# encoding:utf-8 import time import json import openai import openai.error import requests from common import const from models.bot import Bot from models.openai_compatible_bot import OpenAICompatibleBot from models.chatgpt.chat_gpt_session import ChatGPTSession from models.openai.open_ai_image import OpenAIImage from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger from common.token_bucket import TokenBucket from config import conf, load_config from models.baidu.baidu_wenxin_session import BaiduWenxinSession # OpenAI对话模型API (可用) class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot): def __init__(self): super().__init__() # set the default api_key openai.api_key = conf().get("open_ai_api_key") if conf().get("open_ai_api_base"): openai.api_base = conf().get("open_ai_api_base") proxy = conf().get("proxy") if proxy: openai.proxy = proxy if conf().get("rate_limit_chatgpt"): self.tb4chatgpt = TokenBucket(conf().get("rate_limit_chatgpt", 20)) conf_model = conf().get("model") or "gpt-3.5-turbo" self.sessions = SessionManager(ChatGPTSession, model=conf().get("model") or "gpt-3.5-turbo") # o1相关模型不支持system prompt，暂时用文心模型的session self.args = { "model": conf_model, # 对话模型的名称 "temperature": conf().get("temperature", 0.9), # 值在[0,1]之间，越大表示回复越具有不确定性 # "max_tokens":4096, # 回复最大的字符数 "top_p": conf().get("top_p", 1), "frequency_penalty": conf().get("frequency_penalty", 0.0), # [-2,2]之间，该值越大则更倾向于产生不同的内容 "presence_penalty": conf().get("presence_penalty", 0.0), # [-2,2]之间，该值越大则更倾向于产生不同的内容 "request_timeout": conf().get("request_timeout", None), # 请求超时时间，openai接口默认设置为600，对于难问题一般需要较长时间 "timeout": conf().get("request_timeout", None), # 重试超时时间，在这个时间内，将会自动重试 } # 部分模型暂不支持一些参数，特殊处理 if conf_model in [const.O1, const.O1_MINI, const.GPT_5, const.GPT_5_MINI, const.GPT_5_NANO]: remove_keys = ["temperature", "top_p", "frequency_penalty", "presence_penalty"] for key in remove_keys: self.args.pop(key, None) # 如果键不存在，使用 None 来避免抛出错、 if conf_model in [const.O1, const.O1_MINI]: # o1系列模型不支持系统提示词，使用文心模型的session self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or const.O1_MINI) def get_api_config(self): """Get API configuration for OpenAI-compatible base class""" return { 'api_key': conf().get("open_ai_api_key"), 'api_base': conf().get("open_ai_api_base"), 'model': conf().get("model", "gpt-3.5-turbo"), 'default_temperature': conf().get("temperature", 0.9), 'default_top_p': conf().get("top_p", 1.0), 'default_frequency_penalty': conf().get("frequency_penalty", 0.0), 'default_presence_penalty': conf().get("presence_penalty", 0.0), } def reply(self, query, context=None): # acquire reply content if context.type == ContextType.TEXT: logger.info("[CHATGPT] query={}".format(query)) session_id = context["session_id"] reply = None clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"]) if query in clear_memory_commands: self.sessions.clear_session(session_id) reply = Reply(ReplyType.INFO, "记忆已清除") elif query == "#清除所有": self.sessions.clear_all_session() reply = Reply(ReplyType.INFO, "所有人记忆已清除") elif query == "#更新配置": load_config() reply = Reply(ReplyType.INFO, "配置已更新") if reply: return reply session = self.sessions.session_query(query, session_id) logger.debug("[CHATGPT] session query={}".format(session.messages)) api_key = context.get("openai_api_key") model = context.get("gpt_model") new_args = None if model: new_args = self.args.copy() new_args["model"] = model # if context.get('stream'): # # reply in stream # return self.reply_text_stream(query, new_query, session_id) reply_content = self.reply_text(session, api_key, args=new_args) logger.debug( "[CHATGPT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format( session.messages, session_id, reply_content["content"], reply_content["completion_tokens"], ) ) if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0: reply = Reply(ReplyType.ERROR, reply_content["content"]) elif reply_content["completion_tokens"] > 0: self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"]) reply = Reply(ReplyType.TEXT, reply_content["content"]) else: reply = Reply(ReplyType.ERROR, reply_content["content"]) logger.debug("[CHATGPT] reply {} used 0 tokens.".format(reply_content)) return reply elif context.type == ContextType.IMAGE_CREATE: ok, retstring = self.create_img(query, 0) reply = None if ok: reply = Reply(ReplyType.IMAGE_URL, retstring) else: reply = Reply(ReplyType.ERROR, retstring) return reply elif context.type == ContextType.IMAGE: logger.info("[CHATGPT] Image message received") reply = self.reply_image(context) return reply else: reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type)) return reply def reply_image(self, context): """ Process image message using OpenAI Vision API """ import base64 import os try: image_path = context.content logger.info(f"[CHATGPT] Processing image: {image_path}") # Check if file exists if not os.path.exists(image_path): logger.error(f"[CHATGPT] Image file not found: {image_path}") return Reply(ReplyType.ERROR, "图片文件不存在") # Read and encode image with open(image_path, "rb") as f: image_data = f.read() image_base64 = base64.b64encode(image_data).decode("utf-8") # Detect image format extension = os.path.splitext(image_path)[1].lower() mime_type_map = { ".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".png": "image/png", ".gif": "image/gif", ".webp": "image/webp" } mime_type = mime_type_map.get(extension, "image/jpeg") # Get model and API config model = context.get("gpt_model") or conf().get("model", "gpt-4o") api_key = context.get("openai_api_key") or conf().get("open_ai_api_key") api_base = conf().get("open_ai_api_base") # Build vision request messages = [ { "role": "user", "content": [ {"type": "text", "text": "请描述这张图片的内容"}, { "type": "image_url", "image_url": { "url": f"data:{mime_type};base64,{image_base64}" } } ] } ] logger.info(f"[CHATGPT] Calling vision API with model: {model}") # Call OpenAI API kwargs = { "model": model, "messages": messages, "max_tokens": 1000 } if api_key: kwargs["api_key"] = api_key if api_base: kwargs["api_base"] = api_base response = openai.ChatCompletion.create(**kwargs) content = response.choices[0]["message"]["content"] logger.info(f"[CHATGPT] Vision API response: {content[:100]}...") # Clean up temp file try: os.remove(image_path) logger.debug(f"[CHATGPT] Removed temp image file: {image_path}") except: pass return Reply(ReplyType.TEXT, content) except Exception as e: logger.error(f"[CHATGPT] Image processing error: {e}") import traceback logger.error(traceback.format_exc()) return Reply(ReplyType.ERROR, f"图片识别失败: {str(e)}") def reply_text(self, session: ChatGPTSession, api_key=None, args=None, retry_count=0) -> dict: """ call openai's ChatCompletion to get the answer :param session: a conversation session :param session_id: session id :param retry_count: retry count :return: {} """ try: if conf().get("rate_limit_chatgpt") and not self.tb4chatgpt.get_token(): raise openai.error.RateLimitError("RateLimitError: rate limit exceeded") # if api_key == None, the default openai.api_key will be used if args is None: args = self.args response = openai.ChatCompletion.create(api_key=api_key, messages=session.messages, **args) # logger.debug("[CHATGPT] response={}".format(response)) logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"])) return { "total_tokens": response["usage"]["total_tokens"], "completion_tokens": response["usage"]["completion_tokens"], "content": response.choices[0]["message"]["content"], } except Exception as e: need_retry = retry_count < 2 result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"} if isinstance(e, openai.error.RateLimitError): logger.warn("[CHATGPT] RateLimitError: {}".format(e)) result["content"] = "提问太快啦，请休息一下再问我吧" if need_retry: time.sleep(20) elif isinstance(e, openai.error.Timeout): logger.warn("[CHATGPT] Timeout: {}".format(e)) result["content"] = "我没有收到你的消息" if need_retry: time.sleep(5) elif isinstance(e, openai.error.APIError): logger.warn("[CHATGPT] Bad Gateway: {}".format(e)) result["content"] = "请再问我一次" if need_retry: time.sleep(10) elif isinstance(e, openai.error.APIConnectionError): logger.warn("[CHATGPT] APIConnectionError: {}".format(e)) result["content"] = "我连接不到你的网络" if need_retry: time.sleep(5) else: logger.exception("[CHATGPT] Exception: {}".format(e)) need_retry = False self.sessions.clear_session(session.session_id) if need_retry: logger.warn("[CHATGPT] 第{}次重试".format(retry_count + 1)) return self.reply_text(session, api_key, args, retry_count + 1) else: return result class AzureChatGPTBot(ChatGPTBot): def __init__(self): super().__init__() openai.api_type = "azure" openai.api_version = conf().get("azure_api_version", "2023-06-01-preview") self.args["deployment_id"] = conf().get("azure_deployment_id") def create_img(self, query, retry_count=0, api_key=None): text_to_image_model = conf().get("text_to_image") if text_to_image_model == "dall-e-2": api_version = "2023-06-01-preview" endpoint = conf().get("azure_openai_dalle_api_base","open_ai_api_base") # 检查endpoint是否以/结尾 if not endpoint.endswith("/"): endpoint = endpoint + "/" url = "{}openai/images/generations:submit?api-version={}".format(endpoint, api_version) api_key = conf().get("azure_openai_dalle_api_key","open_ai_api_key") headers = {"api-key": api_key, "Content-Type": "application/json"} try: body = {"prompt": query, "size": conf().get("image_create_size", "256x256"),"n": 1} submission = requests.post(url, headers=headers, json=body) operation_location = submission.headers['operation-location'] status = "" while (status != "succeeded"): if retry_count > 3: return False, "图片生成失败" response = requests.get(operation_location, headers=headers) status = response.json()['status'] retry_count += 1 image_url = response.json()['result']['data'][0]['url'] return True, image_url except Exception as e: logger.error("create image error: {}".format(e)) return False, "图片生成失败" elif text_to_image_model == "dall-e-3": api_version = conf().get("azure_api_version", "2024-02-15-preview") endpoint = conf().get("azure_openai_dalle_api_base","open_ai_api_base") # 检查endpoint是否以/结尾 if not endpoint.endswith("/"): endpoint = endpoint + "/" url = "{}openai/deployments/{}/images/generations?api-version={}".format(endpoint, conf().get("azure_openai_dalle_deployment_id","text_to_image"),api_version) api_key = conf().get("azure_openai_dalle_api_key","open_ai_api_key") headers = {"api-key": api_key, "Content-Type": "application/json"} try: body = {"prompt": query, "size": conf().get("image_create_size", "1024x1024"), "quality": conf().get("dalle3_image_quality", "standard")} response = requests.post(url, headers=headers, json=body) response.raise_for_status() # 检查请求是否成功 data = response.json() # 检查响应中是否包含图像 URL if 'data' in data and len(data['data']) > 0 and 'url' in data['data'][0]: image_url = data['data'][0]['url'] return True, image_url else: error_message = "响应中没有图像 URL" logger.error(error_message) return False, "图片生成失败" except requests.exceptions.RequestException as e: # 捕获所有请求相关的异常 try: error_detail = response.json().get('error', {}).get('message', str(e)) except ValueError: error_detail = str(e) error_message = f"{error_detail}" logger.error(error_message) return False, error_message except Exception as e: # 捕获所有其他异常 error_message = f"生成图像时发生错误: {e}" logger.error(error_message) return False, "图片生成失败" else: return False, "图片生成失败，未配置text_to_image参数"