Streamlit PDF Chatbot 🤖

An AI-powered chatbot built with Streamlit that allows users to upload PDF documents and have interactive conversations about their content using OpenAI and LangChain.

Features

• PDF Upload & Processing — Upload single or multiple PDF files for analysis
• Conversational Q&A — Ask questions about your documents in natural language
• Vector Search — Uses FAISS for efficient semantic similarity search
• Conversation Memory — Maintains chat context across multiple questions
• Animated UI States — Visual feedback with animated states (reading, thinking, welcoming)

Tech Stack

• LLM: OpenAI GPT-3.5 Turbo
• Embeddings: OpenAI Embeddings
• Vector Store: FAISS
• Text Processing: LangChain CharacterTextSplitter
• PDF Parsing: PyPDF2
• Framework: Streamlit

How It Works

PDF Upload → Text Extraction → Chunking → Embeddings → FAISS Vector Store
                                                            ↓
User Question → Semantic Search → Relevant Chunks → LLM → Answer

Setup

1. Clone the repository

git clone https://github.com/nofaukost/Streamlit-Chatbot.git
cd Streamlit-Chatbot

2. Install dependencies

pip install -r requirements.txt

3. Set up environment variables

echo "OPENAI_API_KEY=your_api_key_here" > .env

4. Run the app

streamlit run app.py

Project Structure

├── app.py              # Main Streamlit application
├── htmlTemplates.py    # HTML/CSS templates for chat UI
├── requirements.txt    # Python dependencies
├── *.gif               # Animated UI state indicators
└── .env                # Environment variables (not tracked)

License

MIT