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from __future__ import annotations |
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import requests |
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from .base_provider import BaseProvider |
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from ..typing import CreateResult |
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models = { |
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'gpt-3.5-turbo': {'id': 'gpt-3.5-turbo', 'name': 'GPT-3.5'}, |
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'gpt-3.5-turbo-0613': {'id': 'gpt-3.5-turbo-0613', 'name': 'GPT-3.5-0613'}, |
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'gpt-3.5-turbo-16k': {'id': 'gpt-3.5-turbo-16k', 'name': 'GPT-3.5-16K'}, |
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'gpt-3.5-turbo-16k-0613': {'id': 'gpt-3.5-turbo-16k-0613', 'name': 'GPT-3.5-16K-0613'}, |
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'gpt-4': {'id': 'gpt-4', 'name': 'GPT-4'}, |
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'gpt-4-0613': {'id': 'gpt-4-0613', 'name': 'GPT-4-0613'}, |
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'gpt-4-32k': {'id': 'gpt-4-32k', 'name': 'GPT-4-32K'}, |
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'gpt-4-32k-0613': {'id': 'gpt-4-32k-0613', 'name': 'GPT-4-32K-0613'}, |
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} |
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class Aivvm(BaseProvider): |
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url = 'https://chat.aivvm.com' |
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supports_stream = True |
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working = True |
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supports_gpt_35_turbo = True |
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supports_gpt_4 = True |
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@classmethod |
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def create_completion(cls, |
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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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**kwargs |
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) -> CreateResult: |
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if not model: |
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model = "gpt-3.5-turbo" |
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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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headers = { |
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"authority" : "chat.aivvm.com", |
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"accept" : "*/*", |
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"accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3", |
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"content-type" : "application/json", |
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"origin" : "https://chat.aivvm.com", |
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"referer" : "https://chat.aivvm.com/", |
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"sec-ch-ua" : '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"', |
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"sec-ch-ua-mobile" : "?0", |
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"sec-ch-ua-platform" : '"macOS"', |
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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 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36", |
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} |
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json_data = { |
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"model" : models[model], |
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"messages" : messages, |
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"key" : "", |
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"prompt" : "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.", |
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"temperature" : kwargs.get("temperature", 0.7) |
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} |
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response = requests.post( |
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"https://chat.aivvm.com/api/chat", headers=headers, json=json_data, stream=True) |
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response.raise_for_status() |
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for chunk in response.iter_content(chunk_size=None): |
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yield chunk.decode('utf-8') |
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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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('temperature', 'float'), |
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] |
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param = ', '.join([': '.join(p) for p in params]) |
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return f'g4f.provider.{cls.__name__} supports: ({param})' |