import json import time class OpenaiStreamOutputer: """ Create chat completion - OpenAI API Documentation * https://platform.openai.com/docs/api-reference/chat/create """ def __init__(self): current_time = int(time.time()) self.default_data = { "id": "chatcmpl-hugginface", "object": "chat.completion.chunk", "created": current_time, "model": "hugginface", "system_fingerprint": "fp_44709d6fcb", "choices": [], "usage": { "prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0 } } def data_to_string(self, data={}, content_type=""): data_str = f"{json.dumps(data)}" return data_str def output(self, content=None, content_type="Completions", tokens_count=0) -> str: data = self.default_data.copy() if content_type == "Role": data["choices"] = [ { "index": 0, "message": { "role": "assistant", "content": content, }, "logprobs": None, "finish_reason": "stop" } ] elif content_type in [ "Completions", "InternalSearchQuery", "InternalSearchResult", "SuggestedResponses", ]: if content_type in ["InternalSearchQuery", "InternalSearchResult"]: content += "\n" data["choices"] = [ { "index": 0, "message": { "role": "user", "content": content, }, "logprobs": None, "finish_reason": None, } ] elif content_type == "Finished": data["choices"] = [ { "index": 0, "message": { "role": "assistant", "content": content, }, "logprobs": None, "finish_reason": "stop", } ] else: data["choices"] = [ { "index": 0, "message": { "role": "assistant", "content": content, }, "logprobs": None, "finish_reason": None, } ] # Update token counts data["usage"]["prompt_tokens"] += tokens_count data["usage"]["completion_tokens"] += len(content.split()) data["usage"]["total_tokens"] = data["usage"]["prompt_tokens"] + data["usage"]["completion_tokens"] return self.data_to_string(data, content_type)