README.md

metadata

title: FinAgent Infosys AR QA
emoji: 📊
colorFrom: blue
colorTo: indigo
sdk: streamlit
sdk_version: 1.58.0
app_file: app.py
pinned: false
license: mit

📊 FinAgent — Infosys Annual Report Q&A

An agentic Retrieval-Augmented Generation app over the Infosys Integrated Annual Report 2024-25. Hybrid retrieval (BM25 + dense + HyDE) → cross-encoder reranking → LangGraph multi-agent orchestration → FinBERT sentiment → inline Self-RAG faithfulness check, served with Streamlit.

Setup on Hugging Face Spaces

This Space needs one secret to answer questions:

• GROQ_API_KEY — add it under Settings → Variables and secrets → New secret. Get a free key at https://console.groq.com/keys

The UI and models load without it; only the LLM answers require it.

Stack

Groq llama-3.3-70b-versatile · LangGraph · LangChain · ChromaDB (pre-built, shipped in finance_db/) · HuggingFace embeddings (all-mpnet-base-v2) · cross-encoder (ms-marco-MiniLM-L-6-v2) · FinBERT.

First boot downloads ~1 GB of models and takes ~1–2 min. CPU basic (free, 16 GB RAM) is sufficient.