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
This commit is contained in:
6vision
2026-03-23 21:23:35 +08:00
parent baf66a103d
commit f512b55ec2
7 changed files with 231 additions and 9 deletions

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@@ -74,7 +74,7 @@ class AgentLLMModel(LLMModel):
("qwen", const.QWEN_DASHSCOPE), ("qwq", const.QWEN_DASHSCOPE), ("qvq", const.QWEN_DASHSCOPE),
("gemini", const.GEMINI), ("glm", const.ZHIPU_AI), ("claude", const.CLAUDEAPI),
("moonshot", const.MOONSHOT), ("kimi", const.MOONSHOT),
("doubao", const.DOUBAO),
("doubao", const.DOUBAO), ("deepseek", const.DEEPSEEK),
]
def __init__(self, bridge: Bridge, bot_type: str = "chat"):
@@ -115,8 +115,6 @@ class AgentLLMModel(LLMModel):
return const.QWEN_DASHSCOPE
if model_name in [const.MOONSHOT, "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k"]:
return const.MOONSHOT
if model_name in [const.DEEPSEEK_CHAT, const.DEEPSEEK_REASONER]:
return const.OPENAI
for prefix, btype in self._MODEL_PREFIX_MAP:
if model_name.startswith(prefix):
return btype

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@@ -61,6 +61,9 @@ class Bridge(object):
if model_type and model_type.startswith("doubao"):
self.btype["chat"] = const.DOUBAO
if model_type and model_type.startswith("deepseek"):
self.btype["chat"] = const.DEEPSEEK
if model_type in [const.MODELSCOPE]:
self.btype["chat"] = const.MODELSCOPE

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@@ -563,9 +563,9 @@ class ConfigHandler:
}),
("deepseek", {
"label": "DeepSeek",
"api_key_field": "open_ai_api_key",
"api_base_key": None,
"api_base_default": None,
"api_key_field": "deepseek_api_key",
"api_base_key": "deepseek_api_base",
"api_base_default": "https://api.deepseek.com/v1",
"models": [const.DEEPSEEK_CHAT, const.DEEPSEEK_REASONER],
}),
("linkai", {
@@ -579,9 +579,9 @@ class ConfigHandler:
EDITABLE_KEYS = {
"model", "bot_type", "use_linkai",
"open_ai_api_base", "claude_api_base", "gemini_api_base",
"open_ai_api_base", "deepseek_api_base", "claude_api_base", "gemini_api_base",
"zhipu_ai_api_base", "moonshot_base_url", "ark_base_url",
"open_ai_api_key", "claude_api_key", "gemini_api_key",
"open_ai_api_key", "deepseek_api_key", "claude_api_key", "gemini_api_key",
"zhipu_ai_api_key", "dashscope_api_key", "moonshot_api_key",
"ark_api_key", "minimax_api_key", "linkai_api_key",
"agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps",

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@@ -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()

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@@ -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"}

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@@ -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