Optimize tool call conversions to eliminate redundant API lookups

libs/oci/langchain_oci/chat_models/oci_generative_ai.py

@@ -100,22 +100,37 @@
     @staticmethod
     def convert_oci_tool_call_to_langchain(tool_call: Any) -> ToolCall:
         """Convert an OCI tool call to a LangChain ToolCall."""
-        parsed = json.loads(tool_call.arguments)
-
-        # If the parsed result is a string, it means the JSON was escaped, so parse again  # noqa: E501
-        if isinstance(parsed, str):
-            try:
-                parsed = json.loads(parsed)
-            except json.JSONDecodeError:
-                # If it's not valid JSON, keep it as a string
-                pass
+        # Check if this is a Generic/Meta format (has arguments as JSON string)
+        # or Cohere format (has parameters as dict)
+        attribute_map = getattr(tool_call, "attribute_map", None) or {}
+
+        if "arguments" in attribute_map and tool_call.arguments is not None:
+            # Generic/Meta format: parse JSON arguments
+            parsed = json.loads(tool_call.arguments)
+
+            # If the parsed result is a string, it means JSON was escaped
+            if isinstance(parsed, str):
+                try:
+                    parsed = json.loads(parsed)
+                except json.JSONDecodeError:
+                    # If it's not valid JSON, keep it as a string
+                    pass
+            args = parsed
+        else:
+            # Cohere format: parameters is already a dict
+            args = tool_call.parameters
+
+        # Get tool call ID (generate one if not present)
+        tool_id = (
+            tool_call.id
+            if "id" in attribute_map
+            else uuid.uuid4().hex[:]
+        )
 
         return ToolCall(
             name=tool_call.name,
-            args=parsed
-            if "arguments" in tool_call.attribute_map
-            else tool_call.parameters,
-            id=tool_call.id if "id" in tool_call.attribute_map else uuid.uuid4().hex[:],
+            args=args,
+            id=tool_id,
         )
 
 
@@ -271,11 +286,6 @@
                 response.data.chat_response.usage.total_tokens
             )
 
-        # Include tool calls if available
-        if self.chat_tool_calls(response):
-            generation_info["tool_calls"] = self.format_response_tool_calls(
-                self.chat_tool_calls(response)
-            )
         return generation_info
 
     def chat_stream_generation_info(self, event_data: Dict) -> Dict[str, Any]:
@@ -651,10 +661,6 @@
                 response.data.chat_response.usage.total_tokens
             )
 
-        if self.chat_tool_calls(response):
-            generation_info["tool_calls"] = self.format_response_tool_calls(
-                self.chat_tool_calls(response)
-            )
         return generation_info
 
     def chat_stream_generation_info(self, event_data: Dict) -> Dict[str, Any]:
@@ -1400,6 +1406,9 @@
         if stop is not None:
             content = enforce_stop_tokens(content, stop)
 
+        # Fetch raw tool calls once to avoid redundant calls
+        raw_tool_calls = self._provider.chat_tool_calls(response)
+
         generation_info = self._provider.chat_generation_info(response)
 
         llm_output = {
@@ -1408,12 +1417,17 @@
             "request_id": response.request_id,
             "content-length": response.headers["content-length"],
         }
+
         tool_calls = []
-        if "tool_calls" in generation_info:
+        if raw_tool_calls:
             tool_calls = [
                 OCIUtils.convert_oci_tool_call_to_langchain(tool_call)
-                for tool_call in self._provider.chat_tool_calls(response)
+                for tool_call in raw_tool_calls
             ]
+            if "tool_calls" not in generation_info:
+                generation_info["tool_calls"] = self._provider.format_response_tool_calls(
+                    raw_tool_calls
+                )
         message = AIMessage(
             content=content or "",
             additional_kwargs=generation_info,
@@ -1484,7 +1498,7 @@
 
     Attributes:
         auth (httpx.Auth): Authentication handler for OCI request signing.
         compartment_id (str): OCI compartment ID for resource isolation
         model (str): Name of OpenAI model to use.
         conversation_store_id (str | None): Conversation Store Id to use
                                             when generating responses.