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[project]
name = "multimodal-rag-system"
version = "0.1.0"
description = "A multimodal RAG system with FastAPI backend and Streamlit frontend"
readme = "README.md"
requires-python = ">=3.10"
license = {text = "MIT"}
dependencies = [
# Core ML/AI Libraries
"torch==2.1.0",
"torchvision==0.16.0",
"transformers==4.35.0",
"sentence-transformers==2.2.2",
"openai==1.3.0",
"anthropic==0.7.0",
# Computer Vision & Multimodal
"Pillow==10.1.0",
"opencv-python==4.8.1.78",
"clip-openai==1.0.1",
# Vector Databases & Search
"faiss-cpu==1.7.4",
"pinecone-client==2.2.4",
"chromadb==0.4.18",
# RAG & LLM Integration
"langchain==0.0.340",
"langchain-openai==0.0.2",
"langchain-community==0.0.10",
"langgraph==0.0.20",
# API & Backend
"fastapi==0.104.1",
"uvicorn==0.24.0",
"pydantic==2.5.0",
"python-multipart==0.0.6",
# Frontend
"streamlit==1.28.2",
"gradio==4.7.1",
# Data Processing
"pandas==2.1.3",
"numpy==1.24.3",
"scikit-learn==1.3.2",
# Utilities
"python-dotenv==1.0.0",
"requests==2.31.0",
"tqdm==4.66.1",
"pyyaml==6.0.1",
# Evaluation
"nltk==3.8.1",
"rouge-score==0.1.2",
# Deployment
"docker==6.1.3",
"boto3==1.29.7",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0.0",
"black>=22.0.0",
"ruff>=0.1.0",
"mypy>=1.0.0",
]
frontend = [
"streamlit==1.28.2",
"requests==2.31.0",
"python-dotenv==1.0.0",
]
# LangGraph twin of the hand-written agent loop (see requirements_langgraph.txt
# for the operative pin; this group mirrors it for `pip install .[langgraph]`).
langgraph = [
"langgraph==1.2.8",
]
[project.scripts]
rag-setup = "setup:main"
rag-run = "run:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.uv]
dev-dependencies = [
"pytest>=7.0.0",
"black>=22.0.0",
"ruff>=0.1.0",
]
[tool.black]
line-length = 100
target-version = ['py310']
[tool.ruff]
line-length = 100
target-version = "py310"
[tool.mypy]
python_version = "3.12" # repo targets 3.11-3.12 (see CI matrix); 3.10 was stale
warn_return_any = true
warn_unused_configs = true