Apply ensure_ascii=False to remaining LLM services and fix changelog format

This commit is contained in:
Mark Backman
2026-03-12 10:34:29 -04:00
parent 765fbeec63
commit 1fe1f0f439
5 changed files with 9 additions and 20 deletions

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@@ -1,16 +1 @@
# Reduce Call Tool Result Context Size by Allowing UTF-8 in JSON Serialization
This PR changes tool result serialization to prevent UTF-8 code points from being escaped during serialization. This drastically reduces the context size when returning a response that contains languages other than English.
We have been running a monkey-patched version in production and it helped us improve the agent accuracy and control cost better.
```
>>> data = { "message": "أهلًا بالعالم" }
>>> json.dumps(data)
'{"message": "\\u0623\\u0647\\u0644\\u064b\\u0627 \\u0628\\u0627\\u0644\\u0639\\u0627\\u0644\\u0645"}'
>>>
>>>
>>>
>>> json.dumps(data, ensure_ascii=False)
'{"message": "أهلًا بالعالم"}'
```
- Changed tool result JSON serialization to use `ensure_ascii=False`, preserving UTF-8 characters instead of escaping them. This reduces context size and token usage for non-English languages.

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@@ -1044,7 +1044,9 @@ class AWSNovaSonicLLMService(LLMService):
"toolResult": {
"promptName": self._prompt_name,
"contentName": content_name,
"content": json.dumps(result) if isinstance(result, dict) else result,
"content": json.dumps(result, ensure_ascii=False)
if isinstance(result, dict)
else result,
}
}
}

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@@ -200,7 +200,9 @@ class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator):
if message.role == "user":
for part in message.parts:
if part.function_response and part.function_response.id == tool_call_id:
part.function_response.response = {"value": json.dumps(result)}
part.function_response.response = {
"value": json.dumps(result, ensure_ascii=False)
}
@dataclass

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@@ -939,7 +939,7 @@ class GrokRealtimeLLMService(LLMService):
item = events.ConversationItem(
type="function_call_output",
call_id=tool_call_id,
output=json.dumps(result),
output=json.dumps(result, ensure_ascii=False),
)
await self.send_client_event(events.ConversationItemCreateEvent(item=item))

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@@ -1128,7 +1128,7 @@ class OpenAIRealtimeLLMService(LLMService):
item = events.ConversationItem(
type="function_call_output",
call_id=tool_call_id,
output=json.dumps(result),
output=json.dumps(result, ensure_ascii=False),
)
await self.send_client_event(events.ConversationItemCreateEvent(item=item))