LiteAgents 0.3.0a5: guided feature Colabs and recovery fix

The feature Colabs now teach one task at a time: install, enter a key, and run the actual SDK calls. Each explains the expected result and what to change next. The cookbook index follows a learning progression from your first agent to tools, MCP, harness switching, and optional Temporal recovery.

This preview also fixes Pydantic AI checkpoint replay after worker restart. Fresh native conversation IDs no longer cause completed model requests and tools to run again. IDs inside application inputs and outputs are retained.

Durable deployments: upgrade clients and workers together, use a new profile version for new jobs, and finish existing jobs on their original SDK version. Stored request fingerprints change in this preview.

Try the Python tools Colab · All walkthrough previews and validation

Install the preview and the two introductory harnesses:

python -m pip install "liteagents[pydantic-ai,claude-sdk] @ https://github.com/BerriAI/liteagents/releases/download/v0.3.0a5/liteagents-0.3.0a5-py3-none-any.whl"

The PyPI project currently named liteagents is a different package. These examples use the LiteLLM SDK with your model-provider key; neither a gateway nor Temporal is required for ordinary agents.

Validation uses real harnesses, MCP processes, tools, workers, and controlled model responses. It includes repeated notebook runs, fresh wheel installation, and worker crash/restart recovery. It does not establish acceptance for every live model/provider.