Fix excessive token usage with Unicode text in realtime event serialization

[josharsh]

Non-ASCII characters in real-time event data (such as Cyrillic, Chinese, Arabic, etc.) were being unnecessarily escaped during JSON serialisation, causing significant token overhead.

This fix adds ensure_ascii=False to json.dumps() calls in real-time WebSocket event sending, preserving Unicode characters in their original form.

Token savings:

• 54-60% size reduction for Unicode-heavy schemas
• ~116+ tokens saved per typical function schema with Cyrillic descriptions
• Backwards compatible - outputs valid JSON that parses identically

Fixes issue #2428 where Pydantic schema descriptions with Cyrillic text caused 3.6x token overhead.

The fix updates both sync and async realtime connection send() methods to use ensure_ascii=False, which is the modern standard for JSON serialisation with Unicode content.

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Changes being requested

Additional context & links

[tg-bomze]

Unfortunately, your code (pip install git+https://github.com/josharsh/openai-python.git@fix-unicode-token-usage) does not solve the problem in my example:

import json
from pydantic import BaseModel, Field
from openai import OpenAI

import tiktoken
enc = tiktoken.encoding_for_model("gpt-4o")

user_prompt = "My name John"
messages = [{"role": "user", "content": user_prompt}]

class Schema(BaseModel):
    user_name: str = Field(description="Имя пользователя, если он его называл. Если нет, то оставь пустую строку")

schema = Schema.model_json_schema()

print("--- SCHEMA (ensure_ascii=False) ---")
str_schema = json.dumps(schema, ensure_ascii=False)
num_tokens = len(enc.encode(str_schema))
print(str_schema)
print(f"Num tokens: {num_tokens}")

print("\n--- SCHEMA (ensure_ascii=True) ---")
str_schema = json.dumps(schema, ensure_ascii=True)
num_tokens = len(enc.encode(str_schema))
print(str_schema)
print(f"Num tokens: {num_tokens}")

print("\n--- USER PROMPT ---")
num_tokens = len(enc.encode(user_prompt))
print(user_prompt)
print(f"Num tokens: {num_tokens}")

print("\n--- MESSAGES ---")
str_messages = str(messages)
num_tokens = len(enc.encode(str_messages))
print(str_messages)
print(f"Num tokens: {num_tokens}")

with OpenAI(api_key=api_key) as client:
    response = client.beta.chat.completions.parse(
        model="gpt-4o",
        messages=messages,
        response_format=Schema,
    )

print("\n--- Prompt tokens (from response) ---")
print(f"Num tokens: {response.usage.prompt_tokens}")

Result:

-- SCHEMA (ensure_ascii=False) ---
{"properties": {"user_name": {"description": "Имя пользователя, если он его называл. Если нет, то оставь пустую строку", "title": "User Name", "type": "string"}}, "required": ["user_name"], "title": "Schema", "type": "object"}
Num tokens: 65

--- SCHEMA (ensure_ascii=True) ---
{"properties": {"user_name": {"description": "\u0418\u043c\u044f \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f, \u0435\u0441\u043b\u0438 \u043e\u043d \u0435\u0433\u043e \u043d\u0430\u0437\u044b\u0432\u0430\u043b. \u0415\u0441\u043b\u0438 \u043d\u0435\u0442, \u0442\u043e \u043e\u0441\u0442\u0430\u0432\u044c \u043f\u0443\u0441\u0442\u0443\u044e \u0441\u0442\u0440\u043e\u043a\u0443", "title": "User Name", "type": "string"}}, "required": ["user_name"], "title": "Schema", "type": "object"}
Num tokens: 233

--- USER PROMPT ---
My name John
Num tokens: 3

--- MESSAGES ---
[{'role': 'user', 'content': 'My name John'}]
Num tokens: 16

--- Prompt tokens (from response) ---
Num tokens: 240

I think this is a problem on the OpenAI servers' side, because they receive a JSON object and then serialize it without ensure_ascii=False.