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| fastapi==0.115.0 | |
| uvicorn[standard]==0.30.6 | |
| pydantic==2.9.2 | |
| pydantic-settings==2.5.2 | |
| python-dotenv==1.0.1 | |
| # DB | |
| SQLAlchemy==2.0.35 | |
| psycopg[binary]==3.2.3 | |
| # Excel | |
| pandas==2.2.3 | |
| openpyxl==3.1.5 | |
| # Scraping | |
| requests==2.32.3 | |
| beautifulsoup4==4.12.3 | |
| lxml==5.3.0 | |
| # RAG vector store β Pinecone serverless (free starter tier) | |
| pinecone==5.4.2 | |
| # RAG v2 β multimodal ingestion (docling) + jina-clip-v2 ONNX int8 embeddings | |
| docling==2.91.0 | |
| transformers>=4.45,<5 | |
| onnxruntime>=1.18 | |
| onnx>=1.16 | |
| huggingface_hub>=0.24 | |
| pillow>=10.0 | |
| numpy>=1.26 | |
| einops>=0.8 | |
| sentencepiece>=0.2 | |
| timm>=1.0 | |
| # Orchestration β LangGraph 1.x with native interrupt/Command resume | |
| langgraph>=1.0,<2 | |
| langgraph-checkpoint>=4.0,<5 | |
| langchain>=1.0,<2 | |
| langchain-core>=1.0,<2 | |
| langchain-openai>=1.0,<2 | |
| # LLM providers β all accessed via LangChain chat classes that implement | |
| # .bind_tools(). The raw `anthropic` SDK is a transitive dep of | |
| # langchain-anthropic; same for google-genai via langchain-google-genai. | |
| openai>=1.55,<3 | |
| sqlglot>=25 | |
| langchain-anthropic>=1.0,<2 | |
| langchain-google-genai>=2,<3 | |
| # Observability & evaluation β latest production-grade releases (verified on PyPI 2026-05-24) | |
| # NOTE: we don't install the full `arize-phoenix` server here (it pulls FastAPI>=0.135 | |
| # and conflicts with our pin). Phoenix Cloud is the hosted backend, so the OTel | |
| # exporter package alone is enough. | |
| arize-phoenix-otel>=0.16.1 | |
| openinference-instrumentation-langchain>=0.1.66 | |
| openinference-instrumentation-openai>=0.1.49 | |
| openinference-instrumentation-anthropic>=1.0.5 | |
| openinference-instrumentation-google-genai>=1.0.2 | |
| opentelemetry-instrumentation-fastapi>=0.63b1 | |
| # NOTE: `open-rag-eval` is NOT installed β its 0.3.0 dependency graph | |
| # (torch 2.7, llama_index, streamlit, transformers 4.50, openai~=2.7, | |
| # anthropic~=0.72) hard-conflicts with this backend's pins. `app/evals/scorer.py` | |
| # uses the same TREC-style LLM-judge prompt with the same metrics | |
| # (groundedness / hallucination / answer_relevance / context_relevance) via | |
| # the OpenAI SDK directly β identical signal, no dep collision. | |
| apscheduler>=3.11.0 | |
| PyYAML>=6.0 | |