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| import requests | |
| import json | |
| base_urls = {'deepinfra':"https://api.deepinfra.com/v1/openai/chat/completions", "openai":"https://api.openai.com/v1/chat/completions"} | |
| def print_token(token): | |
| if token.token == None: | |
| print() | |
| else: | |
| print(token.token, end="", flush=True) | |
| def get_direct_output(history, model, api_key, stream = False, base_url="openai"): | |
| if base_url in base_urls: | |
| url = base_urls[base_url] | |
| else: | |
| url = base_url | |
| headers = { | |
| "Content-Type": "application/json", | |
| } | |
| data = { | |
| "model": model, | |
| "stream":stream, | |
| "messages": history | |
| } | |
| response = requests.post(url, json=data, headers=headers, stream=stream) | |
| if stream: | |
| return response | |
| return response.json() | |
| class conversation: | |
| class token: | |
| def __init__(self, line): | |
| if line['choices'][0]['finish_reason'] == "stop": | |
| self.token = None | |
| self.model = line["model"] | |
| self.message = {'role':'assistant','content':None} | |
| self.response = line | |
| else: | |
| self.token = line["choices"][0]['delta']['content'] | |
| self.model = line["model"] | |
| self.message = line["choices"][0]['delta'] | |
| self.response = line | |
| def streamingResponse(self, lines, invis): | |
| message = "" | |
| iters = lines.iter_lines(decode_unicode=True) | |
| for line in iters: | |
| if 'data: ' not in line: | |
| continue | |
| line_js = json.loads(line.split('data: ')[1]) | |
| if line_js['choices'][0]['finish_reason'] == "stop": | |
| if not invis: | |
| self.history.append({'role':'assistant', 'content':message}) | |
| yield self.token(line_js) | |
| break | |
| token = self.token(line_js) | |
| message += token.token | |
| yield token | |
| class response: | |
| def __init__(self, json): | |
| print(json) | |
| self.response = json | |
| self.choices = json['choices'] | |
| self.text = json['choices'][0]['message']['content'] | |
| self.message = json['choices'][0]['message'] | |
| self.usage = json['usage'] | |
| self.prompt_tokens = json['usage']['prompt_tokens'] | |
| self.output_tokens = json['usage']['completion_tokens'] | |
| self.total_tokens = json['usage']['total_tokens'] | |
| def __init__(self, api_key='', model='gpt-3.5-turbo', history=None, system_prompt="You are a helpful assistant", base_url="openai"): | |
| if base_url.lower() == "deepinfra" and model == "gpt-3.5-turbo": | |
| model = "meta-llama/Llama-2-70b-chat-hf" | |
| self.base_url = base_url.lower() | |
| self.api_key = api_key | |
| self.model = model | |
| self.history = [{'role':'system',"content":system_prompt}] | |
| if history is not None: | |
| self.history = history | |
| def generate(self, invisible=False, stream=False): | |
| if stream: | |
| res = self.streamingResponse(get_direct_output(self.history, self.model, self.api_key, stream=True, base_url=self.base_url), invisible) | |
| else: | |
| res = self.response(get_direct_output(self.history, self.model, self.api_key, base_url=self.base_url)) | |
| if not invisible: | |
| self.history.append(res.message) | |
| return res | |
| def ask(self, message, invisible=False, stream=False): | |
| if invisible: | |
| out = self.history.copy() | |
| out.append({"role":"user", "content":message}) | |
| else: | |
| self.history.append({"role":"user", "content":message}) | |
| out = self.history | |
| if stream: | |
| res = self.streamingResponse(get_direct_output(out, self.model, self.api_key, stream=True, base_url=self.base_url), invisible) | |
| else: | |
| res = self.response(get_direct_output(out, self.model, self.api_key, base_url=self.base_url)) | |
| if not invisible: | |
| self.history.append(res.message) | |
| return res | |