refactor: finetune through LLMClient interface + get_running_loop

- Add submit_finetune and get_finetune_status abstract methods to LLMClient base
- Implement both methods in ZhipuAIClient using asyncio.get_running_loop()
- Rewrite finetune_service to call llm.submit_finetune / llm.get_finetune_status
  instead of accessing llm._client directly, restoring interface encapsulation
- Replace asyncio.get_event_loop() with get_running_loop() in ZhipuAIClient._call
  and all four methods in RustFSClient (deprecated in Python 3.10+)
- Update test_finetune_service to mock the LLMClient interface methods as AsyncMocks
- Add two new tests in test_llm_client for submit_finetune and get_finetune_status
This commit is contained in:
wh
2026-04-10 16:43:28 +08:00
parent 603382d1fa
commit 0880e1018c
6 changed files with 130 additions and 79 deletions

View File

@@ -9,3 +9,11 @@ class LLMClient(ABC):
@abstractmethod
async def chat_vision(self, model: str, messages: list[dict]) -> str:
"""Send a multimodal (vision) chat request and return the response content string."""
@abstractmethod
async def submit_finetune(self, jsonl_url: str, base_model: str, hyperparams: dict) -> str:
"""Submit a fine-tune job and return the job_id."""
@abstractmethod
async def get_finetune_status(self, job_id: str) -> dict:
"""Return a dict with keys: job_id, status (raw SDK string), progress (int|None), error_message (str|None)."""

View File

@@ -19,8 +19,39 @@ class ZhipuAIClient(LLMClient):
async def chat_vision(self, model: str, messages: list[dict]) -> str:
return await self._call(model, messages)
async def submit_finetune(self, jsonl_url: str, base_model: str, hyperparams: dict) -> str:
loop = asyncio.get_running_loop()
try:
resp = await loop.run_in_executor(
None,
lambda: self._client.fine_tuning.jobs.create(
training_file=jsonl_url,
model=base_model,
hyperparameters=hyperparams,
),
)
return resp.id
except Exception as exc:
raise LLMCallError(f"微调任务提交失败: {exc}") from exc
async def get_finetune_status(self, job_id: str) -> dict:
loop = asyncio.get_running_loop()
try:
resp = await loop.run_in_executor(
None,
lambda: self._client.fine_tuning.jobs.retrieve(job_id),
)
return {
"job_id": resp.id,
"status": resp.status,
"progress": int(resp.progress) if getattr(resp, "progress", None) is not None else None,
"error_message": getattr(resp, "error_message", None),
}
except Exception as exc:
raise LLMCallError(f"查询微调任务失败: {exc}") from exc
async def _call(self, model: str, messages: list[dict]) -> str:
loop = asyncio.get_event_loop()
loop = asyncio.get_running_loop()
try:
response = await loop.run_in_executor(
None,

View File

@@ -21,7 +21,7 @@ class RustFSClient(StorageClient):
)
async def download_bytes(self, bucket: str, path: str) -> bytes:
loop = asyncio.get_event_loop()
loop = asyncio.get_running_loop()
try:
resp = await loop.run_in_executor(
None, lambda: self._s3.get_object(Bucket=bucket, Key=path)
@@ -33,7 +33,7 @@ class RustFSClient(StorageClient):
async def upload_bytes(
self, bucket: str, path: str, data: bytes, content_type: str = "application/octet-stream"
) -> None:
loop = asyncio.get_event_loop()
loop = asyncio.get_running_loop()
try:
await loop.run_in_executor(
None,
@@ -45,7 +45,7 @@ class RustFSClient(StorageClient):
raise StorageError(f"存储上传失败 [{bucket}/{path}]: {exc}") from exc
async def get_presigned_url(self, bucket: str, path: str, expires: int = 3600) -> str:
loop = asyncio.get_event_loop()
loop = asyncio.get_running_loop()
try:
url = await loop.run_in_executor(
None,
@@ -60,7 +60,7 @@ class RustFSClient(StorageClient):
raise StorageError(f"生成预签名 URL 失败 [{bucket}/{path}]: {exc}") from exc
async def get_object_size(self, bucket: str, path: str) -> int:
loop = asyncio.get_event_loop()
loop = asyncio.get_running_loop()
try:
resp = await loop.run_in_executor(
None, lambda: self._s3.head_object(Bucket=bucket, Key=path)

View File

@@ -1,6 +1,4 @@
import asyncio
from app.core.exceptions import LLMCallError
from app.clients.llm.base import LLMClient
from app.core.logging import get_logger
from app.models.finetune_models import (
FinetuneStartRequest,
@@ -17,45 +15,21 @@ _STATUS_MAP = {
}
async def submit_finetune(req: FinetuneStartRequest, llm) -> FinetuneStartResponse:
"""Submit a fine-tune job to ZhipuAI and return the job ID."""
loop = asyncio.get_event_loop()
try:
response = await loop.run_in_executor(
None,
lambda: llm._client.fine_tuning.jobs.create(
training_file=req.jsonl_url,
model=req.base_model,
hyperparameters=req.hyperparams or {},
),
)
job_id = response.id
logger.info("finetune_submit", extra={"job_id": job_id, "model": req.base_model})
return FinetuneStartResponse(job_id=job_id)
except Exception as exc:
logger.error("finetune_submit_error", extra={"error": str(exc)})
raise LLMCallError(f"微调任务提交失败: {exc}") from exc
async def submit_finetune(req: FinetuneStartRequest, llm: LLMClient) -> FinetuneStartResponse:
"""Submit a fine-tune job via the LLMClient interface and return the job ID."""
job_id = await llm.submit_finetune(req.jsonl_url, req.base_model, req.hyperparams or {})
logger.info("finetune_submit", extra={"job_id": job_id, "model": req.base_model})
return FinetuneStartResponse(job_id=job_id)
async def get_finetune_status(job_id: str, llm) -> FinetuneStatusResponse:
"""Retrieve fine-tune job status from ZhipuAI."""
loop = asyncio.get_event_loop()
try:
response = await loop.run_in_executor(
None,
lambda: llm._client.fine_tuning.jobs.retrieve(job_id),
)
status_raw = response.status
status = _STATUS_MAP.get(status_raw, "RUNNING") # conservative fallback
progress = getattr(response, "progress", None)
error_message = getattr(response, "error_message", None)
logger.info("finetune_status", extra={"job_id": job_id, "status": status})
return FinetuneStatusResponse(
job_id=job_id,
status=status,
progress=progress,
error_message=error_message,
)
except Exception as exc:
logger.error("finetune_status_error", extra={"job_id": job_id, "error": str(exc)})
raise LLMCallError(f"微调状态查询失败: {exc}") from exc
async def get_finetune_status(job_id: str, llm: LLMClient) -> FinetuneStatusResponse:
"""Retrieve fine-tune job status via the LLMClient interface."""
raw = await llm.get_finetune_status(job_id)
status = _STATUS_MAP.get(raw["status"], "RUNNING")
logger.info("finetune_status", extra={"job_id": job_id, "status": status})
return FinetuneStatusResponse(
job_id=raw["job_id"],
status=status,
progress=raw["progress"],
error_message=raw["error_message"],
)

View File

@@ -1,8 +1,8 @@
"""T046: Tests for finetune_service — written FIRST (TDD), must FAIL before implementation."""
import asyncio
"""Tests for finetune_service — uses LLMClient interface (no internal SDK access)."""
import pytest
from unittest.mock import MagicMock, AsyncMock, patch
from unittest.mock import MagicMock, AsyncMock
from app.clients.llm.base import LLMClient
from app.core.exceptions import LLMCallError
from app.models.finetune_models import (
FinetuneStartRequest,
@@ -16,18 +16,15 @@ from app.models.finetune_models import (
# ---------------------------------------------------------------------------
def _make_llm(job_id: str = "glm-ft-test", status: str = "running", progress: int | None = None):
"""Return a mock that looks like ZhipuAIClient with ._client.fine_tuning.jobs.*"""
create_resp = MagicMock()
create_resp.id = job_id
retrieve_resp = MagicMock()
retrieve_resp.status = status
retrieve_resp.progress = progress
retrieve_resp.error_message = None # explicitly set to avoid MagicMock auto-attribute
llm = MagicMock()
llm._client.fine_tuning.jobs.create.return_value = create_resp
llm._client.fine_tuning.jobs.retrieve.return_value = retrieve_resp
"""Return a MagicMock(spec=LLMClient) with submit_finetune and get_finetune_status as AsyncMocks."""
llm = MagicMock(spec=LLMClient)
llm.submit_finetune = AsyncMock(return_value=job_id)
llm.get_finetune_status = AsyncMock(return_value={
"job_id": job_id,
"status": status,
"progress": progress,
"error_message": None,
})
return llm
@@ -53,7 +50,7 @@ async def test_submit_finetune_returns_job_id():
@pytest.mark.asyncio
async def test_submit_finetune_calls_sdk_with_correct_params():
async def test_submit_finetune_calls_interface_with_correct_params():
from app.services.finetune_service import submit_finetune
llm = _make_llm(job_id="glm-ft-xyz")
@@ -65,16 +62,16 @@ async def test_submit_finetune_calls_sdk_with_correct_params():
await submit_finetune(req, llm)
llm._client.fine_tuning.jobs.create.assert_called_once_with(
training_file="s3://bucket/train.jsonl",
model="glm-4",
hyperparameters={"n_epochs": 5},
llm.submit_finetune.assert_awaited_once_with(
"s3://bucket/train.jsonl",
"glm-4",
{"n_epochs": 5},
)
@pytest.mark.asyncio
async def test_submit_finetune_none_hyperparams_passes_empty_dict():
"""hyperparams=None should be passed as {} to the SDK."""
"""hyperparams=None should be passed as {} to the interface."""
from app.services.finetune_service import submit_finetune
llm = _make_llm(job_id="glm-ft-nohp")
@@ -85,19 +82,19 @@ async def test_submit_finetune_none_hyperparams_passes_empty_dict():
await submit_finetune(req, llm)
llm._client.fine_tuning.jobs.create.assert_called_once_with(
training_file="s3://bucket/train.jsonl",
model="glm-4",
hyperparameters={},
llm.submit_finetune.assert_awaited_once_with(
"s3://bucket/train.jsonl",
"glm-4",
{},
)
@pytest.mark.asyncio
async def test_submit_finetune_raises_llm_call_error_on_sdk_failure():
async def test_submit_finetune_raises_llm_call_error_on_failure():
from app.services.finetune_service import submit_finetune
llm = MagicMock()
llm._client.fine_tuning.jobs.create.side_effect = RuntimeError("SDK exploded")
llm = MagicMock(spec=LLMClient)
llm.submit_finetune = AsyncMock(side_effect=LLMCallError("微调任务提交失败: SDK exploded"))
req = FinetuneStartRequest(
jsonl_url="s3://bucket/train.jsonl",
@@ -144,11 +141,11 @@ async def test_get_finetune_status_includes_progress():
@pytest.mark.asyncio
async def test_get_finetune_status_raises_llm_call_error_on_sdk_failure():
async def test_get_finetune_status_raises_llm_call_error_on_failure():
from app.services.finetune_service import get_finetune_status
llm = MagicMock()
llm._client.fine_tuning.jobs.retrieve.side_effect = RuntimeError("SDK exploded")
llm = MagicMock(spec=LLMClient)
llm.get_finetune_status = AsyncMock(side_effect=LLMCallError("查询微调任务失败: SDK exploded"))
with pytest.raises(LLMCallError):
await get_finetune_status("glm-ft-bad", llm)

View File

@@ -38,3 +38,44 @@ async def test_llm_call_error_on_sdk_exception(client):
client._client.chat.completions.create.side_effect = RuntimeError("quota exceeded")
with pytest.raises(LLMCallError, match="大模型调用失败"):
await client.chat("glm-4-flash", [{"role": "user", "content": "hi"}])
@pytest.mark.asyncio
async def test_submit_finetune_returns_job_id(client):
"""submit_finetune should call the SDK and return the job id."""
resp = MagicMock()
resp.id = "glm-ft-newjob"
client._client.fine_tuning.jobs.create.return_value = resp
job_id = await client.submit_finetune(
jsonl_url="s3://bucket/train.jsonl",
base_model="glm-4",
hyperparams={"n_epochs": 2},
)
assert job_id == "glm-ft-newjob"
client._client.fine_tuning.jobs.create.assert_called_once_with(
training_file="s3://bucket/train.jsonl",
model="glm-4",
hyperparameters={"n_epochs": 2},
)
@pytest.mark.asyncio
async def test_get_finetune_status_returns_correct_dict(client):
"""get_finetune_status should return a normalized dict with progress coerced to int."""
resp = MagicMock()
resp.id = "glm-ft-abc"
resp.status = "running"
resp.progress = "75" # SDK may return string; should be coerced to int
resp.error_message = None
client._client.fine_tuning.jobs.retrieve.return_value = resp
result = await client.get_finetune_status("glm-ft-abc")
assert result == {
"job_id": "glm-ft-abc",
"status": "running",
"progress": 75,
"error_message": None,
}