --------------------------------------------------------
@property
def is_running(self) -> bool:
return self._running
def stop(self) -> None:
"""Signal the loop to stop after the current tick."""
self._running = False
logger.info("CampaignLoop stop requested")
async def run(self) -> list[TickResult]:
"""Start the campaign loop.
Returns the list of tick results (for testing / benchmarking).
Runs until M2 complete, externally stopped, or max_ticks reached.
"""
self._running = True
logger.info(
"CampaignLoop starting — gabs=%s:%d tick=%.1fs",
self._host,
self._port,
self._tick_seconds,
)
client = GabsClient(host=self._host, port=self._port)
try:
await self._connect_with_retry(client)
except RuntimeError as exc: # noqa: BLE001
logger.error("CampaignLoop: could not connect to GABS — aborting: %s", exc)
self._running = False
return self.history
tick_num = 0
try:
while self._running:
tick_num += 1
if self._max_ticks > 0 and tick_num > self._max_ticks:
logger.info("CampaignLoop: max_ticks=%d reached", self._max_ticks)
break
result = await self._run_tick(client, tick_num)
self.history.append(result)
await self._emit(result)
if result.m2_complete:
logger.info(
"M2 COMPLETE! Party=%d troops, Gold=%d denars",
result.party_size,
result.gold,
)
break
if result.error and not self._running:
break
await asyncio.sleep(self._tick_seconds)
finally:
await client.disconnect()
self._running = False
logger.info("CampaignLoop stopped after %d ticks", tick_num)
return self.history
# -- internal: single tick ---------------------------------------------
async def _run_tick(self, client: "Any", tick_num: int) -> TickResult:
"""Execute one observe → decide → act cycle."""
start = time.monotonic()
# 1. Observe
raw_state = await client.get_game_state()
state = parse_campaign_state(raw_state)
state = _override_tick(state, tick_num)
# 2. Decide
decision = await decide(state)
# 3. Act
action_result = await self._dispatch(decision, client)
duration_ms = int((time.monotonic() - start) * 1000)
return TickResult(
tick=tick_num,
timestamp=datetime.now(UTC).isoformat(),
party_size=state.party.party_size,
gold=state.economy.gold,
action=decision.action,
action_status=action_result.status.value,
reasoning=decision.reasoning,
duration_ms=duration_ms,
m2_complete=state.m2_complete,
)
async def _dispatch(self, decision: "Any", client: "Any") -> "Any":
"""Route the decision to the correct GABS action function."""
action = decision.action
if action == M2Action.MOVE:
if not decision.settlement_id:
logger.warning("MOVE decision has no settlement_id — skipping")
return ActionResult(
status=ActionStatus.FAILURE,
message="MOVE missing settlement_id",
)
return await move_to_settlement(
client,
decision.settlement_id,
settlement_name=decision.settlement_name,
)
elif action == M2Action.TRADE:
if not decision.item_id:
logger.warning("TRADE decision has no item_id — skipping")
return ActionResult(
status=ActionStatus.FAILURE,
message="TRADE missing item_id",
)
return await buy_item(
client,
decision.item_id,
decision.quantity,
settlement_id=decision.settlement_id,
)
elif action == M2Action.RECRUIT:
return await recruit_all(
client,
settlement_id=decision.settlement_id,
)
elif action == M2Action.ENGAGE:
if not decision.party_id:
logger.warning("ENGAGE decision has no party_id — skipping")
return ActionResult(
status=ActionStatus.FAILURE,
message="ENGAGE missing party_id",
)
return await engage_party(
client,
decision.party_id,
party_name=decision.party_name,
)
else: # WAIT or unknown
logger.debug("Tick %s: WAIT — %s", decision.action, decision.reasoning)
return ActionResult(
status=ActionStatus.NOOP,
message=f"WAIT: {decision.reasoning}",
)
# -- internal: connectivity --------------------------------------------
async def _connect_with_retry(self, client: "Any") -> None:
"""Try to connect, retrying up to _MAX_RECONNECT_ATTEMPTS times."""
for attempt in range(1, _MAX_RECONNECT_ATTEMPTS + 1):
try:
await client.connect()
return
except Exception as exc: # noqa: BLE001
logger.warning(
"GABS connect attempt %d/%d failed: %s",
attempt,
_MAX_RECONNECT_ATTEMPTS,
exc,
)
if attempt < _MAX_RECONNECT_ATTEMPTS:
await asyncio.sleep(_RECONNECT_DELAY)
raise RuntimeError(
f"Could not connect to GABS at {self._host}:{self._port} "
f"after {_MAX_RECONNECT_ATTEMPTS} attempts"
)
# -- internal: event emission ------------------------------------------
async def _emit(self, result: TickResult) -> None:
"""Emit tick data to the event bus (best-effort)."""
try:
from infrastructure.events.bus import event_bus # noqa: PLC0415
await event_bus.publish(
"bannerlord.tick",
{
"tick": result.tick,
"party_size": result.party_size,
"gold": result.gold,
"action": result.action,
"action_status": result.action_status,
"m2_complete": result.m2_complete,
"duration_ms": result.duration_ms,
},
)
except Exception as exc: # noqa: BLE001
logger.debug("CampaignLoop emit skipped: %s", exc)
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _override_tick(state: "Any", tick_num: int) -> "Any":
"""Set the tick counter from the loop (GABS may not provide it)."""
if state.tick == 0:
state.tick = tick_num
return state

View File

@@ -0,0 +1,213 @@
"""Bannerlord campaign state models.
Parses the raw GABS ``game/get_state`` payload into typed models and
tracks the M2 progress counters: party size and gold accumulation.
Done-condition (from issue #1094):
party_size >= 100 AND gold >= 10_000
"""
from __future__ import annotations
import logging
from dataclasses import dataclass, field
from datetime import UTC, datetime
from typing import Any
logger = logging.getLogger(__name__)
# M2 victory conditions
M2_TROOP_GOAL = 100
M2_GOLD_GOAL = 10_000
@dataclass
class PartyState:
"""Current party composition and position."""
party_size: int = 0
wounded: int = 0
prisoners: int = 0
food_days: float = 0.0
morale: float = 100.0
current_settlement: str = ""
speed: float = 0.0
@dataclass
class EconomyState:
"""Current gold and trade state."""
gold: int = 0
daily_income: int = 0
daily_expenses: int = 0
@property
def net_income(self) -> int:
return self.daily_income - self.daily_expenses
@dataclass
class NearbyParty:
"""A nearby lord/bandit party visible on the map."""
party_id: str
name: str
faction: str
is_hostile: bool
troop_count: int
distance: float
@dataclass
class Settlement:
"""A settlement visible or reachable from the current position."""
settlement_id: str
name: str
faction: str
is_friendly: bool
distance: float
has_recruits: bool = False
has_trade_goods: bool = False
@dataclass
class CampaignState:
"""Full parsed snapshot of the GABS game state.
Built from the raw ``dict`` returned by ``GabsClient.get_game_state()``.
"""
tick: int = 0
timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
party: PartyState = field(default_factory=PartyState)
economy: EconomyState = field(default_factory=EconomyState)
nearby_parties: list[NearbyParty] = field(default_factory=list)
settlements: list[Settlement] = field(default_factory=list)
raw: dict[str, Any] = field(default_factory=dict)
# -- M2 progress -------------------------------------------------------
@property
def troops_progress(self) -> str:
"""Human-readable M2 troop progress."""
return f"{self.party.party_size}/{M2_TROOP_GOAL}"
@property
def gold_progress(self) -> str:
"""Human-readable M2 gold progress."""
return f"{self.economy.gold:,}/{M2_GOLD_GOAL:,}"
@property
def m2_complete(self) -> bool:
"""True when both M2 victory conditions are met."""
return self.party.party_size >= M2_TROOP_GOAL and self.economy.gold >= M2_GOLD_GOAL
# -- hostile detection -------------------------------------------------
def hostile_bandits_nearby(self, max_distance: float = 5.0) -> list[NearbyParty]:
"""Return hostile bandit parties within *max_distance* map units."""
return [
p
for p in self.nearby_parties
if p.is_hostile and "bandit" in p.faction.lower() and p.distance <= max_distance
]
def nearest_settlement(self, *, friendly_only: bool = False) -> Settlement | None:
"""Return the closest (optionally friendly) settlement."""
candidates = [s for s in self.settlements if not friendly_only or s.is_friendly]
if not candidates:
return None
return min(candidates, key=lambda s: s.distance)
def nearest_recruit_settlement(self) -> Settlement | None:
"""Return the nearest settlement that has recruits available."""
candidates = [s for s in self.settlements if s.has_recruits]
if not candidates:
return None
return min(candidates, key=lambda s: s.distance)
# ---------------------------------------------------------------------------
# Parser
# ---------------------------------------------------------------------------
def parse_campaign_state(raw: dict[str, Any]) -> CampaignState:
"""Build a ``CampaignState`` from the raw GABS state dict.
Unknown / missing fields are silently defaulted so the parser never
crashes when GABS returns partial data.
"""
if not raw:
logger.debug("parse_campaign_state: empty payload — returning default state")
return CampaignState(raw=raw)
# -- party -------------------------------------------------------------
party_raw = raw.get("party", {})
party = PartyState(
party_size=int(party_raw.get("size", 0)),
wounded=int(party_raw.get("wounded", 0)),
prisoners=int(party_raw.get("prisoners", 0)),
food_days=float(party_raw.get("food_days", 0.0)),
morale=float(party_raw.get("morale", 100.0)),
current_settlement=str(party_raw.get("current_settlement", "")),
speed=float(party_raw.get("speed", 0.0)),
)
# -- economy -----------------------------------------------------------
economy_raw = raw.get("economy", {})
economy = EconomyState(
gold=int(economy_raw.get("gold", 0)),
daily_income=int(economy_raw.get("daily_income", 0)),
daily_expenses=int(economy_raw.get("daily_expenses", 0)),
)
# -- nearby parties ----------------------------------------------------
nearby_parties = []
for p in raw.get("nearby_parties", []):
try:
if not isinstance(p, dict) or not p.get("id"):
logger.debug("Skipping malformed nearby_party entry: missing id")
continue
nearby_parties.append(
NearbyParty(
party_id=str(p.get("id", "")),
name=str(p.get("name", "")),
faction=str(p.get("faction", "")),
is_hostile=bool(p.get("is_hostile", False)),
troop_count=int(p.get("troop_count", 0)),
distance=float(p.get("distance", 999.0)),
)
)
except (KeyError, ValueError, TypeError, AttributeError) as exc:
logger.debug("Skipping malformed nearby_party entry: %s", exc)
# -- settlements -------------------------------------------------------
settlements = []
for s in raw.get("settlements", []):
try:
settlements.append(
Settlement(
settlement_id=str(s.get("id", "")),
name=str(s.get("name", "")),
faction=str(s.get("faction", "")),
is_friendly=bool(s.get("is_friendly", False)),
distance=float(s.get("distance", 999.0)),
has_recruits=bool(s.get("has_recruits", False)),
has_trade_goods=bool(s.get("has_trade_goods", False)),
)
)
except (KeyError, ValueError, TypeError, AttributeError) as exc:
logger.debug("Skipping malformed settlement entry: %s", exc)
return CampaignState(
tick=int(raw.get("tick", 0)),
timestamp=datetime.now(UTC),
party=party,
economy=economy,
nearby_parties=nearby_parties,
settlements=settlements,
raw=raw,
)

284
src/bannerlord/decision.py Normal file
View File

@@ -0,0 +1,284 @@
"""LLM-powered campaign decision engine for Bannerlord M2.
Builds a structured prompt from the current ``CampaignState`` and asks
the local Qwen3 model (via Ollama) to choose one action from the M2
action vocabulary. Returns a ``CampaignDecision`` pydantic model with
the chosen action and its parameters.
The decision model is intentionally simple for M2:
MOVE → move to a named settlement
TRADE → buy a trade item
RECRUIT → hire troops at current/nearby settlement
ENGAGE → fight a nearby bandit party
WAIT → idle (e.g. low food, waiting for morale to recover)
Qwen3 responds in JSON mode with temperature=0.1 for deterministic play.
"""
from __future__ import annotations
import json
import logging
from enum import StrEnum
from typing import Any
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Decision schema
# ---------------------------------------------------------------------------
class M2Action(StrEnum):
"""Vocabulary of actions available in the M2 milestone."""
MOVE = "MOVE"
TRADE = "TRADE"
RECRUIT = "RECRUIT"
ENGAGE = "ENGAGE"
WAIT = "WAIT"
class CampaignDecision:
"""Parsed LLM decision for one campaign tick.
Attributes
----------
action:
One of the ``M2Action`` values.
settlement_id:
Target settlement ID (for MOVE / RECRUIT / TRADE).
settlement_name:
Human-readable settlement name (for logging).
item_id:
Trade item to buy (for TRADE).
quantity:
Trade quantity (for TRADE).
party_id:
Target party ID (for ENGAGE).
party_name:
Human-readable party name (for ENGAGE / logging).
reasoning:
LLM's brief explanation of the choice.
"""
def __init__(
self,
action: M2Action = M2Action.WAIT,
*,
settlement_id: str = "",
settlement_name: str = "",
item_id: str = "",
quantity: int = 1,
party_id: str = "",
party_name: str = "",
reasoning: str = "",
) -> None:
self.action = action
self.settlement_id = settlement_id
self.settlement_name = settlement_name
self.item_id = item_id
self.quantity = quantity
self.party_id = party_id
self.party_name = party_name
self.reasoning = reasoning
def __repr__(self) -> str:
return (
f"CampaignDecision(action={self.action!r}, "
f"reasoning={self.reasoning[:60]!r})"
)
# ---------------------------------------------------------------------------
# Prompt builder
# ---------------------------------------------------------------------------
def build_decision_prompt(state: "Any") -> list[dict[str, str]]:
"""Return an OpenAI-style message list for the decision LLM.
Parameters
----------
state:
A ``CampaignState`` instance.
"""
# Build a compact context block
party = state.party
econ = state.economy
ctx_lines = [
f"Campaign tick: {state.tick}",
f"Party size: {party.party_size} troops ({party.wounded} wounded)",
f"Food: {party.food_days:.1f} days remaining",
f"Morale: {party.morale:.0f}/100",
f"Gold: {econ.gold:,} denars (net {econ.net_income:+d}/day)",
f"Current location: {party.current_settlement or 'travelling'}",
"",
"== M2 GOALS ==",
f"Troops: {state.troops_progress} (need 100)",
f"Gold: {state.gold_progress} (need 10,000)",
"",
]
# Nearby bandits
bandits = state.hostile_bandits_nearby()
if bandits:
ctx_lines.append("== NEARBY HOSTILE BANDITS ==")
for b in bandits[:3]:
ctx_lines.append(
f" - {b.name} (id={b.party_id}, {b.troop_count} troops, "
f"{b.distance:.1f} away)"
)
ctx_lines.append("")
# Settlements
settlements = state.settlements[:5]
if settlements:
ctx_lines.append("== REACHABLE SETTLEMENTS ==")
for s in settlements:
flags = []
if s.has_recruits:
flags.append("recruits")
if s.has_trade_goods:
flags.append("trade")
if not s.is_friendly:
flags.append("hostile-faction")
flag_str = f" [{', '.join(flags)}]" if flags else ""
ctx_lines.append(
f" - {s.name} (id={s.settlement_id}, "
f"{s.distance:.1f} away{flag_str})"
)
ctx_lines.append("")
context = "\n".join(ctx_lines)
system_prompt = (
"You are the campaign manager for Timmy, an autonomous Bannerlord agent. "
"Your job is to choose the single best action for this campaign tick. "
"Respond ONLY with a JSON object — no prose, no markdown fences.\n\n"
"JSON schema:\n"
'{\n'
' "action": "MOVE|TRADE|RECRUIT|ENGAGE|WAIT",\n'
' "settlement_id": "<id or empty>",\n'
' "settlement_name": "<name or empty>",\n'
' "item_id": "<item or empty>",\n'
' "quantity": <int>,\n'
' "party_id": "<id or empty>",\n'
' "party_name": "<name or empty>",\n'
' "reasoning": "<one sentence>"\n'
"}\n\n"
"Priority rules:\n"
"1. ENGAGE bandits only if they are weak (< 15 troops) and we have > 25 troops.\n"
"2. RECRUIT when a nearby settlement has recruits and party < 80 troops.\n"
"3. TRADE when gold < 5000 and a settlement has trade goods.\n"
"4. MOVE toward the nearest settlement with recruits or trade goods.\n"
"5. WAIT only if food < 1 day or morale < 40."
)
user_prompt = f"Current game state:\n\n{context}\nChoose the best action."
return [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
]
# ---------------------------------------------------------------------------
# Response parser
# ---------------------------------------------------------------------------
def parse_decision(raw_response: str) -> CampaignDecision:
"""Parse the LLM JSON response into a ``CampaignDecision``.
Falls back to ``WAIT`` on any parse error so the loop never crashes.
"""
# Strip accidental markdown code fences
text = raw_response.strip()
if text.startswith("```"):
lines = text.splitlines()
text = "\n".join(
line for line in lines if not line.startswith("```")
).strip()
try:
data = json.loads(text)
except json.JSONDecodeError as exc:
logger.warning("Decision parse error (bad JSON): %s | raw=%r", exc, raw_response[:200])
return CampaignDecision(action=M2Action.WAIT, reasoning="parse error")
try:
action_str = str(data.get("action", "WAIT")).upper()
try:
action = M2Action(action_str)
except ValueError:
logger.warning("Unknown action %r — defaulting to WAIT", action_str)
action = M2Action.WAIT
return CampaignDecision(
action=action,
settlement_id=str(data.get("settlement_id", "")),
settlement_name=str(data.get("settlement_name", "")),
item_id=str(data.get("item_id", "")),
quantity=max(1, int(data.get("quantity", 1))),
party_id=str(data.get("party_id", "")),
party_name=str(data.get("party_name", "")),
reasoning=str(data.get("reasoning", "")),
)
except (KeyError, ValueError, TypeError) as exc:
logger.warning("Decision parse error (bad fields): %s", exc)
return CampaignDecision(action=M2Action.WAIT, reasoning=f"field error: {exc}")
# ---------------------------------------------------------------------------
# Main entry point
# ---------------------------------------------------------------------------
async def decide(state: "Any") -> CampaignDecision:
"""Ask the local LLM to choose a campaign action.
Uses the cascade router (Ollama → Claude fallback) configured in
``config/providers.yaml``. Gracefully returns WAIT on any LLM failure.
Parameters
----------
state:
A ``CampaignState`` instance.
Returns
-------
CampaignDecision
The chosen action and its parameters.
"""
from config import settings
messages = build_decision_prompt(state)
model = settings.bannerlord_model
try:
from infrastructure.router import get_router
router = get_router()
response = await router.complete(
messages=messages,
model=model,
temperature=0.1,
)
raw_text: str = response.get("content", "")
decision = parse_decision(raw_text)
logger.info(
"Decision [tick=%d]: %s%s",
state.tick,
decision.action,
decision.reasoning,
)
return decision
except Exception as exc: # noqa: BLE001
logger.warning("Decision LLM call failed: %s — defaulting to WAIT", exc)
return CampaignDecision(
action=M2Action.WAIT,
reasoning=f"LLM unavailable: {exc}",
)

View File

@@ -0,0 +1,195 @@
"""GABS TCP/JSON-RPC client for Bannerlord.
Connects to the GABS C# mod (Bannerlord.GABS) over TCP on port 4825
and dispatches JSON-RPC 2.0 requests. All I/O is async; synchronous
callers must wrap in ``asyncio.to_thread()``.
Architecture:
Bannerlord (Windows VM) ← GABS C# mod ← TCP:4825 ← this client
Usage::
async with GabsClient() as client:
state = await client.get_game_state()
result = await client.call("party/move_to_settlement",
{"settlement_id": "town_A1"})
"""
from __future__ import annotations
import asyncio
import json
import logging
from typing import Any
from config import settings
logger = logging.getLogger(__name__)
# JSON-RPC framing: each message is newline-delimited UTF-8 JSON.
_ENCODING = "utf-8"
_NEWLINE = b"\n"
_DEFAULT_TIMEOUT = 30.0
class GabsError(Exception):
"""Raised when GABS returns a JSON-RPC error response."""
def __init__(self, code: int, message: str, data: Any = None) -> None:
super().__init__(f"GABS error {code}: {message}")
self.code = code
self.data = data
class GabsClient:
"""Async TCP JSON-RPC 2.0 client for the GABS Bannerlord mod.
Parameters
----------
host:
GABS server host (Windows VM IP or ``localhost`` for port-forwarded).
port:
GABS server port (default 4825).
timeout:
Per-call timeout in seconds.
"""
def __init__(
self,
*,
host: str | None = None,
port: int | None = None,
timeout: float = _DEFAULT_TIMEOUT,
) -> None:
self._host = host or settings.gabs_host
self._port = port or settings.gabs_port
self._timeout = timeout
self._reader: asyncio.StreamReader | None = None
self._writer: asyncio.StreamWriter | None = None
self._req_id = 0
self._connected = False
# -- lifecycle ---------------------------------------------------------
async def connect(self) -> None:
"""Open the TCP connection to GABS."""
try:
self._reader, self._writer = await asyncio.wait_for(
asyncio.open_connection(self._host, self._port),
timeout=self._timeout,
)
self._connected = True
logger.info("GabsClient connected to %s:%d", self._host, self._port)
except (OSError, asyncio.TimeoutError) as exc:
logger.warning("GabsClient could not connect to GABS: %s", exc)
self._connected = False
raise
async def disconnect(self) -> None:
"""Close the TCP connection."""
if self._writer is not None:
try:
self._writer.close()
await self._writer.wait_closed()
except Exception as exc: # noqa: BLE001
logger.debug("GabsClient disconnect error (ignored): %s", exc)
self._connected = False
self._reader = None
self._writer = None
logger.info("GabsClient disconnected")
@property
def is_connected(self) -> bool:
return self._connected
# -- context manager ---------------------------------------------------
async def __aenter__(self) -> "GabsClient":
await self.connect()
return self
async def __aexit__(self, *_: Any) -> None:
await self.disconnect()
# -- public API --------------------------------------------------------
async def call(self, method: str, params: dict[str, Any] | None = None) -> Any:
"""Call a GABS tool and return the result.
Parameters
----------
method:
GABS tool name, e.g. ``"party/move_to_settlement"``.
params:
Tool parameters dict.
Returns
-------
Any
The ``result`` field from the JSON-RPC response.
Raises
------
GabsError
If GABS returns an error response.
RuntimeError
If not connected.
"""
if not self._connected or self._writer is None or self._reader is None:
raise RuntimeError("GabsClient is not connected — call connect() first")
self._req_id += 1
request = {
"jsonrpc": "2.0",
"id": self._req_id,
"method": method,
"params": params or {},
}
raw = json.dumps(request).encode(_ENCODING) + _NEWLINE
try:
self._writer.write(raw)
await asyncio.wait_for(self._writer.drain(), timeout=self._timeout)
line = await asyncio.wait_for(
self._reader.readline(), timeout=self._timeout
)
except asyncio.TimeoutError as exc:
raise RuntimeError(f"GABS call '{method}' timed out after {self._timeout}s") from exc
except (OSError, ConnectionResetError) as exc:
self._connected = False
raise RuntimeError(f"GABS connection lost during '{method}': {exc}") from exc
response = json.loads(line.decode(_ENCODING))
if "error" in response:
err = response["error"]
raise GabsError(
code=err.get("code", -1),
message=err.get("message", "unknown error"),
data=err.get("data"),
)
return response.get("result")
async def get_game_state(self) -> dict[str, Any]:
"""Return the full game state snapshot from GABS.
Returns an empty dict and logs a warning if GABS is unreachable.
"""
try:
result = await self.call("game/get_state")
return result if isinstance(result, dict) else {}
except (GabsError, RuntimeError) as exc:
logger.warning("GABS get_game_state failed: %s", exc)
return {}
async def ping(self) -> bool:
"""Return True if GABS responds to a ping."""
try:
await self.call("game/ping")
return True
except Exception as exc: # noqa: BLE001
logger.debug("GABS ping failed: %s", exc)
return False

View File

@@ -99,6 +99,14 @@ 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,
@@ -144,6 +152,10 @@ 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] = [
@@ -290,6 +302,7 @@ 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.
@@ -361,6 +374,17 @@ class Settings(BaseSettings):
error_feedback_enabled: bool = True # Auto-create bug report tasks
error_dedup_window_seconds: int = 300 # 5-min dedup window
# ── Bannerlord / GABS ─────────────────────────────────────────────
# GABS (Bannerlord Agent Bridge System) TCP/JSON-RPC server.
# Runs inside the Windows VM hosting Bannerlord.
# Override with GABS_HOST / GABS_PORT env vars.
gabs_host: str = "localhost"
gabs_port: int = 4825
# Decision model for the Bannerlord campaign agent (Qwen3 preferred).
bannerlord_model: str = "qwen3:14b"
# Campaign-tick interval in seconds (real-time pause between in-game days).
bannerlord_tick_seconds: float = 5.0
# ── Scripture / Biblical Integration ──────────────────────────────
# Enable the biblical text module.
scripture_enabled: bool = True

View File

@@ -45,6 +45,7 @@ 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
@@ -374,13 +375,21 @@ def _startup_init() -> None:
def _startup_background_tasks() -> list[asyncio.Task]:
"""Spawn all recurring background tasks (non-blocking)."""
return [
bg_tasks = [
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:
@@ -631,6 +640,7 @@ 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")

View File

@@ -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, 100)
sats = min(settings.grok_max_sats_per_query, settings.grok_sats_hard_cap)
ln.create_invoice(sats, f"Grok: {message[:50]}")
invoice_note = f" | {sats} sats"
except Exception as exc:

View File

@@ -0,0 +1,74 @@
"""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}

View File

@@ -143,64 +143,49 @@ 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."""
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))
return _render_task_list(
request,
"SELECT * FROM tasks WHERE status='pending_approval' ORDER BY created_at DESC",
"No pending tasks",
)
@router.get("/tasks/active", response_class=HTMLResponse)
async def tasks_active(request: Request):
"""Return HTMX partial for active (approved/running/paused) 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))
return _render_task_list(
request,
"SELECT * FROM tasks WHERE status IN ('approved','running','paused') ORDER BY created_at DESC",
"No active tasks",
)
@router.get("/tasks/completed", response_class=HTMLResponse)
async def tasks_completed(request: Request):
"""Return HTMX partial for completed/vetoed/failed tasks (last 50)."""
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))
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",
)
# ---------------------------------------------------------------------------

View File

@@ -179,6 +179,13 @@
</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">

View File

@@ -0,0 +1,63 @@
{# 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>

View File

@@ -0,0 +1,264 @@
"""
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

View File

@@ -0,0 +1,7 @@
"""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
"""

View File

@@ -0,0 +1,497 @@
"""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

View File

@@ -0,0 +1,56 @@
"""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

View File

@@ -32,6 +32,15 @@ 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."""
@@ -301,6 +310,22 @@ 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 != ""
@@ -457,6 +482,25 @@ 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:
@@ -510,6 +554,15 @@ 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:
@@ -582,6 +635,14 @@ 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}")
@@ -778,6 +839,48 @@ 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

View File

@@ -0,0 +1,306 @@
"""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 {})},
)

View File

@@ -0,0 +1,234 @@
"""Bannerlord world adapter — bridges GABS to the WorldInterface contract.
Allows the existing ``Heartbeat`` loop to drive the Bannerlord campaign
by treating it as just another game world. Wraps the async ``GabsClient``
for synchronous use (the ``Heartbeat`` calls ``observe()`` and ``act()``
synchronously).
Async callers should use ``CampaignLoop`` directly — it is more efficient
and handles the full M2 logic natively.
Usage::
adapter = BannerlordWorldAdapter()
adapter.connect()
heartbeat = Heartbeat(world=adapter, interval=5.0)
await heartbeat.run_once()
adapter.disconnect()
"""
from __future__ import annotations
import asyncio
import logging
from infrastructure.world.interface import WorldInterface
from infrastructure.world.types import (
ActionResult,
ActionStatus,
CommandInput,
PerceptionOutput,
)
logger = logging.getLogger(__name__)
class BannerlordWorldAdapter(WorldInterface):
"""WorldInterface adapter for Bannerlord via GABS.
Wraps ``GabsClient`` and ``CampaignState`` to present the Bannerlord
campaign map as a ``WorldInterface``-compatible world.
Parameters
----------
host:
Override GABS server host (defaults to ``settings.gabs_host``).
port:
Override GABS server port (defaults to ``settings.gabs_port``).
"""
def __init__(
self,
*,
host: str | None = None,
port: int | None = None,
) -> None:
from config import settings
self._host = host or settings.gabs_host
self._port = port or settings.gabs_port
self._connected = False
self._client = None
self._loop: asyncio.AbstractEventLoop | None = None
# -- lifecycle ---------------------------------------------------------
def connect(self) -> None:
"""Open the GABS TCP connection (synchronous wrapper)."""
from bannerlord.gabs_client import GabsClient
self._client = GabsClient(host=self._host, port=self._port)
try:
self._loop = asyncio.get_event_loop()
except RuntimeError:
self._loop = asyncio.new_event_loop()
asyncio.set_event_loop(self._loop)
try:
self._loop.run_until_complete(self._client.connect())
self._connected = True
logger.info("BannerlordWorldAdapter connected to GABS")
except Exception as exc: # noqa: BLE001
logger.warning("BannerlordWorldAdapter: GABS connect failed: %s", exc)
self._connected = False
def disconnect(self) -> None:
"""Close the GABS TCP connection (synchronous wrapper)."""
if self._client is not None and self._loop is not None:
try:
self._loop.run_until_complete(self._client.disconnect())
except Exception as exc: # noqa: BLE001
logger.debug("BannerlordWorldAdapter disconnect error: %s", exc)
self._connected = False
@property
def is_connected(self) -> bool:
return self._connected
# -- core contract -----------------------------------------------------
def observe(self) -> PerceptionOutput:
"""Poll GABS for current game state and return structured perception."""
from bannerlord.campaign_state import parse_campaign_state
if not self._connected or self._client is None or self._loop is None:
return PerceptionOutput(
location="disconnected",
entities=[],
events=["gabs_disconnected"],
raw={"error": "GABS not connected"},
)
try:
raw = self._loop.run_until_complete(self._client.get_game_state())
state = parse_campaign_state(raw)
# Build entities list from settlements and nearby parties
entities: list[str] = []
for s in state.settlements[:5]:
entities.append(f"settlement:{s.name}")
for p in state.nearby_parties[:3]:
prefix = "hostile" if p.is_hostile else "friendly"
entities.append(f"{prefix}_party:{p.name}")
# Build events list
events: list[str] = []
if state.party.food_days < 2.0:
events.append("low_food")
if state.party.morale < 40:
events.append("low_morale")
if state.hostile_bandits_nearby():
events.append("bandits_nearby")
if state.m2_complete:
events.append("m2_complete")
location = state.party.current_settlement or "campaign_map"
return PerceptionOutput(
location=location,
entities=entities,
events=events,
raw=raw,
)
except Exception as exc: # noqa: BLE001
logger.warning("BannerlordWorldAdapter.observe() failed: %s", exc)
return PerceptionOutput(
location="unknown",
entities=[],
events=[f"observe_error:{exc}"],
raw={"error": str(exc)},
)
def act(self, command: CommandInput) -> ActionResult:
"""Dispatch a campaign command to GABS.
Recognized ``command.action`` values:
- ``"move"`` → party/move_to_settlement (target = settlement_id)
- ``"trade"`` → inventory/buy_item (target = item_id)
- ``"recruit"`` → party/recruit_all
- ``"engage"`` → party/engage_party (target = party_id)
Parameters
----------
command:
WorldInterface ``CommandInput`` with action, target, parameters.
"""
if not self._connected or self._client is None or self._loop is None:
return ActionResult(
status=ActionStatus.FAILURE,
message="GABS not connected",
)
try:
return self._loop.run_until_complete(self._async_act(command))
except Exception as exc: # noqa: BLE001
logger.warning("BannerlordWorldAdapter.act() failed: %s", exc)
return ActionResult(
status=ActionStatus.FAILURE,
message=f"act failed: {exc}",
)
async def _async_act(self, command: CommandInput) -> ActionResult:
"""Async implementation of act()."""
from bannerlord.campaign_actions import (
buy_item,
engage_party,
move_to_settlement,
recruit_all,
)
action = command.action.lower()
params = command.parameters
if action == "move":
settlement_id = command.target or params.get("settlement_id", "")
return await move_to_settlement(
self._client,
settlement_id,
settlement_name=params.get("settlement_name", ""),
)
elif action == "trade":
item_id = command.target or params.get("item_id", "")
quantity = int(params.get("quantity", 1))
return await buy_item(
self._client,
item_id,
quantity,
settlement_id=params.get("settlement_id", ""),
)
elif action == "recruit":
return await recruit_all(
self._client,
settlement_id=params.get("settlement_id", ""),
)
elif action == "engage":
party_id = command.target or params.get("party_id", "")
return await engage_party(
self._client,
party_id,
party_name=params.get("party_name", ""),
)
else:
return ActionResult(
status=ActionStatus.NOOP,
message=f"Unknown action: {command.action}",
)
def speak(self, message: str, target: str | None = None) -> None:
"""Log the message — GABS has no chat mechanism in M2."""
logger.info("BannerlordWorldAdapter.speak: %r (target=%r)", message, target)

View File

@@ -0,0 +1,17 @@
"""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",
]

View File

@@ -0,0 +1,195 @@
"""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)

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@@ -0,0 +1,167 @@
"""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 ""

View File

@@ -0,0 +1,160 @@
"""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)]

View File

@@ -215,6 +215,119 @@ 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
# ---------------------------------------------------------------------------
@@ -265,65 +378,9 @@ async def run_agentic_loop(
)
# Phase 2: Execution
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")
await _execute_all_steps(
agent, task, task_id, steps, total_steps, session_id, result, on_progress
)
# Phase 3: Summary
_summarize(result, total_steps, was_truncated)

View File

@@ -0,0 +1,488 @@
"""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)

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src/timmy/mcp_bridge.py Normal file
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"""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,
}

175
src/timmy/paperclip.py Normal file
View File

@@ -0,0 +1,175 @@
"""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())

View File

@@ -0,0 +1,42 @@
"""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()

View File

@@ -0,0 +1,367 @@
"""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

View File

@@ -473,6 +473,69 @@ 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
@@ -672,6 +735,7 @@ 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)
@@ -829,6 +893,11 @@ 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"],
},
}

View File

@@ -14,10 +14,17 @@ 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(100, "--price", help="Price per request in sats"),
price: int = typer.Option(
None, "--price", help="Price per request in sats (default: from config)"
),
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")

View File

View File

@@ -0,0 +1,102 @@
"""Unit tests for bannerlord.campaign_actions."""
from __future__ import annotations
from unittest.mock import AsyncMock, MagicMock
import pytest
from bannerlord.campaign_actions import (
GabsTool,
buy_item,
engage_party,
move_to_settlement,
recruit_all,
)
from infrastructure.world.types import ActionStatus
def _mock_client(return_value=None, raise_exc=None):
"""Build a mock GabsClient."""
client = MagicMock()
if raise_exc is not None:
client.call = AsyncMock(side_effect=raise_exc)
else:
client.call = AsyncMock(return_value=return_value)
return client
class TestMoveToSettlement:
async def test_success(self):
client = _mock_client({"eta_days": 2})
result = await move_to_settlement(client, "town_A1", settlement_name="Marunath")
assert result.status == ActionStatus.SUCCESS
client.call.assert_called_once_with(
GabsTool.MOVE_TO_SETTLEMENT, {"settlement_id": "town_A1"}
)
async def test_failure_on_gabs_error(self):
client = _mock_client(raise_exc=RuntimeError("GABS timeout"))
result = await move_to_settlement(client, "town_A1")
assert result.status == ActionStatus.FAILURE
assert "GABS timeout" in result.message
async def test_uses_settlement_id_as_label_when_no_name(self):
client = _mock_client({})
result = await move_to_settlement(client, "town_B2")
assert result.status == ActionStatus.SUCCESS
assert "town_B2" in result.message
class TestBuyItem:
async def test_success(self):
client = _mock_client({"cost": 100})
result = await buy_item(client, "grain", 5)
assert result.status == ActionStatus.SUCCESS
assert "grain" in result.message
client.call.assert_called_once_with(
GabsTool.BUY_ITEM, {"item_id": "grain", "quantity": 5}
)
async def test_includes_settlement_id_when_given(self):
client = _mock_client({})
await buy_item(client, "iron", 2, settlement_id="town_A1")
call_params = client.call.call_args[0][1]
assert call_params["settlement_id"] == "town_A1"
async def test_failure_logged_gracefully(self):
client = _mock_client(raise_exc=Exception("inventory full"))
result = await buy_item(client, "wool", 10)
assert result.status == ActionStatus.FAILURE
class TestRecruitAll:
async def test_success(self):
client = _mock_client({"recruited": 15})
result = await recruit_all(client)
assert result.status == ActionStatus.SUCCESS
assert "15" in result.message
async def test_success_with_settlement(self):
client = _mock_client({"recruited": 8})
result = await recruit_all(client, settlement_id="town_A1")
call_params = client.call.call_args[0][1]
assert call_params["settlement_id"] == "town_A1"
async def test_failure_graceful(self):
client = _mock_client(raise_exc=RuntimeError("no recruits"))
result = await recruit_all(client)
assert result.status == ActionStatus.FAILURE
class TestEngageParty:
async def test_success(self):
client = _mock_client({"outcome": "victory", "loot": 200})
result = await engage_party(client, "bandit_1", party_name="Forest Bandits")
assert result.status == ActionStatus.SUCCESS
assert "victory" in result.message
async def test_failure_graceful(self):
client = _mock_client(raise_exc=RuntimeError("party not found"))
result = await engage_party(client, "bandit_1")
assert result.status == ActionStatus.FAILURE

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@@ -0,0 +1,200 @@
"""Unit tests for bannerlord.campaign_loop."""
from __future__ import annotations
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from bannerlord.campaign_loop import CampaignLoop, TickResult
from bannerlord.decision import CampaignDecision, M2Action
from infrastructure.world.types import ActionResult, ActionStatus
def _make_game_state(*, troops: int = 30, gold: int = 2000) -> dict:
return {
"tick": 0,
"party": {
"size": troops,
"wounded": 0,
"food_days": 5.0,
"morale": 80.0,
"current_settlement": "town_A1",
},
"economy": {"gold": gold, "daily_income": 200, "daily_expenses": 150},
"nearby_parties": [],
"settlements": [
{
"id": "town_A1",
"name": "Marunath",
"faction": "aserai",
"is_friendly": True,
"distance": 0.0,
"has_recruits": True,
"has_trade_goods": False,
}
],
}
class TestCampaignLoopDispatch:
"""Tests for the internal _dispatch() routing."""
def _loop(self) -> CampaignLoop:
return CampaignLoop(tick_seconds=0.0, max_ticks=1)
async def test_dispatch_move(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(
action=M2Action.MOVE,
settlement_id="town_A1",
settlement_name="Marunath",
)
with patch("bannerlord.campaign_loop.move_to_settlement", new_callable=AsyncMock) as mock_move:
mock_move.return_value = ActionResult(status=ActionStatus.SUCCESS, message="ok")
await loop._dispatch(decision, client)
mock_move.assert_called_once_with(client, "town_A1", settlement_name="Marunath")
async def test_dispatch_recruit(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(
action=M2Action.RECRUIT,
settlement_id="town_A1",
)
with patch("bannerlord.campaign_loop.recruit_all", new_callable=AsyncMock) as mock_recruit:
mock_recruit.return_value = ActionResult(status=ActionStatus.SUCCESS, message="15 recruited")
await loop._dispatch(decision, client)
mock_recruit.assert_called_once()
async def test_dispatch_engage(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(
action=M2Action.ENGAGE,
party_id="bandit_1",
party_name="Forest Bandits",
)
with patch("bannerlord.campaign_loop.engage_party", new_callable=AsyncMock) as mock_engage:
mock_engage.return_value = ActionResult(status=ActionStatus.SUCCESS, message="victory")
await loop._dispatch(decision, client)
mock_engage.assert_called_once_with(client, "bandit_1", party_name="Forest Bandits")
async def test_dispatch_trade(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(
action=M2Action.TRADE,
item_id="grain",
quantity=5,
)
with patch("bannerlord.campaign_loop.buy_item", new_callable=AsyncMock) as mock_buy:
mock_buy.return_value = ActionResult(status=ActionStatus.SUCCESS, message="bought")
await loop._dispatch(decision, client)
mock_buy.assert_called_once_with(client, "grain", 5, settlement_id="")
async def test_dispatch_wait_returns_noop(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(action=M2Action.WAIT, reasoning="low food")
result = await loop._dispatch(decision, client)
assert result.status == ActionStatus.NOOP
async def test_dispatch_move_missing_settlement_id(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(action=M2Action.MOVE, settlement_id="")
result = await loop._dispatch(decision, client)
assert result.status == ActionStatus.FAILURE
async def test_dispatch_engage_missing_party_id(self):
loop = self._loop()
client = MagicMock()
decision = CampaignDecision(action=M2Action.ENGAGE, party_id="")
result = await loop._dispatch(decision, client)
assert result.status == ActionStatus.FAILURE
class TestCampaignLoopRun:
"""Integration-level tests for the full run() loop (mocked GABS)."""
async def test_run_stops_at_max_ticks(self):
"""Loop respects max_ticks and returns correct number of results."""
game_state = _make_game_state()
with (
patch("bannerlord.campaign_loop.GabsClient") as MockClient,
patch("bannerlord.campaign_loop.decide", new_callable=AsyncMock) as mock_decide,
patch("bannerlord.campaign_loop.move_to_settlement", new_callable=AsyncMock) as mock_move,
):
# Setup fake client
fake_client = AsyncMock()
fake_client.get_game_state = AsyncMock(return_value=game_state)
fake_client.connect = AsyncMock()
fake_client.disconnect = AsyncMock()
MockClient.return_value = fake_client
mock_decide.return_value = CampaignDecision(
action=M2Action.MOVE,
settlement_id="town_B1",
settlement_name="Epicrotea",
reasoning="moving",
)
mock_move.return_value = ActionResult(status=ActionStatus.SUCCESS, message="ok")
loop = CampaignLoop(tick_seconds=0.0, max_ticks=3)
results = await loop.run()
assert len(results) == 3
assert all(isinstance(r, TickResult) for r in results)
async def test_run_stops_when_m2_complete(self):
"""Loop exits early when M2 conditions are met."""
# State with M2 already complete
game_state = _make_game_state(troops=100, gold=10000)
with (
patch("bannerlord.campaign_loop.GabsClient") as MockClient,
patch("bannerlord.campaign_loop.decide", new_callable=AsyncMock) as mock_decide,
):
fake_client = AsyncMock()
fake_client.get_game_state = AsyncMock(return_value=game_state)
fake_client.connect = AsyncMock()
fake_client.disconnect = AsyncMock()
MockClient.return_value = fake_client
mock_decide.return_value = CampaignDecision(
action=M2Action.WAIT,
reasoning="done",
)
loop = CampaignLoop(tick_seconds=0.0, max_ticks=10)
results = await loop.run()
# Should exit after first tick (m2_complete = True)
assert len(results) == 1
assert results[0].m2_complete is True
async def test_run_aborts_on_connect_failure(self):
"""Loop returns empty history if GABS cannot be reached."""
with patch("bannerlord.campaign_loop.GabsClient") as MockClient:
fake_client = AsyncMock()
fake_client.connect = AsyncMock(side_effect=OSError("refused"))
fake_client.disconnect = AsyncMock()
MockClient.return_value = fake_client
loop = CampaignLoop(tick_seconds=0.0, max_ticks=5)
results = await loop.run()
assert results == []
def test_stop_sets_running_false(self):
loop = CampaignLoop()
loop._running = True
loop.stop()
assert not loop.is_running

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@@ -0,0 +1,150 @@
"""Unit tests for bannerlord.campaign_state."""
from __future__ import annotations
import pytest
from bannerlord.campaign_state import (
M2_GOLD_GOAL,
M2_TROOP_GOAL,
CampaignState,
NearbyParty,
Settlement,
parse_campaign_state,
)
class TestParseCampaignState:
def test_empty_dict_returns_defaults(self):
state = parse_campaign_state({})
assert state.party.party_size == 0
assert state.economy.gold == 0
assert state.nearby_parties == []
assert state.settlements == []
def test_full_payload_parsed(self):
raw = {
"tick": 5,
"party": {
"size": 30,
"wounded": 2,
"prisoners": 1,
"food_days": 3.5,
"morale": 75.0,
"current_settlement": "town_A1",
"speed": 5.2,
},
"economy": {
"gold": 4500,
"daily_income": 200,
"daily_expenses": 150,
},
"nearby_parties": [
{
"id": "bandit_1",
"name": "Forest Bandits",
"faction": "bandit",
"is_hostile": True,
"troop_count": 10,
"distance": 3.0,
}
],
"settlements": [
{
"id": "town_A1",
"name": "Marunath",
"faction": "aserai",
"is_friendly": True,
"distance": 0.0,
"has_recruits": True,
"has_trade_goods": False,
}
],
}
state = parse_campaign_state(raw)
assert state.tick == 5
assert state.party.party_size == 30
assert state.party.wounded == 2
assert state.economy.gold == 4500
assert state.economy.net_income == 50
assert len(state.nearby_parties) == 1
assert state.nearby_parties[0].name == "Forest Bandits"
assert len(state.settlements) == 1
assert state.settlements[0].name == "Marunath"
def test_malformed_entries_skipped(self):
raw = {
"nearby_parties": [{"id": "ok", "name": "Good", "faction": "bandit",
"is_hostile": True, "troop_count": 5, "distance": 2.0},
{"bad": "data"}],
"settlements": [None, "not_a_dict"],
}
state = parse_campaign_state(raw)
assert len(state.nearby_parties) == 1
assert state.settlements == []
class TestCampaignStateProperties:
def _make_state(self, *, troops: int, gold: int) -> CampaignState:
state = CampaignState()
state.party.party_size = troops
state.economy.gold = gold
return state
def test_m2_not_complete_by_default(self):
state = self._make_state(troops=20, gold=0)
assert not state.m2_complete
def test_m2_complete_when_both_goals_met(self):
state = self._make_state(troops=M2_TROOP_GOAL, gold=M2_GOLD_GOAL)
assert state.m2_complete
def test_m2_not_complete_if_only_troops_met(self):
state = self._make_state(troops=M2_TROOP_GOAL, gold=M2_GOLD_GOAL - 1)
assert not state.m2_complete
def test_m2_not_complete_if_only_gold_met(self):
state = self._make_state(troops=M2_TROOP_GOAL - 1, gold=M2_GOLD_GOAL)
assert not state.m2_complete
def test_troops_progress_string(self):
state = self._make_state(troops=45, gold=0)
assert state.troops_progress == f"45/{M2_TROOP_GOAL}"
def test_gold_progress_string(self):
state = self._make_state(troops=0, gold=3000)
assert "3,000" in state.gold_progress
def test_hostile_bandits_nearby_filter(self):
state = CampaignState()
state.nearby_parties = [
NearbyParty("b1", "Bandits", "bandit", True, 10, 2.0),
NearbyParty("l1", "Lord", "empire", False, 50, 1.0),
NearbyParty("b2", "Far Bandits", "bandit", True, 5, 10.0),
]
nearby = state.hostile_bandits_nearby(max_distance=5.0)
assert len(nearby) == 1
assert nearby[0].party_id == "b1"
def test_nearest_settlement_returns_closest(self):
state = CampaignState()
state.settlements = [
Settlement("s1", "Far Town", "empire", True, 10.0),
Settlement("s2", "Near Town", "empire", True, 2.0),
]
nearest = state.nearest_settlement()
assert nearest.settlement_id == "s2"
def test_nearest_recruit_settlement(self):
state = CampaignState()
state.settlements = [
Settlement("s1", "Town A", "empire", True, 5.0, has_recruits=False),
Settlement("s2", "Town B", "empire", True, 8.0, has_recruits=True),
]
recruit = state.nearest_recruit_settlement()
assert recruit.settlement_id == "s2"
def test_nearest_settlement_none_when_empty(self):
state = CampaignState()
assert state.nearest_settlement() is None

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@@ -0,0 +1,154 @@
"""Unit tests for bannerlord.decision."""
from __future__ import annotations
import json
import pytest
from bannerlord.campaign_state import (
CampaignState,
EconomyState,
NearbyParty,
PartyState,
Settlement,
)
from bannerlord.decision import (
M2Action,
CampaignDecision,
build_decision_prompt,
parse_decision,
)
def _make_state(
*,
troops: int = 30,
gold: int = 2000,
food_days: float = 5.0,
morale: float = 80.0,
settlements: list | None = None,
nearby_parties: list | None = None,
) -> CampaignState:
state = CampaignState()
state.party = PartyState(
party_size=troops,
food_days=food_days,
morale=morale,
)
state.economy = EconomyState(gold=gold, daily_income=200, daily_expenses=150)
state.settlements = settlements or []
state.nearby_parties = nearby_parties or []
return state
class TestBuildDecisionPrompt:
def test_returns_two_messages(self):
state = _make_state()
messages = build_decision_prompt(state)
assert len(messages) == 2
assert messages[0]["role"] == "system"
assert messages[1]["role"] == "user"
def test_user_message_includes_party_info(self):
state = _make_state(troops=45, gold=3000)
messages = build_decision_prompt(state)
user_content = messages[1]["content"]
assert "45" in user_content
assert "3,000" in user_content
def test_bandits_appear_in_prompt_when_nearby(self):
state = _make_state(
nearby_parties=[NearbyParty("b1", "Forest Bandits", "bandit", True, 10, 2.0)]
)
messages = build_decision_prompt(state)
user_content = messages[1]["content"]
assert "Forest Bandits" in user_content
def test_settlements_appear_in_prompt(self):
state = _make_state(
settlements=[Settlement("s1", "Marunath", "aserai", True, 3.0, has_recruits=True)]
)
messages = build_decision_prompt(state)
user_content = messages[1]["content"]
assert "Marunath" in user_content
def test_system_prompt_contains_action_vocabulary(self):
state = _make_state()
messages = build_decision_prompt(state)
system = messages[0]["content"]
for action in ("MOVE", "TRADE", "RECRUIT", "ENGAGE", "WAIT"):
assert action in system
class TestParseDecision:
def test_valid_move_decision(self):
raw = json.dumps({
"action": "MOVE",
"settlement_id": "town_A1",
"settlement_name": "Marunath",
"item_id": "",
"quantity": 1,
"party_id": "",
"party_name": "",
"reasoning": "Moving to recruit troops",
})
decision = parse_decision(raw)
assert decision.action == M2Action.MOVE
assert decision.settlement_id == "town_A1"
assert decision.settlement_name == "Marunath"
def test_valid_recruit_decision(self):
raw = json.dumps({
"action": "RECRUIT",
"settlement_id": "town_A1",
"settlement_name": "Marunath",
"item_id": "",
"quantity": 1,
"party_id": "",
"party_name": "",
"reasoning": "Has recruits available",
})
decision = parse_decision(raw)
assert decision.action == M2Action.RECRUIT
def test_valid_engage_decision(self):
raw = json.dumps({
"action": "ENGAGE",
"settlement_id": "",
"settlement_name": "",
"item_id": "",
"quantity": 1,
"party_id": "bandit_1",
"party_name": "Forest Bandits",
"reasoning": "Weak bandits — easy XP",
})
decision = parse_decision(raw)
assert decision.action == M2Action.ENGAGE
assert decision.party_id == "bandit_1"
def test_wait_on_invalid_json(self):
decision = parse_decision("not json at all")
assert decision.action == M2Action.WAIT
def test_wait_on_unknown_action(self):
raw = json.dumps({"action": "TELEPORT", "reasoning": "hack"})
decision = parse_decision(raw)
assert decision.action == M2Action.WAIT
def test_strips_markdown_fences(self):
raw = '```json\n{"action": "WAIT", "reasoning": "low food"}\n```'
decision = parse_decision(raw)
assert decision.action == M2Action.WAIT
def test_quantity_minimum_one(self):
raw = json.dumps({"action": "TRADE", "item_id": "grain", "quantity": -5, "reasoning": "x"})
decision = parse_decision(raw)
assert decision.quantity == 1
def test_missing_optional_fields_default_to_empty(self):
raw = json.dumps({"action": "WAIT", "reasoning": "resting"})
decision = parse_decision(raw)
assert decision.settlement_id == ""
assert decision.party_id == ""
assert decision.item_id == ""

View File

@@ -0,0 +1,120 @@
"""Unit tests for bannerlord.gabs_client."""
from __future__ import annotations
import asyncio
import json
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from bannerlord.gabs_client import GabsClient, GabsError
class TestGabsClientCall:
"""Tests for GabsClient.call() using mock StreamReader/Writer."""
def _make_client(self, response: dict) -> GabsClient:
"""Return a pre-connected GabsClient with mocked I/O."""
client = GabsClient(host="localhost", port=4825, timeout=5.0)
client._connected = True
writer = MagicMock()
writer.write = MagicMock()
writer.drain = AsyncMock()
raw_response = json.dumps(response).encode() + b"\n"
reader = MagicMock()
reader.readline = AsyncMock(return_value=raw_response)
client._reader = reader
client._writer = writer
return client
async def test_successful_call_returns_result(self):
client = self._make_client({"jsonrpc": "2.0", "id": 1, "result": {"status": "ok"}})
result = await client.call("game/ping")
assert result == {"status": "ok"}
async def test_error_response_raises_gabs_error(self):
client = self._make_client({
"jsonrpc": "2.0",
"id": 1,
"error": {"code": -32601, "message": "Method not found"},
})
with pytest.raises(GabsError) as exc_info:
await client.call("unknown/method")
assert exc_info.value.code == -32601
async def test_not_connected_raises_runtime_error(self):
client = GabsClient()
with pytest.raises(RuntimeError, match="not connected"):
await client.call("game/ping")
async def test_request_id_increments(self):
client = self._make_client({"jsonrpc": "2.0", "id": 1, "result": {}})
await client.call("game/ping")
# Reset reader for second call
client._reader.readline = AsyncMock(
return_value=json.dumps({"jsonrpc": "2.0", "id": 2, "result": {}}).encode() + b"\n"
)
await client.call("game/ping")
assert client._req_id == 2
async def test_get_game_state_returns_empty_on_error(self):
client = GabsClient()
client._connected = True
writer = MagicMock()
writer.write = MagicMock()
writer.drain = AsyncMock()
reader = MagicMock()
reader.readline = AsyncMock(side_effect=OSError("connection reset"))
client._reader = reader
client._writer = writer
result = await client.get_game_state()
assert result == {}
async def test_ping_returns_true_on_success(self):
client = self._make_client({"jsonrpc": "2.0", "id": 1, "result": "pong"})
result = await client.ping()
assert result is True
async def test_ping_returns_false_on_failure(self):
client = GabsClient()
result = await client.ping()
assert result is False
class TestGabsClientLifecycle:
async def test_connect_failure_sets_not_connected(self):
client = GabsClient(host="localhost", port=9999, timeout=0.1)
with pytest.raises(Exception):
await client.connect()
assert not client.is_connected
async def test_context_manager_calls_connect_and_disconnect(self):
client = GabsClient()
connect_called = False
disconnect_called = False
async def _fake_connect():
nonlocal connect_called
connect_called = True
client._connected = True
async def _fake_disconnect():
nonlocal disconnect_called
disconnect_called = True
client._connected = False
client.connect = _fake_connect
client.disconnect = _fake_disconnect
async with client as c:
assert c is client
assert connect_called
assert disconnect_called

View File

@@ -147,10 +147,12 @@ 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"])

View File

@@ -0,0 +1,499 @@
"""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"

View File

@@ -0,0 +1,267 @@
"""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)

View File

@@ -242,6 +242,145 @@ 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."""

View File

@@ -0,0 +1,332 @@
"""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 == {}

View File

@@ -489,6 +489,197 @@ 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."""

View File

@@ -0,0 +1,183 @@
"""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

View File

@@ -0,0 +1,394 @@
"""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

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@@ -0,0 +1,607 @@
"""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 == ""

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@@ -0,0 +1,353 @@
"""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

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"""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

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@@ -0,0 +1,460 @@
"""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"]

View File

@@ -87,6 +87,11 @@ 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]