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from requests import post
from time import time
class T3nsorResponse:
class Completion:
class Choices:
def __init__(self, choice: dict) -> None:
self.text = choice['text']
self.content = self.text.encode()
self.index = choice['index']
self.logprobs = choice['logprobs']
self.finish_reason = choice['finish_reason']
def __repr__(self) -> str:
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>'''
def __init__(self, choices: dict) -> None:
self.choices = [self.Choices(choice) for choice in choices]
class Usage:
def __init__(self, usage_dict: dict) -> None:
self.prompt_tokens = usage_dict['prompt_tokens']
self.completion_tokens = usage_dict['completion_tokens']
self.total_tokens = usage_dict['total_tokens']
def __repr__(self):
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>'''
def __init__(self, response_dict: dict) -> None:
self.response_dict = response_dict
self.id = response_dict['id']
self.object = response_dict['object']
self.created = response_dict['created']
self.model = response_dict['model']
self.completion = self.Completion(response_dict['choices'])
self.usage = self.Usage(response_dict['usage'])
def json(self) -> dict:
return self.response_dict
class Completion:
model = {
'model': {
'id' : 'gpt-3.5-turbo',
'name' : 'Default (GPT-3.5)'
}
}
def create(
prompt: str = 'hello world',
messages: list = []) -> T3nsorResponse:
response = post('https://www.t3nsor.tech/api/chat', json = Completion.model | {
'messages' : messages,
'key' : '',
'prompt' : prompt
})
return T3nsorResponse({
'id' : f'cmpl-1337-{int(time())}',
'object' : 'text_completion',
'created': int(time()),
'model' : Completion.model,
'choices': [{
'text' : response.text,
'index' : 0,
'logprobs' : None,
'finish_reason' : 'stop'
}],
'usage': {
'prompt_chars' : len(prompt),
'completion_chars' : len(response.text),
'total_chars' : len(prompt) + len(response.text)
}
})
class StreamCompletion:
model = {
'model': {
'id' : 'gpt-3.5-turbo',
'name' : 'Default (GPT-3.5)'
}
}
def create(
prompt: str = 'hello world',
messages: list = []) -> T3nsorResponse:
response = post('https://www.t3nsor.tech/api/chat', stream = True, json = Completion.model | {
'messages' : messages,
'key' : '',
'prompt' : prompt
})
for resp in response.iter_lines():
if resp:
yield T3nsorResponse({
'id' : f'cmpl-1337-{int(time())}',
'object' : 'text_completion',
'created': int(time()),
'model' : Completion.model,
'choices': [{
'text' : resp.decode(),
'index' : 0,
'logprobs' : None,
'finish_reason' : 'stop'
}],
'usage': {
'prompt_chars' : len(prompt),
'completion_chars' : len(resp.decode()),
'total_chars' : len(prompt) + len(resp.decode())
}
})
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