v0.14.1

Fixed

• One line in the changelog was off
• Testing the release workflow

v0.14.0

Added

• 🏷️ New expose_exception_to_llm decorator allows function exceptions to be exposed to the local language model. This is useful for when the model is running code via IPython's run_cell or any other interpreter where the model needs feedback on exceptions.

Changed

• 🔄 Package name changed from murkrow to chatlab! 💬🔬
• 🤓 Simplified the register methods of the Conversation and FunctionRegistry classes. The parameters parameters_model and json_schema are replaced by a single parameter parameter_schema, which can be a pydantic model or a JSON schema. This streamlines and simplifies the function registration process by accepting both pydantic models and JSON schema as parameter schemas in a single argument instead of two separate arguments. This reduces ambiguity and simplifies the implementation.
• 💪🏻 Improved typing for messaging
• 📝 Documentation improvements
• 📜 When outputs and inputs are too big, allow scrolling instead of overflowing
• 🔐 Check for OPENAI_API_KEY on Conversation creation

Fixed

• 🐛 Fixed the run_cell builtin to actually return the result. This reintroduces side effects of display output, meaning outputs from run_cell will now appear in the notebook and be visible to the Language Model as part of the run.
• ✅ Extended type for parameters_model is now correctly Optional[Type["BaseModel"]] so that you can extend a model for parameters in your own typed Python code. This is now mypy compliant.

Removed

• 🚗 Took out the auto_continue option since it only applied to function calls and generally should be True for function call responses

v0.13.0

Added

• 🐍 Include a builtin python chat function to handle the model's hallucination of python being an available chat function. Enable it with allow_hallucinated_python to the Conversation or the FunctionRegistry. NOTE: it runs in the same runtime as the Conversation and will be used to execute arbitrary code. Use with caution. Or delight.
• 🤩 Auto infer schemas for functions. Run session.register(function). This is a great way to get started quickly. Note: you will get better results in some cases by using You may still get better results out of using pydantic models since those can have descriptions and other metadata in the resulting JSON schema.
• 🆕 Accept functions with a JSON Schema for Function calling. This should make functions portable across any other libraries are are accepting the OpenAI standard for function calling.

Changed

• Session has been renamed to Conversation to be more understandable. Session will have a deprecation warning until it is removed for 1.0.0.
• chat has been renamed to submit to better reflect that it's sending the current batch of messages on. chat will have a deprecation warning until it is removed for 1.0.0
• Shifted some errors that bubbled up as exceptions to the end user to instead be system messages for the LLM

Removed

• Removed deltas iterator for StreamCompletion, favoring the new conversations API instead.

v0.12.3

Fixed

• Don't emit empty assistant messages

v0.12.2

Added

• Updated README with more documentation

v0.12.1

Fixed

• Fixed a bug where zero functions would create an InvalidRequestError: [] is too short - 'functions'

v0.12.0

Added

• A little chat function displayer

v0.11.4

Added

• Created a simple OpenAI chat interface for use in interactive computing environments