Skip to content

v0.10.0
Compare
Choose a tag to compare
@bakaburg1 bakaburg1 released this 29 May 15:24
· 1 commit to main since this release
v0.10.0
1383da7
This commit was created on github.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.

Enhancements

  • Change interrogate_llm to prompt_llm: Renamed the interrogate_llm function to prompt_llm to better reflect its purpose of generating prompts for language models (Commit: [2f9eedd]).
  • Model Logging for LLM Requests: Added a log_request parameter to use_openai_llm, use_azure_llm, and use_custom_llm functions to log the specific endpoint and model being used (Commit: [7e85f2f]).
  • Handling Long LLM Responses: Improved the handling of LLM responses that exceed the output token limit. Users are now prompted to decide how to proceed, and incomplete answers are saved to a file for reference (Commit: [18cfada]).
  • Model Parameter for Custom LLM APIs: Added a model parameter to LLM calls to allow specifying a model for custom APIs with multiple models (Commit: [cd4227b]).

Fixes

  • Restore Correct Speaker Extraction for Webex VTT: Fixed the parsing of Webex VTT files which was broken by the implementation of MS Teams VTT parsing (Commit: [d189980]).
  • Remove Newlines from JSON Output: Fixed an issue where some custom LLMs produced invalid JSON with newlines, causing errors during parsing (Commit: [e9e578a]).
  • Support JSON Mode for Custom LLMs: Ensured that most custom LLMs now support JSON mode by keeping the JSON mode option in the call (Commit: [f4df24c]).

Documentation

  • Improve Code Comments and Error Handling: Enhanced code comments and error handling for better clarity and maintenance (Commit: [4b689ff]).

Summary

This pull request introduces several enhancements to the LLM handling, including logging the model being used, better management of long responses, and support for specifying models in custom APIs. It also includes fixes for speaker extraction in Webex VTT files and handling of JSON outputs from custom LLMs. Additionally, code comments and error handling have been improved for better clarity.

In the land of code so bright,
LLMs now log their might.
Webex speakers found their way,
JSON errors kept at bay.
With models clear and prompts so neat,
Minutemaker's now complete!

Full Changelog: v0.9.0...v0.10.0

Assets 2
Loading