Build and Deploy the Chatbot you own this product

basics of software architecture • intermediate API experience
skills learned
create a chatbot using LangServe and Streamlit • deploy to the cloud through Streamlit Cloud

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In this liveProject, you’ll step into the role of a software developer at InfoHub, an AI startup attempting to build a chatbot that can answer queries about a company’s knowledge base. You’ve already built the basics of the chatbot—now it needs to be deployed! To do this, you’ll use the LangChain feature LangServe to create a LangChain server application. You’ll build your chatbot using Streamlit and then deploy it to the Streamlit cloud.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Pablo Elgueta
Over the past seven years, Pablo has been deeply involved in the tech industry, specifically focusing on software product development for the last four years. He worked at Microsoft, where he expanded his expertise in large-scale technology solutions. His academic journey led him to earn an MSc in Data Science and Machine Learning, where he researched the application of OpenAI’s GPT3 to predict cryptocurrency prices for his dissertation. Pablo has also spoken at the API Days conference, discussing the practical implementation of Large Language Models (LLMs). He has developed 'FanPods,’ an innovative app that turns text into AI-driven audiobooks. As an LLM Engineer at AffiliateAI, Pablo is crafting solutions for chat-based data retrieval using LLMs.


This liveProject is for intermediate-level Python developers. No special tools are required—you can perform everything you need using a normal IDE or Jupyter Notebook.

  • Intermediate Python
  • Basics of Pandas
  • Basics of the OpenAI API
  • Basics of software engineering
  • Intermediate API experience

  • Basics of tokens
  • Basics of embeddings
  • Basics of LLMs


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