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Changelog

Haverscript is a language for building LLM-based agents, providing a flexible and composable way to interact with large language models. This CHANGELOG documents notable changes to the Haverscript project.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.2.1] - 2024-12-30

Added

  • Support for Python 3.10 and 3.11. Python 3.9 and earlier is not supported.

[0.2.0] - 2024-12-30

Added

  • Adding Middleware type for composable prompt and response handlers.

  • Middleware can be added using |, giving a small pipe-based representation of flow. The following middleware components are available:

    • echo() adds echoing of prompts and replies.
    • retry() which uses the tenacity package to provide a generic retry.
    • validate() which checks the response for a predicate.
    • stats() adds a dynamic single line summary of each LLM call.
    • cache() add a caching component.
    • transcript() adds a transcript component (transcripts the session to a file).
    • trace() logs the calls through the middleware in both directions.
    • fresh() requests a fresh call to the LLM.
    • options() sets specific options.
    • model() set the model being used.
    • format() requires the output in JSON, with an optional pydantic class schema.
    • meta() is a hook to allow middleware to act like a test-time LLM.

  • Adding prompt specific flags to Model.chat.

    • images : list[str] are images to be passed to the model.
    • middleware: Middleware appends a chat-specific middleware to the call.

  • Added Service class, that can be asked about models, and can generate Models.

  • Added response.value, which return the JSON dict of the reply, the pydantic class, or None.

  • Added spinner when waiting for the first token from LLM when using echo.

  • Added metrics to Response, which contains basic metrics about the LLM call.

  • Added render() method to Model, for outputing markdown-style session viewing.

  • Added load() method to Model, for parsing markdown-style sessions.

  • Added LLMError, and subclasses.

  • Added support for together.ai's API as a first-class alternative to ollama.

  • Added many more examples.

  • Added many more tests.

Fixed

Changed

  • Updated children method to return all children when no prompt is supplied.
  • Reworked SQL cache schema to store context as chain of responses, and use a string pool.
  • Using the cache now uses LLM results in order, until exhausted, then calls the LLM.

Removed

This release includes breaking API changes, which are outlined below. In all cases, the functionality has been replaced with something more general and principled.

The concepts that caused changes are

  • One you have a Response, that interaction with the LLM is considered done. There are no longer functions that attempt to re-run the call. Instead, middleware functions can be used to filter out responses as needed.
  • The is not longer the concept of a Response being "fresh". Instead, the cache uses a cursor when reading cached responses, and it is possible to ask that a specific interaction bypasses the cache (using the fresh() middleware).
  • Most helper methods (echo(), cache(), etc) are now Middleware, and thus more flexible.

Specifically, here are the changes:

  • Removed check() and redo() from Response. Replace it with validate() and retry() before the call to chat, or as chat-specific middleware.
  • Removed fresh from Response. The concept of fresh responses has been replaced with a more robust caching middleware. There is now fresh() middleware.
  • Removed json() from Model. It is replaced with the more general format() middleware.
  • echo() and cache() are no longer Model methods, and now Middleware instances.
  • The utility functions accept and valid_json are removed. They added no value, given the removal of redo.

So, previously we would have session = connect("modelname").echo(), and we now have session = connect("modelname") | echo().

[0.1.0] - 2024-09-23

Initial release

  • First release of the project.