feat(agent/llm/openai): Include compatibility tool call extraction in LLM response parse-fix loop

1 files changed, 22 insertions, 24 deletions

diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py
index 506286949..af26ba961 100644
--- a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py
+++ b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py
@@ -377,29 +377,17 @@ class OpenAIProvider(
                 **completion_kwargs,
             )
 
-            _response_msg = _response.choices[0].message
-            if (
-                tool_calls_compat_mode
-                and _response_msg.content
-                and not _response_msg.tool_calls
-            ):
-                tool_calls = list(
-                    _tool_calls_compat_extract_calls(_response_msg.content)
-                )
-            elif _response_msg.tool_calls:
-                tool_calls = [
-                    AssistantToolCall(**tc.dict()) for tc in _response_msg.tool_calls
-                ]
-            else:
-                tool_calls = None
-
-            assistant_message = AssistantChatMessage(
-                content=_response_msg.content,
-                tool_calls=tool_calls,
+            _assistant_msg = _response.choices[0].message
+            assistant_msg = AssistantChatMessage(
+                content=_assistant_msg.content,
+                tool_calls=(
+                    [AssistantToolCall(**tc.dict()) for tc in _assistant_msg.tool_calls]
+                    if _assistant_msg.tool_calls
+                    else None
+                ),
             )
-
             response = ChatModelResponse(
-                response=assistant_message,
+                response=assistant_msg,
                 model_info=OPEN_AI_CHAT_MODELS[model_name],
                 prompt_tokens_used=(
                     _response.usage.prompt_tokens if _response.usage else 0
@@ -418,11 +406,21 @@ class OpenAIProvider(
             # LLM fix its mistake(s).
             try:
                 attempts += 1
-                response.parsed_result = completion_parser(assistant_message)
+
+                if (
+                    tool_calls_compat_mode
+                    and assistant_msg.content
+                    and not assistant_msg.tool_calls
+                ):
+                    assistant_msg.tool_calls = list(
+                        _tool_calls_compat_extract_calls(assistant_msg.content)
+                    )
+
+                response.parsed_result = completion_parser(assistant_msg)
                 break
             except Exception as e:
                 self._logger.warning(f"Parsing attempt #{attempts} failed: {e}")
-                self._logger.debug(f"Parsing failed on response: '''{_response_msg}'''")
+                self._logger.debug(f"Parsing failed on response: '''{assistant_msg}'''")
                 if attempts < self._configuration.fix_failed_parse_tries:
                     model_prompt.append(
                         ChatMessage.system(f"ERROR PARSING YOUR RESPONSE:\n\n{e}")
@@ -722,7 +720,7 @@ def _tool_calls_compat_extract_calls(response: str) -> Iterator[AssistantToolCal
     else:
         block = re.search(r"```(?:tool_calls)?\n(.*)\n```\s*$", response, re.DOTALL)
         if not block:
-            raise ValueError("Could not find tool calls block in response")
+            raise ValueError("Could not find tool_calls block in response")
         tool_calls: list[AssistantToolCallDict] = json.loads(block.group(1))
 
     for t in tool_calls: