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MerCry c1d76093aa feat(AISVC-T7): 嵌入模型可插拔设计与文档解析支持 [AC-AISVC-29, AC-AISVC-30, AC-AISVC-31, AC-AISVC-32, AC-AISVC-33, AC-AISVC-34, AC-AISVC-35, AC-AISVC-36, AC-AISVC-37, AC-AISVC-38, AC-AISVC-39, AC-AISVC-40, AC-AISVC-41] 
- 新增 EmbeddingProvider 抽象基类和工厂模式 [AC-AISVC-29, AC-AISVC-30]
- 实现 OllamaEmbeddingProvider 和 OpenAIEmbeddingProvider [AC-AISVC-29, AC-AISVC-30]
- 新增 EmbeddingConfigManager 支持配置热更新 [AC-AISVC-31, AC-AISVC-32]
- 新增 DocumentParser 抽象接口和工厂类 [AC-AISVC-33]
- 实现 PDF/Word/Excel/Text 文档解析器 [AC-AISVC-33, AC-AISVC-34, AC-AISVC-35]
- 新增嵌入管理 API 端点 [AC-AISVC-38, AC-AISVC-39, AC-AISVC-40, AC-AISVC-41]
- 更新文档上传流程支持多格式文档解析 [AC-AISVC-36, AC-AISVC-37]
- 更新 OpenAPI 契约添加嵌入管理接口
- 添加数据库初始化脚本
- 更新规范文档标记 Phase 7 完成
 		2026-02-24 23:08:08 +08:00
..
app feat(AISVC-T7): 嵌入模型可插拔设计与文档解析支持 [AC-AISVC-29, AC-AISVC-30, AC-AISVC-31, AC-AISVC-32, AC-AISVC-33, AC-AISVC-34, AC-AISVC-35, AC-AISVC-36, AC-AISVC-37, AC-AISVC-38, AC-AISVC-39, AC-AISVC-40, AC-AISVC-41] 2026-02-24 23:08:08 +08:00
scripts feat(AISVC-T7): 嵌入模型可插拔设计与文档解析支持 [AC-AISVC-29, AC-AISVC-30, AC-AISVC-31, AC-AISVC-32, AC-AISVC-33, AC-AISVC-34, AC-AISVC-35, AC-AISVC-36, AC-AISVC-37, AC-AISVC-38, AC-AISVC-39, AC-AISVC-40, AC-AISVC-41] 2026-02-24 23:08:08 +08:00
tests feat(ai-service): add Phase 5 integration and contract tests [AC-AISVC-10,11,17,18] 2026-02-24 13:53:55 +08:00
README.md feat(AISVC-T7): 嵌入模型可插拔设计与文档解析支持 [AC-AISVC-29, AC-AISVC-30, AC-AISVC-31, AC-AISVC-32, AC-AISVC-33, AC-AISVC-34, AC-AISVC-35, AC-AISVC-36, AC-AISVC-37, AC-AISVC-38, AC-AISVC-39, AC-AISVC-40, AC-AISVC-41] 2026-02-24 23:08:08 +08:00
pyproject.toml feat(ai-service): implement LLM Adapter for T3.1 [AC-AISVC-02, AC-AISVC-06] 2026-02-24 13:19:38 +08:00

README.md

AI Service

Python AI Service for intelligent chat with RAG support.

Features

  • Multi-tenant isolation via X-Tenant-Id header
  • SSE streaming support via Accept: text/event-stream
  • RAG-powered responses with confidence scoring

Prerequisites

  • PostgreSQL 12+
  • Qdrant vector database
  • Python 3.10+

Installation

pip install -e ".[dev]"

Database Initialization

Option 1: Using Python script (Recommended)

# Create database and tables
python scripts/init_db.py --create-db

# Or just create tables (database must exist)
python scripts/init_db.py

Option 2: Using SQL script

# Connect to PostgreSQL and run
psql -U postgres -f scripts/init_db.sql

Configuration

Create a .env file in the project root:

AI_SERVICE_DATABASE_URL=postgresql+asyncpg://postgres:password@localhost:5432/ai_service
AI_SERVICE_QDRANT_URL=http://localhost:6333
AI_SERVICE_LLM_API_KEY=your-api-key
AI_SERVICE_LLM_BASE_URL=https://api.openai.com/v1
AI_SERVICE_LLM_MODEL=gpt-4o-mini
AI_SERVICE_DEBUG=true

Running

uvicorn app.main:app --host 0.0.0.0 --port 8000

API Endpoints

Chat API

  • POST /ai/chat - Generate AI reply (supports SSE streaming)
  • GET /ai/health - Health check

Admin API

  • GET /admin/kb/documents - List documents
  • POST /admin/kb/documents - Upload document
  • GET /admin/kb/index/jobs/{jobId} - Get indexing job status
  • DELETE /admin/kb/documents/{docId} - Delete document
  • POST /admin/rag/experiments/run - Run RAG experiment
  • GET /admin/sessions - List chat sessions
  • GET /admin/sessions/{sessionId} - Get session details