feat(deepseek): add independent DeepSeek bot module with dedicated config

Separate DeepSeek from ChatGPTBot into its own module (models/deepseek/) with dedicated deepseek_api_key and deepseek_api_base config fields, avoiding config conflicts when switching between providers. Backward compatible with old users who configured DeepSeek via open_ai_api_key/open_ai_api_base through automatic fallback.

Made-with: Cursor

models/bot_factory.py

@@ -17,7 +17,11 @@ def create_bot(bot_type):
         from models.baidu.baidu_wenxin import BaiduWenxinBot
         return BaiduWenxinBot()
 
-    elif bot_type in (const.OPENAI, const.CHATGPT, const.DEEPSEEK):  # OpenAI-compatible API
+    elif bot_type == const.DEEPSEEK:
+        from models.deepseek.deepseek_bot import DeepSeekBot
+        return DeepSeekBot()
+
+    elif bot_type in (const.OPENAI, const.CHATGPT):  # OpenAI-compatible API
         from models.chatgpt.chat_gpt_bot import ChatGPTBot
         return ChatGPTBot()
 

models/deepseek/deepseek_bot.py

@@ -0,0 +1,160 @@
+# encoding:utf-8
+
+"""
+DeepSeek Bot — fully OpenAI-compatible, uses its own API key / base config.
+"""
+
+import time
+
+import requests
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf, load_config
+from .deepseek_session import DeepSeekSession
+
+DEFAULT_API_BASE = "https://api.deepseek.com/v1"
+
+
+class DeepSeekBot(Bot, OpenAICompatibleBot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(
+            DeepSeekSession,
+            model=conf().get("model") or const.DEEPSEEK_CHAT,
+        )
+        conf_model = conf().get("model") or const.DEEPSEEK_CHAT
+        self.args = {
+            "model": conf_model,
+            "temperature": conf().get("temperature", 0.7),
+            "top_p": conf().get("top_p", 1.0),
+            "frequency_penalty": conf().get("frequency_penalty", 0.0),
+            "presence_penalty": conf().get("presence_penalty", 0.0),
+        }
+
+    # ---------- config helpers ----------
+
+    @property
+    def api_key(self):
+        return conf().get("deepseek_api_key") or conf().get("open_ai_api_key")
+
+    @property
+    def api_base(self):
+        url = (
+            conf().get("deepseek_api_base")
+            or conf().get("open_ai_api_base")
+            or DEFAULT_API_BASE
+        )
+        return url.rstrip("/")
+
+    def get_api_config(self):
+        """OpenAICompatibleBot interface — used by call_with_tools()."""
+        return {
+            "api_key": self.api_key,
+            "api_base": self.api_base,
+            "model": conf().get("model", const.DEEPSEEK_CHAT),
+            "default_temperature": conf().get("temperature", 0.7),
+            "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),
+        }
+
+    # ---------- simple chat (non-agent mode) ----------
+
+    def reply(self, query, context=None):
+        if context.type == ContextType.TEXT:
+            logger.info("[DEEPSEEK] 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("[DEEPSEEK] session query={}".format(session.messages))
+
+            new_args = self.args.copy()
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[DEEPSEEK] 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("[DEEPSEEK] reply {} used 0 tokens.".format(reply_content))
+            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, args=None, retry_count: int = 0) -> dict:
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key,
+            }
+            body = args.copy()
+            body["messages"] = session.messages
+
+            res = requests.post(
+                f"{self.api_base}/chat/completions",
+                headers=headers,
+                json=body,
+                timeout=180,
+            )
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"],
+                }
+            else:
+                response = res.json()
+                error = response.get("error", {})
+                logger.error(
+                    f"[DEEPSEEK] chat failed, status_code={res.status_code}, "
+                    f"msg={error.get('message')}, type={error.get('type')}"
+                )
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                return result
+        except Exception as e:
+            logger.exception(e)
+            if retry_count < 2:
+                return self.reply_text(session, args, retry_count + 1)
+            return {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}

models/deepseek/deepseek_session.py

@@ -0,0 +1,57 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class DeepSeekSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="deepseek-chat"):
+        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)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        content = msg.get("content", "")
+        if isinstance(content, str):
+            tokens += len(content)
+        elif isinstance(content, list):
+            for block in content:
+                if isinstance(block, dict):
+                    tokens += len(block.get("text", ""))
+    return tokens