pydantic-deep
Batteries-included agent harness for Python — tool-calling, sandboxed execution, multi-agent teams, and unlimited context on Pydantic AI
Decision gist · record as of 2026-08-14
Yes—if 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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Needs a valid model provider API key (Anthropic, OpenAI, etc.) and an async runtime to execute agent.run().
- Low friction: pure Python wheel with no compiled dependencies.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) means you can use, modify, and redistribute freely in commercial or private projects with minimal restrictions—just include the license notice.
last release 2026-08-05 (9 days) · last repo commit 2026-08-05 · 1,030 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 127,515 downloads/mo, #11,740 on PyPI
Alternatives
Verify before relying
pip install pydantic-deep
from pydantic_deep import create_deep_agent
agent = await create_deep_agent(model="anthropic:claude-sonnet-4-6")
result = await agent.run("Build a REST API for auth")- Whether all 8 runtime dependencies (chardet, pydantic-ai-backend, pydantic-ai-shields, pydantic-ai-slim, pydantic-ai-todo, pydantic, subagents-pydantic-ai, summarization-pydantic-ai) are stable or also in beta.
- Actual resource overhead and latency of live run forking with copy-on-write filesystem overlays under typical workloads.
- Whether Docker sandbox execution is required or optional for the framework use case.
- Production readiness and breaking-change stability policy given the beta status and rapid release cadence.
What it is and 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).
The 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—no 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.
Use it for
- Build a self-hosted terminal coding assistant that plans, edits files, runs tests, and searches the web—on 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.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes—if 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.
Install
pydantic-deep on PyPI
Before you install
Low friction: pure Python wheel with no compiled dependencies. Active maintenance—released 9 days ago with recent commits. Early beta status (Development Status 4) but 1030 GitHub stars and 127515 monthly downloads suggest solid adoption for a young project (first release December 2025).
Requires Python 3.10 or later. Needs a valid model provider API key (Anthropic, OpenAI, etc.) and an async runtime to execute agent.run().
License in practice
MIT license (permissive) means you can use, modify, and redistribute freely in commercial or private projects with minimal restrictions—just include the license notice.
Quickstart
pip install pydantic-deep
from pydantic_deep import create_deep_agent
agent = await create_deep_agent(model="anthropic:claude-sonnet-4-6")
result = await agent.run("Build a REST API for auth")Verify before relying
- Whether all 8 runtime dependencies (chardet, pydantic-ai-backend, pydantic-ai-shields, pydantic-ai-slim, pydantic-ai-todo, pydantic, subagents-pydantic-ai, summarization-pydantic-ai) are stable or also in beta.
- Actual resource overhead and latency of live run forking with copy-on-write filesystem overlays under typical workloads.
- Whether Docker sandbox execution is required or optional for the framework use case.
- Production readiness and breaking-change stability policy given the beta status and rapid release cadence.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packageschardetpydantic-ai-backendpydantic-ai-shieldspydantic-ai-slimpydantic-ai-todopydanticsubagents-pydantic-aisummarization-pydantic-ai |
| Maintenance | Actively maintained 9 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 127,515 / month, #11,740 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: pydantic_deep-0.3.43-py3-none-any.whl
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See also agent-utilities · pydantic-ai-backend · pydantic-ai-harness · subagents-pydantic-ai · pydantic-ai · pydantic-ai-todo · deepagents · summarization-pydantic-ai · altimate-datapilot-cli · autokeren