🔖 bump llmchat version 0.2.5

✨ support vision models

README.md

@@ -8,7 +8,7 @@
 
 # nonebot-plugin-llmchat
 
-_✨ 支持多API预设、MCP协议、联网搜索的AI群聊插件 ✨_
+_✨ 支持多API预设、MCP协议、联网搜索、视觉模型的AI群聊插件 ✨_
 
 
 <a href="./LICENSE">
@@ -17,7 +17,8 @@ _✨ 支持多API预设、MCP协议、联网搜索的AI群聊插件 ✨_
 <a href="https://pypi.python.org/pypi/nonebot-plugin-llmchat">
     <img src="https://img.shields.io/pypi/v/nonebot-plugin-llmchat.svg" alt="pypi">
 </a>
-<img src="https://img.shields.io/badge/python-3.9+-blue.svg" alt="python">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<a href="https://deepwiki.com/FuQuan233/nonebot-plugin-llmchat"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
 
 </div>
 
@@ -107,6 +108,8 @@ _✨ 支持多API预设、MCP协议、联网搜索的AI群聊插件 ✨_
 | LLMCHAT__DEFAULT_PRESET | 否 | off | 默认使用的预设名称，配置为off则为关闭 |
 | LLMCHAT__RANDOM_TRIGGER_PROB | 否 | 0.05 | 默认随机触发概率 [0, 1] |
 | LLMCHAT__DEFAULT_PROMPT | 否 | 你的回答应该尽量简洁、幽默、可以使用一些语气词、颜文字。你应该拒绝回答任何政治相关的问题。 | 默认提示词 |
+| LLMCHAT__BLACKLIST_USER_IDS | 否 | [] | 黑名单用户ID列表，机器人将不会处理黑名单用户的消息 |
+| LLMCHAT__IGNORE_PREFIXES | 否 | [] | 需要忽略的消息前缀列表，匹配到这些前缀的消息不会处理 |
 | LLMCHAT__MCP_SERVERS | 否 | {} | MCP服务器配置，具体见下表 |
 
 其中LLMCHAT__API_PRESETS为一个列表，每项配置有以下的配置项
@@ -119,6 +122,8 @@ _✨ 支持多API预设、MCP协议、联网搜索的AI群聊插件 ✨_
 | max_tokens | 否 | 2048 | 最大响应token数 |
 | temperature | 否 | 0.7 | 生成温度 |
 | proxy | 否 | 无 | 请求API时使用的HTTP代理 |
+| support_mcp | 否 | False | 是否支持MCP协议 |
+| support_image | 否 | False | 是否支持图片输入 |
 
 
 LLMCHAT__MCP_SERVERS同样为一个dict，key为服务器名称，value配置的格式基本兼容 Claude.app 的配置格式，具体支持如下
@@ -151,10 +156,18 @@ LLMCHAT__MCP_SERVERS同样为一个dict，key为服务器名称，value配置的
         "proxy": "http://10.0.0.183:7890"
     },
     {
-        "name": "deepseek-r1",
+        "name": "deepseek-v1",
         "api_key": "sk-your-api-key",
-        "model_name": "deepseek-reasoner",
-        "api_base": "https://api.deepseek.com"
+        "model_name": "deepseek-chat",
+        "api_base": "https://api.deepseek.com",
+        "support_mcp": true
+    },
+    {
+        "name": "some-vison-model",
+        "api_key": "sk-your-api-key",
+        "model_name": "some-vison-model",
+        "api_base": "https://some-vison-model.com/api",
+        "support_image": true
     }
     ]
     LLMCHAT__MCP_SERVERS='
@@ -195,4 +208,4 @@ LLMCHAT__MCP_SERVERS同样为一个dict，key为服务器名称，value配置的
 
 ### 效果图
 ![](img/mcp_demo.jpg)
-![](img/demo.png)
+![](img/demo.png)

nonebot_plugin_llmchat/__init__.py

@@ -1,10 +1,12 @@
 import asyncio
+import base64
 from collections import defaultdict, deque
 from datetime import datetime
 import json
 import os
 import random
 import re
+import ssl
 import time
 from typing import TYPE_CHECKING
 
@@ -37,11 +39,14 @@ require("nonebot_plugin_apscheduler")
 from nonebot_plugin_apscheduler import scheduler
 
 if TYPE_CHECKING:
-    from openai.types.chat import ChatCompletionMessageParam
+    from openai.types.chat import (
+        ChatCompletionContentPartParam,
+        ChatCompletionMessageParam,
+    )
 
 __plugin_meta__ = PluginMetadata(
     name="llmchat",
-    description="支持多API预设、MCP协议、联网搜索的AI群聊插件",
+    description="支持多API预设、MCP协议、联网搜索、视觉模型的AI群聊插件",
     usage="""@机器人 + 消息 开启对话""",
     type="application",
     homepage="https://github.com/FuQuan233/nonebot-plugin-llmchat",
@@ -160,6 +165,16 @@ async def is_triggered(event: GroupMessageEvent) -> bool:
     if state.preset_name == "off":
         return False
 
+    # 黑名单用户
+    if event.user_id in plugin_config.blacklist_user_ids:
+        return False
+
+    # 忽略特定前缀的消息
+    msg_text = event.get_plaintext().strip()
+    for prefix in plugin_config.ignore_prefixes:
+        if msg_text.startswith(prefix):
+            return False
+
     state.past_events.append(event)
 
     # 原有@触发条件
@@ -176,7 +191,7 @@ async def is_triggered(event: GroupMessageEvent) -> bool:
 # 消息处理器
 handler = on_message(
     rule=Rule(is_triggered),
-    priority=10,
+    priority=99,
     block=False,
 )
 
@@ -197,6 +212,46 @@ async def handle_message(event: GroupMessageEvent):
         task.add_done_callback(tasks.discard)
         tasks.add(task)
 
+async def process_images(event: GroupMessageEvent) -> list[str]:
+    base64_images = []
+    for segement in event.get_message():
+        if segement.type == "image":
+            image_url = segement.data.get("url") or segement.data.get("file")
+            if image_url:
+                try:
+                    # 处理高版本 httpx 的 [SSL: SSLV3_ALERT_HANDSHAKE_FAILURE] 报错
+                    ssl_context = ssl.create_default_context()
+                    ssl_context.check_hostname = False
+                    ssl_context.verify_mode = ssl.CERT_NONE
+                    ssl_context.set_ciphers("DEFAULT@SECLEVEL=2")
+
+                    # 下载图片并将图片转换为base64
+                    async with httpx.AsyncClient(verify=ssl_context) as client:
+                        response = await client.get(image_url, timeout=10.0)
+                        if response.status_code != 200:
+                            logger.error(f"下载图片失败: {image_url}, 状态码: {response.status_code}")
+                            continue
+                        image_data = response.content
+                        base64_data = base64.b64encode(image_data).decode("utf-8")
+                        base64_images.append(base64_data)
+                except Exception as e:
+                    logger.error(f"处理图片时出错: {e}")
+    logger.debug(f"共处理 {len(base64_images)} 张图片")
+    return base64_images
+
+async def send_split_messages(message_handler, content: str):
+    """
+    将消息按分隔符<botbr>分段并发送
+    """
+    logger.info(f"准备发送分段消息，分段数：{len(content.split('<botbr>'))}")
+    for segment in content.split("<botbr>"):
+        # 跳过空消息
+        if not segment.strip():
+            continue
+        segment = segment.strip()  # 删除前后多余的换行和空格
+        await asyncio.sleep(2)  # 避免发送过快
+        logger.debug(f"发送消息分段 内容：{segment[:50]}...")  # 只记录前50个字符避免日志过大
+        await message_handler.send(Message(segment))
 
 async def process_messages(group_id: int):
     state = group_states[group_id]
@@ -252,14 +307,28 @@ async def process_messages(group_id: int):
                 {"role": "system", "content": systemPrompt}
             ]
 
+            while len(state.history) > 0 and state.history[0]["role"] != "user":
+                state.history.popleft()
+
             messages += list(state.history)[-plugin_config.history_size * 2 :]
 
             # 没有未处理的消息说明已经被处理了，跳过
             if state.past_events.__len__() < 1:
                 break
 
+            content: list[ChatCompletionContentPartParam] = []
+
             # 将机器人错过的消息推送给LLM
-            content = ",".join([format_message(ev) for ev in state.past_events])
+            past_events_snapshot = list(state.past_events)
+            for ev in past_events_snapshot:
+                text_content = format_message(ev)
+                content.append({"type": "text", "text": text_content})
+
+                # 将消息中的图片转成 base64
+                if preset.support_image:
+                    base64_images = await process_images(ev)
+                    for base64_image in base64_images:
+                        content.append({"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}})
 
             new_messages: list[ChatCompletionMessageParam] = [
                 {"role": "user", "content": content}
@@ -268,10 +337,6 @@ async def process_messages(group_id: int):
             logger.debug(
                 f"发送API请求 模型：{preset.model_name} 历史消息数：{len(messages)}"
             )
-            mcp_client = MCPClient(plugin_config.mcp_servers)
-            await mcp_client.connect_to_servers()
-
-            available_tools = await mcp_client.get_available_tools()
 
             client_config = {
                 "model": preset.model_name,
@@ -280,7 +345,10 @@ async def process_messages(group_id: int):
                 "timeout": 60,
             }
 
+            mcp_client = MCPClient(plugin_config.mcp_servers)
             if preset.support_mcp:
+                await mcp_client.connect_to_servers()
+                available_tools = await mcp_client.get_available_tools()
                 client_config["tools"] = available_tools
 
             response = await client.chat.completions.create(
@@ -291,10 +359,7 @@ async def process_messages(group_id: int):
             if response.usage is not None:
                 logger.debug(f"收到API响应 使用token数：{response.usage.total_tokens}")
 
-            final_message = []
             message = response.choices[0].message
-            if message.content:
-                final_message.append(message.content)
 
             # 处理响应并处理工具调用
             while preset.support_mcp and message.tool_calls:
@@ -302,6 +367,11 @@ async def process_messages(group_id: int):
                     "role": "assistant",
                     "tool_calls": [tool_call.model_dump() for tool_call in message.tool_calls]
                 })
+
+                # 发送LLM调用工具时的回复，一般没有
+                if message.content:
+                    await send_split_messages(handler, message.content)
+
                 # 处理每个工具调用
                 for tool_call in message.tool_calls:
                     tool_name = tool_call.function.name
@@ -316,7 +386,7 @@ async def process_messages(group_id: int):
                     new_messages.append({
                         "role": "tool",
                         "tool_call_id": tool_call.id,
-                        "content": str(result.content)
+                        "content": str(result)
                     })
 
                 # 将工具调用的结果交给 LLM
@@ -326,8 +396,6 @@ async def process_messages(group_id: int):
                 )
 
                 message = response.choices[0].message
-                if message.content:
-                    final_message.append(message.content)
 
             await mcp_client.cleanup()
 
@@ -339,6 +407,11 @@ async def process_messages(group_id: int):
                 or matched_reasoning_content
             )
 
+            new_messages.append({
+                "role": "assistant",
+                "content": reply,
+            })
+
             # 请求成功后再保存历史记录，保证user和assistant穿插，防止R1模型报错
             for message in new_messages:
                 state.history.append(message)
@@ -357,20 +430,7 @@ async def process_messages(group_id: int):
                     logger.error(f"合并转发消息发送失败：\n{e!s}\n")
 
             assert reply is not None
-            logger.info(
-                f"准备发送回复消息 群号：{group_id} 消息分段数：{len(reply.split('<botbr>'))}"
-            )
-            for r in reply.split("<botbr>"):
-                # 似乎会有空消息的情况导致string index out of range异常
-                if len(r) == 0 or r.isspace():
-                    continue
-                # 删除前后多余的换行和空格
-                r = r.strip()
-                await asyncio.sleep(2)
-                logger.debug(
-                    f"发送消息分段 内容：{r[:50]}..."
-                )  # 只记录前50个字符避免日志过大
-                await handler.send(Message(r))
+            await send_split_messages(handler, reply)
 
         except Exception as e:
             logger.opt(exception=e).error(f"API请求失败 群号：{group_id}")
@@ -407,7 +467,7 @@ async def handle_preset(event: GroupMessageEvent, args: Message = CommandArg()):
 
 edit_preset_handler = on_command(
     "修改设定",
-    priority=99,
+    priority=1,
     block=True,
     permission=(SUPERUSER | GROUP_ADMIN | GROUP_OWNER),
 )
@@ -424,7 +484,7 @@ async def handle_edit_preset(event: GroupMessageEvent, args: Message = CommandAr
 
 reset_handler = on_command(
     "记忆清除",
-    priority=99,
+    priority=1,
     block=True,
     permission=(SUPERUSER | GROUP_ADMIN | GROUP_OWNER),
 )
@@ -441,7 +501,7 @@ async def handle_reset(event: GroupMessageEvent, args: Message = CommandArg()):
 
 set_prob_handler = on_command(
     "设置主动回复概率",
-    priority=99,
+    priority=1,
     block=True,
     permission=(SUPERUSER | GROUP_ADMIN | GROUP_OWNER),
 )

nonebot_plugin_llmchat/config.py

@@ -12,6 +12,7 @@ class PresetConfig(BaseModel):
     temperature: float = Field(0.7, description="生成温度（0-2]")
     proxy: str = Field("", description="HTTP代理服务器")
     support_mcp: bool = Field(False, description="是否支持MCP")
+    support_image: bool = Field(False, description="是否支持图片输入")
 
 class MCPServerConfig(BaseModel):
     """MCP服务器配置"""
@@ -42,6 +43,11 @@ class ScopedConfig(BaseModel):
         description="默认提示词",
     )
     mcp_servers: dict[str, MCPServerConfig] = Field({}, description="MCP服务器配置")
+    blacklist_user_ids: set[int] = Field(set(), description="黑名单用户ID列表")
+    ignore_prefixes: list[str] = Field(
+        default_factory=list,
+        description="需要忽略的消息前缀列表，匹配到这些前缀的消息不会处理"
+    )
 
 
 class Config(BaseModel):

nonebot_plugin_llmchat/mcpclient.py

@@ -1,3 +1,4 @@
+import asyncio
 from contextlib import AsyncExitStack
 
 from mcp import ClientSession, StdioServerParameters
@@ -64,9 +65,13 @@ class MCPClient:
         server_name, real_tool_name = tool_name.split("___")
         logger.info(f"正在服务器[{server_name}]上调用工具[{real_tool_name}]")
         session = self.sessions[server_name]
-        response = await session.call_tool(real_tool_name, tool_args)
+        try:
+            response = await asyncio.wait_for(session.call_tool(real_tool_name, tool_args), timeout=30)
+        except asyncio.TimeoutError:
+            logger.error(f"调用工具[{real_tool_name}]超时")
+            return f"调用工具[{real_tool_name}]超时"
         logger.debug(f"工具[{real_tool_name}]调用完成，响应: {response}")
-        return response
+        return response.content
 
     def get_friendly_name(self, tool_name: str):
         server_name, real_tool_name = tool_name.split("___")

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "nonebot-plugin-llmchat"
-version = "0.2.0"
+version = "0.2.5"
 description = "Nonebot AI group chat plugin supporting multiple API preset configurations"
 license = "GPL"
 authors = ["FuQuan i@fuquan.moe"]