LiteLLM Minor Fixes & Improvements (11/19/2024) (#6820)

* fix(anthropic/chat/transformation.py): add json schema as values: json_schema

fixes passing pydantic obj to anthropic

Fixes https://github.com/BerriAI/litellm/issues/6766

* (feat): Add timestamp_granularities parameter to transcription API (#6457)

* Add timestamp_granularities parameter to transcription API

* add param to the local test

* fix(databricks/chat.py): handle max_retries optional param handling for openai-like calls

Fixes issue with calling finetuned vertex ai models via databricks route

* build(ui/): add team admins via proxy ui

* fix: fix linting error

* test: fix test

* docs(vertex.md): refactor docs

* test: handle overloaded anthropic model error

* test: remove duplicate test

* test: fix test

* test: update test to handle model overloaded error

---------

Co-authored-by: Show <35062952+BrunooShow@users.noreply.github.com>

tests/local_testing/test_amazing_vertex_completion.py

@@ -3129,9 +3129,12 @@ async def test_vertexai_embedding_finetuned(respx_mock: MockRouter):
         assert all(isinstance(x, float) for x in embedding["embedding"])
 
 
+@pytest.mark.parametrize("max_retries", [None, 3])
 @pytest.mark.asyncio
 @pytest.mark.respx
-async def test_vertexai_model_garden_model_completion(respx_mock: MockRouter):
+async def test_vertexai_model_garden_model_completion(
+    respx_mock: MockRouter, max_retries
+):
     """
     Relevant issue: https://github.com/BerriAI/litellm/issues/6480
 
@@ -3189,6 +3192,7 @@ async def test_vertexai_model_garden_model_completion(respx_mock: MockRouter):
         messages=messages,
         vertex_project="633608382793",
         vertex_location="us-central1",
+        max_retries=max_retries,
     )
 
     # Assert request was made correctly

tests/local_testing/test_completion.py

@@ -1222,32 +1222,6 @@ def test_completion_mistral_api_modified_input():
             pytest.fail(f"Error occurred: {e}")
 
 
-def test_completion_claude2_1():
-    try:
-        litellm.set_verbose = True
-        print("claude2.1 test request")
-        messages = [
-            {
-                "role": "system",
-                "content": "Your goal is generate a joke on the topic user gives.",
-            },
-            {"role": "user", "content": "Generate a 3 liner joke for me"},
-        ]
-        # test without max tokens
-        response = completion(model="claude-2.1", messages=messages)
-        # Add any assertions here to check the response
-        print(response)
-        print(response.usage)
-        print(response.usage.completion_tokens)
-        print(response["usage"]["completion_tokens"])
-        # print("new cost tracking")
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
-# test_completion_claude2_1()
-
-
 @pytest.mark.asyncio
 async def test_acompletion_claude2_1():
     try:
@@ -1268,6 +1242,8 @@ async def test_acompletion_claude2_1():
         print(response.usage.completion_tokens)
         print(response["usage"]["completion_tokens"])
         # print("new cost tracking")
+    except litellm.InternalServerError:
+        pytest.skip("model is overloaded.")
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
@@ -4514,19 +4490,22 @@ async def test_dynamic_azure_params(stream, sync_mode):
 @pytest.mark.flaky(retries=3, delay=1)
 async def test_completion_ai21_chat():
     litellm.set_verbose = True
-    response = await litellm.acompletion(
-        model="jamba-1.5-large",
-        user="ishaan",
-        tool_choice="auto",
-        seed=123,
-        messages=[{"role": "user", "content": "what does the document say"}],
-        documents=[
-            {
-                "content": "hello world",
-                "metadata": {"source": "google", "author": "ishaan"},
-            }
-        ],
-    )
+    try:
+        response = await litellm.acompletion(
+            model="jamba-1.5-large",
+            user="ishaan",
+            tool_choice="auto",
+            seed=123,
+            messages=[{"role": "user", "content": "what does the document say"}],
+            documents=[
+                {
+                    "content": "hello world",
+                    "metadata": {"source": "google", "author": "ishaan"},
+                }
+            ],
+        )
+    except litellm.InternalServerError:
+        pytest.skip("Model is overloaded")
 
 
 @pytest.mark.parametrize(

tests/local_testing/test_whisper.py

@@ -51,10 +51,15 @@ from litellm import Router
         ),
     ],
 )
-@pytest.mark.parametrize("response_format", ["json", "vtt"])
+@pytest.mark.parametrize(
+    "response_format, timestamp_granularities",
+    [("json", None), ("vtt", None), ("verbose_json", ["word"])],
+)
 @pytest.mark.parametrize("sync_mode", [True, False])
 @pytest.mark.asyncio
-async def test_transcription(model, api_key, api_base, response_format, sync_mode):
+async def test_transcription(
+    model, api_key, api_base, response_format, sync_mode, timestamp_granularities
+):
     if sync_mode:
         transcript = litellm.transcription(
             model=model,
@@ -62,6 +67,7 @@ async def test_transcription(model, api_key, api_base, response_format, sync_mod
             api_key=api_key,
             api_base=api_base,
             response_format=response_format,
+            timestamp_granularities=timestamp_granularities,
             drop_params=True,
         )
     else: