Welcome to the Santaan Chatbot repository. This project was developed for Santaan Startup and serves as an intelligent medical assistant, designed to provide precise, document-based responses to user queries. Leveraging advanced AI technologies, this chatbot ensures accurate and contextually relevant interactions.
- Provides contextual answers by extracting information from medical resources.
- Utilizes state-of-the-art language models for high-quality response generation.
- Employs search with embeddings and vector storage for efficient query handling.
- Includes a user-friendly interface powered by Streamlit.
- Designed for scalability and adaptability in medical assistant applications.
chunker.py: Responsible for loading PDF files and splitting them into smaller, manageable text chunks for processing.embedder.py: Initializes the Hugging Face embeddings model for vector representation of the text chunks.vdb.py: Handles Pinecone vector store operations, including indexing and performing similarity searches on embeddings.chatbot.py: Implements the chatbot’s Streamlit interface, integrating document search and response generation functionalities.requirements.txt: Lists all dependencies necessary to set up and run the project.
- Clone the Repository
Clone the repository using the following command:git clone https://github.com/your-repo/santaan-chatbot.git cd santaan-chatbot - Install Dependencies
Install the required dependencies by running:
pip install -r requirements.txt
- Set Environment Variables
Create a .env file in the root directory and include the following:
PINECONE_API_KEY=your_pinecone_api_key GROQ_API_KEY=your_groq_api_key
- Run the Application
Start the Streamlit application using the command:
streamlit run chatbot.py
- Interact with the Chatbot Open the URL provided by Streamlit in your browser and start chatting! 💬
Developed with ❤️ by Dharsini Sri Balasubramaniam
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