add test for ft endpoints on azure

litellm/proxy/fine_tuning_endpoints/endpoints.py

@@ -40,11 +40,20 @@ fine_tuning_config = None
 
 def set_fine_tuning_config(config):
     global fine_tuning_config
+    if not isinstance(config, list):
+        raise ValueError("invalid fine_tuning config, expected a list is not a list")
+
+    for element in config:
+        if isinstance(element, dict):
+            for key, value in element.items():
+                if isinstance(value, str) and value.startswith("os.environ/"):
+                    element[key] = litellm.get_secret(value)
+
     fine_tuning_config = config
 
 
 # Function to search for specific custom_llm_provider and return its configuration
-def get_provider_config(
+def get_fine_tuning_provider_config(
     custom_llm_provider: str,
 ):
     global fine_tuning_config
@@ -122,7 +131,7 @@ async def create_fine_tuning_job(
         )
 
         # get configs for custom_llm_provider
-        llm_provider_config = get_provider_config(
+        llm_provider_config = get_fine_tuning_provider_config(
             custom_llm_provider=fine_tuning_request.custom_llm_provider,
         )
 

litellm/proxy/openai_files_endpoints/files_endpoints.py

@@ -34,6 +34,34 @@ from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 
 router = APIRouter()
 
+files_config = None
+
+
+def set_files_config(config):
+    global files_config
+    if not isinstance(config, list):
+        raise ValueError("invalid files config, expected a list is not a list")
+
+    for element in config:
+        if isinstance(element, dict):
+            for key, value in element.items():
+                if isinstance(value, str) and value.startswith("os.environ/"):
+                    element[key] = litellm.get_secret(value)
+
+    files_config = config
+
+
+def get_files_provider_config(
+    custom_llm_provider: str,
+):
+    global files_config
+    if files_config is None:
+        raise ValueError("files_config is not set, set it on your config.yaml file.")
+    for setting in files_config:
+        if setting.get("custom_llm_provider") == custom_llm_provider:
+            return setting
+    return None
+
 
 @router.post(
     "/v1/files",
@@ -49,6 +77,7 @@ async def create_file(
     request: Request,
     fastapi_response: Response,
     purpose: str = Form(...),
+    custom_llm_provider: str = Form(...),
     file: UploadFile = File(...),
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
@@ -100,11 +129,17 @@ async def create_file(
 
         _create_file_request = CreateFileRequest(file=file_data, **data)
 
-        # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
+        # get configs for custom_llm_provider
-        response = await litellm.acreate_file(
+        llm_provider_config = get_files_provider_config(
-            custom_llm_provider="openai", **_create_file_request
+            custom_llm_provider=custom_llm_provider
         )
 
+        # add llm_provider_config to data
+        _create_file_request.update(llm_provider_config)
+
+        # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
+        response = await litellm.acreate_file(**_create_file_request)
+
         ### ALERTING ###
         asyncio.create_task(
             proxy_logging_obj.update_request_status(

tests/openai_batch_completions.jsonl

@@ -0,0 +1,2 @@
+{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo-0125", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 10}}
+{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo-0125", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 10}}

tests/test_openai_fine_tuning.py

@@ -0,0 +1,23 @@
+from openai import AsyncOpenAI
+import os
+import pytest
+
+
+@pytest.mark.asyncio
+async def test_openai_fine_tuning():
+    """
+    [PROD Test] Ensures logprobs are returned correctly
+    """
+    client = AsyncOpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
+
+    file_name = "openai_batch_completions.jsonl"
+    _current_dir = os.path.dirname(os.path.abspath(__file__))
+    file_path = os.path.join(_current_dir, file_name)
+
+    response = await client.files.create(
+        extra_body={"custom_llm_provider": "azure"},
+        file=open(file_path, "rb"),
+        purpose="fine-tune",
+    )
+
+    print("response from files.create: {}".format(response))