# coding=utf-8 """ @Time :2026/6/24 @Author :tao.chen Pydantic request models for the FastAPI route layer. The underlying tool functions in tools/*.py still take keyword arguments; these models exist only so fastapi-mcp can call the routes via tools/call (which sends args as a JSON body) without 422-ing on dict-typed parameters like spark_conf. """ from pydantic import BaseModel, Field class EmptyRequest(BaseModel): """Used for tools that take no arguments (list_connections, list_pending_jobs).""" pass class SaveConnectionRequest(BaseModel): name: str master: str deploy_mode: str = "cluster" yarn_rm_url: str | None = None spark_conf: dict[str, str] | None = None ssl_verify: bool | None = None ssl_ca_bundle: str | None = None auth_type: str = "none" auth_user: str | None = None auth_password: str | None = None auth_principal: str | None = None auth_keytab: str | None = None class PrepareSubmitJobRequest(BaseModel): connection: str script_path: str = Field( ..., description=( "Absolute path to the PySpark script inside the container's " "filesystem. Must point at an existing regular file. For " "LLM-generated code, call generate_job_file(code=...) first " "and pass the returned script_path here. For pre-existing " "files on the host, mount them via a docker volume and pass " "the in-container path. Returns 400 with a remediation hint " "if the path is missing or not a file." ), ) queue: str = "default" executor_memory: str = "4G" executor_cores: int = 2 num_executors: int = 2 class PendingIdRequest(BaseModel): pending_id: str class JobIdRequest(BaseModel): job_id: str class GetJobLogsRequest(BaseModel): job_id: str tail_chars: int = 5000 class ConnectionNameRequest(BaseModel): name: str class GenerateJobFileRequest(BaseModel): code: str = Field( ..., description=( "Full PySpark source code to write to disk. Will be passed verbatim " "to spark-submit after the agent calls prepare_submit_job on the " "returned path." ), ) class ReadJobFileRequest(BaseModel): script_path: str = Field( ..., description=( "Absolute path to a PySpark script inside the container's " "filesystem. Must point at an existing regular file." ), ) class UpdateJobFileRequest(BaseModel): script_path: str = Field( ..., description=( "Absolute path to an existing PySpark script inside the " "container's filesystem. Must be under SPARK_EXECUTOR_JOBS_DIR " "(the same dir generate_job_file writes to) — protects against " "overwriting host-mounted configs or other critical files." ), ) content: str = Field( ..., description=( "New file content (replaces the file in full; no merge/diff). " "Maximum 1 MB to keep the MCP response bounded." ), )