fix(ollama_chat.py): fix passing assistant message with tool call param

Fixes https://github.com/BerriAI/litellm/issues/5319

litellm/llms/ollama_chat.py

@@ -4,14 +4,17 @@ import traceback
 import types
 import uuid
 from itertools import chain
-from typing import Optional
+from typing import List, Optional
 
 import aiohttp
 import httpx
 import requests
+from pydantic import BaseModel
 
 import litellm
 from litellm import verbose_logger
+from litellm.types.llms.ollama import OllamaToolCall, OllamaToolCallFunction
+from litellm.types.llms.openai import ChatCompletionAssistantToolCall
 
 
 class OllamaError(Exception):
@@ -175,7 +178,7 @@ class OllamaChatConfig:
                 ## CHECK IF MODEL SUPPORTS TOOL CALLING ##
                 try:
                     model_info = litellm.get_model_info(
-                        model=model, custom_llm_provider="ollama_chat"
+                        model=model, custom_llm_provider="ollama"
                     )
                     if model_info.get("supports_function_calling") is True:
                         optional_params["tools"] = value
@@ -237,13 +240,30 @@ def get_ollama_response(
     function_name = optional_params.pop("function_name", None)
     tools = optional_params.pop("tools", None)
 
+    new_messages = []
     for m in messages:
-        if "role" in m and m["role"] == "tool":
+        if isinstance(
-            m["role"] = "assistant"
+            m, BaseModel
+        ):  # avoid message serialization issues - https://github.com/BerriAI/litellm/issues/5319
+            m = m.model_dump(exclude_none=True)
+        if m.get("tool_calls") is not None and isinstance(m["tool_calls"], list):
+            new_tools: List[OllamaToolCall] = []
+            for tool in m["tool_calls"]:
+                typed_tool = ChatCompletionAssistantToolCall(**tool)  # type: ignore
+                if typed_tool["type"] == "function":
+                    ollama_tool_call = OllamaToolCall(
+                        function=OllamaToolCallFunction(
+                            name=typed_tool["function"]["name"],
+                            arguments=json.loads(typed_tool["function"]["arguments"]),
+                        )
+                    )
+                    new_tools.append(ollama_tool_call)
+            m["tool_calls"] = new_tools
+        new_messages.append(m)
 
     data = {
         "model": model,
-        "messages": messages,
+        "messages": new_messages,
         "options": optional_params,
         "stream": stream,
     }
@@ -263,7 +283,7 @@ def get_ollama_response(
         },
     )
     if acompletion is True:
-        if stream == True:
+        if stream is True:
             response = ollama_async_streaming(
                 url=url,
                 api_key=api_key,
@@ -283,7 +303,7 @@ def get_ollama_response(
                 function_name=function_name,
             )
         return response
-    elif stream == True:
+    elif stream is True:
         return ollama_completion_stream(
             url=url, api_key=api_key, data=data, logging_obj=logging_obj
         )

litellm/main.py

@@ -2464,7 +2464,7 @@ def completion(
                 model_response=model_response,
                 encoding=encoding,
             )
-            if acompletion is True or optional_params.get("stream", False) == True:
+            if acompletion is True or optional_params.get("stream", False) is True:
                 return generator
 
             response = generator

litellm/tests/test_function_calling.py

@@ -54,6 +54,7 @@ def get_current_weather(location, unit="fahrenheit"):
 )
 def test_parallel_function_call(model):
     try:
+        litellm.set_verbose = True
         # Step 1: send the conversation and available functions to the model
         messages = [
             {

litellm/types/llms/ollama.py

@@ -0,0 +1,24 @@
+import json
+from typing import Any, Optional, TypedDict, Union
+
+from pydantic import BaseModel
+from typing_extensions import (
+    Protocol,
+    Required,
+    Self,
+    TypeGuard,
+    get_origin,
+    override,
+    runtime_checkable,
+)
+
+
+class OllamaToolCallFunction(
+    TypedDict
+):  # follows - https://github.com/ollama/ollama/blob/6bd8a4b0a1ac15d5718f52bbe1cd56f827beb694/api/types.go#L148
+    name: str
+    arguments: dict
+
+
+class OllamaToolCall(TypedDict):
+    function: OllamaToolCallFunction