RAG与MCP工具集成系统

docker run -d -p 6379:6379 --name devops-redis redis:7-alpine
python mcp_server.py  # Terminal 1
python agent_api.py   # Terminal 2

curl http://localhost:8000/health
curl -X POST "http://localhost:8000/rag/ingest?directory=data/docs"
python test_mcp_tools.py
k6 run k6/load_test.js

# Press Ctrl+C in both terminals
docker stop devops-redis

pip install fastapi uvicorn chromadb pydantic groq python-dotenv langgraph langchain-core redis requests

docker run -d -p 6379:6379 --name devops-redis redis:7-alpine

docker exec -it devops-redis redis-cli ping
# Expected: PONG

GROQ_API_KEY=gsk_your_key_here
REDIS_URL=redis://localhost:6379
BASIC_RPM=10
PRO_RPM=60
VIP_RPM=300

python mcp_server.py

✓ Database initialized
✓ Sample server data seeded
✓ MCP Server started

python agent_api.py

✓ Connected to Redis at redis://localhost:6379
✓ Groq LLM configured
✓ LangGraph workflow initialized
✓ MCP client connected to server
INFO:     Uvicorn running on http://0.0.0.0:8000

curl -X POST "http://localhost:8000/rag/ingest?directory=data/docs"

{
  "status": "success",
  "documents_ingested": 45,
  "message": "Ingested 45 chunks from data/docs"
}

curl http://localhost:8000/health

curl -X POST "http://localhost:8000/agent/query" `
  -H "Content-Type: application/json" `
  -H "X-Client-ID: basic-test" `
  -d '{\"message\": \"What is the deployment procedure?\"}'

# Send 15 requests (over 10 RPM limit)
for ($i=1; $i -le 15; $i++) {
  Write-Host "Request $i"
  curl -X POST "http://localhost:8000/agent/query" `
    -H "Content-Type: application/json" `
    -H "X-Client-ID: basic-ratelimit-test" `
    -d '{\"message\": \"Test\"}'
  Start-Sleep -Milliseconds 500
}

# Create ticket
curl -X POST "http://localhost:8000/agent/query" `
  -H "X-Client-ID: vip-test" `
  -H "Content-Type: application/json" `
  -d '{\"message\": \"Create a critical ticket for database outage\"}'

# Get ticket
curl -X POST "http://localhost:8000/agent/query" `
  -H "X-Client-ID: vip-test" `
  -H "Content-Type: application/json" `
  -d '{\"message\": \"Get ticket 1\"}'

# Append note
curl -X POST "http://localhost:8000/agent/query" `
  -H "X-Client-ID: vip-test" `
  -H "Content-Type: application/json" `
  -d '{\"message\": \"Append note to deploy-2024-01: Success\"}'

choco install k6

# Basic tier test
k6 run k6/simple_test_basic.js

# Comprehensive test
k6 run k6/load_test.js

# Mixed clients test
k6 run k6/simple_test_mixed.js

python test_mcp_tools.py

python eval_rag.py

Client (k6/curl) → Rate Limiter (Redis) → LangGraph Orchestrator
                                                ↓
                                    ┌───────────┴────────────┐
                                    ↓                        ↓
                                RAG System              MCP Tools
                                    ↓                        ↓
                                ChromaDB                SQLite DB

1. Client → API: Request with X-Client-ID header
2. Rate Limiter → Redis: Check bucket state (Leaky Bucket)
3. If allowed → Orchestrator: Process request
4. Orchestrator → RAG/MCP: Based on intent
5. Response → Client: With rate limit headers

lab7-devops-agent/
├── agent_api.py              # FastAPI server with rate limiting
├── rate_limiter.py           # Redis + Leaky Bucket implementation
├── devops_orchestrator.py    # LangGraph orchestrator
├── rag_system.py             # RAG with ChromaDB
├── mcp_server.py             # MCP server (3 tools)
├── mcp_client.py             # MCP client
├── test_mcp_tools.py         # Automated tool tests
├── eval_rag.py               # RAG evaluation script
├── docker-compose.yml        # Redis + API services
├── Dockerfile                # API container image
├── requirements.txt          # Python dependencies
├── .env                      # Environment variables
├── k6/
│   ├── load_test.js         # Comprehensive k6 test
│   ├── simple_test_basic.js # Basic tier test
│   ├── simple_test_pro.js   # Pro tier test
│   └── simple_test_mixed.js # Mixed clients test
├── data/
│   └── docs/                # DevOps documentation (10+ files)
│       ├── deployment_procedure.md
│       ├── incident_management.md
│       ├── server_maintenance.md
│       ├── monitoring.md
│       ├── backup_policy.md
│       └── ... (5+ more)
└── tests/
    ├── test_queries.json    # RAG test queries
    └── eval_results.json    # Evaluation results

# Start all services
docker-compose up -d

# Check status
docker-compose ps

# View logs
docker-compose logs -f agent-api

# Ingest documents
curl -X POST "http://localhost:8000/rag/ingest?directory=data/docs"

# Stop services
docker-compose down

docker ps | findstr redis
docker start devops-redis

curl http://localhost:8000/health
# Check "redis_ready": true

# Restart MCP server (Terminal 1)
# Press Ctrl+C, then:
python mcp_server.py

docker exec -it devops-redis redis-cli FLUSHALL

netstat -ano | findstr :8000
taskkill /PID <PID> /F