{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/18"}],"enrichment":{"capability":"A Python framework and terminal assistant for building autonomous AI agents with tool-calling, sandboxed execution, multi-agent coordination, and live run forking\u2014all type-safe and model-agnostic.","skillfed_tags":["agent-framework","llm-tool-calling","multi-agent"],"use_cases":["Build a self-hosted terminal coding assistant that plans, edits files, runs tests, and searches the web\u2014on your choice of model.","Spawn multi-agent teams with shared TODO lists and peer messaging to parallelize research, code review, or data processing tasks.","Prototype agentic workflows with automatic fallback-model retry, persistent memory across sessions, and sandboxed Docker execution.","Use live run forking to explore multiple solution branches in a single agent run and let test results or an AI judge pick the best approach.","Build type-safe structured-output agents that connect to MCP servers (GitHub, Figma, custom) without rewiring the plumbing each time.","Deploy headless agents with unlimited context that auto-summarize when approaching token limits, never hitting a context wall."],"what_it_does":"Pydantic Deep Agents is a complete agent harness built on Pydantic AI that lets you build autonomous AI assistants in Python or run one as a self-hosted terminal TUI. It wraps an LLM with planning, tool-calling (file I/O, shell, web search, browser automation), persistent memory, multi-agent coordination, sandboxed execution, and unlimited context via auto-summarization. The framework is 100% type-safe and works with any model provider (Claude, GPT, Gemini, local).\n\nThe standout feature is live run forking: when an agent faces a decision (e.g., \"refactor with a decorator or context manager?\"), it can branch the run into parallel isolated copies, each trying a different approach. An AI judge or test-runner output picks the winner, and the winning branch's history becomes the parent run's continuation. This is unique to pydantic-deep\u2014no other agent framework has it. You can use it as a library (one `create_deep_agent()` call) or as a CLI tool without Python setup.","worth_installing":"Yes\u2014if you want to build or run an autonomous AI agent in Python. The framework is actively maintained, MIT-licensed, has low install friction, and offers unique features (live run forking, multi-agent coordination, type safety) that other agent libraries don't. Beta status and rapid release cadence mean breaking changes are possible, but 1030 stars and 127515 monthly downloads suggest the community is already adopting it. Start with the terminal assistant to see if the model fits your workflow, then drop into the framework if you need to customize."},"id":"pydantic-deep","links":{"html":"https://skillfed.io/packages/pydantic-deep","md":"https://skillfed.io/packages/pydantic-deep.md","pypi":"https://pypi.org/project/pydantic-deep/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-05","license_spdx":"MIT","license_treatment":"permissive","name":"pydantic-deep","python_support":"supports_current","summary":"Batteries-included agent harness for Python \u2014 tool-calling, sandboxed execution, multi-agent teams, and unlimited context on Pydantic AI"},"popularity":{"monthly_downloads":127515,"position":11740,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.43"}