多智能体投注优化系统

┌─────────────────────────────────────────────────────────────┐
│                    USER REQUEST                              │
│  "Build 8-leg 100x parlay for Bengals vs Packers"          │
└──────────────────────┬──────────────────────────────────────┘
                       │
                       ▼
            ┌──────────────────────┐
            │  Crew Orchestrator   │
            │  - Request Analysis  │
            │  - Agent Routing     │
            └──────────┬───────────┘
                       │
        ┌──────────────┼──────────────┐
        ▼              ▼              ▼
┌───────────────┐ ┌──────────────┐ ┌─────────────────┐
│ Roster Agent  │ │ Stats Agent  │ │ Parlay Optimizer│
│ • Injuries    │ │ • ML Models  │ │ • Combinations  │
│ • Availability│ │ • Props      │ │ • Correlations  │
│ • Weather     │ │ • Matchups   │ │ • Optimization  │
└───────┬───────┘ └──────┬───────┘ └────────┬────────┘
        │                │                   │
        └────────────────┼───────────────────┘
                         ▼
                  ┌─────────────┐
                  │  QA Agent   │
                  │ • Validate  │
                  │ • Correlate │
                  │ • Approve   │
                  └──────┬──────┘
                         │
                         ▼
              ┌──────────────────────┐
              │  2-3 Parlay Options   │
              │  • 8 legs            │
              │  • ~100x multiplier  │
              │  • Confidence scores │
              │  • Full reasoning    │
              └──────────────────────┘

# Clone repository
git clone https://github.com/mattarm/fantasy_mcp.git
cd fantasy_mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Copy environment template
cp env.example .env

# Edit .env and add your OpenAI API key
OPENAI_API_KEY=your_key_here
OPENAI_MODEL=gpt-4

# Other optional configurations
AGENT_VERBOSE=true
PARLAY_MIN_CONFIDENCE=0.65
PARLAY_MAX_LEGS=15

# Run validation tests
python test_agent_system.py

# Start MCP server
python -m fantasy_mcp.main

"Put together high confidence 8 leg parlay with a 100x return for this weeks Bengals Packers game"

"Put together a 800x parlay for this Sunday's noon games"

# Use build_optimized_parlay tool
result = await mcp_client.call_tool("build_optimized_parlay", {
    "request": "Build 8-leg 100x parlay for Bengals vs Packers game"
})

# Get parlay history
history = await mcp_client.call_tool("get_parlay_history", {
    "limit": 10
})

# Retrieve specific parlay
parlay = await mcp_client.call_tool("get_parlay_by_id", {
    "parlay_id": "abc123..."
})

fantasy_mcp/
├── src/fantasy_mcp/
│   ├── agents/              # AI agents
│   │   ├── roster_intelligence_agent.py
│   │   ├── stats_props_agent.py
│   │   ├── qa_agent.py
│   │   └── parlay_optimizer_agent.py
│   ├── crews/               # Crew orchestration
│   │   ├── betting_crew.py
│   │   └── crew_orchestrator.py
│   ├── tools/               # Agent tools
│   │   ├── roster_tools.py
│   │   ├── stats_tools.py
│   │   ├── betting_tools.py
│   │   └── data_tools.py
│   ├── data_store/          # Data management
│   │   ├── file_manager.py
│   │   └── cache_manager.py
│   ├── services/            # Core services
│   │   ├── sleeper_api.py
│   │   ├── ml_predictor.py
│   │   └── betting_advisor.py
│   ├── api/                 # MCP server
│   │   └── mcp_server.py
│   └── core/                # Core utilities
│       ├── config.py
│       └── database.py
├── data/                    # File-based storage
│   ├── players/
│   ├── stats/
│   ├── predictions/
│   ├── bets/parlays/
│   └── cache/
├── tests/                   # Test suite
├── archive/                 # Archived old scripts
├── test_agent_system.py     # System tests
├── AGENT_SYSTEM_README.md   # Detailed agent docs
├── IMPLEMENTATION_SUMMARY.md # Implementation details
└── requirements.txt         # Dependencies

# AI/LLM (Required)
OPENAI_API_KEY=your_key_here
OPENAI_MODEL=gpt-4

# Agent Configuration
AGENT_VERBOSE=true
AGENT_MAX_ITERATIONS=15
AGENT_MAX_EXECUTION_TIME=300

# Parlay Settings
PARLAY_MIN_CONFIDENCE=0.65
PARLAY_MAX_LEGS=15
PARLAY_CORRELATION_THRESHOLD=0.3

# Betting Configuration
DEFAULT_BANKROLL=1000.0
KELLY_FRACTION=0.25

data/
├── players/
│   └── {player_id}.json         # Player info
├── stats/
│   └── {player_id}/
│       └── {season}_week_{week}.json
├── predictions/
│   └── {date}/
│       └── {player_id}.json     # ML predictions
├── bets/
│   ├── parlays/
│   │   └── {parlay_id}.json     # Saved parlays
│   └── history/
└── cache/
    └── {cache_key}.json         # API cache

# Run system tests
python test_agent_system.py

# With full agent execution (requires API key)
OPENAI_API_KEY=your_key python test_agent_system.py

# Run pytest suite
pytest tests/

# Run with coverage
pytest --cov=src/fantasy_mcp

{
    "request": "Natural language parlay request"
}

{
    "limit": 10  # Number of parlays to retrieve
}

{
    "parlay_id": "unique_parlay_id"
}