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

app/clients/llm/base.py

@@ -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)."""

app/clients/llm/zhipuai_client.py

@@ -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,

app/clients/storage/rustfs_client.py

@@ -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)

app/services/finetune_service.py

@@ -1,6 +1,4 @@
-import asyncio
+from app.clients.llm.base import LLMClient
-
-from app.core.exceptions import LLMCallError
 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:
+async def submit_finetune(req: FinetuneStartRequest, llm: LLMClient) -> FinetuneStartResponse:
-    """Submit a fine-tune job to ZhipuAI and return the job ID."""
+    """Submit a fine-tune job via the LLMClient interface and return the job ID."""
-    loop = asyncio.get_event_loop()
+    job_id = await llm.submit_finetune(req.jsonl_url, req.base_model, req.hyperparams or {})
-    try:
+    logger.info("finetune_submit", extra={"job_id": job_id, "model": req.base_model})
-        response = await loop.run_in_executor(
+    return FinetuneStartResponse(job_id=job_id)
-            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 get_finetune_status(job_id: str, llm) -> FinetuneStatusResponse:
+async def get_finetune_status(job_id: str, llm: LLMClient) -> FinetuneStatusResponse:
-    """Retrieve fine-tune job status from ZhipuAI."""
+    """Retrieve fine-tune job status via the LLMClient interface."""
-    loop = asyncio.get_event_loop()
+    raw = await llm.get_finetune_status(job_id)
-    try:
+    status = _STATUS_MAP.get(raw["status"], "RUNNING")
-        response = await loop.run_in_executor(
+    logger.info("finetune_status", extra={"job_id": job_id, "status": status})
-            None,
+    return FinetuneStatusResponse(
-            lambda: llm._client.fine_tuning.jobs.retrieve(job_id),
+        job_id=raw["job_id"],
-        )
+        status=status,
-        status_raw = response.status
+        progress=raw["progress"],
-        status = _STATUS_MAP.get(status_raw, "RUNNING")  # conservative fallback
+        error_message=raw["error_message"],
-        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

tests/test_finetune_service.py

@@ -1,8 +1,8 @@
-"""T046: Tests for finetune_service — written FIRST (TDD), must FAIL before implementation."""
+"""Tests for finetune_service — uses LLMClient interface (no internal SDK access)."""
-import asyncio
 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.*"""
+    """Return a MagicMock(spec=LLMClient) with submit_finetune and get_finetune_status as AsyncMocks."""
-    create_resp = MagicMock()
+    llm = MagicMock(spec=LLMClient)
-    create_resp.id = job_id
+    llm.submit_finetune = AsyncMock(return_value=job_id)
-
+    llm.get_finetune_status = AsyncMock(return_value={
-    retrieve_resp = MagicMock()
+        "job_id": job_id,
-    retrieve_resp.status = status
+        "status": status,
-    retrieve_resp.progress = progress
+        "progress": progress,
-    retrieve_resp.error_message = None  # explicitly set to avoid MagicMock auto-attribute
+        "error_message": None,
-
+    })
-    llm = MagicMock()
-    llm._client.fine_tuning.jobs.create.return_value = create_resp
-    llm._client.fine_tuning.jobs.retrieve.return_value = retrieve_resp
     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(
+    llm.submit_finetune.assert_awaited_once_with(
-        training_file="s3://bucket/train.jsonl",
+        "s3://bucket/train.jsonl",
-        model="glm-4",
+        "glm-4",
-        hyperparameters={"n_epochs": 5},
+        {"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(
+    llm.submit_finetune.assert_awaited_once_with(
-        training_file="s3://bucket/train.jsonl",
+        "s3://bucket/train.jsonl",
-        model="glm-4",
+        "glm-4",
-        hyperparameters={},
+        {},
     )
 
 
 @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 = MagicMock(spec=LLMClient)
-    llm._client.fine_tuning.jobs.create.side_effect = RuntimeError("SDK exploded")
+    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 = MagicMock(spec=LLMClient)
-    llm._client.fine_tuning.jobs.retrieve.side_effect = RuntimeError("SDK exploded")
+    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)

tests/test_llm_client.py

@@ -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,
+    }