2023-09-03 04:26:26 -04:00
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from __future__ import annotations
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2023-11-18 23:36:04 -05:00
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import uuid, json, asyncio
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2023-11-11 04:14:39 -05:00
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from py_arkose_generator.arkose import get_values_for_request
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2023-11-18 23:36:04 -05:00
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from asyncstdlib.itertools import tee
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from async_property import async_cached_property
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2023-08-27 19:43:45 -04:00
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2023-10-04 01:20:51 -04:00
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from ..base_provider import AsyncGeneratorProvider
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from ..helper import get_browser, get_event_loop
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2023-10-09 07:33:20 -04:00
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from ...typing import AsyncResult, Messages
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2023-10-04 01:20:51 -04:00
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from ...requests import StreamSession
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2023-11-18 23:36:04 -05:00
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models = {
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"gpt-3.5": "text-davinci-002-render-sha",
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"gpt-3.5-turbo": "text-davinci-002-render-sha",
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"gpt-4": "gpt-4",
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"gpt-4-gizmo": "gpt-4-gizmo"
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}
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2023-09-03 04:26:26 -04:00
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2023-10-03 16:12:56 -04:00
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class OpenaiChat(AsyncGeneratorProvider):
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url = "https://chat.openai.com"
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working = True
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needs_auth = True
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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_access_token: str = None
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@classmethod
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async def create(
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cls,
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prompt: str = None,
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model: str = "",
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messages: Messages = [],
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history_disabled: bool = False,
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action: str = "next",
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conversation_id: str = None,
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parent_id: str = None,
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**kwargs
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) -> Response:
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if prompt:
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messages.append({"role": "user", "content": prompt})
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generator = cls.create_async_generator(
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model,
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messages,
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history_disabled=history_disabled,
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action=action,
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conversation_id=conversation_id,
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parent_id=parent_id,
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response_fields=True,
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**kwargs
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)
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fields: ResponseFields = await anext(generator)
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if "access_token" not in kwargs:
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kwargs["access_token"] = cls._access_token
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return Response(
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generator,
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fields,
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action,
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messages,
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kwargs
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)
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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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2023-10-09 07:33:20 -04:00
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timeout: int = 120,
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2023-09-05 11:27:24 -04:00
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access_token: str = None,
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2023-11-12 04:12:05 -05:00
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auto_continue: bool = False,
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history_disabled: bool = True,
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action: str = "next",
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conversation_id: str = None,
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parent_id: str = None,
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response_fields: bool = False,
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**kwargs
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) -> AsyncResult:
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if not model:
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model = "gpt-3.5"
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elif model not in models:
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raise ValueError(f"Model are not supported: {model}")
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if not parent_id:
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parent_id = str(uuid.uuid4())
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if not access_token:
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access_token = await cls.get_access_token(proxy)
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headers = {
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"Accept": "text/event-stream",
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"Authorization": f"Bearer {access_token}",
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2023-11-18 23:36:04 -05:00
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"Cookie": 'intercom-device-id-dgkjq2bp=0f047573-a750-46c8-be62-6d54b56e7bf0; ajs_user_id=user-iv3vxisaoNodwWpxmNpMfekH; ajs_anonymous_id=fd91be0b-0251-4222-ac1e-84b1071e9ec1; __Host-next-auth.csrf-token=d2b5f67d56f7dd6a0a42ae4becf2d1a6577b820a5edc88ab2018a59b9b506886%7Ce5c33eecc460988a137cbc72d90ee18f1b4e2f672104f368046df58e364376ac; _cfuvid=gt_mA.q6rue1.7d2.AR0KHpbVBS98i_ppfi.amj2._o-1700353424353-0-604800000; cf_clearance=GkHCfPSFU.NXGcHROoe4FantnqmnNcluhTNHz13Tk.M-1700353425-0-1-dfe77f81.816e9bc2.714615da-0.2.1700353425; __Secure-next-auth.callback-url=https%3A%2F%2Fchat.openai.com; intercom-session-dgkjq2bp=UWdrS1hHazk5VXN1c0V5Q1F0VXdCQmsyTU9pVjJMUkNpWnFnU3dKWmtIdGwxTC9wbjZuMk5hcEc0NWZDOGdndS0tSDNiaDNmMEdIL1RHU1dFWDBwOHFJUT09--f754361b91fddcd23a13b288dcb2bf8c7f509e91; _uasid="Z0FBQUFBQmxXVnV0a3dmVno4czRhcDc2ZVcwaUpSNUdZejlDR25YSk5NYTJQQkpyNmRvOGxjTHMyTlAxWmJhaURrMVhjLXZxQXdZeVpBbU1aczA5WUpHT2dwaS1MOWc4MnhyNWFnbGRzeGdJcGFKT0ZRdnBTMVJHcGV2MGNTSnVQY193c0hqUWIycHhQRVF4dENlZ3phcDdZeHgxdVhoalhrZmtZME9NbWhMQjdVR3Vzc3FRRk0ybjJjNWMwTWtIRjdPb19lUkFtRmV2MDVqd1kwWU11QTYtQkdZenEzVHhLMGplY1hZM3FlYUt1cVZaNWFTRldleEJETzJKQjk1VTJScy1GUnMxUVZWMnVxYklxMjdockVZbkZyd1R4U1RtMnA1ZzlSeXphdmVOVk9xeEdrRkVOSjhwTVd1QzFtQjhBcWdDaE92Q1VlM2pwcjFQTXRuLVJNRVlZSGpIdlZ0aGV3PT0="; _dd_s=rum=0&expire=1700356244884; __Secure-next-auth.session-token=eyJhbGciOiJkaXIiLCJlbmMiOiJBMjU2R0NNIn0..3aK6Fbdy2_8f07bf.8eT2xgonrCnz7ySY6qXFsg3kzL6UQfXKAYaw3tyn-6_X9657zy47k9qGvmi9mF0QKozj5jau3_Ca62AQQ7FmeC6Y2F1urtzqrXqwTTsQ2LuzFPIQkx6KKb2DXc8zW2-oyEzJ_EY5yxfLB2RlRkSh3M7bYNZh4_ltEcfkj38s_kIPGMxv34udtPWGWET99MCjkdwQWXylJag4s0fETA0orsBAKnGCyqAUNJbb_D7BYtGSV-MQ925kZMG6Di_QmfO0HQWURDYjmdRNcuy1PT_xJ1DJko8sjL42i4j3RhkNDkhqCIqyYImz2eHFWHW7rYKxTkrBhlCPMS5hRdcCswD7JYPcSBiwnVRYgyOocFGXoFvQgIZ2FX9NiZ3SMEVM1VwIGSE-qH0H2nMa8_iBvsOgOWJgKjVAvzzyzZvRVDUUHzJrikSFPNONVDU3h-04c1kVL4qIu9DfeTPN7n8AvNmYwMbro0L9-IUAeXNo4-pwF0Kt-AtTsamqWvMqnK4O_YOyLnDDlvkmnOvDC2d5uinwlQIxr6APO6qFfGLlHiLZemKoekxEE1Fx70dl-Ouhk1VIzbF3OC6XNNxeBm9BUYUiHdL0wj2H9rHgX4cz6ZmS_3VTgpD6UJh-evu5KJ2gIvjYmVbyzEN0aPNDxfvBaOm-Ezpy4bUJ2bUrOwNn-0knWkDiTvjYmNhCyefPCtCF6rpKNay8PCw_yh79C4SdEP6Q4V7LI0Tvdi5uz7kLCiBC4AT9L0ao1WDX03mkUOpjvzHDvPLmj8chW3lTVm_kA0eYGQY4wT0jzleWlfV0Q8rB2oYECNLWksA3F1zlGfcl4lQjprvTXRePkvAbMpoJEsZD3Ylq7-foLDLk4-M2LYAFZDs282AY04sFjAjQBxTELFCCuDgTIgTXSIskY_XCxpVXDbdLlbCJY7XVK45ybwtfqwlKRp8Mo0B131uQAFc-migHaUaoGujxJJk21bP8F0OmhNYHBo4FQqE1rQm2JH5bNM7txKeh5KXdJgVUVbRSr7OIp_OF5-Bx_v9eRBGAIDkue26E2-O8Rnrp5zQ5TnvecQLDaUzWavCLPwsZ0_gsOLBxNOmauNYZtF8IElCsQSFDdhoiMxXsYUm4ZYKEAy3GWq8HGTAvBhNkh1hvnI7y-d8-DOaZf_D_D98-olZfm-LUkeosLNpPB9rxYMqViCiW3KrXE9Yx0wlFm5ePKaVvR7Ym_EPhSOhJBKFPCvdTdMZSNPUcW0ZJBVByq0A9sxD51lYq3gaFyqh94S4s_ox182AQ3szGzHkdgLcnQmJG9OYvKxAVcd43eg6_gODAYhx02GjbMw-7JTAhyXSeCrlMteHyOXl8hai-3LilC3PmMzi7Vbu49dhF1s4LcVlUowen5ira44rQQaB26mdaOUoQfodgt66M3RTWGPXyK1Nb72AzSXsCKyaQPbzeb6cN0fdGSdG4ktwvR04eFNEkquo_3aKu2GmUKTD0XcRx9dYrfXjgY-X1DDTVs1YND2gRhdx7FFEeBVjtbj2UqmG3Rvd4IcHGe7OnYWw2MHDcol68SsR1KckXWwWREz7YTGUnDB2M1kx_H4W2mjclytnlHOnYU3RflegRPeSTbdzUZJvGKXCCz45luHkQWN_4DExE76D-9YqbFIz-RY5yL4h-Zs-i2xjm2K-4xCMM9nQIOqhLMqixIZQ2ldDAidKoYtbs5ppzbcBLyrZM96bq9DwRBY3aacqWdlRd-TfX0wv5KO4fo0sSh5FsuhuN0zcEV_NNXgqIEM_p14EcPqgbrAvCBQ8os70TRBQLXiF0EniSofGjxwF8kQvUk3C6Wfc8cTTeN-E6GxCVTn91HBwA1iSEZlRLMVb8_BcRJNqwbgnb_07jR6-eo42u88CR3KQdAWwbQRdMxsURFwZ0ujHXVGG0Ll6qCFBcHXWyDO1x1yHdHnw8_8yF26pnA2iPzrFR-8glMgIA-639sLuGAxjO1_ZuvJ9CAB41Az9S_jaZwaWy215Hk4-BRYD-MKmHtonwo3rrxhE67WJgbbu14efsw5nT6ow961pffgwXov5VA1Rg7nv1E8RvQOx7umWW6o8R4W6L8f2COsmPTXfgwIjoJKkjhUqAQ8ceG7cM0ET-38yaC0ObU8EkXfdGGgxI28qTEZWczG66_iM4hw7QEGCY5Cz2kbO6LETAiw9OsSigtBvDS7f0Ou0bZ41pdK7G3FmvdZAnjWPjObnDF4k4uWfn7mzt0fgj3FyqK20JezRDyGuAbUUhOvtZpc9sJpzxR34eXEZTouuALrHcGuNij4z6rx51FrQsaMtiup8QVrhtZbXtKLMYnWYSbkhuTeN2wY-xV1ZUsQlakIZszzGF7kuIG87KKWMpuPMvbXjz6Pp_gWJiIC6aQuk8xl5g0iBPycf_6Q-MtpuYxzNE2TpI1RyR9mHeXmteoRzrFiWp7yEC-QGNFyAJgxTqxM3CjHh1Jt6IddOsmn89rUo1dZM2Smijv_fbIv3avXLkIPX1KZjILeJCtpU0wAdsihDaRiRgDdx8fG__F8zuP0n7ziHas73cwrfg-Ujr6DhC0gTNxyd9dDA_oho9N7CQcy6EFmfNF2te7zpLony0859jtRv2t1TnpzAa1VvMK4u6mXuJ2XDo04_6GzLO3aPHinMdl1BcIAWnqAqWAu3euGFLTHOhXlfijut9N1OCifd_
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2023-09-05 11:27:24 -04:00
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}
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2023-11-18 23:36:04 -05:00
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async with StreamSession(
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proxies={"https": proxy},
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impersonate="chrome110",
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headers=headers,
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timeout=timeout
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) as session:
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data = {
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"action": action,
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"arkose_token": await get_arkose_token(proxy, timeout),
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"conversation_id": conversation_id,
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"parent_message_id": parent_id,
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"model": models[model],
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"history_and_training_disabled": history_disabled and not auto_continue,
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}
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if action != "continue":
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data["messages"] = [{
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"id": str(uuid.uuid4()),
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"author": {"role": "user"},
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"content": {"content_type": "text", "parts": [messages[-1]["content"]]},
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}]
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first = True
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end_turn = EndTurn()
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while first or auto_continue and not end_turn.is_end:
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first = False
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2023-11-12 04:12:05 -05:00
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async with session.post(f"{cls.url}/backend-api/conversation", json=data) as response:
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try:
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response.raise_for_status()
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except:
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raise RuntimeError(f"Error {response.status_code}: {await response.text()}")
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last_message = 0
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2023-11-12 04:12:05 -05:00
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async for line in response.iter_lines():
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if line.startswith(b"data: "):
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line = line[6:]
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if line == b"[DONE]":
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break
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try:
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line = json.loads(line)
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except:
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continue
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if "message" not in line:
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continue
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if "error" in line and line["error"]:
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raise RuntimeError(line["error"])
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if "message_type" not in line["message"]["metadata"]:
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continue
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if line["message"]["author"]["role"] != "assistant":
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continue
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if line["message"]["metadata"]["message_type"] in ("next", "continue", "variant"):
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conversation_id = line["conversation_id"]
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parent_id = line["message"]["id"]
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if response_fields:
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response_fields = False
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yield ResponseFields(conversation_id, parent_id, end_turn)
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new_message = line["message"]["content"]["parts"][0]
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yield new_message[last_message:]
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last_message = len(new_message)
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if "finish_details" in line["message"]["metadata"]:
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if line["message"]["metadata"]["finish_details"]["type"] == "max_tokens":
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end_turn.end()
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2023-11-12 04:12:05 -05:00
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data = {
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"action": "continue",
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"arkose_token": await get_arkose_token(proxy, timeout),
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2023-11-12 04:12:05 -05:00
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"conversation_id": conversation_id,
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2023-11-18 23:36:04 -05:00
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"parent_message_id": parent_id,
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"model": models[model],
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2023-11-12 04:12:05 -05:00
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"history_and_training_disabled": False,
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}
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await asyncio.sleep(5)
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2023-10-03 16:12:56 -04:00
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@classmethod
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2023-11-18 23:36:04 -05:00
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async def browse_access_token(cls, proxy: str = None) -> str:
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2023-10-22 17:53:18 -04:00
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def browse() -> str:
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try:
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from selenium.webdriver.common.by import By
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from selenium.webdriver.support.ui import WebDriverWait
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from selenium.webdriver.support import expected_conditions as EC
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2023-08-25 00:41:32 -04:00
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2023-11-18 23:36:04 -05:00
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driver = get_browser("~/openai", proxy=proxy)
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2023-10-22 17:53:18 -04:00
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except ImportError:
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return
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try:
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driver.get(f"{cls.url}/")
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2023-10-22 17:53:18 -04:00
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WebDriverWait(driver, 1200).until(
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EC.presence_of_element_located((By.ID, "prompt-textarea"))
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)
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javascript = "return (await (await fetch('/api/auth/session')).json())['accessToken']"
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return driver.execute_script(javascript)
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finally:
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driver.quit()
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loop = get_event_loop()
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return await loop.run_in_executor(
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None,
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browse
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)
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2023-08-25 00:41:32 -04:00
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2023-10-03 17:53:17 -04:00
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@classmethod
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async def get_access_token(cls, proxy: str = None) -> str:
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if not cls._access_token:
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2023-11-18 23:36:04 -05:00
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cls._access_token = await cls.browse_access_token(proxy)
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2023-10-03 17:53:17 -04:00
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if not cls._access_token:
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raise RuntimeError("Read access token failed")
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return cls._access_token
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2023-08-27 19:43:45 -04:00
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2023-08-25 00:41:32 -04:00
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@classmethod
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@property
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def params(cls):
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params = [
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("model", "str"),
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("messages", "list[dict[str, str]]"),
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("stream", "bool"),
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("proxy", "str"),
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2023-09-05 11:27:24 -04:00
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("access_token", "str"),
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2023-08-25 00:41:32 -04:00
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]
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param = ", ".join([": ".join(p) for p in params])
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2023-10-28 01:21:00 -04:00
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return f"g4f.provider.{cls.__name__} supports: ({param})"
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2023-11-18 23:36:04 -05:00
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async def get_arkose_token(proxy: str = None, timeout: int = None) -> str:
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2023-10-28 01:21:00 -04:00
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config = {
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"pkey": "3D86FBBA-9D22-402A-B512-3420086BA6CC",
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"surl": "https://tcr9i.chat.openai.com",
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"headers": {
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"User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36'
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},
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"site": "https://chat.openai.com",
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}
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2023-11-11 04:14:39 -05:00
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args_for_request = get_values_for_request(config)
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async with StreamSession(
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proxies={"https": proxy},
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impersonate="chrome107",
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2023-11-18 23:36:04 -05:00
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timeout=timeout
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2023-11-11 04:14:39 -05:00
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) as session:
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async with session.post(**args_for_request) as response:
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response.raise_for_status()
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decoded_json = await response.json()
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if "token" in decoded_json:
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return decoded_json["token"]
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2023-11-18 23:36:04 -05:00
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raise RuntimeError(f"Response: {decoded_json}")
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class EndTurn():
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def __init__(self):
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self.is_end = False
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def end(self):
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self.is_end = True
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class ResponseFields():
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def __init__(
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self,
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conversation_id: str,
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message_id: str,
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end_turn: EndTurn
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):
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self.conversation_id = conversation_id
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self.message_id = message_id
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self._end_turn = end_turn
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class Response():
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def __init__(
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self,
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generator: AsyncResult,
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fields: ResponseFields,
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action: str,
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messages: Messages,
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options: dict
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):
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self.aiter, self.copy = tee(generator)
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self.fields = fields
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self.action = action
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self._messages = messages
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self._options = options
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def __aiter__(self):
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return self.aiter
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@async_cached_property
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async def message(self) -> str:
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return "".join([chunk async for chunk in self.copy])
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async def next(self, prompt: str, **kwargs) -> Response:
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return await OpenaiChat.create(
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**self._options,
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prompt=prompt,
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messages=await self.messages,
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action="next",
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conversation_id=self.fields.conversation_id,
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parent_id=self.fields.message_id,
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**kwargs
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)
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async def do_continue(self, **kwargs) -> Response:
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if self.end_turn:
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raise RuntimeError("Can't continue message. Message already finished.")
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return await OpenaiChat.create(
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**self._options,
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messages=await self.messages,
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action="continue",
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conversation_id=self.fields.conversation_id,
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parent_id=self.fields.message_id,
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**kwargs
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)
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async def variant(self, **kwargs) -> Response:
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if self.action != "next":
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raise RuntimeError("Can't create variant with continue or variant request.")
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return await OpenaiChat.create(
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|
**self._options,
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messages=self._messages,
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action="variant",
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conversation_id=self.fields.conversation_id,
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parent_id=self.fields.message_id,
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**kwargs
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)
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|
@async_cached_property
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|
|
async def messages(self):
|
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|
messages = self._messages
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|
messages.append({
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|
"role": "assistant", "content": await self.message
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})
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return messages
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|
@property
|
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|
def end_turn(self):
|
|
|
|
return self.fields._end_turn.is_end
|