https://github.com/extrawest/conversational_rag_pdf

Conversational RAG with PDF and chat history
https://github.com/extrawest/conversational_rag_pdf

ai chatbot chromadb gemma2 groq groq-api huggingface-embeddings langchain rag streamlit streamlit-webapp vector-database

Last synced: 6 months ago
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Conversational RAG with PDF and chat history

• Host: GitHub
• URL: https://github.com/extrawest/conversational_rag_pdf
• Owner: extrawest
• License: apache-2.0
• Created: 2024-11-05T15:25:26.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-11-05T15:45:13.000Z (11 months ago)
• Last Synced: 2025-03-30T17:46:37.714Z (7 months ago)
• Topics: ai, chatbot, chromadb, gemma2, groq, groq-api, huggingface-embeddings, langchain, rag, streamlit, streamlit-webapp, vector-database
• Language: Python
• Homepage:
• Size: 15.6 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
#  Conversational RAG with PDF and chat history showcase

[![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)]()

[![Maintaner](https://img.shields.io/static/v1?label=Andriy%20Gulak&message=Maintainer&color=red)](mailto:andriy.gulak@extrawest.com)

[![Ask Me Anything !](https://img.shields.io/badge/Ask%20me-anything-1abc9c.svg)](https://github.com/extrawest/conversational_rag_pdf/issues)

[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

## PROJECT INFO

- **Langchain RAG with PDF**

- Streamlit for interactive app and slick UI

- **Chatbot with RAG capabilities. Works with Gemma2-9b via Groq API**

## Features

- Langchain AI RAG Chatbot

- HuggingFace Embeddings - all-MiniLM-L6-v2

- Gemma2-9b-It via Groq API

- Chroma DB Vector Store

- Streamlit for interactive data fullstack apps

## Demo

[rag.webm](https://github.com/user-attachments/assets/1c3a3795-ed3c-4703-9aa8-27c2f90b4c34)

## Installing:

**1. Clone this repo to your folder:**

```

git clone THIS REPO

```

**2. Create a virtual environment**

**3. Install the dependencies**

```

pip install -r requirements.txt

```

**3. Run the app**

```

streamlit run app.py

```

[Extrawest.com](https://www.extrawest.com), 2024