add vertex generateContent

litellm/proxy/vertex_ai_endpoints/vertex_endpoints.py

@@ -1,3 +1,4 @@
+import ast
 import asyncio
 import traceback
 from datetime import datetime, timedelta, timezone
@@ -78,7 +79,21 @@ async def execute_post_vertex_ai_request(
     vertex_project = default_vertex_config.get("vertex_project", None)
     vertex_location = default_vertex_config.get("vertex_location", None)
     vertex_credentials = default_vertex_config.get("vertex_credentials", None)
-    request_data_json = await request.json()
+
+    request_data_json = {}
+    body = await request.body()
+    body_str = body.decode()
+    if len(body_str) > 0:
+        try:
+            request_data_json = ast.literal_eval(body_str)
+        except:
+            request_data_json = json.loads(body_str)
+
+    verbose_proxy_logger.debug(
+        "Request received by LiteLLM:\n{}".format(
+            json.dumps(request_data_json, indent=4)
+        ),
+    )
 
     response = (
         await vertex_fine_tuning_apis_instance.pass_through_vertex_ai_POST_request(
@@ -93,6 +108,41 @@ async def execute_post_vertex_ai_request(
     return response
 
 
+@router.post(
+    "/vertex-ai/publishers/google/models/{model_id:path}:generateContent",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["Vertex AI endpoints"],
+)
+async def vertex_generate_content(
+    request: Request,
+    fastapi_response: Response,
+    model_id: str,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+):
+    """
+    this is a pass through endpoint for the Vertex AI API. /generateContent endpoint
+
+    Example Curl:
+    ```
+    curl http://localhost:4000/vertex-ai/publishers/google/models/gemini-1.5-flash-001:generateContent \
+      -H "Content-Type: application/json" \
+      -H "Authorization: Bearer sk-1234" \
+      -d '{"contents":[{"role": "user", "parts":[{"text": "hi"}]}]}'
+    ```
+
+    Vertex API Reference: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#rest
+    it uses the vertex ai credentials on the proxy and forwards to vertex ai api
+    """
+    try:
+        response = await execute_post_vertex_ai_request(
+            request=request,
+            route=f"/publishers/google/models/{model_id}:generateContent",
+        )
+        return response
+    except Exception as e:
+        raise exception_handler(e) from e
+
+
 @router.post(
     "/vertex-ai/tuningJobs",
     dependencies=[Depends(user_api_key_auth)],
@@ -106,6 +156,8 @@ async def vertex_create_fine_tuning_job(
     """
     this is a pass through endpoint for the Vertex AI API. /tuningJobs endpoint
 
+    Vertex API Reference: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning
+
     it uses the vertex ai credentials on the proxy and forwards to vertex ai api
     """
     try:
@@ -116,3 +168,32 @@ async def vertex_create_fine_tuning_job(
         return response
     except Exception as e:
         raise exception_handler(e) from e
+
+
+@router.post(
+    "/vertex-ai/tuningJobs/{job_id:path}:cancel",
+    dependencies=[Depends(user_api_key_auth)],
+    tags=["Vertex AI endpoints"],
+)
+async def vertex_cancel_fine_tuning_job(
+    request: Request,
+    job_id: str,
+    fastapi_response: Response,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+):
+    """
+    this is a pass through endpoint for the Vertex AI API. tuningJobs/{job_id:path}:cancel
+
+    Vertex API Reference: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning#cancel_a_tuning_job
+
+    it uses the vertex ai credentials on the proxy and forwards to vertex ai api
+    """
+    try:
+
+        response = await execute_post_vertex_ai_request(
+            request=request,
+            route=f"/tuningJobs/{job_id}:cancel",
+        )
+        return response
+    except Exception as e:
+        raise exception_handler(e) from e