fix(ollama_chat.py): fix sync tool calling

Fixes https://github.com/BerriAI/litellm/issues/5245

litellm/llms/ollama_chat.py

@@ -313,7 +313,7 @@ def get_ollama_response(
 
     ## RESPONSE OBJECT
     model_response.choices[0].finish_reason = "stop"
-    if data.get("format", "") == "json":
+    if data.get("format", "") == "json" and function_name is not None:
         function_call = json.loads(response_json["message"]["content"])
         message = litellm.Message(
             content=None,
@@ -321,8 +321,10 @@ def get_ollama_response(
                 {
                     "id": f"call_{str(uuid.uuid4())}",
                     "function": {
-                        "name": function_call["name"],
-                        "arguments": json.dumps(function_call["arguments"]),
+                        "name": function_call.get("name", function_name),
+                        "arguments": json.dumps(
+                            function_call.get("arguments", function_call)
+                        ),
                     },
                     "type": "function",
                 }
@@ -331,9 +333,10 @@ def get_ollama_response(
         model_response.choices[0].message = message  # type: ignore
         model_response.choices[0].finish_reason = "tool_calls"
     else:
-        model_response.choices[0].message.content = response_json["message"]["content"]  # type: ignore
+        _message = litellm.Message(**response_json["message"])
+        model_response.choices[0].message = _message  # type: ignore
     model_response.created = int(time.time())
-    model_response.model = "ollama/" + model
+    model_response.model = "ollama_chat/" + model
     prompt_tokens = response_json.get("prompt_eval_count", litellm.token_counter(messages=messages))  # type: ignore
     completion_tokens = response_json.get(
         "eval_count", litellm.token_counter(text=response_json["message"]["content"])

litellm/proxy/_new_secret_config.yaml

@@ -1,4 +1,4 @@
 model_list:
-  - model_name: "*"
+  - model_name: "ollama-llama3.1"
     litellm_params:
-      model: "*"
+      model: "ollama_chat/llama3.1"

litellm/tests/test_ollama.py

@@ -1,20 +1,25 @@
 import asyncio
-import sys, os
+import os
+import sys
 import traceback
+
 from dotenv import load_dotenv
 
 load_dotenv()
-import os, io
+import io
+import os
 
 sys.path.insert(
     0, os.path.abspath("../..")
 )  # Adds the parent directory to the system path
-import pytest
-import litellm
 from unittest import mock
 
+import pytest
+
+import litellm
+
 ## for ollama we can't test making the completion call
-from litellm.utils import EmbeddingResponse, get_optional_params, get_llm_provider
+from litellm.utils import EmbeddingResponse, get_llm_provider, get_optional_params
 
 
 def test_get_ollama_params():
@@ -48,21 +53,31 @@ def test_get_ollama_model():
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
+
 # test_get_ollama_model()
-        
+
+
 def test_ollama_json_mode():
-    # assert that format: json gets passed as is to ollama 
+    # assert that format: json gets passed as is to ollama
     try:
-        converted_params = get_optional_params(custom_llm_provider="ollama", model="llama2", format = "json", temperature=0.5)
+        converted_params = get_optional_params(
+            custom_llm_provider="ollama", model="llama2", format="json", temperature=0.5
+        )
         print("Converted params", converted_params)
-        assert converted_params == {'temperature': 0.5, 'format': 'json'}, f"{converted_params} != {'temperature': 0.5, 'format': 'json'}"
+        assert converted_params == {
+            "temperature": 0.5,
+            "format": "json",
+        }, f"{converted_params} != {'temperature': 0.5, 'format': 'json'}"
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+
+
 # test_ollama_json_mode()
 
 
 mock_ollama_embedding_response = EmbeddingResponse(model="ollama/nomic-embed-text")
 
+
 @mock.patch(
     "litellm.llms.ollama.ollama_embeddings",
     return_value=mock_ollama_embedding_response,
@@ -70,7 +85,9 @@ mock_ollama_embedding_response = EmbeddingResponse(model="ollama/nomic-embed-tex
 def test_ollama_embeddings(mock_embeddings):
     # assert that ollama_embeddings is called with the right parameters
     try:
-        embeddings = litellm.embedding(model="ollama/nomic-embed-text", input=["hello world"])
+        embeddings = litellm.embedding(
+            model="ollama/nomic-embed-text", input=["hello world"]
+        )
         print(embeddings)
         mock_embeddings.assert_called_once_with(
             api_base="http://localhost:11434",
@@ -83,8 +100,11 @@ def test_ollama_embeddings(mock_embeddings):
         )
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+
+
 # test_ollama_embeddings()
 
+
 @mock.patch(
     "litellm.llms.ollama.ollama_aembeddings",
     return_value=mock_ollama_embedding_response,
@@ -92,7 +112,9 @@ def test_ollama_embeddings(mock_embeddings):
 def test_ollama_aembeddings(mock_aembeddings):
     # assert that ollama_aembeddings is called with the right parameters
     try:
-        embeddings = asyncio.run(litellm.aembedding(model="ollama/nomic-embed-text", input=["hello world"]))
+        embeddings = asyncio.run(
+            litellm.aembedding(model="ollama/nomic-embed-text", input=["hello world"])
+        )
         print(embeddings)
         mock_aembeddings.assert_called_once_with(
             api_base="http://localhost:11434",
@@ -105,4 +127,48 @@ def test_ollama_aembeddings(mock_aembeddings):
         )
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+
+
 # test_ollama_aembeddings()
+
+
+def test_ollama_chat_function_calling():
+    import json
+
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "get_current_weather",
+                "description": "Get the current weather in a given location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {"type": "string"},
+                        "unit": {
+                            "type": "string",
+                            "enum": ["celsius", "fahrenheit"],
+                        },
+                    },
+                    "required": ["location"],
+                },
+            },
+        },
+    ]
+
+    messages = [
+        {"role": "user", "content": "What's the weather like in San Francisco?"}
+    ]
+
+    response = litellm.completion(
+        model="ollama_chat/llama3.1",
+        messages=messages,
+        tools=tools,
+    )
+    tool_calls = response.choices[0].message.get("tool_calls", None)
+
+    assert tool_calls is not None
+
+    print(json.loads(tool_calls[0].function.arguments))
+
+    print(response)