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from __future__ import annotations

import uuid

from aiohttp import ClientSession

from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider

models = {
    "gpt-4": {
        "id": "gpt-4",
        "name": "GPT-4",
        "maxLength": 24000,
        "tokenLimit": 8000,
    },
    "gpt-4-0613": {
        "id": "gpt-4-0613",
        "name": "GPT-4",
        "maxLength": 32000,
        "tokenLimit": 8000,
    },
    "gpt-3.5-turbo": {
        "id": "gpt-3.5-turbo",
        "name": "GPT-3.5-Turbo",
        "maxLength": 48000,
        "tokenLimit": 14000,
        "context": "16K",
    },
    "gpt-3.5-turbo-16k": {
        "id": "gpt-3.5-turbo-16k",
        "name": "GPT-3.5-16k",
        "maxLength": 48000,
        "tokenLimit": 16000,
    },
    "gpt-4-1106-preview": {
        "id": "gpt-4-1106-preview",
        "name": "GPT-4-Turbo",
        "maxLength": 260000,
        "tokenLimit": 126000,
        "context": "128K",
    },
    "gpt-4-plus": {
        "id": "gpt-4-plus",
        "name": "GPT-4-Plus",
        "maxLength": 130000,
        "tokenLimit": 31000,
        "context": "32K",
    },
    "gemini-pro": {
        "id": "gemini-pro",
        "name": "Gemini-Pro",
        "maxLength": 120000,
        "tokenLimit": 30000,
        "context": "32K",
    },
    "claude-2": {
        "id": "claude-2",
        "name": "Claude-2-200k",
        "maxLength": 800000,
        "tokenLimit": 200000,
        "context": "200K",
    },
    "claude-instant-1": {
        "id": "claude-instant-1",
        "name": "Claude-instant-1",
        "maxLength": 400000,
        "tokenLimit": 100000,
        "context": "100K",
    }
}


class Liaobots(AsyncGeneratorProvider):
    url = "https://liaobots.site"
    working = True
    supports_message_history = True
    supports_gpt_35_turbo = True
    supports_gpt_4 = True
    _auth_code = None

    @classmethod
    async def create_async_generator(
        cls,
        model: str,
        messages: Messages,
        auth: str = None,
        proxy: str = None,
        **kwargs
    ) -> AsyncResult:
        model = model if model in models else "gpt-3.5-turbo"
        headers = {
            "authority": "liaobots.com",
            "content-type": "application/json",
            "origin": cls.url,
            "referer": f"{cls.url}/",
            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36",
        }
        async with ClientSession(
            headers=headers
        ) as session:
            cls._auth_code = auth if isinstance(auth, str) else cls._auth_code
            if not cls._auth_code:
                async with session.post(
                    "https://liaobots.work/recaptcha/api/login",
                    proxy=proxy,
                    data={"token": "abcdefghijklmnopqrst"},
                    verify_ssl=False
                ) as response:
                    response.raise_for_status()
                async with session.post(
                    "https://liaobots.work/api/user",
                    proxy=proxy,
                    json={"authcode": ""},
                    verify_ssl=False
                ) as response:
                    response.raise_for_status()
                    cls._auth_code = (await response.json(content_type=None))["authCode"]
            data = {
                "conversationId": str(uuid.uuid4()),
                "model": models[model],
                "messages": messages,
                "key": "",
                "prompt": kwargs.get("system_message", "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully."),
            }
            async with session.post(
                "https://liaobots.work/api/chat",
                proxy=proxy,
                json=data,
                headers={"x-auth-code": cls._auth_code},
                verify_ssl=False
            ) as response:
                response.raise_for_status()
                async for stream in response.content.iter_any():
                    if stream:
                        yield stream.decode()