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()) } })