Michael Chang's blog post introduces "data-driven-characters," a repository designed to create and interact with character chatbots grounded in existing corpora, such as movie transcripts, using LangChain. This tool provides users with the ability to export character definitions to platforms like character.ai, debug locally, or host a Streamlit app in their browser, offering more control over memory management and character grounding than existing solutions like character.ai. The tool allows for the creation of chatbots that maintain character integrity by utilizing detailed backstory information, thus enhancing the authenticity and informativeness of interactions. Through several example architectures, data-driven-characters demonstrates how different methods of packaging information—such as character summaries and transcript retrieval—affect the chatbot's responses. While character.ai offers accessibility and entertainment, data-driven-characters provides a customizable experience, enabling users to upload any corpus and chat with any character, albeit with some limitations in replicating dialogue style. The project aims to foster a decentralized ecosystem for creating bespoke data-driven characters, inviting contributions from the community to expand its capabilities and improve user interfaces.