https://github.com/samay-jain/voice_assistant_rag_system_using_langchain_and_streamlit

Voice Assistant RAG System using LangChain, Whisper, and Streamlit - A voice-enabled assistant that lets you ask questions by speaking, processes your custom documents, and responds with natural speech. Built with LangChain, Ollama, Whisper, ElevenLabs, and Streamlit.
https://github.com/samay-jain/voice_assistant_rag_system_using_langchain_and_streamlit

ai-assistant document-processing elevenlabs faiss langchain llm ollama python rag retrieval-augmented-generation speech-recognition streamlit text-to-speech voice-assistant whisper

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Voice Assistant RAG System using LangChain, Whisper, and Streamlit - A voice-enabled assistant that lets you ask questions by speaking, processes your custom documents, and responds with natural speech. Built with LangChain, Ollama, Whisper, ElevenLabs, and Streamlit.

• Host: GitHub
• URL: https://github.com/samay-jain/voice_assistant_rag_system_using_langchain_and_streamlit
• Owner: samay-jain
• Created: 2025-07-06T16:26:46.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-07-06T17:22:11.000Z (about 1 year ago)
• Last Synced: 2025-07-06T17:46:22.010Z (about 1 year ago)
• Topics: ai-assistant, document-processing, elevenlabs, faiss, langchain, llm, ollama, python, rag, retrieval-augmented-generation, speech-recognition, streamlit, text-to-speech, voice-assistant, whisper
• Language: Python
• Homepage:
• Size: 367 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🎙️ Voice Assistant RAG

> A fully interactive, voice-controlled AI assistant powered by Retrieval-Augmented Generation (RAG), Whisper speech-to-text, and ElevenLabs voice synthesis.

---

![RAG Voice Assistant Demo](https://img.shields.io/badge/LLM-Ollama-blue?style=flat-square)

![Built with Streamlit](https://img.shields.io/badge/Frontend-Streamlit-orange?style=flat-square)

![License](https://img.shields.io/badge/License-MIT-green.svg?style=flat-square)

---

## 🚀 Features

- 🔍 **RAG-based Q&A**: Ask voice questions, get accurate answers sourced from your documents.

- 🗂️ **Knowledge Base Setup**: Upload `.pdf`, `.txt`, or `.md` files and embed them using local FAISS vector store.

- 🎧 **Whisper Integration**: High-quality speech-to-text transcription using OpenAI's Whisper model.

- 🗣️ **ElevenLabs TTS**: Convert AI responses into realistic voice output.

- 🧠 **Chat Memory**: Keeps track of your conversation context.

- 🖥️ **Streamlit UI**: Clean, interactive web interface — no CLI needed.

---

## Demonstration

![image](https://github.com/user-attachments/assets/0ed75a54-c751-47e4-a2c0-1fe5d637c44f)

![image](https://github.com/user-attachments/assets/d45c4579-5b77-4006-b72a-e395d867b9f7)

![image](https://github.com/user-attachments/assets/6461935d-8896-40f8-ae73-4f89787dac94)

---

## 🛠️ Tech Stack

| Layer       | Technology             |

|------------|-------------------------|

| Frontend   | Streamlit               |

| LLM        | `llama3.2` via Ollama |

| Embedding  | `nomic-embed-text` via Ollama |

| Vector DB  | FAISS                   |

| STT        | Whisper (`base` model)  |

| TTS        | ElevenLabs              |

---

### Clone the repo and navigate into it

```git clone https://github.com/samay-jain/Voice_Assistant_RAG_System_using_LangChain_and_Streamlit```

### Create and activate virtual environment

```python -m venv venv && source venv/bin/activate  # On Windows use: venv\Scripts\activate```

### Install dependencies

```pip install -r requirements.txt```

### Add your ElevenLabs API key in a .env file

```echo "ELEVEN_LABS_API_KEY=your_api_key_here" > .env```

### Pull required Ollama models

```ollama pull llama3.2 && ollama pull nomic-embed-text```

### Run the app

```streamlit run main.py```

---