Financial_bot / requirements.txt
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# ── Environment ────────────────────────────────────────────────────────────────
python-dotenv # load .env for local dev
# ── Document Fetching ──────────────────────────────────────────────────────────
requests==2.32.4 # HTTP calls to SEC EDGAR
# ── Document Parsing ──────────────────────────────────────────────────────────
docling # PDF/HTML parser with table understanding
tf-keras # fixes Keras 3 conflict with transformers
# ── Chunking ──────────────────────────────────────────────────────────────────
langchain-experimental # SemanticChunker (gradient method)
langchain-text-splitters # RecursiveCharacterTextSplitter (fallback)
# ── Embeddings ────────────────────────────────────────────────────────────────
langchain-huggingface # HuggingFaceEmbeddings wrapper
sentence-transformers # all-MiniLM-L6-v2 + ms-marco reranker + NLI verifier
# ── Vector Store ──────────────────────────────────────────────────────────────
chromadb # local vector DB (dev / notebook use)
qdrant-client # Qdrant Cloud vector DB (production / deployment)
# ── LLM + RAG Chain ───────────────────────────────────────────────────────────
langchain # RAG chain orchestration
langchain-community # Ollama LLM wrapper (local fallback)
langchain-core # base abstractions
langchain-google-genai # Google Gemini API (primary LLM for deployment)
google-generativeai # Gemini SDK
# ── Verification + Grounding ──────────────────────────────────────────────────
nltk # sentence tokenizer for claim splitting
# NLI model auto-downloaded on first use:
# cross-encoder/nli-deberta-v3-small (~180 MB)
# ── Data Handling ─────────────────────────────────────────────────────────────
pandas # dataframe operations
numpy<2.0 # pinned β€” docling + pyarrow need <2.0
# ── Web Application ───────────────────────────────────────────────────────────
streamlit>=1.39.0 # chat UI for Hugging Face Spaces deployment