mirror of
https://github.com/xtekky/gpt4free.git
synced 2025-12-06 02:30:41 -08:00
540 lines
20 KiB
Python
540 lines
20 KiB
Python
from __future__ import annotations
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import uuid
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import json
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from aiohttp import ClientSession, BaseConnector
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from .helper import get_connector
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from ..requests import raise_for_status
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from ..errors import RateLimitError
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models = {
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"claude-3-5-sonnet-20241022": {
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"id": "claude-3-5-sonnet-20241022",
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"name": "claude-3-5-sonnet-20241022",
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"model": "claude-3-5-sonnet-20241022",
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"provider": "Anthropic",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 25.366666666666667,
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},
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"claude-3-5-sonnet-20241022-t": {
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"id": "claude-3-5-sonnet-20241022-t",
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"name": "claude-3-5-sonnet-20241022-t",
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"model": "claude-3-5-sonnet-20241022-t",
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"provider": "Anthropic",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 39.820754716981135,
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},
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"claude-3-7-sonnet-20250219": {
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"id": "claude-3-7-sonnet-20250219",
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"name": "claude-3-7-sonnet-20250219",
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"model": "claude-3-7-sonnet-20250219",
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"provider": "Anthropic",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 47.02970297029703,
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},
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"claude-3-7-sonnet-20250219-t": {
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"id": "claude-3-7-sonnet-20250219-t",
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"name": "claude-3-7-sonnet-20250219-t",
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"model": "claude-3-7-sonnet-20250219-t",
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"provider": "Anthropic",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 39.04289693593315,
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},
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"deepseek-v3": {
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"id": "deepseek-v3",
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"name": "deepseek-v3",
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"model": "deepseek-v3",
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"provider": "DeepSeek",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 40.484657419083646,
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},
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"gemini-1.0-pro-latest-123": {
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"id": "gemini-1.0-pro-latest-123",
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"name": "gemini-1.0-pro-latest-123",
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"model": "gemini-1.0-pro-latest-123",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 10,
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},
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"gemini-2.0-flash": {
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"id": "gemini-2.0-flash",
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"name": "gemini-2.0-flash",
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"model": "gemini-2.0-flash",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 216.44162436548223,
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},
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"gemini-2.0-flash-exp": {
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"id": "gemini-2.0-flash-exp",
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"name": "gemini-2.0-flash-exp",
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"model": "gemini-2.0-flash-exp",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 0,
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"tps": 0,
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},
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"gemini-2.0-flash-thinking-exp": {
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"id": "gemini-2.0-flash-thinking-exp",
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"name": "gemini-2.0-flash-thinking-exp",
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"model": "gemini-2.0-flash-thinking-exp",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 0,
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"tps": 0,
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},
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"gemini-2.5-flash-preview-04-17": {
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"id": "gemini-2.5-flash-preview-04-17",
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"name": "gemini-2.5-flash-preview-04-17",
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"model": "gemini-2.5-flash-preview-04-17",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 189.84010840108402,
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},
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"gemini-2.5-pro-official": {
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"id": "gemini-2.5-pro-official",
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"name": "gemini-2.5-pro-official",
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"model": "gemini-2.5-pro-official",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 91.00613496932516,
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},
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"gemini-2.5-pro-preview-03-25": {
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"id": "gemini-2.5-pro-preview-03-25",
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"name": "gemini-2.5-pro-preview-03-25",
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"model": "gemini-2.5-pro-preview-03-25",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 99.05660377358491,
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"tps": 45.050511247443765,
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},
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"gemini-2.5-pro-preview-05-06": {
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"id": "gemini-2.5-pro-preview-05-06",
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"name": "gemini-2.5-pro-preview-05-06",
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"model": "gemini-2.5-pro-preview-05-06",
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"provider": "Google",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 99.29617834394904,
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},
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"gpt-4-turbo-2024-04-09": {
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"id": "gpt-4-turbo-2024-04-09",
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"name": "gpt-4-turbo-2024-04-09",
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"model": "gpt-4-turbo-2024-04-09",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 1,
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},
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"gpt-4.1": {
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"id": "gpt-4.1",
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"name": "gpt-4.1",
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"model": "gpt-4.1",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 42.857142857142854,
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"tps": 19.58032786885246,
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},
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"gpt-4.1-mini": {
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"id": "gpt-4.1-mini",
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"name": "gpt-4.1-mini",
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"model": "gpt-4.1-mini",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 68.75,
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"tps": 12.677576601671309,
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},
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"gpt-4.1-mini-2025-04-14": {
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"id": "gpt-4.1-mini-2025-04-14",
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"name": "gpt-4.1-mini-2025-04-14",
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"model": "gpt-4.1-mini-2025-04-14",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 94.23076923076923,
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"tps": 8.297687861271676,
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},
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"gpt-4o-2024-11-20": {
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"id": "gpt-4o-2024-11-20",
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"name": "gpt-4o-2024-11-20",
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"model": "gpt-4o-2024-11-20",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 73.3955223880597,
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},
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"gpt-4o-mini-2024-07-18": {
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"id": "gpt-4o-mini-2024-07-18",
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"name": "gpt-4o-mini-2024-07-18",
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"model": "gpt-4o-mini-2024-07-18",
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"provider": "OpenAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 26.874455100261553,
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},
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"grok-3": {
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"id": "grok-3",
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"name": "grok-3",
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"model": "grok-3",
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"provider": "xAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 51.110652663165794,
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},
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"grok-3-reason": {
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"id": "grok-3-reason",
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"name": "grok-3-reason",
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"model": "grok-3-reason",
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"provider": "xAI",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 62.81976744186046,
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},
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"o3-mini-2025-01-31": {
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"id": "o3-mini-2025-01-31",
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"name": "o3-mini-2025-01-31",
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"model": "o3-mini-2025-01-31",
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"provider": "Unknown",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 125.31410256410257,
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},
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"qwen3-235b-a22b": {
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"id": "qwen3-235b-a22b",
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"name": "qwen3-235b-a22b",
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"model": "qwen3-235b-a22b",
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"provider": "Alibaba",
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"maxLength": 0,
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"tokenLimit": 0,
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"context": 0,
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"success_rate": 100,
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"tps": 25.846153846153847,
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},
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}
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class Liaobots(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://liaobots.work"
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working = True
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supports_message_history = True
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supports_system_message = True
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default_model = "grok-3"
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models = list(models.keys())
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model_aliases = {
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# Anthropic
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"claude-3.5-sonnet": "claude-3-5-sonnet-20241022",
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"claude-3.5-sonnet": "claude-3-5-sonnet-20241022-t",
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"claude-3.7-sonnet": "claude-3-7-sonnet-20250219",
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"claude-3.7-sonnet": "claude-3-7-sonnet-20250219-t",
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# DeepSeek
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#"deepseek-v3": "deepseek-v3",
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# Google
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"gemini-1.0-pro": "gemini-1.0-pro-latest-123",
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"gemini-2.0-flash": "gemini-2.0-flash-exp",
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"gemini-2.0-flash-thinking": "gemini-2.0-flash-thinking-exp",
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"gemini-2.5-flash": "gemini-2.5-flash-preview-04-17",
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"gemini-2.5-pro": "gemini-2.5-pro-official",
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"gemini-2.5-pro": "gemini-2.5-pro-preview-03-25",
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"gemini-2.5-pro": "gemini-2.5-pro-preview-05-06",
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# OpenAI
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"gpt-4-turbo": "gpt-4-turbo-2024-04-09",
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"gpt-4.1-mini": "gpt-4.1-mini-2025-04-14",
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"gpt-4": "gpt-4o-2024-11-20",
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"gpt-4o": "gpt-4o-2024-11-20",
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"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
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# xAI
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"grok-3-reason": "grok-3-reason",
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"o3-mini": "o3-mini-2025-01-31",
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"qwen3-235b": "qwen3-235b-a22b",
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}
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_auth_code = None
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_cookie_jar = None
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@classmethod
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def is_supported(cls, model: str) -> bool:
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"""
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Check if the given model is supported.
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"""
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return model in models or model in cls.model_aliases
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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connector: BaseConnector = None,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(model)
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"content-type": "application/json",
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"dnt": "1",
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"origin": "https://liaobots.work",
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"priority": "u=1, i",
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"referer": "https://liaobots.work/en",
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"sec-ch-ua": "\"Chromium\";v=\"135\", \"Not-A.Brand\";v=\"8\"",
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": "\"Linux\"",
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"sec-fetch-dest": "empty",
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"sec-fetch-mode": "cors",
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"sec-fetch-site": "same-origin",
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"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36"
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}
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async with ClientSession(
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headers=headers,
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cookie_jar=cls._cookie_jar,
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connector=get_connector(connector, proxy, True)
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) as session:
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# First, get a valid auth code
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await cls.get_auth_code(session)
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# Create conversation ID
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conversation_id = str(uuid.uuid4())
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# Prepare request data
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data = {
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"conversationId": conversation_id,
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"models": [{
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"modelId": model,
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"provider": models[model]["provider"]
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}],
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"search": "false",
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"messages": messages,
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"key": "",
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"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。")
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}
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# Try to make the chat request
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try:
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# Make the chat request with the current auth code
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async with session.post(
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f"{cls.url}/api/chat",
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json=data,
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headers={"x-auth-code": cls._auth_code},
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ssl=False
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) as response:
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# Check if we got a streaming response
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content_type = response.headers.get("Content-Type", "")
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if "text/event-stream" in content_type:
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async for line in response.content:
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if line.startswith(b"data: "):
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try:
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response_data = json.loads(line[6:])
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# Check for error response
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if response_data.get("error") is True:
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# Raise RateLimitError for payment required or other errors
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if "402" in str(response_data.get("res_status", "")):
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raise RateLimitError("This model requires payment or credits")
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else:
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error_msg = response_data.get('message', 'Unknown error')
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raise RateLimitError(f"Error: {error_msg}")
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# Process normal response
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if response_data.get("role") == "assistant" and "content" in response_data:
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content = response_data.get("content")
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yield content
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except json.JSONDecodeError:
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continue
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else:
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# Not a streaming response, might be an error or HTML
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response_text = await response.text()
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# If we got HTML, we need to bypass CAPTCHA
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if response_text.startswith("<!DOCTYPE html>"):
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await cls.bypass_captcha(session)
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# Get a fresh auth code
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await cls.get_auth_code(session)
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# Try the request again
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async with session.post(
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f"{cls.url}/api/chat",
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json=data,
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headers={"x-auth-code": cls._auth_code},
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ssl=False
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) as response2:
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# Check if we got a streaming response
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content_type = response2.headers.get("Content-Type", "")
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if "text/event-stream" in content_type:
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async for line in response2.content:
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if line.startswith(b"data: "):
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try:
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response_data = json.loads(line[6:])
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# Check for error response
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if response_data.get("error") is True:
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# Raise RateLimitError for payment required or other errors
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if "402" in str(response_data.get("res_status", "")):
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raise RateLimitError("This model requires payment or credits")
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else:
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error_msg = response_data.get('message', 'Unknown error')
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raise RateLimitError(f"Error: {error_msg}")
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# Process normal response
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if response_data.get("role") == "assistant" and "content" in response_data:
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content = response_data.get("content")
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yield content
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except json.JSONDecodeError:
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continue
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else:
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raise RateLimitError("Failed to get streaming response")
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else:
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raise RateLimitError("Failed to connect to the service")
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except Exception as e:
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# If it's already a RateLimitError, re-raise it
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if isinstance(e, RateLimitError):
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raise
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# Otherwise, wrap it in a RateLimitError
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raise RateLimitError(f"Error processing request: {str(e)}")
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@classmethod
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async def bypass_captcha(cls, session: ClientSession) -> None:
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"""
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Bypass the CAPTCHA verification by directly making the recaptcha API request.
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"""
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try:
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# First, try the direct recaptcha API request
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async with session.post(
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f"{cls.url}/recaptcha/api/login",
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json={"token": "abcdefghijklmnopqrst"},
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ssl=False
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) as response:
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|
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
|