Fixed bug where non-dynamic routes for OpenAI LLM weren't working.

semantic_router/llms/openai.py

@@ -58,22 +58,49 @@ class OpenAILLM(BaseLLM):
                 tools=tools,  # type: ignore # MyPy expecting Iterable[ChatCompletionToolParam] | NotGiven, but dict is accepted by OpenAI.
             )
 
-            tool_calls = completion.choices[0].message.tool_calls
-            if tool_calls is None:
-                raise ValueError("Invalid output, expected a tool call.")
-            if len(tool_calls) != 1:
-                raise ValueError(
-                    "Invalid output, expected a single tool to be specified."
-                )
-            arguments = tool_calls[0].function.arguments
-            if arguments is None:
-                raise ValueError("Invalid output, expected arguments to be specified.")
-            output = str(arguments)  # str to keep MyPy happy.
+            if function_schema:
+                tool_calls = completion.choices[0].message.tool_calls
+                if tool_calls is None:
+                    raise ValueError("Invalid output, expected a tool call.")
+                if len(tool_calls) != 1:
+                    raise ValueError(
+                        "Invalid output, expected a single tool to be specified."
+                    )
+                arguments = tool_calls[0].function.arguments
+                if arguments is None:
+                    raise ValueError("Invalid output, expected arguments to be specified.")
+                output = str(arguments)  # str to keep MyPy happy.
+            else:
+                content = completion.choices[0].message.content
+                if content is None:
+                    raise ValueError("Invalid output, expected content.")
+                output = str(content) # str to keep MyPy happy.
+                
             return output
 
         except Exception as e:
             logger.error(f"LLM error: {e}")
             raise Exception(f"LLM error: {e}") from e
+        
+    def __call__(self, messages: List[Message]) -> str:
+        if self.client is None:
+            raise ValueError("OpenAI client is not initialized.")
+        try:
+            completion = self.client.chat.completions.create(
+                model=self.name,
+                messages=[m.to_openai() for m in messages],
+                temperature=self.temperature,
+                max_tokens=self.max_tokens,
+            )
+
+            output = completion.choices[0].message.content
+
+            if not output:
+                raise Exception("No output generated")
+            return output
+        except Exception as e:
+            logger.error(f"LLM error: {e}")
+            raise Exception(f"LLM error: {e}") from e
 
     def extract_function_inputs(
         self, query: str, function_schema: dict[str, Any]