118 lines
No EOL
4.3 KiB
Python
118 lines
No EOL
4.3 KiB
Python
from requests import post
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from time import time
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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_tokens']
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self.completion_tokens = usage_dict['completion_tokens']
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self.total_tokens = usage_dict['total_tokens']
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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', 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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response = post('https://www.t3nsor.tech/api/chat', 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 resp in response.iter_lines():
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if resp:
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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' : resp.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(resp.decode()),
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'total_chars' : len(prompt) + len(resp.decode())
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}
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}) |