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8 Commits

Author SHA1 Message Date
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2dcd214156 fix(ollama): cooldown noisy failed endpoints
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2026-05-25 12:11:48 +08:00
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45cd55b2da fix(api): enforce global ollama endpoint order
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2026-05-19 12:32:19 +08:00
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c4854bb355 fix(ai): isolate heavy Ollama workloads from GCP alert lane
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2026-05-05 23:06:07 +08:00
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b4055c5915 feat(embedding): ADR-110 升級 bge-m3:latest 1024 維向量
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GCP-A (34.143.170.20) 無 nomic-embed-text，改用 bge-m3:latest（專用
多語言 embedding 模型），產生 1024 維向量。

變更：
- embedding_service.py: 加入 bge-m3:latest=1024 維到 MODEL_DIMENSIONS，
  預設模型改為 bge-m3:latest，更新文件說明
- playbook_embedding_repository.py + interfaces.py: 更新維度說明
- migrations/embedding_bge_m3_1024.sql: pgvector schema 遷移
  rag_chunks + playbook_embeddings vector(768) → vector(1024)
- scripts/reembed_bge_m3.py: 遷移後重新嵌入現有資料的 script

遷移步驟：
  1. 執行 embedding_bge_m3_1024.sql（清空現有 768 維向量，變更維度）
  2. 執行 python scripts/reembed_bge_m3.py 重新嵌入

2026-05-04 ogt + Claude Sonnet 4.6

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-04 11:18:20 +08:00
OG T
f2c18c4e63 feat(D1): models.json 集中化 — ADR-067 五大 Ollama 應用 hardcode 消除
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- models.json v1.3.0: providers.ollama.models 新增 9 個 purpose keys
  (drift_summary/drift_intent/log_anomaly/nemoclaw/playbook_draft/
   code_review/embedding/rag_generate/image_analysis)
- drift_narrator_service: NARRATOR_MODEL → get_model("ollama","drift_summary")
- drift_interpreter: MODEL → get_model("ollama","drift_intent")
- log_summary_service: SUMMARY_MODEL → get_model("ollama","log_anomaly")
- local_code_review_service: _MODEL_OLLAMA → get_model("ollama","code_review")
- image_analysis_service: _MODEL → get_model("ollama","image_analysis")
- decision_manager: nemoclaw + playbook_draft 兩處 → get_model()
- embedding_service: get_embedding_service() factory → get_model("ollama","embedding")
- knowledge_service: OllamaEmbeddingService(model=...) → get_model()

所有模型名稱現在統一由 models.json 管理，修改模型只需改一個檔案。
LOGBOOK 更新：D1 完成 + B2 已完成確認

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-04-11 20:45:53 +08:00
OG T
8724ed7dcf fix(mcp): P1 修復 - DI 一致性 + 測試補充 + 配置優化 
首席架構師審查 P1 修復清單:

P1-1 RAG Provider DI 模式一致性:
- 支援 rag_service 參數注入
- 新增 close() 方法
- TYPE_CHECKING 延遲導入

P1-3 RAG 測試補充:
- test_rag_provider.py (9 tests)
- DI 注入/Lazy Load/Tool Schema/驗證/Close

P1-4 Grafana Config 快取優化:
- URL/Key 首次查詢後快取
- 減少重複 settings 存取

P1-5 Embedding 維度配置化:
- MODEL_DIMENSIONS 字典 (qwen/llama/nomic)
- default_dimension 參數
- 支援更多模型

測試: 9/9 PASSED

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-03-29 16:23:30 +08:00
OG T
e26ea526b1 fix(api): lint errors in Rate Limiter + RAG services 
- Remove unused imports (settings, uuid)
- Add 'from e' to exception raises (B904)
- Add strict=True to zip() (B905)
- Remove unused variable

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-03-26 16:03:16 +08:00
OG T
bf32c4b1f2 feat(api): Phase 13.2 AI Rate Limiter + RAG 基礎設施 (#84) 
Rate Limiter (防止 Gemini 用量暴衝):
- ai_rate_limiter.py: RPM/Daily/Token 三層閥值
- openclaw.py: 整合 rate limit 檢查，超限自動降級
- health.py: /health/ai-usage 監控端點

RAG Tool 基礎 (#84 進行中):
- embedding_service.py: Ollama embedding 封裝
- rag_service.py: Redis vector search 服務

閥值設定:
- Gemini: 10 RPM, 500/day, 100K tokens/day
- Claude: 5 RPM, 200/day, 50K tokens/day

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2026-03-26 15:52:57 +08:00