Xi Zhang
7959495a13
* feat(deploy): implement standalone LangGraph server and CLI command for deployment * feat(deploy): enhance port validation and environment variable management for deployment * Refactor langgraph dev deployment and introduce workspace sidecar protocol - Updated the deployment mode handling in `server.py` to use a single environment variable `EVOSCIENTIST_DEPLOY_MODE` with values `full` and `stripped`. - Enhanced the `manager.py` to implement a workspace fingerprint sidecar, allowing cross-process reuse of langgraph dev instances while ensuring workspace consistency. - Introduced functions to write and read the workspace sidecar, with error handling for missing or corrupt data. - Added tests for the workspace sidecar functionality, including validation of the JSON schema and ensuring proper error handling for workspace mismatches. - Updated existing tests to reflect changes in deployment mode handling and added new tests for signal handling during shutdown. - Ensured that cleanup routines remove the workspace sidecar alongside the PID file during shutdown. * fix(langgraph): improve workspace sidecar checks for process ownership and stale handles
23 lines
809 B
Python
23 lines
809 B
Python
"""EvoScientist deploy mode.
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Standalone LangGraph server launcher. ``EvoSci deploy`` starts a
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``langgraph dev`` subprocess hosting the fully-equipped main agent
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(MCP + async sub-agents enabled), exposed at
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``http://localhost:{port}`` for external LangChain-compatible UIs
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and SDK clients.
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This module is intentionally separate from ``EvoScientist.cli``:
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deploy mode does NOT load an in-process CLI agent, session DB, channel
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runtime, or TUI — those are all TUI / serve concerns. Deploy only
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manages the lifecycle of the langgraph dev subprocess (and ccproxy if
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OAuth is configured).
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"""
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from __future__ import annotations
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# Importing the server submodule registers the ``@app.command()`` decorator
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# on the shared Typer ``app`` from ``EvoScientist.cli._app``.
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from . import server
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__all__ = ["server"]
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