Fix tool calling on Llama API (#3064)

## Summary

The ReasoningTools require optional params to be handled correctly.

Fixes #3063 

## Type of change

- [ ] Bug fix
- [ ] New feature
- [ ] Breaking change
- [ ] Improvement
- [ ] Model update
- [ ] Other:

---

## Checklist

- [ ] Code complies with style guidelines
- [ ] Ran format/validation scripts (`./scripts/format.sh` and
`./scripts/validate.sh`)
- [ ] Self-review completed
- [ ] Documentation updated (comments, docstrings)
- [ ] Examples and guides: Relevant cookbook examples have been included
or updated (if applicable)
- [ ] Tested in clean environment
- [ ] Tests added/updated (if applicable)

---

## Additional Notes

Add any important context (deployment instructions, screenshots,
security considerations, etc.)

---------

Co-authored-by: ysolanky <yash@phidata.com>

Author: dirkbrnd

libs/agno/agno/models/meta/llama.py

@@ -152,6 +152,13 @@ def request_kwargs(self) -> Dict[str, Any]:
         # Add tools
         if self._tools is not None and len(self._tools) > 0:
             request_params["tools"] = self._tools
+            
+            # Fix optional parameters where the "type" is [<type>, null]
+            for tool in request_params["tools"]:  # type: ignore
+                if "parameters" in tool["function"] and "properties" in tool["function"]["parameters"]:  # type: ignore
+                    for _, obj in tool["function"]["parameters"].get("properties", {}).items():  # type: ignore
+                        if isinstance(obj["type"], list):
+                            obj["type"] = obj["type"][0]
 
         if self.response_format is not None:
             request_params["response_format"] = self.response_format
@@ -267,7 +274,6 @@ async def ainvoke_stream(self, messages: List[Message]) -> AsyncIterator[CreateC
             log_error(f"Error from Llama API: {e}")
             raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e
 
-    # Override base method
     @staticmethod
     def parse_tool_calls(tool_calls_data: List[EventDeltaToolCallDeltaFunction]) -> List[Dict[str, Any]]:
         """

libs/agno/agno/models/meta/llama_openai.py

@@ -33,9 +33,65 @@ class LlamaOpenAI(OpenAILike):
 
     api_key: Optional[str] = getenv("LLAMA_API_KEY")
     base_url: Optional[str] = "https://api.llama.com/compat/v1/"
+    
+    # Request parameters
+    max_completion_tokens: Optional[int] = None
+    repetition_penalty: Optional[float] = None
+    temperature: Optional[float] = None
+    top_p: Optional[float] = None
+    top_k: Optional[int] = None
+    extra_headers: Optional[Any] = None
+    extra_query: Optional[Any] = None
+    extra_body: Optional[Any] = None
+    request_params: Optional[Dict[str, Any]] = None
 
     supports_native_structured_outputs: bool = False
     supports_json_schema_outputs: bool = True
+    
+    
+    @property
+    def request_kwargs(self) -> Dict[str, Any]:
+        """
+        Returns keyword arguments for API requests.
+
+        Returns:
+            Dict[str, Any]: A dictionary of keyword arguments for API requests.
+        """
+        # Define base request parameters
+        base_params = {
+            "max_completion_tokens": self.max_completion_tokens,
+            "repetition_penalty": self.repetition_penalty,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+            "top_k": self.top_k,
+            "extra_headers": self.extra_headers,
+            "extra_query": self.extra_query,
+            "extra_body": self.extra_body,
+            "request_params": self.request_params,
+        }
+
+        # Filter out None values
+        request_params = {k: v for k, v in base_params.items() if v is not None}
+
+        # Add tools
+        if self._tools is not None and len(self._tools) > 0:
+            request_params["tools"] = self._tools
+            
+            # Fix optional parameters where the "type" is [<type>, null]
+            for tool in request_params["tools"]:  # type: ignore
+                if "parameters" in tool["function"] and "properties" in tool["function"]["parameters"]:  # type: ignore
+                    for _, obj in tool["function"]["parameters"].get("properties", {}).items():  # type: ignore
+                        if isinstance(obj["type"], list):
+                            obj["type"] = obj["type"][0]
+
+        if self.response_format is not None:
+            request_params["response_format"] = self.response_format
+
+        # Add additional request params if provided
+        if self.request_params:
+            request_params.update(self.request_params)
+
+        return request_params
 
     def _format_message(self, message: Message) -> Dict[str, Any]:
         """

libs/agno/tests/integration/models/meta/llama/test_tool_use.py

@@ -180,7 +180,6 @@ def get_the_weather_in_tokyo():
     assert "Tokyo" in response.content
 
 
-@pytest.mark.skip("Llama models do not not accept optional parameters")
 def test_tool_call_custom_tool_optional_parameters():
     def get_the_weather(city: Optional[str] = None):
         """

libs/agno/tests/integration/models/meta/llama_openai/test_tool_use.py

@@ -180,7 +180,6 @@ def get_the_weather_in_tokyo():
     assert "Tokyo" in response.content
 
 
-@pytest.mark.skip("Llama models do not not accept optional parameters")
 def test_tool_call_custom_tool_optional_parameters():
     def get_the_weather(city: Optional[str] = None):
         """