This project aims to develop an end-to-end medical chatbot leveraging state-of-the-art technologies and frameworks. The chatbot will provide users with a seamless and interactive experience for obtaining medical information and assistance. The key components of the project include llama 2, Flask, llm, Langchain, and Pinecone.
llama 2 serves as the core natural language processing (NLP) engine for the chatbot. It is designed to understand and interpret user input, enabling the chatbot to respond intelligently and contextually to medical queries.
Flask is employed as the web framework to create a robust and scalable backend for the chatbot. It facilitates communication between the user interface and the underlying logic, ensuring a smooth user experience.
llm (Language Model) contributes to the project by enhancing the chatbot's language understanding capabilities. It leverages advanced machine learning techniques to improve the accuracy and relevance of responses.
Langchain is utilized for secure and efficient communication between different components of the chatbot. It ensures that data transmission is encrypted and meets the necessary security standards, especially crucial when dealing with sensitive medical information.
Pinecone serves as the intelligent indexing and search engine for the chatbot. It enables the system to quickly retrieve relevant medical information and deliver accurate responses to user queries.
- Medical Information Retrieval: The chatbot will be capable of retrieving accurate and up-to-date medical information from various sources.
- Natural Language Understanding: Leveraging llama 2 and llm, the chatbot will understand and respond to user queries in a human-like manner.
- Secure Communication: Langchain ensures secure communication, safeguarding user data and maintaining privacy.
- Intelligent Search: Pinecone enhances the chatbot's search capabilities, allowing it to provide precise and relevant answers to user questions.
- Clone the repository:
git clone https://github.com/your/repository.git - Install dependencies:
pip install -r requirements.txt - Configure API keys for llama 2, Langchain, and Pinecone in the respective configuration files.
- Run the Flask application:
python app.py - Access the chatbot interface through the provided URL.
Feel free to explore and enhance the project by integrating additional features, improving NLP models, and expanding the medical knowledge base.
Contributions to the project are welcome. Please follow the contribution guidelines outlined in the CONTRIBUTING.md file.
This project is licensed under the MIT License, granting users the freedom to use, modify, and distribute the software.