test_avertex_batch_prediction

2026-08-18 04:28:19 +00:00 · 2025-02-14 22:03:24 -08:00
parent 8de6e7c292
commit 0ffd99afff
1 changed files with 124 additions and 29 deletions
@@ -27,6 +27,7 @@ verbose_logger.setLevel(logging.DEBUG)
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.utils import StandardLoggingPayload
 import random
+from unittest.mock import patch, MagicMock


 def load_vertex_ai_credentials():
@@ -367,37 +368,131 @@ async def test_async_create_batch(provider):
        cleanup_azure_ft_models()


+mock_file_response = {
+    "kind": "storage#object",
+    "id": "litellm-local/litellm-vertex-files/publishers/google/models/gemini-1.5-flash-001/5f7b99ad-9203-4430-98bf-3b45451af4cb/1739598666670574",
+    "selfLink": "https://www.googleapis.com/storage/v1/b/litellm-local/o/litellm-vertex-files%2Fpublishers%2Fgoogle%2Fmodels%2Fgemini-1.5-flash-001%2F5f7b99ad-9203-4430-98bf-3b45451af4cb",
+    "mediaLink": "https://storage.googleapis.com/download/storage/v1/b/litellm-local/o/litellm-vertex-files%2Fpublishers%2Fgoogle%2Fmodels%2Fgemini-1.5-flash-001%2F5f7b99ad-9203-4430-98bf-3b45451af4cb?generation=1739598666670574&alt=media",
+    "name": "litellm-vertex-files/publishers/google/models/gemini-1.5-flash-001/5f7b99ad-9203-4430-98bf-3b45451af4cb",
+    "bucket": "litellm-local",
+    "generation": "1739598666670574",
+    "metageneration": "1",
+    "contentType": "application/json",
+    "storageClass": "STANDARD",
+    "size": "416",
+    "md5Hash": "hbBNj7C8KJ7oVH+JmyRM6A==",
+    "crc32c": "oDmiUA==",
+    "etag": "CO7D0IT+xIsDEAE=",
+    "timeCreated": "2025-02-15T05:51:06.741Z",
+    "updated": "2025-02-15T05:51:06.741Z",
+    "timeStorageClassUpdated": "2025-02-15T05:51:06.741Z",
+    "timeFinalized": "2025-02-15T05:51:06.741Z",
+}
+
+mock_vertex_batch_response = {
+    "name": "projects/123456789/locations/us-central1/batchPredictionJobs/test-batch-id-456",
+    "displayName": "litellm_batch_job",
+    "model": "projects/123456789/locations/us-central1/models/gemini-1.5-flash-001",
+    "modelVersionId": "v1",
+    "inputConfig": {
+        "gcsSource": {
+            "uris": [
+                "gs://litellm-local/litellm-vertex-files/publishers/google/models/gemini-1.5-flash-001/5f7b99ad-9203-4430-98bf-3b45451af4cb"
+            ]
+        }
+    },
+    "outputConfig": {
+        "gcsDestination": {"outputUriPrefix": "gs://litellm-local/batch-outputs/"}
+    },
+    "dedicatedResources": {
+        "machineSpec": {
+            "machineType": "n1-standard-4",
+            "acceleratorType": "NVIDIA_TESLA_T4",
+            "acceleratorCount": 1,
+        },
+        "startingReplicaCount": 1,
+        "maxReplicaCount": 1,
+    },
+    "state": "JOB_STATE_RUNNING",
+    "createTime": "2025-02-15T05:51:06.741Z",
+    "startTime": "2025-02-15T05:51:07.741Z",
+    "updateTime": "2025-02-15T05:51:08.741Z",
+    "labels": {"key1": "value1", "key2": "value2"},
+    "completionStats": {"successfulCount": 0, "failedCount": 0, "remainingCount": 100},
+}
+
+
@pytest.mark.asyncio
 async def test_avertex_batch_prediction():
-    load_vertex_ai_credentials()
-    litellm.set_verbose = True
-    file_name = "vertex_batch_completions.jsonl"
-    _current_dir = os.path.dirname(os.path.abspath(__file__))
-    file_path = os.path.join(_current_dir, file_name)
-    file_obj = await litellm.acreate_file(
-        file=open(file_path, "rb"),
-        purpose="batch",
-        custom_llm_provider="vertex_ai",
-    )
-    print("Response from creating file=", file_obj)
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post"
+    ) as mock_post:
+        # Configure mock responses
+        mock_response = MagicMock()
+        mock_response.raise_for_status.return_value = None

-    batch_input_file_id = file_obj.id
-    assert (
-        batch_input_file_id is not None
-    ), f"Failed to create file, expected a non null file_id but got {batch_input_file_id}"
+        # Set up different responses for different API calls
+        async def mock_side_effect(*args, **kwargs):
+            url = kwargs.get("url", "")
+            if "files" in url:
+                mock_response.json.return_value = mock_file_response
+            elif "batch" in url:
+                mock_response.json.return_value = mock_vertex_batch_response
+                mock_response.status_code = 200
+            return mock_response

-    create_batch_response = await litellm.acreate_batch(
-        completion_window="24h",
-        endpoint="/v1/chat/completions",
-        input_file_id=batch_input_file_id,
-        custom_llm_provider="vertex_ai",
-        metadata={"key1": "value1", "key2": "value2"},
-    )
-    print("create_batch_response=", create_batch_response)
+        mock_post.side_effect = mock_side_effect

-    retrieved_batch = await litellm.aretrieve_batch(
-        batch_id=create_batch_response.id,
-        custom_llm_provider="vertex_ai",
-    )
-    print("retrieved_batch=", retrieved_batch)
-    pass
+        # load_vertex_ai_credentials()
+        litellm.set_verbose = True
+        litellm._turn_on_debug()
+        file_name = "vertex_batch_completions.jsonl"
+        _current_dir = os.path.dirname(os.path.abspath(__file__))
+        file_path = os.path.join(_current_dir, file_name)
+
+        # Create file
+        file_obj = await litellm.acreate_file(
+            file=open(file_path, "rb"),
+            purpose="batch",
+            custom_llm_provider="vertex_ai",
+        )
+        print("Response from creating file=", file_obj)
+
+        assert (
+            file_obj.id
+            == "gs://litellm-local/litellm-vertex-files/publishers/google/models/gemini-1.5-flash-001/5f7b99ad-9203-4430-98bf-3b45451af4cb"
+        )
+
+        # Create batch
+        create_batch_response = await litellm.acreate_batch(
+            completion_window="24h",
+            endpoint="/v1/chat/completions",
+            input_file_id=file_obj.id,
+            custom_llm_provider="vertex_ai",
+            metadata={"key1": "value1", "key2": "value2"},
+        )
+        print("create_batch_response=", create_batch_response)
+
+        assert create_batch_response.id == "test-batch-id-456"
+        assert (
+            create_batch_response.input_file_id
+            == "gs://litellm-local/litellm-vertex-files/publishers/google/models/gemini-1.5-flash-001/5f7b99ad-9203-4430-98bf-3b45451af4cb"
+        )
+
+        # Mock the retrieve batch response
+        with patch(
+            "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.get"
+        ) as mock_get:
+            mock_get_response = MagicMock()
+            mock_get_response.json.return_value = mock_vertex_batch_response
+            mock_get_response.status_code = 200
+            mock_get_response.raise_for_status.return_value = None
+            mock_get.return_value = mock_get_response
+
+            retrieved_batch = await litellm.aretrieve_batch(
+                batch_id=create_batch_response.id,
+                custom_llm_provider="vertex_ai",
+            )
+            print("retrieved_batch=", retrieved_batch)
+
+            assert retrieved_batch.id == "test-batch-id-456"