Claude
6b9f278294
The plan's route signatures used query parameters, which worked for direct HTTP callers and unit tests, but fastapi-mcp's HTTP transport passes tools/call arguments as a JSON body. dict-typed parameters like spark_conf arrived as a string and the route returned 422. Refactor each route to take a single Pydantic body model (saved in spark_executor/tools/requests.py). Underlying tool functions unchanged. Integration tests in tests/integration/test_mcp_routes.py now exercise the full body-based roundtrip (save_connection with spark_conf, prepare → list → get, list_connections with empty body).
51 lines
1.1 KiB
Python
51 lines
1.1 KiB
Python
# coding=utf-8
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"""
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@Time :2026/6/24
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@Author :tao.chen
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Pydantic request models for the FastAPI route layer. The underlying tool
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functions in tools/*.py still take keyword arguments; these models exist only
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so fastapi-mcp can call the routes via tools/call (which sends args as a
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JSON body) without 422-ing on dict-typed parameters like spark_conf.
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"""
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from pydantic import BaseModel, Field
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class EmptyRequest(BaseModel):
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"""Used for tools that take no arguments (list_connections, list_pending_jobs)."""
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pass
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class SaveConnectionRequest(BaseModel):
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name: str
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master: str
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deploy_mode: str = "cluster"
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yarn_rm_url: str | None = None
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spark_conf: dict[str, str] | None = None
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class PrepareSubmitJobRequest(BaseModel):
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connection: str
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script_path: str
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queue: str = "default"
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executor_memory: str = "4G"
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executor_cores: int = 2
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num_executors: int = 2
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class PendingIdRequest(BaseModel):
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pending_id: str
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class JobIdRequest(BaseModel):
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job_id: str
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class GetJobLogsRequest(BaseModel):
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job_id: str
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tail_chars: int = 5000
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class ConnectionNameRequest(BaseModel):
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name: str
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