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Pydantic Deepagents
Build Claude Code–style deep agents in Python: tool-calling, sandboxed execution, multi-agent teams, skills, checkpoints, and unlimited context — all on Pydantic AI.
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01
At a glance.
A compact read before the deeper capability notes and official setup links.
02
Core features.
Feature cards focus on what the tool helps users do, not generated setup commands.
The batteries-included deep agent harness for Python. .
Terminal AI assistant out of the box — or build production agents with one function call.
2026-04-22 v0.3.17 — LiteParse document parsing toolset (includeliteparse=True).
Subagents still get BASEPROMPT automatically.
2026-04-12 v0.3.8 — Stuck loop detection, context limit warnings for the model, expanded context file discovery (CLAUDE.md, .cursorrules, etc.), eviction & orphan repair migrated to capabilities hooks.
2026-04-10 v0.3.5 — Headless runner (pydantic-deep run), Docker sandbox with named workspaces, browser automation via Playwright, Harbor adapter for Terminal Bench evaluation.
Pydantic Deep Agents is an agent harness — the complete infrastructure that wraps an LLM and makes it a functional autonomous agent.
The model provides intelligence; the harness provides planning, tools, memory, sandboxed execution, and unlimited context.
04
Agent / Skill / MCP / Workflow fit.
This panel keeps technical format separate from the user-facing AI category.
05
Official setup path.
Generated install snippets are intentionally not mirrored here because they drift. The page links to source-owned setup docs instead.
06
Evidence and adoption notes.
These notes help a user decide whether to investigate the official project further.
Source repository last pushed at 2026-05-18T10:13:01Z.
Generated from source metadata; confirm operational details in the official project before adopting it.
Review the upstream license, maintenance activity, and issue history before using it in production.
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