# Ragiment — rag-standard (LlamaIndex) requirements
# Generated by ragiment.dev

# LlamaIndex core
llama-index-core>=0.10
PyYAML>=6.0

# LLM + embedding model SDKs
llama-index-llms-openai>=0.2
llama-index-embeddings-openai>=0.2

# Vector store
llama-index-vector-stores-pinecone>=0.2
pinecone>=5.0

# Hybrid retrieval
llama-index-retrievers-bm25>=0.3

# Document loading
pypdf>=4.0
python-docx>=1.1
beautifulsoup4>=4.12

# Document source connector — google_drive
google-api-python-client>=2.131.0
google-auth>=2.29.0
google-auth-httplib2>=0.2.0

# API server (serve.py) + local .env loading + eval suite
fastapi>=0.110
uvicorn[standard]>=0.29
pydantic>=2.0
python-dotenv>=1.0
requests>=2.32
