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output-parsers

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This repository covers all the code materials covered within Jose Portilla's Langchain with Python Bootcamp on Udemy.

  • Updated May 2, 2025
  • Jupyter Notebook

Successfully developed a Multi-Domain AI Personal Assistant using LangChain, OpenAI, and Streamlit. The application seamlessly integrates multiple specialized capabilities, including document-based question answering (QA), Python code execution, debugging, explanation and optimization, web search, latest news retrieval, and currency conversion.

  • Updated May 2, 2025
  • Python

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

This repo showcases using Grok AI prompts with LangChain templates to build dynamic AI workflows. It supports prompt formats including YAML, XML, chat-based, and string prompts. Users can create reusable, structured prompts for conversational AI and data parsing. Perfect for integrating flexible prompt management with AI models efficiently.

  • Updated May 25, 2025
  • Jupyter Notebook

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 3, 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 Jun 1, 2025
  • Python

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