Join me in this tutorial as we delve into the creation of an advanced Health Care Chatbot leveraging the capabilities of open-source technologies. Discover the utilization of Sentence Transformers for embeddings, employ Faiss CPU for vector storage, and seamlessly integrate Llama 2, a robust language model, using the Streamlit library to establish a dynamic conversational interface. Embark on this step-by-step journey with us to craft a smart and effective HealthCare Chatbot, harnessing readily available resources. Whether you’re new to the field or an experienced enthusiast, explore the realm of conversational AI and drive healthcare innovation right away.
This HealthCareBot was built using Llama2 and Sentence Transformers. The bot is powered by Langchain and Streamlit. The bot runs on a decent CPU machine with a minimum of 14GB of RAM.
#ai #langchain #streamlit #largelanguagemodels #generativeai #llama2 #llm
Github Code to Project:https://github.com/InsightEdge01/LLama2HealthCareChatBot/tree/master
llama2 (Quantized model):https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
Faiss GitHub: https://python.langchain.com/docs/integrations/vectorstores/faiss
Sentence Transformers Hugging Face: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
CTransformers GitHub: https://github.com/marella/ctransformers
Buy me Coffee:https://www.buymeacoffee.com/DataInsightEdge
Llama2-70B-Multi-Document Chatbot: https://youtu.be/vhghB81vViM?si=zW8-RRCL4jdz_eS4