History

MerCry fd04ed2cef fix: 修复RAG检索多个问题并更新嵌入模型配置 [AC-AISVC-50] 主要修复: 1. 修复ConfigForm和EmbeddingConfigForm组件watch死循环导致内存溢出 2. 修复向量存储格式与检索格式不匹配问题 3. 修复两阶段检索和混合检索互斥问题 4. 修复RRF融合时vector字段丢失问题 5. 修复embedding_full未归一化导致相似度计算错误 6. 修复嵌入模型配置表单不显示参数问题功能增强: - 添加with_vectors参数支持返回向量用于重排序 - 新增两阶段+混合检索组合策略 - 更新README嵌入模型配置说明，推荐nomic-embed-text-v2-moe - 添加cleanup_qdrant.py脚本用于清理向量数据		2026-02-26 14:45:21 +08:00
..
app	fix: 修复RAG检索多个问题并更新嵌入模型配置 [AC-AISVC-50]	2026-02-26 14:45:21 +08:00
scripts	fix: 修复RAG检索多个问题并更新嵌入模型配置 [AC-AISVC-50]	2026-02-26 14:45:21 +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
.dockerignore	feat: 添加Docker容器部署配置 [AC-AISVC-01]	2026-02-26 01:22:30 +08:00
Dockerfile	fix: Docker构建时复制README.md文件 [AC-AISVC-01]	2026-02-26 02:13:26 +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	fix: 添加python-multipart依赖解决表单解析错误 [AC-AISVC-01]	2026-02-26 02:29:56 +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