This template provides a streamlined approach for developers to create custom AI LLMs using LangChain.js, enabling training on proprietary data for tailored applications. It targets developers seeking to build specialized AI assistants or knowledge bases without extensive LLM development expertise.

How It Works

The template leverages LangChain.js to manage the LLM interaction and data processing pipeline. User-provided data, formatted as markdown files within a designated training directory, is processed and stored in a vector store. This vector store facilitates efficient retrieval of relevant information to augment the LLM's responses, guided by a customizable base prompt.

Quick Start & Requirements

• Install: yarn install or npm install
• Run training: yarn train or npm train
• Run application: node index.js
• Prerequisites: Node.js, Yarn/NPM, OpenAI API Key (as OPENAI_API_KEY environment variable).

Highlighted Details

• Enables custom LLM training on user-provided markdown data.
• Utilizes LangChain.js for LLM orchestration and data retrieval.
• Customizable base prompt for tailored AI behavior.

Maintenance & Community

No specific community channels or maintenance details are provided in the README.

Licensing & Compatibility

The repository is hosted on GitHub, implying a likely open-source license, but the specific license is not stated in the README. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The template relies on OpenAI's API, incurring associated costs. The README does not detail the underlying vector store technology or provide performance benchmarks. The project appears to be a personal template rather than a widely adopted framework, with no explicit mention of community support or ongoing maintenance.