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.
Vector DB: FAISS
Embedding Model: nomic-ai/nomic-embed-text-v1
LLM: Mistral-7B-Instruct-v0.2
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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.
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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. 💻✨
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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 asYOUR_TOGETHER_API_KEY
.
- Save it in the secrets variable provided by the hosting with the name
5. To run the app.py
file, open the CMD Terminal and and type streamlit run FULL_FILE_PATH_OF_APP.PY
.
If you have any questions or feedback, please raise an github issue.