Bring the starter agents' Python dependency pins (pyproject.toml + uv.lock
for adk, langgraph-fastapi, langgraph-python, pydantic-ai, strands-python;
requirements.txt + docker override for crewai-crews) in line with the
showcase fleet pin standard.
The smoke build path (docker/Dockerfile.agent) runs `uv sync` against
agent/pyproject.toml + agent/uv.lock, but those still pinned
ag-ui-langgraph==0.0.34 (and the lock still pinned copilotkit==0.1.87).
copilotkit 0.1.93 requires ag-ui-langgraph[fastapi]>=0.0.35, so uv sync
failed with "No solution found" and the langgraph-fastapi smoke job went
red. The prior fix only bumped the production Dockerfile's
`uv pip install`, which the smoke path does not use.
Bump pyproject to ag-ui-langgraph[fastapi]==0.0.37 and regenerate uv.lock
(copilotkit 0.1.87->0.1.93, ag-ui-langgraph 0.0.34->0.0.37). Verified by
building docker/Dockerfile.agent locally: uv sync now resolves and the
agent boots ("Uvicorn running on 0.0.0.0:8123" / "Application startup
complete") serving HTTP 200 on /health.
Also reconcile parity: strands-python's entrypoint.sh legitimately diverges
from the langgraph-python north-star (it boots the strands agent via
`uv run python main.py` and serves Next via `next start`, not serve.py +
standalone server.js). Add entrypoint.sh to strands-python's
allowedDivergence, mirroring how langgraph-js already declares its own
custom entrypoint. parity:check now reports 0 errors.
Jordan Ritter