2023-09-03 11:26:26 +03:00
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from __future__ import annotations
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import json
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from abc import ABC, abstractmethod
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import requests
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2023-08-17 16:31:01 +03:00
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2023-10-04 08:20:51 +03:00
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from ...typing import Any, CreateResult
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from ..base_provider import BaseProvider
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2023-08-17 16:31:01 +03:00
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2023-09-12 05:40:10 +03:00
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class Equing(BaseProvider):
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2023-08-27 18:37:44 +03:00
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url: str = 'https://next.eqing.tech/'
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2023-09-12 05:40:10 +03:00
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working = False
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2023-08-27 18:37:44 +03:00
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supports_stream = True
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2023-08-17 16:31:01 +03:00
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supports_gpt_35_turbo = True
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supports_gpt_4 = False
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@staticmethod
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@abstractmethod
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def create_completion(
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model: str,
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messages: list[dict[str, str]],
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stream: bool, **kwargs: Any) -> CreateResult:
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headers = {
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'authority' : 'next.eqing.tech',
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'accept' : 'text/event-stream',
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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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'cache-control' : 'no-cache',
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'content-type' : 'application/json',
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'origin' : 'https://next.eqing.tech',
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'plugins' : '0',
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'pragma' : 'no-cache',
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'referer' : 'https://next.eqing.tech/',
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'sec-ch-ua' : '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
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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/115.0.0.0 Safari/537.36',
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'usesearch' : 'false',
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'x-requested-with' : 'XMLHttpRequest'
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}
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json_data = {
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'messages' : messages,
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'stream' : stream,
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'model' : model,
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'temperature' : kwargs.get('temperature', 0.5),
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'presence_penalty' : kwargs.get('presence_penalty', 0),
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'frequency_penalty' : kwargs.get('frequency_penalty', 0),
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'top_p' : kwargs.get('top_p', 1),
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}
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response = requests.post('https://next.eqing.tech/api/openai/v1/chat/completions',
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headers=headers, json=json_data, stream=stream)
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2023-10-23 10:46:25 +03:00
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2023-08-22 10:07:22 +03:00
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if not stream:
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yield response.json()["choices"][0]["message"]["content"]
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return
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for line in response.iter_content(chunk_size=1024):
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if line:
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if b'content' in line:
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line_json = json.loads(line.decode('utf-8').split('data: ')[1])
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if token := line_json['choices'][0]['delta'].get('content'):
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yield token
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