TritonGPT Release Notes

TritonGPT updated with a refreshed UI design and the ability to save and organize chats. Users can now upload and interact with documents using an AI Assistant. Additionally, users can search across all documents and websites, switch between Assistants within a chat flow, and access a Prompt Gallery to reuse previously created prompts. Other new features include the ability to see the context behind an Assistant's response, share chats with others, and interact with specific sources within the chat flow. A new AI Assistant, Fund Manager Coach, is now broadly available. View more detailed release notes.

TritonGPT is now available to all employees that are part of campus and health sciences, totalling close to 37,000 faculty, staff and student staff. If you are part of those units and are having difficulty accessing TritonGPT, contact the Service Desk. 

TritonGPT now uses the Llama 3 LLM to power the UC San Diego Assistant and the General AI Assistant. Llama 3 was trained on a much larger dataset (15T tokens) compared to Llama 2 (2.2T tokens), resulting in improved performance across various benchmarks. Llama 3 offers better reasoning abilities, code generation, and instruction-following capabilities compared to Llama 2.

As part of this enhancement, an upgrade was made to the Virtual Large Language Model (VLLM) environment. VLLM is a powerful and versatile open-source library that makes it easier and more efficient to use large language models (LLMs) for inference and serving. 

TritonGPT now uses campus Single Sign-on for authentication. This replaces the previous authentication method which was the Google Authenticator. This deployment also included some minor user interface improvements.

Enhancements and bug fixes to JD Helper: updated wording in the JD Helper flow to clarify what is needed in order to produce better outcomes in retrieving job cards. Enhanced JD Helper system prompt to provide more robust output. 

Launched production candidate that will support use by employees of campus and health sciences. Danswer enterprise code base and larger embedding model. User experience improvements. 

Added additional hardware into the environment in perparation for campus launch. 

Initial proof of concept version deployed and made available to over 400 pilot users.