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from __future__ import annotations
import uuid
import json
from aiohttp import ClientSession, BaseConnector
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import get_connector
from ..requests import raise_for_status
from ..errors import RateLimitError
models = {
"claude-3-5-sonnet-20241022": {
"id": "claude-3-5-sonnet-20241022",
"name": "claude-3-5-sonnet-20241022",
"model": "claude-3-5-sonnet-20241022",
"provider": "Anthropic",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 25.366666666666667,
},
"claude-3-5-sonnet-20241022-t": {
"id": "claude-3-5-sonnet-20241022-t",
"name": "claude-3-5-sonnet-20241022-t",
"model": "claude-3-5-sonnet-20241022-t",
"provider": "Anthropic",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 39.820754716981135,
},
"claude-3-7-sonnet-20250219": {
"id": "claude-3-7-sonnet-20250219",
"name": "claude-3-7-sonnet-20250219",
"model": "claude-3-7-sonnet-20250219",
"provider": "Anthropic",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 47.02970297029703,
},
"claude-3-7-sonnet-20250219-t": {
"id": "claude-3-7-sonnet-20250219-t",
"name": "claude-3-7-sonnet-20250219-t",
"model": "claude-3-7-sonnet-20250219-t",
"provider": "Anthropic",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 39.04289693593315,
},
"deepseek-v3": {
"id": "deepseek-v3",
"name": "deepseek-v3",
"model": "deepseek-v3",
"provider": "DeepSeek",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 40.484657419083646,
},
"gemini-1.0-pro-latest-123": {
"id": "gemini-1.0-pro-latest-123",
"name": "gemini-1.0-pro-latest-123",
"model": "gemini-1.0-pro-latest-123",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 10,
},
"gemini-2.0-flash": {
"id": "gemini-2.0-flash",
"name": "gemini-2.0-flash",
"model": "gemini-2.0-flash",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 216.44162436548223,
},
"gemini-2.0-flash-exp": {
"id": "gemini-2.0-flash-exp",
"name": "gemini-2.0-flash-exp",
"model": "gemini-2.0-flash-exp",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 0,
"tps": 0,
},
"gemini-2.0-flash-thinking-exp": {
"id": "gemini-2.0-flash-thinking-exp",
"name": "gemini-2.0-flash-thinking-exp",
"model": "gemini-2.0-flash-thinking-exp",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 0,
"tps": 0,
},
"gemini-2.5-flash-preview-04-17": {
"id": "gemini-2.5-flash-preview-04-17",
"name": "gemini-2.5-flash-preview-04-17",
"model": "gemini-2.5-flash-preview-04-17",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 189.84010840108402,
},
"gemini-2.5-pro-official": {
"id": "gemini-2.5-pro-official",
"name": "gemini-2.5-pro-official",
"model": "gemini-2.5-pro-official",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 91.00613496932516,
},
"gemini-2.5-pro-preview-03-25": {
"id": "gemini-2.5-pro-preview-03-25",
"name": "gemini-2.5-pro-preview-03-25",
"model": "gemini-2.5-pro-preview-03-25",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 99.05660377358491,
"tps": 45.050511247443765,
},
"gemini-2.5-pro-preview-05-06": {
"id": "gemini-2.5-pro-preview-05-06",
"name": "gemini-2.5-pro-preview-05-06",
"model": "gemini-2.5-pro-preview-05-06",
"provider": "Google",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 99.29617834394904,
},
"gpt-4-turbo-2024-04-09": {
"id": "gpt-4-turbo-2024-04-09",
"name": "gpt-4-turbo-2024-04-09",
"model": "gpt-4-turbo-2024-04-09",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 1,
},
"gpt-4.1": {
"id": "gpt-4.1",
"name": "gpt-4.1",
"model": "gpt-4.1",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 42.857142857142854,
"tps": 19.58032786885246,
},
"gpt-4.1-mini": {
"id": "gpt-4.1-mini",
"name": "gpt-4.1-mini",
"model": "gpt-4.1-mini",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 68.75,
"tps": 12.677576601671309,
},
"gpt-4.1-mini-2025-04-14": {
"id": "gpt-4.1-mini-2025-04-14",
"name": "gpt-4.1-mini-2025-04-14",
"model": "gpt-4.1-mini-2025-04-14",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 94.23076923076923,
"tps": 8.297687861271676,
},
"gpt-4o-2024-11-20": {
"id": "gpt-4o-2024-11-20",
"name": "gpt-4o-2024-11-20",
"model": "gpt-4o-2024-11-20",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 73.3955223880597,
},
"gpt-4o-mini-2024-07-18": {
"id": "gpt-4o-mini-2024-07-18",
"name": "gpt-4o-mini-2024-07-18",
"model": "gpt-4o-mini-2024-07-18",
"provider": "OpenAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 26.874455100261553,
},
"grok-3": {
"id": "grok-3",
"name": "grok-3",
"model": "grok-3",
"provider": "xAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 51.110652663165794,
},
"grok-3-reason": {
"id": "grok-3-reason",
"name": "grok-3-reason",
"model": "grok-3-reason",
"provider": "xAI",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 62.81976744186046,
},
"o3-mini-2025-01-31": {
"id": "o3-mini-2025-01-31",
"name": "o3-mini-2025-01-31",
"model": "o3-mini-2025-01-31",
"provider": "Unknown",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 125.31410256410257,
},
"qwen3-235b-a22b": {
"id": "qwen3-235b-a22b",
"name": "qwen3-235b-a22b",
"model": "qwen3-235b-a22b",
"provider": "Alibaba",
"maxLength": 0,
"tokenLimit": 0,
"context": 0,
"success_rate": 100,
"tps": 25.846153846153847,
},
}
class Liaobots(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://liaobots.work"
working = True
supports_message_history = True
supports_system_message = True
default_model = "grok-3"
models = list(models.keys())
model_aliases = {
# Anthropic
"claude-3.5-sonnet": "claude-3-5-sonnet-20241022",
"claude-3.5-sonnet": "claude-3-5-sonnet-20241022-t",
"claude-3.7-sonnet": "claude-3-7-sonnet-20250219",
"claude-3.7-sonnet": "claude-3-7-sonnet-20250219-t",
# DeepSeek
#"deepseek-v3": "deepseek-v3",
# Google
"gemini-1.0-pro": "gemini-1.0-pro-latest-123",
"gemini-2.0-flash": "gemini-2.0-flash-exp",
"gemini-2.0-flash-thinking": "gemini-2.0-flash-thinking-exp",
"gemini-2.5-flash": "gemini-2.5-flash-preview-04-17",
"gemini-2.5-pro": "gemini-2.5-pro-official",
"gemini-2.5-pro": "gemini-2.5-pro-preview-03-25",
"gemini-2.5-pro": "gemini-2.5-pro-preview-05-06",
# OpenAI
"gpt-4-turbo": "gpt-4-turbo-2024-04-09",
"gpt-4.1-mini": "gpt-4.1-mini-2025-04-14",
"gpt-4": "gpt-4o-2024-11-20",
"gpt-4o": "gpt-4o-2024-11-20",
"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
# xAI
"grok-3-reason": "grok-3-reason",
"o3-mini": "o3-mini-2025-01-31",
"qwen-3-235b": "qwen3-235b-a22b",
}
_auth_code = None
_cookie_jar = None
@classmethod
def is_supported(cls, model: str) -> bool:
"""
Check if the given model is supported.
"""
return model in models or model in cls.model_aliases
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
connector: BaseConnector = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"content-type": "application/json",
"dnt": "1",
"origin": "https://liaobots.work",
"priority": "u=1, i",
"referer": "https://liaobots.work/en",
"sec-ch-ua": "\"Chromium\";v=\"135\", \"Not-A.Brand\";v=\"8\"",
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": "\"Linux\"",
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36"
}
async with ClientSession(
headers=headers,
cookie_jar=cls._cookie_jar,
connector=get_connector(connector, proxy, True)
) as session:
# First, get a valid auth code
await cls.get_auth_code(session)
# Create conversation ID
conversation_id = str(uuid.uuid4())
# Prepare request data
data = {
"conversationId": conversation_id,
"models": [{
"modelId": model,
"provider": models[model]["provider"]
}],
"search": "false",
"messages": messages,
"key": "",
"prompt": kwargs.get("system_message", "你是 {{model}}，一个由 {{provider}} 训练的大型语言模型，请仔细遵循用户的指示。")
}
# Try to make the chat request
try:
# Make the chat request with the current auth code
async with session.post(
f"{cls.url}/api/chat",
json=data,
headers={"x-auth-code": cls._auth_code},
ssl=False
) as response:
# Check if we got a streaming response
content_type = response.headers.get("Content-Type", "")
if "text/event-stream" in content_type:
async for line in response.content:
if line.startswith(b"data: "):
try:
response_data = json.loads(line[6:])
# Check for error response
if response_data.get("error") is True:
# Raise RateLimitError for payment required or other errors
if "402" in str(response_data.get("res_status", "")):
raise RateLimitError("This model requires payment or credits")
else:
error_msg = response_data.get('message', 'Unknown error')
raise RateLimitError(f"Error: {error_msg}")
# Process normal response
if response_data.get("role") == "assistant" and "content" in response_data:
content = response_data.get("content")
yield content
except json.JSONDecodeError:
continue
else:
# Not a streaming response, might be an error or HTML
response_text = await response.text()
# If we got HTML, we need to bypass CAPTCHA
if response_text.startswith("<!DOCTYPE html>"):
await cls.bypass_captcha(session)
# Get a fresh auth code
await cls.get_auth_code(session)
# Try the request again
async with session.post(
f"{cls.url}/api/chat",
json=data,
headers={"x-auth-code": cls._auth_code},
ssl=False
) as response2:
# Check if we got a streaming response
content_type = response2.headers.get("Content-Type", "")
if "text/event-stream" in content_type:
async for line in response2.content:
if line.startswith(b"data: "):
try:
response_data = json.loads(line[6:])
# Check for error response
if response_data.get("error") is True:
# Raise RateLimitError for payment required or other errors
if "402" in str(response_data.get("res_status", "")):
raise RateLimitError("This model requires payment or credits")
else:
error_msg = response_data.get('message', 'Unknown error')
raise RateLimitError(f"Error: {error_msg}")
# Process normal response
if response_data.get("role") == "assistant" and "content" in response_data:
content = response_data.get("content")
yield content
except json.JSONDecodeError:
continue
else:
raise RateLimitError("Failed to get streaming response")
else:
raise RateLimitError("Failed to connect to the service")
except Exception as e:
# If it's already a RateLimitError, re-raise it
if isinstance(e, RateLimitError):
raise
# Otherwise, wrap it in a RateLimitError
raise RateLimitError(f"Error processing request: {str(e)}")
@classmethod
async def bypass_captcha(cls, session: ClientSession) -> None:
"""
Bypass the CAPTCHA verification by directly making the recaptcha API request.
"""
try:
# First, try the direct recaptcha API request
async with session.post(
f"{cls.url}/recaptcha/api/login",
json={"token": "abcdefghijklmnopqrst"},
ssl=False
) as response:
if response.status == 200:
try:
response_text = await response.text()
# Try to parse as JSON
try:
response_data = json.loads(response_text)
# Check if we got a successful response
if response_data.get("code") == 200:
cls._cookie_jar = session.cookie_jar
except json.JSONDecodeError:
pass
except Exception:
pass
except Exception:
pass
@classmethod
async def get_auth_code(cls, session: ClientSession) -> None:
"""
Get a valid auth code by sending a request with an empty authcode.
"""
try:
# Send request with empty authcode to get a new one
auth_request_data = {
"authcode": "",
"recommendUrl": "https://liaobots.work/zh"
}
async with session.post(
f"{cls.url}/api/user",
json=auth_request_data,
ssl=False
) as response:
if response.status == 200:
response_text = await response.text()
try:
response_data = json.loads(response_text)
if "authCode" in response_data:
cls._auth_code = response_data["authCode"]
cls._cookie_jar = session.cookie_jar
return
except json.JSONDecodeError:
# If we got HTML, it might be the CAPTCHA page
if response_text.startswith("<!DOCTYPE html>"):
await cls.bypass_captcha(session)
# Try again after bypassing CAPTCHA
async with session.post(
f"{cls.url}/api/user",
json=auth_request_data,
ssl=False
) as response2:
if response2.status == 200:
response_text2 = await response2.text()
try:
response_data2 = json.loads(response_text2)
if "authCode" in response_data2:
cls._auth_code = response_data2["authCode"]
cls._cookie_jar = session.cookie_jar
return
except json.JSONDecodeError:
pass
except Exception:
pass
# If we're here, we couldn't get a valid auth code
# Set a default one as a fallback
cls._auth_code = "DvS3A5GTE9f0D" # Fallback to one of the provided auth codes
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