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output-parsers

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Successfully developed an LLM application that provides AI-powered, structured insights based on user queries. The app features a dynamic response generator with progress indicators, interactive upvote/downvote options, and a clean, engaging user interface built using Streamlit. Ideal for personalized meal, fitness, and health-related advice.

  • Updated Mar 27, 2025
  • Python

Successfully developed an interview preparation guide using Langchain which can effectively guide users in their interview preparation process and job search journeys by providing valuable insights and feedback regarding their performance. It generates a comprehensive list of questions pertaining to a user query as well.

  • Updated Apr 3, 2025
  • Python

Successfully designed and developed a customer support chatbot that leverages LangChain and Pinecone for efficient retrieval-augmented generation (RAG), enabling intelligent and context-aware responses to user queries.

  • Updated Mar 25, 2025
  • Python

Successfully developed an interview preparation guide using Langchain which can effectively guide users in their interview preparation process and job search journeys by providing valuable insights and feedback regarding their performance. It generates a comprehensive list of questions pertaining to a user query as well.

  • Updated Apr 24, 2025
  • Python

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