Fix a bug where debug logging fails with Iterable objects

Author: seratch

src/agents/extensions/models/litellm_model.py

@@ -48,6 +48,7 @@
 from ...tracing.span_data import GenerationSpanData
 from ...tracing.spans import Span
 from ...usage import Usage
+from ...util._json import _to_dump_compatible
 
 
 class InternalChatCompletionMessage(ChatCompletionMessage):
@@ -286,10 +287,20 @@ async def _fetch_response(
         if _debug.DONT_LOG_MODEL_DATA:
             logger.debug("Calling LLM")
         else:
+            messages_json = json.dumps(
+                _to_dump_compatible(converted_messages),
+                indent=2,
+                ensure_ascii=False,
+            )
+            tools_json = json.dumps(
+                _to_dump_compatible(converted_tools),
+                indent=2,
+                ensure_ascii=False,
+            )
             logger.debug(
                 f"Calling Litellm model: {self.model}\n"
-                f"{json.dumps(converted_messages, indent=2, ensure_ascii=False)}\n"
-                f"Tools:\n{json.dumps(converted_tools, indent=2, ensure_ascii=False)}\n"
+                f"{messages_json}\n"
+                f"Tools:\n{tools_json}\n"
                 f"Stream: {stream}\n"
                 f"Tool choice: {tool_choice}\n"
                 f"Response format: {response_format}\n"
@@ -369,9 +380,9 @@ def convert_message_to_openai(
         if message.role != "assistant":
             raise ModelBehaviorError(f"Unsupported role: {message.role}")
 
-        tool_calls: list[
-            ChatCompletionMessageFunctionToolCall | ChatCompletionMessageCustomToolCall
-        ] | None = (
+        tool_calls: (
+            list[ChatCompletionMessageFunctionToolCall | ChatCompletionMessageCustomToolCall] | None
+        ) = (
             [LitellmConverter.convert_tool_call_to_openai(tool) for tool in message.tool_calls]
             if message.tool_calls
             else None

src/agents/models/openai_chatcompletions.py

@@ -23,6 +23,7 @@
 from ..tracing.span_data import GenerationSpanData
 from ..tracing.spans import Span
 from ..usage import Usage
+from ..util._json import _to_dump_compatible
 from .chatcmpl_converter import Converter
 from .chatcmpl_helpers import HEADERS, ChatCmplHelpers
 from .chatcmpl_stream_handler import ChatCmplStreamHandler
@@ -258,9 +259,19 @@ async def _fetch_response(
         if _debug.DONT_LOG_MODEL_DATA:
             logger.debug("Calling LLM")
         else:
+            messages_json = json.dumps(
+                _to_dump_compatible(converted_messages),
+                indent=2,
+                ensure_ascii=False,
+            )
+            tools_json = json.dumps(
+                _to_dump_compatible(converted_tools),
+                indent=2,
+                ensure_ascii=False,
+            )
             logger.debug(
-                f"{json.dumps(converted_messages, indent=2, ensure_ascii=False)}\n"
-                f"Tools:\n{json.dumps(converted_tools, indent=2, ensure_ascii=False)}\n"
+                f"{messages_json}\n"
+                f"Tools:\n{tools_json}\n"
                 f"Stream: {stream}\n"
                 f"Tool choice: {tool_choice}\n"
                 f"Response format: {response_format}\n"

src/agents/models/openai_responses.py

@@ -38,6 +38,7 @@
 )
 from ..tracing import SpanError, response_span
 from ..usage import Usage
+from ..util._json import _to_dump_compatible
 from ..version import __version__
 from .interface import Model, ModelTracing
 
@@ -263,10 +264,20 @@ async def _fetch_response(
         if _debug.DONT_LOG_MODEL_DATA:
             logger.debug("Calling LLM")
         else:
+            input_json = json.dumps(
+                _to_dump_compatible(list_input),
+                indent=2,
+                ensure_ascii=False,
+            )
+            tools_json = json.dumps(
+                _to_dump_compatible(converted_tools.tools),
+                indent=2,
+                ensure_ascii=False,
+            )
             logger.debug(
                 f"Calling LLM {self.model} with input:\n"
-                f"{json.dumps(list_input, indent=2, ensure_ascii=False)}\n"
-                f"Tools:\n{json.dumps(converted_tools.tools, indent=2, ensure_ascii=False)}\n"
+                f"{input_json}\n"
+                f"Tools:\n{tools_json}\n"
                 f"Stream: {stream}\n"
                 f"Tool choice: {tool_choice}\n"
                 f"Response format: {response_format}\n"

src/agents/util/_json.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import Literal
+from collections.abc import Iterable
+from typing import Any, Literal
 
 from pydantic import TypeAdapter, ValidationError
 from typing_extensions import TypeVar
@@ -29,3 +30,20 @@ def validate_json(json_str: str, type_adapter: TypeAdapter[T], partial: bool) ->
         raise ModelBehaviorError(
             f"Invalid JSON when parsing {json_str} for {type_adapter}; {e}"
         ) from e
+
+
+def _to_dump_compatible(obj: Any) -> Any:
+    return _to_dump_compatible_internal(obj)
+
+
+def _to_dump_compatible_internal(obj: Any) -> Any:
+    if isinstance(obj, dict):
+        return {k: _to_dump_compatible_internal(v) for k, v in obj.items()}
+
+    if isinstance(obj, (list, tuple)):
+        return [_to_dump_compatible_internal(x) for x in obj]
+
+    if isinstance(obj, Iterable) and not isinstance(obj, (str, bytes, bytearray)):
+        return [_to_dump_compatible_internal(x) for x in obj]
+
+    return obj

tests/utils/test_json.py

@@ -0,0 +1,32 @@
+import json
+
+from openai.types.responses.response_output_message_param import ResponseOutputMessageParam
+from openai.types.responses.response_output_text_param import ResponseOutputTextParam
+
+from agents.util._json import _to_dump_compatible
+
+
+def test_to_dump_compatible():
+    # Given a list of message dictionaries, ensure the returned list is a deep copy.
+    input_iter = [
+        ResponseOutputMessageParam(
+            id="a75654dc-7492-4d1c-bce0-89e8312fbdd7",
+            content=[
+                ResponseOutputTextParam(
+                    type="output_text",
+                    text="Hey, what's up?",
+                    annotations=[],
+                )
+            ].__iter__(),
+            role="assistant",
+            status="completed",
+            type="message",
+        )
+    ].__iter__()
+    # this fails if any of the properties are Iterable objects.
+    # result = json.dumps(input_iter)
+    result = json.dumps(_to_dump_compatible(input_iter))
+    assert (
+        result
+        == """[{"id": "a75654dc-7492-4d1c-bce0-89e8312fbdd7", "content": [{"type": "output_text", "text": "Hey, what's up?", "annotations": []}], "role": "assistant", "status": "completed", "type": "message"}]"""  # noqa: E501
+    )