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MedChat - ✨RAG based AI Chatbot🤖 for Indian Medicines 🇮🇳

Explore 15K+ Indian Medicines💊 with Ease!

About The Project

MedChat🤖 is an innovative RAG-based generative AI chatbot designed for inquiries regarding Indian medicines💊. Leveraging Open web data on Indian Medicines, this project was meticulously developed using Streamlit, LangChain, and the TogetherAI API, powered by Mistral-7B. Users can pose questions or seek information about medications, and MedChat, through its advanced similarity search capabilities, delivers accurate responses in most cases. The chatbot features a chat history that spans up to two conversations, enhancing user experience and facilitating seamless interactions.

⚠️Disclaimer: The results furnished by the chatbot are for informational purposes only and may not always be accurate. It is crucial to seek advice from a qualified medical professional for precise healthcare recommendations.

Vector DB: FAISS Embedding Model: nomic-ai/nomic-embed-text-v1 LLM: Mistral-7B-Instruct-v0.2

Check out the live demo on Hugging Face

Getting Started

1. Clone the repository:

  • git clone https://github.com/harshitv804/MedChat.git

2. Download the vector db files from https://huggingface.co/spaces/harshitv804/MedChat/tree/main/medchat_db and save it in a folder named medchat_db in the same directory.

3. Install necessary packages:

  • pip install -r requirements.txt

4. Sign up with Together AI today and get $25 worth of free credit! 🎉 Whether you choose to use it for a short-term project or opt for a long-term commitment, Together AI offers cost-effective solutions compared to the OpenAI API. 🚀 You also have the flexibility to explore other Language Models (LLMs) or APIs if you prefer. For a comprehensive list of options, check out this link: python.langchain.com/docs/integrations/llms . Once signed up, seamlessly integrate Together AI into your Python environment by setting the API Key as an environment variable. 💻✨

  •  os.environ["TOGETHER_API_KEY"] = "YOUR_TOGETHER_API_KEY"`
  • If you are going to host it in streamlit, huggingface or other...
    • Save it in the secrets variable provided by the hosting with the name TOGETHER_API_KEY and key as YOUR_TOGETHER_API_KEY.

5. To run the app.py file, open the CMD Terminal and and type streamlit run FULL_FILE_PATH_OF_APP.PY.

Contact

If you have any questions or feedback, please raise an github issue.