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pineconedb

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Develop an advanced chatbot leveraging cutting-edge technologies capable of file uploads, enabling users to receive tailored responses based on the content of the uploaded files. Integrate various tools and agents to enhance the chatbot's capability for comprehensive and accurate responses.

  • Updated Jan 24, 2024
  • Python

The Medical Chatbot, built with Flask, integrates NLP libraries like Langchain and Hugging Face Transformers for text processing and embedding generation. Utilizing Pinecone as a vector database, it efficiently stores and retrieves data, offering users an interactive platform for medical inquiries.

  • Updated Apr 6, 2024
  • Python

Learning NextJs 14 with app router. Messing with proper server/client component architecture, Next API routes, Next streaming, Next cache beta, retrieval augmented generation with OpenAI embeddings API, PineconeDB to store context/query embeddings, and chatbot with OpenAI prompt.

  • Updated Jan 16, 2024
  • TypeScript

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