Major updates

• New Prompt Engineering Algorithm: The upgraded prompt engineering algorithm implements the PE2 method, which significantly enhances the quality of created prompts.
  • Benchmark Update: Demonstrates a considerable advancement over the zero-shot setup, with a 20% improvement demonstrated in the GSM-8k benchmark.
• CodeEnvironment Introduction: This feature allows the execution and validation of code generated by the Agent. For instance, Python code synthesized by the Agent is checked for errors within this environment, enabling continuous improvement.
  • Guide to Code Generation: A tutorial on crafting a code generation agent, focusing on Python script development for data format conversion.
• Custom Matching Function: Users can now define their own matching function to align agent predictions with ground truth examples.

Minor improvements

• instructions_first Parameter: This offers greater control over how the final prompt is structured prior to execution by the Runtime, particularly useful for tasks involving large pieces of text.
• Prompt Diffs: This feature in the Notebook environment highlights incremental changes in the instruction generation history.
• Skill Improvement Without Explicit Feedback: Enables enhancement of skills indirectly.
• CI/CD Enhancements: Integration of code formatting and test-checking features.
• OpenAI API Retry Mechanism: Addition of retries for the OpenAI API, addressing issues reported in https://github.com/HumanSignal/Adala/issues/41.

Full Changelog: https://github.com/HumanSignal/Adala/compare/0.0.3...0.0.4