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@hmirin hmirin released this 01 Feb 14:37
· 36 commits to main since this release
v0.2.0
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PromptTrail v0.2.0 Release Notes

We're excited to announce the release of PromptTrail v0.2.0, featuring significant improvements in modular agent development, model support, and developer experience.

Major Features

Subroutines for Modular Agents

  • Introduced SubroutineTemplate for creating modular, reusable components within larger agents
  • Added flexible session initialization with SessionInitStrategy:
    • CleanSessionStrategy for isolated contexts
    • InheritSystemStrategy for system message preservation
    • LastNMessagesStrategy for recent context retention
    • FilteredInheritStrategy for custom message selection
  • Implemented SquashStrategy for post-execution message handling:
    • LastMessageStrategy for final output retention
    • FilterByRoleStrategy for role-based filtering
    • LLMFilteringStrategy and LLMSummarizingStrategy for AI-powered context management

Enhanced Model Support

  • Added support for Google Gemini and Anthropic Claude Sonnet models
  • Added local LLM support using Hugging Face Transformers

API Improvements

  • Unified configuration system:
    • Merged Parameters into consolidated Config class
    • Streamlined model settings and API key management
  • Introduced unified ToolingTemplate supporting both OpenAI and Anthropic models
  • Standardized message roles across all models
  • Implemented new logging system with Debuggable base class

Technical Updates

Dependency Upgrades

  • anthropic: v0.45.2
  • openai: v1.61.0
  • google-generativeai: v0.8.4

Code Quality Improvements

  • Renamed Message.sender to Message.role for industry standard alignment
  • Simplified model class names (e.g., OpenAIChatCompletionModel to OpenAIModel)
  • Enhanced type safety in tool system
  • Transitioned to session-based state management
  • Implemented template-driven API enhancements
  • Streamlined metadata handling in Session class

Developer Tools

  • Added automated code review bot (examples/dogfooding/auto_code_review.py)
  • Enhanced project documentation and tooling processes
  • Improved debugging capabilities through standardized logging

For detailed documentation and migration guides, please refer to our documentation website.

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