137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
from time import time
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from requests import post
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headers = {
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'authority': 'www.t3nsor.tech',
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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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'cache-control': 'no-cache',
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'content-type': 'application/json',
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'origin': 'https://www.t3nsor.tech',
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'pragma': 'no-cache',
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'referer': 'https://www.t3nsor.tech/',
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'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "Not:A-Brand";v="99"',
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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/112.0.0.0 Safari/537.36',
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}
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class T3nsorResponse:
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class Completion:
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class Choices:
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def __init__(self, choice: dict) -> None:
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self.text = choice['text']
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self.content = self.text.encode()
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self.index = choice['index']
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self.logprobs = choice['logprobs']
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self.finish_reason = choice['finish_reason']
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def __repr__(self) -> str:
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return f'''<__main__.APIResponse.Completion.Choices(\n text = {self.text.encode()},\n index = {self.index},\n logprobs = {self.logprobs},\n finish_reason = {self.finish_reason})object at 0x1337>'''
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def __init__(self, choices: dict) -> None:
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self.choices = [self.Choices(choice) for choice in choices]
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class Usage:
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def __init__(self, usage_dict: dict) -> None:
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self.prompt_tokens = usage_dict['prompt_chars']
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self.completion_tokens = usage_dict['completion_chars']
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self.total_tokens = usage_dict['total_chars']
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def __repr__(self):
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return f'''<__main__.APIResponse.Usage(\n prompt_tokens = {self.prompt_tokens},\n completion_tokens = {self.completion_tokens},\n total_tokens = {self.total_tokens})object at 0x1337>'''
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def __init__(self, response_dict: dict) -> None:
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self.response_dict = response_dict
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self.id = response_dict['id']
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self.object = response_dict['object']
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self.created = response_dict['created']
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self.model = response_dict['model']
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self.completion = self.Completion(response_dict['choices'])
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self.usage = self.Usage(response_dict['usage'])
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def json(self) -> dict:
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return self.response_dict
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class Completion:
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model = {
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'model': {
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'id': 'gpt-3.5-turbo',
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'name': 'Default (GPT-3.5)'
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}
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}
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def create(
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prompt: str = 'hello world',
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messages: list = []) -> T3nsorResponse:
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response = post('https://www.t3nsor.tech/api/chat', headers=headers, json=Completion.model | {
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'messages': messages,
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'key': '',
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'prompt': prompt
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})
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return T3nsorResponse({
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'id': f'cmpl-1337-{int(time())}',
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'object': 'text_completion',
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'created': int(time()),
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'model': Completion.model,
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'choices': [{
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'text': response.text,
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'index': 0,
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'logprobs': None,
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'finish_reason': 'stop'
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}],
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'usage': {
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'prompt_chars': len(prompt),
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'completion_chars': len(response.text),
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'total_chars': len(prompt) + len(response.text)
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}
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})
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class StreamCompletion:
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model = {
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'model': {
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'id': 'gpt-3.5-turbo',
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'name': 'Default (GPT-3.5)'
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}
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}
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def create(
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prompt: str = 'hello world',
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messages: list = []) -> T3nsorResponse:
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print('t3nsor api is down, this may not work, refer to another module')
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response = post('https://www.t3nsor.tech/api/chat', headers=headers, stream=True, json=Completion.model | {
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'messages': messages,
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'key': '',
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'prompt': prompt
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})
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for chunk in response.iter_content(chunk_size=2046):
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yield T3nsorResponse({
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'id': f'cmpl-1337-{int(time())}',
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'object': 'text_completion',
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'created': int(time()),
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'model': Completion.model,
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'choices': [{
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'text': chunk.decode(),
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'index': 0,
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'logprobs': None,
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'finish_reason': 'stop'
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}],
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'usage': {
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'prompt_chars': len(prompt),
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'completion_chars': len(chunk.decode()),
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'total_chars': len(prompt) + len(chunk.decode())
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}
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})
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