pyproject.toml

[project]
name = "portfolio-intelligence-platform"
version = "0.1.0"
description = "AI-powered portfolio analysis platform with MCP orchestration"
readme = "README.md"
requires-python = ">=3.10"
dependencies = [
    # AI Framework - use slim without mcp extra to avoid conflict with gradio[mcp]
    "pydantic-ai-slim[anthropic]==1.18.0",
    "anthropic>=0.39.0",
    "instructor>=1.6.4",
    # Agent Orchestration
    "langgraph>=0.1.0",
    "langchain-anthropic>=0.1.0",
    "langchain-core>=0.2.0",
    # MCP Framework - fastmcp 2.9.1 is latest compatible with mcp==1.10.1 (gradio[mcp] requirement)
    # Note: fastmcp 2.9.2+ requires mcp<1.10.0 which conflicts with gradio[mcp]
    "fastmcp==2.9.1",
    # Frontend - gradio with native MCP support
    "gradio[mcp]==5.49.1",
    # Backend
    "fastapi>=0.104.0",
    "uvicorn[standard]>=0.24.0",
    "pydantic>=2.5.0",
    # Database
    "supabase>=2.9.0",
    "psycopg2-binary>=2.9.9",
    # Caching & Rate Limiting
    "redis>=5.0.0",
    "upstash-redis>=0.15.0",
    "orjson>=3.10.0",
    # Quantitative Finance (P0 - Deterministic Models)
    # Research validated: Package name is 'pyportfolioopt', import as 'pypfopt'
    "pyportfolioopt>=1.5.6",
    "riskfolio-lib>=7.0.0",
    "arch>=8.0.0",
    "quantstats>=0.0.77",
    # Data & Analysis
    "pandas>=2.2.3",
    "numpy>=2.0.0",
    "yfinance>=0.2.40",
    "scipy>=1.11.0",
    "matplotlib>=3.8.0",
    "plotly>=5.18.0",
    # Export & Reporting
    "reportlab>=4.0.0",
    "pypdf>=3.17.0",
    # Feature Engineering (manual implementations used instead of pandas-ta)
    "PyWavelets>=1.4.1",
    "scikit-learn>=1.3.0",
    # ML Models (P1 - Optional)
    "torch>=2.0.0",
    "xgboost>=3.1.0",
    "chronos-forecasting>=1.0.0",
    # Deep Learning Time Series Models
    "granite-tsfm>=0.2.22",
    "neuralforecast>=3.1.0",
    # Utilities
    "python-dotenv>=1.0.0",
    "httpx>=0.25.0",
    "tenacity>=8.2.0",
    "python-dateutil>=2.8.0",
    # Sentiment Analysis
    "vaderSentiment>=3.3.2",
    # Text-to-Speech
    "elevenlabs>=1.0.0",
    # Monitoring & Observability
    "sentry-sdk[fastapi]>=2.0.0,<3.0.0",  # Pin to stable, avoid 3.0 alpha
    "fmp-data>=1.0.2",
]

[dependency-groups]
dev = [
    "pytest>=7.4.0",
    "pytest-asyncio>=0.21.0",
    "ruff>=0.1.0",
    "black>=23.11.0",
    "mypy>=1.7.0",
    "typer>=0.20.0",
]

[tool.hatch.build.targets.wheel]
packages = ["backend"]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"