https://github.com/fosetorico/chat-with-multiple-pdf-documents
End-to-End PDF Chatbot for Conversational Search and Knowledge Extraction from Multiple PDF Documents using advanced text processing, FAISS vector storage, Gemini AI, and Google Generative AI embeddings for accurate and context-aware responses.
https://github.com/fosetorico/chat-with-multiple-pdf-documents
chatbot faiss-vector-database gemini googlegenerativeai llm vector-database
Last synced: about 1 year ago
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End-to-End PDF Chatbot for Conversational Search and Knowledge Extraction from Multiple PDF Documents using advanced text processing, FAISS vector storage, Gemini AI, and Google Generative AI embeddings for accurate and context-aware responses.
- Host: GitHub
- URL: https://github.com/fosetorico/chat-with-multiple-pdf-documents
- Owner: fosetorico
- License: mit
- Created: 2025-01-24T14:36:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-07T16:59:42.000Z (over 1 year ago)
- Last Synced: 2025-02-07T17:36:48.020Z (over 1 year ago)
- Topics: chatbot, faiss-vector-database, gemini, googlegenerativeai, llm, vector-database
- Language: Python
- Homepage: https://huggingface.co/spaces/valleeneutral/multi-PDF_chatBot
- Size: 842 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Research Bot for PDF-Based Data Summarization and Insight Extraction
#### Link: https://huggingface.co/spaces/valleeneutral/multi-PDF_chatBot
This project is an AI-powered chatbot designed to summarize, analyze, and extract insights from multiple PDF documents. It leverages Google Gemini AI, FAISS vector storage, and Google Generative AI embeddings to provide accurate, context-aware responses based on document content.
## Features
1. Multi-PDF Chat Support – Query multiple documents in one session.
2. Google Gemini AI – Generates intelligent, human-like responses.
3. FAISS Vector Storage – Efficient document chunk retrieval.
4. Google Generative AI Embeddings – Enhances contextual understanding.
## Steps to run this Project
#### 1. Clone the repository
```
git clone https://github.com/fosetorico/Chat-With-Multiple-PDF-Documents.git
```
#### 2. Create a conda environment after opening the repository
```
conda create -n your-chosen-name python=3.10 -y
```
```
conda activate your-chosen-name
```
#### 3. Rename the '.env.example' file to '.env' and insert your Google API key
#### 4. Install the requirements
```
pip install -r requirements.txt
```
#### 5. Finally run the following command
```
streamlit run app.py
```