62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
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import asyncio
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from app.core.exceptions import LLMCallError
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from app.core.logging import get_logger
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from app.models.finetune_models import (
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FinetuneStartRequest,
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FinetuneStartResponse,
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FinetuneStatusResponse,
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)
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logger = get_logger(__name__)
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_STATUS_MAP = {
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"running": "RUNNING",
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"succeeded": "SUCCESS",
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"failed": "FAILED",
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}
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async def submit_finetune(req: FinetuneStartRequest, llm) -> FinetuneStartResponse:
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"""Submit a fine-tune job to ZhipuAI and return the job ID."""
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loop = asyncio.get_event_loop()
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try:
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response = await loop.run_in_executor(
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None,
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lambda: llm._client.fine_tuning.jobs.create(
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training_file=req.jsonl_url,
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model=req.base_model,
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hyperparameters=req.hyperparams or {},
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),
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)
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job_id = response.id
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logger.info("finetune_submit", extra={"job_id": job_id, "model": req.base_model})
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return FinetuneStartResponse(job_id=job_id)
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except Exception as exc:
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logger.error("finetune_submit_error", extra={"error": str(exc)})
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raise LLMCallError(f"微调任务提交失败: {exc}") from exc
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async def get_finetune_status(job_id: str, llm) -> FinetuneStatusResponse:
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"""Retrieve fine-tune job status from ZhipuAI."""
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loop = asyncio.get_event_loop()
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try:
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response = await loop.run_in_executor(
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None,
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lambda: llm._client.fine_tuning.jobs.retrieve(job_id),
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)
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status_raw = response.status
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status = _STATUS_MAP.get(status_raw, "RUNNING") # conservative fallback
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progress = getattr(response, "progress", None)
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error_message = getattr(response, "error_message", None)
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logger.info("finetune_status", extra={"job_id": job_id, "status": status})
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return FinetuneStatusResponse(
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job_id=job_id,
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status=status,
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progress=progress,
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error_message=error_message,
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)
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except Exception as exc:
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logger.error("finetune_status_error", extra={"job_id": job_id, "error": str(exc)})
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raise LLMCallError(f"微调状态查询失败: {exc}") from exc
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