chore: the bot directory was changed to models

models/chatgpt/chat_gpt_bot.py

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+# 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
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    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"

models/chatgpt/chat_gpt_session.py

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+from models.session_manager import Session
+from common.log import logger
+from common import const
+
+"""
+    e.g.  [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Who won the world series in 2020?"},
+        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
+        {"role": "user", "content": "Where was it played?"}
+    ]
+"""
+
+
+class ChatGPTSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="gpt-3.5-turbo"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+# refer to https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
+def num_tokens_from_messages(messages, model):
+    """Returns the number of tokens used by a list of messages."""
+
+    if model in ["wenxin", "xunfei"] or model.startswith(const.GEMINI):
+        return num_tokens_by_character(messages)
+
+    import tiktoken
+
+    if model in ["gpt-3.5-turbo-0301", "gpt-35-turbo", "gpt-3.5-turbo-1106", "moonshot", const.LINKAI_35]:
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    elif model in ["gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-turbo-0613",
+                   "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-35-turbo-16k", "gpt-4-turbo-preview",
+                   "gpt-4-1106-preview", const.GPT4_TURBO_PREVIEW, const.GPT4_VISION_PREVIEW, const.GPT4_TURBO_01_25,
+                   const.GPT_4o, const.GPT_4O_0806, const.GPT_4o_MINI, const.LINKAI_4o, const.LINKAI_4_TURBO, const.GPT_5, const.GPT_5_MINI, const.GPT_5_NANO]:
+        return num_tokens_from_messages(messages, model="gpt-4")
+    elif model.startswith("claude-3"):
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    try:
+        encoding = tiktoken.encoding_for_model(model)
+    except KeyError:
+        logger.debug("Warning: model not found. Using cl100k_base encoding.")
+        encoding = tiktoken.get_encoding("cl100k_base")
+    if model == "gpt-3.5-turbo":
+        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
+        tokens_per_name = -1  # if there's a name, the role is omitted
+    elif model == "gpt-4":
+        tokens_per_message = 3
+        tokens_per_name = 1
+    else:
+        logger.debug(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo.")
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    num_tokens = 0
+    for message in messages:
+        num_tokens += tokens_per_message
+        for key, value in message.items():
+            num_tokens += len(encoding.encode(value))
+            if key == "name":
+                num_tokens += tokens_per_name
+    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
+    return num_tokens
+
+
+def num_tokens_by_character(messages):
+    """Returns the number of tokens used by a list of messages."""
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens