feat FT cancel and LIST endpoints for Azure

Author: ishaan-jaff

litellm/fine_tuning/main.py

@@ -279,6 +279,25 @@ def cancel_fine_tuning_job(
     """
     try:
         optional_params = GenericLiteLLMParams(**kwargs)
+        ### TIMEOUT LOGIC ###
+        timeout = optional_params.timeout or kwargs.get("request_timeout", 600) or 600
+        # set timeout for 10 minutes by default
+
+        if (
+            timeout is not None
+            and isinstance(timeout, httpx.Timeout)
+            and supports_httpx_timeout(custom_llm_provider) == False
+        ):
+            read_timeout = timeout.read or 600
+            timeout = read_timeout  # default 10 min timeout
+        elif timeout is not None and not isinstance(timeout, httpx.Timeout):
+            timeout = float(timeout)  # type: ignore
+        elif timeout is None:
+            timeout = 600.0
+
+        _is_async = kwargs.pop("acancel_fine_tuning_job", False) is True
+
+        # OpenAI
         if custom_llm_provider == "openai":
 
             # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
@@ -301,25 +320,6 @@ def cancel_fine_tuning_job(
                 or litellm.openai_key
                 or os.getenv("OPENAI_API_KEY")
             )
-            ### TIMEOUT LOGIC ###
-            timeout = (
-                optional_params.timeout or kwargs.get("request_timeout", 600) or 600
-            )
-            # set timeout for 10 minutes by default
-
-            if (
-                timeout is not None
-                and isinstance(timeout, httpx.Timeout)
-                and supports_httpx_timeout(custom_llm_provider) == False
-            ):
-                read_timeout = timeout.read or 600
-                timeout = read_timeout  # default 10 min timeout
-            elif timeout is not None and not isinstance(timeout, httpx.Timeout):
-                timeout = float(timeout)  # type: ignore
-            elif timeout is None:
-                timeout = 600.0
-
-            _is_async = kwargs.pop("acancel_fine_tuning_job", False) is True
 
             response = openai_fine_tuning_apis_instance.cancel_fine_tuning_job(
                 api_base=api_base,
@@ -330,6 +330,40 @@ def cancel_fine_tuning_job(
                 max_retries=optional_params.max_retries,
                 _is_async=_is_async,
             )
+        # Azure OpenAI
+        elif custom_llm_provider == "azure":
+            api_base = optional_params.api_base or litellm.api_base or get_secret("AZURE_API_BASE")  # type: ignore
+
+            api_version = (
+                optional_params.api_version
+                or litellm.api_version
+                or get_secret("AZURE_API_VERSION")
+            )  # type: ignore
+
+            api_key = (
+                optional_params.api_key
+                or litellm.api_key
+                or litellm.azure_key
+                or get_secret("AZURE_OPENAI_API_KEY")
+                or get_secret("AZURE_API_KEY")
+            )  # type: ignore
+
+            extra_body = optional_params.get("extra_body", {})
+            azure_ad_token: Optional[str] = None
+            if extra_body is not None:
+                azure_ad_token = extra_body.pop("azure_ad_token", None)
+            else:
+                azure_ad_token = get_secret("AZURE_AD_TOKEN")  # type: ignore
+
+            response = azure_fine_tuning_apis_instance.cancel_fine_tuning_job(
+                api_base=api_base,
+                api_key=api_key,
+                api_version=api_version,
+                fine_tuning_job_id=fine_tuning_job_id,
+                timeout=timeout,
+                max_retries=optional_params.max_retries,
+                _is_async=_is_async,
+            )
         else:
             raise litellm.exceptions.BadRequestError(
                 message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
@@ -405,6 +439,25 @@ def list_fine_tuning_jobs(
     """
     try:
         optional_params = GenericLiteLLMParams(**kwargs)
+        ### TIMEOUT LOGIC ###
+        timeout = optional_params.timeout or kwargs.get("request_timeout", 600) or 600
+        # set timeout for 10 minutes by default
+
+        if (
+            timeout is not None
+            and isinstance(timeout, httpx.Timeout)
+            and supports_httpx_timeout(custom_llm_provider) == False
+        ):
+            read_timeout = timeout.read or 600
+            timeout = read_timeout  # default 10 min timeout
+        elif timeout is not None and not isinstance(timeout, httpx.Timeout):
+            timeout = float(timeout)  # type: ignore
+        elif timeout is None:
+            timeout = 600.0
+
+        _is_async = kwargs.pop("alist_fine_tuning_jobs", False) is True
+
+        # OpenAI
         if custom_llm_provider == "openai":
 
             # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
@@ -427,25 +480,6 @@ def list_fine_tuning_jobs(
                 or litellm.openai_key
                 or os.getenv("OPENAI_API_KEY")
             )
-            ### TIMEOUT LOGIC ###
-            timeout = (
-                optional_params.timeout or kwargs.get("request_timeout", 600) or 600
-            )
-            # set timeout for 10 minutes by default
-
-            if (
-                timeout is not None
-                and isinstance(timeout, httpx.Timeout)
-                and supports_httpx_timeout(custom_llm_provider) == False
-            ):
-                read_timeout = timeout.read or 600
-                timeout = read_timeout  # default 10 min timeout
-            elif timeout is not None and not isinstance(timeout, httpx.Timeout):
-                timeout = float(timeout)  # type: ignore
-            elif timeout is None:
-                timeout = 600.0
-
-            _is_async = kwargs.pop("alist_fine_tuning_jobs", False) is True
 
             response = openai_fine_tuning_apis_instance.list_fine_tuning_jobs(
                 api_base=api_base,
@@ -457,6 +491,41 @@ def list_fine_tuning_jobs(
                 max_retries=optional_params.max_retries,
                 _is_async=_is_async,
             )
+        # Azure OpenAI
+        elif custom_llm_provider == "azure":
+            api_base = optional_params.api_base or litellm.api_base or get_secret("AZURE_API_BASE")  # type: ignore
+
+            api_version = (
+                optional_params.api_version
+                or litellm.api_version
+                or get_secret("AZURE_API_VERSION")
+            )  # type: ignore
+
+            api_key = (
+                optional_params.api_key
+                or litellm.api_key
+                or litellm.azure_key
+                or get_secret("AZURE_OPENAI_API_KEY")
+                or get_secret("AZURE_API_KEY")
+            )  # type: ignore
+
+            extra_body = optional_params.get("extra_body", {})
+            azure_ad_token: Optional[str] = None
+            if extra_body is not None:
+                azure_ad_token = extra_body.pop("azure_ad_token", None)
+            else:
+                azure_ad_token = get_secret("AZURE_AD_TOKEN")  # type: ignore
+
+            response = azure_fine_tuning_apis_instance.list_fine_tuning_jobs(
+                api_base=api_base,
+                api_key=api_key,
+                api_version=api_version,
+                after=after,
+                limit=limit,
+                timeout=timeout,
+                max_retries=optional_params.max_retries,
+                _is_async=_is_async,
+            )
         else:
             raise litellm.exceptions.BadRequestError(
                 message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(

litellm/llms/fine_tuning_apis/azure.py

@@ -91,13 +91,15 @@ def cancel_fine_tuning_job(
         api_base: Optional[str],
         timeout: Union[float, httpx.Timeout],
         max_retries: Optional[int],
-        organization: Optional[str],
+        organization: Optional[str] = None,
+        api_version: Optional[str] = None,
         client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
     ):
         openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
             get_azure_openai_client(
                 api_key=api_key,
                 api_base=api_base,
+                api_version=api_version,
                 timeout=timeout,
                 max_retries=max_retries,
                 organization=organization,
@@ -141,15 +143,17 @@ def list_fine_tuning_jobs(
         api_base: Optional[str],
         timeout: Union[float, httpx.Timeout],
         max_retries: Optional[int],
-        organization: Optional[str],
+        organization: Optional[str] = None,
         client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
+        api_version: Optional[str] = None,
         after: Optional[str] = None,
         limit: Optional[int] = None,
     ):
         openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
             get_azure_openai_client(
                 api_key=api_key,
                 api_base=api_base,
+                api_version=api_version,
                 timeout=timeout,
                 max_retries=max_retries,
                 organization=organization,
@@ -175,4 +179,3 @@ def list_fine_tuning_jobs(
         verbose_logger.debug("list fine tuning job, after= %s, limit= %s", after, limit)
         response = openai_client.fine_tuning.jobs.list(after=after, limit=limit)  # type: ignore
         return response
-        pass

litellm/tests/test_fine_tuning_api.py

@@ -146,25 +146,31 @@ async def test_azure_create_fine_tune_jobs_async():
     assert create_fine_tuning_response.id is not None
     assert create_fine_tuning_response.model == "gpt-35-turbo-1106"
 
-    # # list fine tuning jobs
-    # print("listing ft jobs")
-    # ft_jobs = await litellm.alist_fine_tuning_jobs(limit=2)
-    # print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
-    # assert len(list(ft_jobs)) > 0
+    # list fine tuning jobs
+    print("listing ft jobs")
+    ft_jobs = await litellm.alist_fine_tuning_jobs(
+        limit=2,
+        custom_llm_provider="azure",
+        api_key=os.getenv("AZURE_SWEDEN_API_KEY"),
+        api_base="https://my-endpoint-sweden-berri992.openai.azure.com/",
+    )
+    print("response from litellm.list_fine_tuning_jobs=", ft_jobs)
 
     # # delete file
 
     # await litellm.afile_delete(
     #     file_id=file_obj.id,
     # )
 
-    # # cancel ft job
-    # response = await litellm.acancel_fine_tuning_job(
-    #     fine_tuning_job_id=create_fine_tuning_response.id,
-    # )
+    # cancel ft job
+    response = await litellm.acancel_fine_tuning_job(
+        fine_tuning_job_id=create_fine_tuning_response.id,
+        custom_llm_provider="azure",
+        api_key=os.getenv("AZURE_SWEDEN_API_KEY"),
+        api_base="https://my-endpoint-sweden-berri992.openai.azure.com/",
+    )
 
-    # print("response from litellm.cancel_fine_tuning_job=", response)
+    print("response from litellm.cancel_fine_tuning_job=", response)
 
-    # assert response.status == "cancelled"
-    # assert response.id == create_fine_tuning_response.id
-    # pass
+    assert response.status == "cancelled"
+    assert response.id == create_fine_tuning_response.id