---
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.