deepagents
https://github.com/langchain-ai/deepagents
Python
Deep Agents is an agent harness built on langchain and langgraph. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped to handle complex agentic tasks.
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- Issues
- perf(sdk): cache converted OpenAI tool schema for token counting
- ModelCallLimitMiddleware + `response_format` ends with empty structured_response l
- Add `fork` option to the `task` tool so subagents can inherit parent conversation history
- `invalid_tool_calls` end the run silently and deferred repair is marked successful
- Notify when a background async task finishes
- Add `ToolSelectionMiddleware` for per-turn tool filtering
- MCP-prefixed tool names can collide with MCP and built-in tools
- Improve profile lookup for `provider:model` variant specs
- Add structured JSON output to headless dcode
- BaseSandbox.grep silently fails on backends whose execute() transport is text-only (the -Z NUL separator is stripped) — e.g. Daytona
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