title	FinVoice
emoji	🏦
colorFrom	blue
colorTo	indigo
sdk	gradio
sdk_version	4.36.0
app_file	app.py
pinned	false

🏦 FinVoice AI - Production BFSI Voice Agent

An autonomous, multi-lingual AI voice agent built for the Banking, Financial Services, and Insurance (BFSI) sector. This system is designed as a Forward Deployed Engineering (FDE) prototype that routes real-time voice queries using a stateful agent graph, processes Retrieval-Augmented Generation (RAG) for banking policies, calls mock REST APIs for customer data, and gracefully escalates frustrated customers to human agents.

🌟 Key Capabilities

• Stateful Reasoning (LangGraph): Uses a deterministic Directed Acyclic Graph (DAG) to guarantee reliable API routing and avoid infinite AI loops.
• Multilingual Voice-to-Voice:
  • STT: Leverages Groq's whisper-large-v3-turbo for instantaneous multilingual transcription.
  • TTS: Uses Microsoft Azure Neural TTS (edge-tts) to generate hyper-realistic, native-sounding Indian regional accents (Hindi, Tamil, Marathi, Telugu, etc.)
• RAG Vector Search: Uses HuggingFace Embeddings (all-MiniLM-L6-v2) and FAISS to retrieve real banking policies locally.
• Contextual API Tool-Calling: Executes backend mock functions (e.g. get_loan_status, check_kyc) dynamically based on user intent.
• Dynamic Slang Generation: Employs a 120-Billion parameter LLM (openai/gpt-oss-120b via Groq) specifically prompted to generate colloquial conversational dialects rather than robotic formal text.

🚀 Tech Stack

• Agent Framework: LangGraph, LangChain
• LLM: gpt-oss-120b (Groq API)
• Backend: FastAPI, Python 3.10+
• Frontend: Gradio (Enterprise UI Theme)
• RAG: FAISS, HuggingFace Sentence Transformers
• Audio: Groq Whisper API, Edge-TTS

⚙️ Installation & Local Setup

1. Clone the repository:

   git clone https://github.com/yourusername/FinVoice.git
   cd FinVoice

2. Install dependencies:

   pip install -r requirements.txt
   pip install edge-tts

3. Setup environment variables (.env):

   GROQ_API_KEY=your_groq_key

4. Run the Web Application:

   python main.py --mode ui

5. Run automated Multilingual tests:

   python test_multilingual.py

🏗️ Architecture

The core agent logic runs inside app/agent/nodes.py which defines 5 specific nodes:

1. stt_node: Ingests audio, calls Whisper API, detects language.
2. intent_node: Uses LLM to classify if the query needs a Tool, Policy (RAG), or Human.
3. tool_execution_node: Routes dynamically to backend Python functions.
4. generation_node: Translates the result into the detected language using colloquial slang.
5. tts_node: Generates Microsoft Azure Neural Voice files.