Honcho is a sophisticated platform designed for creating AI agents and applications powered by Large Language Models (LLMs) that adapt to user needs over time. In this article, we will guide you through the various aspects of Honcho, from its structure to its functionality. Let’s dive in!
Table of Contents
Project Structure
The Honcho project is organized into multiple repositories, with this particular one hosting the core service logic. This core is implemented as a FastAPI server API that manages application state data. Additionally, there are client SDKs created using Stainless. Currently, you can access both Python and TypeScript/JavaScript SDKs. For example usage, samples are located within each SDK repository as well as in the API Reference.
Usage
Currently, there is a demo server of Honcho running at demo.honcho.dev. However, this server is not meant for production use and lacks reliability guarantees—it’s strictly for evaluation. A private beta for an isolated production-ready version of Honcho is in progress. If you’re interested, fill out this typeform to allow the Plastic Labs team to reach out for onboarding. Additionally, if you’re keen on experimenting, you can self-host Honcho for testing. Additional details on setting up a local version can be found in the Contributing file.
Architecture
The functionality of Honcho is divided into two primary services: Storage and Insights.
Storage
Honcho comprises various components used to store application and user data for managing conversations, modeling user psychology, and creating Retrieval-Augmented Generation (RAG) applications. In simple terms, think of it like a library:
- Apps
- Users
- Sessions
- Messages
- Metamessages
- Collections
- Documents
Imagine the library as “Honcho,” and the sections as follows:
- Apps: Different genres of books, each for separate features.
- Users: Bibliophiles who come into the library, where their reading preferences are noted.
- Sessions: Conversations held in cozy reading corners, reflecting discussions about books.
- Messages: Tiny notes exchanged among readers, either as their thoughts or summations.
- Metamessages: Annotations made by librarians about readers’ preferences, enhancing recommendations.
- Collections: Curated selections of books based on themes.
- Documents: Individual books with deep insights for readers.
Insights
The Insights feature pushes the functionality of Honcho beyond just storing data. As messages and sessions accumulate, Honcho asynchronously reasons about user psychology, storing essential insights in a designated collection. Developers can use these insights to tailor applications to better serve user needs via the Dialectic Endpoint. By querying this endpoint, you can gain deeper understanding about users, akin to asking a well-read librarian for tailored book suggestions.
License
Honcho is licensed under the AGPL-3.0 License. For more information, please visit the License file.
Troubleshooting
If you encounter any issues during your journey with Honcho, here are some tips:
- Ensure you have the correct environment set up as per the documentation.
- Look through the SDK documentation for example usage if you face difficulties.
- Check out the demo server access; if it is down, it may be under maintenance.
- For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.