Three-Project Series

Build a Custom Chatbot Using LangChain and ChatGPT you own this product

intermediate Python • basic API experience
skills learned
tokenize texts • store and retrieve embeddings • simplify LLM integration • deploy LangChain applications
Pablo Elgueta
3 weeks · 2-4 hours per week average · BEGINNER

pro $24.99 per month

  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose one free eBook per month to keep
  • exclusive 50% discount on all purchases

lite $19.99 per month

  • access to all Manning books, including MEAPs!


5, 10 or 20 seats+ for your team - learn more

InfoHub has a groundbreaking idea—a chatbot that can answer a company’s questions about its knowledge base just like the user was conversing with a real human expert! This idea can now become a reality thanks to the latest advances in large language models (LLMs). That’s exactly what you’ll be doing in this liveProject series! You’ll step into the developer role at InfoHub, and deliver a chatbot capable of everything from troubleshooting tech issues to answering queries about product specifications. You’ll integrate GPT-3.5 into a chatbot to understand user questions and retrieve related embeddings, utilize ChromaDB to manage storage and retrieval, and then deploy the whole system via Streamlit.

These projects are designed for learning purposes and are not complete, production-ready applications or solutions.

here's what's included

Project 1 Augment with Embeddings

In this liveProject, you’ll become a software engineer at InfoHub, an up-and-coming AI startup looking to revolutionize how companies interact with their knowledge bases. InfoHub seeks to utilize groundbreaking large language models to deliver a system whereby a user’s questions about company data can be answered through a Q&A-style language interface. You’ll begin by assisting them in creating this tool by processing, tokenizing, and converting data into embeddings with BeautifulSoup and tiktoken.

Project 2 Q&A Using Vector Databases

In this liveProject, you'll join InfoHub, an AI startup disrupting corporate knowledge management. They aim to unlock a company’s knowledge base through conversational Q&A-style user interfaces that use breakthrough language models. You'll leverage LangChain, a framework optimized for integrating LLMs into apps, to integrate InfoHub's data, vector stores, and language models into a single solution. You’ll prepare your data, create a vector store to embed your documents, and then use LangChain to combine it with an LLM.

Project 3 Build and Deploy the Chatbot

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.

book resources

When you start each of the projects in this series, you'll get full access to the following book for 90 days.

choose your plan


only $41.67 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Build a Custom Chatbot Using LangChain and ChatGPT project for free

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 series 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 tokens
  • Basics of embeddings
  • Basics of LLMs

you will learn

In this liveProject series, you’ll learn the ins and outs of building an LLM-based chatbot application, working with groundbreaking foundation models.

  • Tokenize texts for large language models utilizing tiktoken, which is crucial for obeying token limits
  • Store and retrieve embeddings and processed data efficiently using pandas DataFrames
  • Traverse directories and subdirectories thoroughly using the OS library's os.walk function
  • Simplify LLM integration for applications utilizing the LangChain framework
  • Convert textual data into numerical embeddings utilizing OpenAI's large language models
  • Combine language models with vectorized data to swiftly answer users' queries accurately via RetrievalQA
  • Easily deploy LangChain applications and provide API access utilizing LangServe
  • Build front-end ML applications leveraging the open-source Streamlit framework


You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.