修复错误代码

add: 增加查看info命令

README.md

@@ -1,3 +1,25 @@
 # maubot-llmplus
 -------
 maubot plugin: llm plus
+
+order:
+- !ai info
+> View the configuration information currently in official use.
+- !ai platform list
+> list platforms.
+- !ai platform current
+> query current platform in use.
+- !ai model list
+> list models on current platform.
+- !ai model current
+> query current model in use.
+- !ai use [model_name]
+> switch model in platform, you can use `!ai model list` command query model list.
+- !ai switch [platform_name]
+> switch platform
+> support platforms:
+> - local_ai#ollama
+> - local_ai#lmstudio
+> - openai
+> - anthropic
+

base-config.yaml

@@ -1,39 +1,105 @@
+# allow users
 allowed_users: []
 
+# allow update and read permission users
+allow_update_read_command_users: []
+
+# allow readonly permission users
+allow_readonly_command_users: []
+
+# current use platform
 use_platform: local_ai
 
-name:
+# bot name
+name: "ai bot"
 
-reply_in_thread:
+reply_in_thread: true
 
-enable_multi_user:
+enable_multi_user: true
 
-system_prompt: ""
+# system prompt
+system_prompt: "response in chinese"
 
+# platform config
 platforms:
   local_ai:
     type: ollama
-    url: http://localhost:11434
+    url: http://192.168.32.162:11434
     api_key:
     model: llama3.2
+    temperature: 1
+    max_tokens: 2000
     max_words: 1000
-    max_context_messages: 100
+    max_context_messages: 20
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
+  qwen:
+    # 国内: https://dashscope.aliyuncs.com
+    # 海外: https://dashscope-intl.aliyuncs.com
+    url: https://dashscope.aliyuncs.com
+    api_key:
+    model: qwen-plus
+    temperature: 0.7
+    top_p: 0.8
+    max_tokens: 2000
+    max_words: 1000
+    max_context_messages: 20
+    # 是否开启深度思考模式（仅 qwq 系列支持）
+    enable_thinking: false
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
+  deepseek:
+    url: https://api.deepseek.com
+    api_key:
+    model:
+    max_words: 1000
+    max_context_messages: 20
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
+  gemini:
+    url: https://generativelanguage.googleapis.com
+    api_key:
+    model: gemini-2.0-flash
+    temperature: 1
+    max_tokens: 2000
+    max_words: 1000
+    max_context_messages: 20
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
   openai:
-    url:
+    url: https://api.openai.com
     api_key:
-    model:
-    max_tokens:
-    max_words:
-    temperature:
+    model: gpt-4o-mini
+    max_tokens: 2000
+    max_words: 1000
+    max_context_messages: 20
+    temperature: 1
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
   anthropic:
-    url:
+    url: https://api.anthropic.com
     api_key:
-    max_tokens:
-    model:
-    max_words:
+    model: claude-3-5-sonnet-20240620
+    max_words: 1000
+    max_tokens: 2000
+    max_context_messages: 20
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
+  xai:
+    url: https://api.x.ai
+    api_key:
+    model: grok-beta
+    temperature: 1
+    max_tokens: 1000
+    max_words: 2000
+    max_context_messages: 20
+    # 是否开启流式输出（开启后 Element 中消息会逐步更新）
+    streaming: false
 
+
+# additional prompt
 additional_prompt:
   - role: user
-    content: xxx
+    content: "What model is currently in use?"
   - role: system
-    content: xxx
+    content: "you can response text contain user name"

maubot_llmplus/aibot.py

@@ -1,3 +1,4 @@
+import asyncio
 import re
 
 from typing import Type
@@ -9,36 +10,16 @@ from mautrix.util.config import BaseProxyConfig, ConfigUpdateHelper
 
 from maubot_llmplus.local_paltform import Ollama, LmStudio
 from maubot_llmplus.platforms import Platform
-from maubot_llmplus.thrid_platform import OpenAi, Anthropic
-
-"""
-配置文件加载
-"""
+from maubot_llmplus.plugin import AbsExtraConfigPlugin, Config
+from maubot_llmplus.thrid_platform import OpenAi, Anthropic, XAi, Deepseek, Gemini, Qwen
 
 
-class Config(BaseProxyConfig):
-    def do_update(self, helper: ConfigUpdateHelper) -> None:
-        helper.copy("allowed_users")
-        helper.copy("use_platform")
-        helper.copy("name")
-        helper.copy("reply_in_thread")
-        helper.copy("enable_multi_user")
-        helper.copy("system_prompt")
-        helper.copy("platforms")
-        helper.copy("additional_prompt")
-
-
-class AiBotPlugin(Plugin):
-    name: str
+class AiBotPlugin(AbsExtraConfigPlugin):
 
     async def start(self) -> None:
         await super().start()
         # 加载并更新配置
         self.config.load_and_update()
-        # 决定当前机器人的名称
-        self.name = self.config['name'] or \
-                    await self.client.get_displayname(self.client.mxid) or \
-                    self.client.parse_user_id(self.client.mxid)[0]
 
     """
     判断sender是否是allowed_users中的成员
@@ -58,6 +39,31 @@ class AiBotPlugin(Plugin):
         self.log.debug(f"{sender} doesn't match allowed_users")
         pass
 
+    def is_allow_command(self, sender: str, command_key: str) -> bool:
+        allow_users = self.config[command_key]
+        # 如果一个都没有配置，都没有权限可以执行更新命令
+        if len(allow_users) <= 0:
+            return False
+
+        # sender是否是配置中的一员, 如果是就允许进行命令修改执行，否则只有可读命令的执行
+        for u in allow_users:
+            if re.match(u, sender):
+                return True
+        self.log.debug(f"{sender} doesn't match {command_key}")
+        pass
+
+    def is_allow_update_read_command(self, sender: str) -> bool:
+        return self.is_allow_command(sender, "allow_update_read_command_users")
+
+    def is_allow_readonly_command(self, sender: str) -> bool:
+        is_update_read = self.is_allow_update_read_command(sender)
+        # 如果读写都有权限，就一定会有读权限，返回True
+        if is_update_read:
+            return True
+
+        # 如果没有读写权限，需要判断是否有只读权限
+        return self.is_allow_command(sender, "allow_readonly_command_users")
+
     """
     判断是否应该让AI进行回应
     回应条件：
@@ -75,6 +81,10 @@ class AiBotPlugin(Plugin):
         if event.sender == self.client.mxid:
             return False
 
+        # 如果发送的消息中，第一个字符是感叹号，不进行回复
+        if event.content.body[0] == '!':
+            return False
+
         # 判断这个用户是否在允许列表中, 不存在返回False
         # 如果列表为空, 继续往下执行
         if not self.is_allow(event.sender):
@@ -86,7 +96,7 @@ class AiBotPlugin(Plugin):
             return False
 
         # 检查是否发送消息中有带上机器人的别名
-        if re.search("(^|\s)(@)?" + self.name + "([ :,.!?]|$)", event.content.body, re.IGNORECASE):
+        if re.search("(^|\\s)(@)?" + self.get_bot_name() + "([ :,.!?]|$)", event.content.body, re.IGNORECASE):
             return True
 
         # 当聊天室只有两个人并且其中一个是机器人时
@@ -105,6 +115,7 @@ class AiBotPlugin(Plugin):
             if parent_event.sender == self.client.mxid:
                 return True
 
+
     @event.on(EventType.ROOM_MESSAGE)
     async def on_message(self, event: MessageEvent) -> None:
         if not await self.should_respond(event):
@@ -114,17 +125,26 @@ class AiBotPlugin(Plugin):
             await event.mark_read()
             await self.client.set_typing(event.room_id, timeout=99999)
             platform = self.get_ai_platform()
+
+            if platform.is_streaming_enabled():
+                await self._handle_streaming(event, platform)
+                return
+
             chat_completion = await platform.create_chat_completion(self, event)
             self.log.debug(
                 f"发送结果 {chat_completion.message}, {chat_completion.model}, {chat_completion.finish_reason}")
-            # ai gpt调用
-            # 关闭typing提示
             await self.client.set_typing(event.room_id, timeout=0)
-            # 打开typing提示
-            resp_content = chat_completion.message['content']
-            response = TextMessageEventContent(msgtype=MessageType.TEXT, body=resp_content, format=Format.HTML,
-                                               formatted_body=markdown.render(resp_content))
-            await event.respond(response, in_thread=self.config['reply_in_thread'])
+            if chat_completion.result:
+                resp_content = chat_completion.message['content']
+                response = TextMessageEventContent(msgtype=MessageType.TEXT, body=resp_content, format=Format.HTML,
+                                                   formatted_body=markdown.render(resp_content))
+                await event.respond(response, in_thread=self.config['reply_in_thread'])
+            else:
+                resp_content = "调用失败，请检查: " + chat_completion.finish_reason
+                response = TextMessageEventContent(msgtype=MessageType.TEXT, body=resp_content, format=Format.HTML,
+                                                   formatted_body=markdown.render(resp_content))
+                await event.respond(response, in_thread=self.config['reply_in_thread'])
+
         except Exception as e:
             self.log.exception(f"Something went wrong: {e}")
             await event.respond(f"Something went wrong: {e}")
@@ -132,21 +152,94 @@ class AiBotPlugin(Plugin):
 
         return None
 
+    async def _handle_streaming(self, evt: MessageEvent, platform) -> None:
+        # 发送初始占位消息；on_message 已设 typing=on，等收到第一个 chunk 再关掉
+        placeholder = TextMessageEventContent(
+            msgtype=MessageType.TEXT, body="▌", format=Format.HTML, formatted_body="▌"
+        )
+        response_event_id = await evt.respond(placeholder, in_thread=self.config['reply_in_thread'])
+        self.log.debug("Streaming: placeholder sent")
+
+        accumulated = ""
+        last_edit_len = 0
+        first_chunk = True
+        EDIT_THRESHOLD = 100
+
+        async def send_edit(content: TextMessageEventContent) -> None:
+            # shield 防止 wait_for 超时时 cancel send_task，保护 mautrix 内部锁不残留
+            send_task = asyncio.ensure_future(self.client.send_message(evt.room_id, content))
+            try:
+                await asyncio.wait_for(asyncio.shield(send_task), timeout=8.0)
+            except asyncio.TimeoutError:
+                self.log.debug("Streaming: edit timed out, waiting naturally")
+                await send_task
+            except Exception as e:
+                self.log.warning(f"Streaming: edit error: {e}")
+                if not send_task.done():
+                    await send_task
+
+        try:
+            async for chunk in platform.create_chat_completion_stream(self, evt):
+                if first_chunk:
+                    # 收到第一个 chunk 才关掉 typing，等待期间用户可见 typing 指示器
+                    await self.client.set_typing(evt.room_id, timeout=0)
+                    first_chunk = False
+                accumulated += chunk
+                if len(accumulated) - last_edit_len >= EDIT_THRESHOLD:
+                    display = accumulated + " ▌"
+                    new_content = TextMessageEventContent(
+                        msgtype=MessageType.TEXT,
+                        body=display,
+                        format=Format.HTML,
+                        formatted_body=markdown.render(display)
+                    )
+                    new_content.set_edit(response_event_id)
+                    self.log.debug(f"Streaming: mid-edit, accumulated={len(accumulated)}")
+                    await send_edit(new_content)
+                    last_edit_len = len(accumulated)
+        except Exception as e:
+            self.log.exception(f"Streaming error: {e}")
+            if not accumulated:
+                accumulated = f"Streaming error: {e}"
+        finally:
+            if first_chunk:
+                await self.client.set_typing(evt.room_id, timeout=0)
+
+        self.log.debug(f"Streaming: loop done, total={len(accumulated)}")
+
+        if not accumulated:
+            accumulated = "（无响应）"
+        final_content = TextMessageEventContent(
+            msgtype=MessageType.TEXT,
+            body=accumulated,
+            format=Format.HTML,
+            formatted_body=markdown.render(accumulated)
+        )
+        final_content.set_edit(response_event_id)
+        self.log.debug("Streaming: sending final edit")
+        await send_edit(final_content)
+        self.log.debug("Streaming: final edit done")
+
     def get_ai_platform(self) -> Platform:
-        use_platform = self.config['use_platform']
-        if use_platform == 'local_ai':
-            type = self.config['platforms']['local_ai']['type']
-            if type == 'ollama':
-                return Ollama(self.config, self.name, self.http)
-            elif type == 'lmstudio':
-                return LmStudio(self.config, self.name, self.http)
-            else:
-                raise ValueError(f"not found platform type: {type}")
+        use_platform = self.config.cur_platform
         if use_platform == 'openai':
-            return OpenAi(self.config, self.name, self.http)
+            return OpenAi(self.config, self.http)
         if use_platform == 'anthropic':
-            return Anthropic(self.config, self.name, self.http)
-        raise ValueError(f"unknown backend type {use_platform}")
+            return Anthropic(self.config, self.http)
+        if use_platform == 'xai':
+            return XAi(self.config, self.http)
+        if use_platform == 'deepseek':
+            return Deepseek(self.config, self.http)
+        if use_platform == 'gemini':
+            return Gemini(self.config, self.http)
+        if use_platform == 'qwen':
+            return Qwen(self.config, self.http)
+        if use_platform == 'local_ai#ollama':
+            return Ollama(self.config, self.http)
+        if use_platform == 'local_ai#lmstudio':
+            return LmStudio(self.config, self.http)
+        else:
+            raise ValueError(f"not found platform type: {type}")
 
     """
         父命令
@@ -157,20 +250,142 @@ class AiBotPlugin(Plugin):
 
     """
     """
-    @ai_command.subcommand(help="")
+    @ai_command.subcommand(help="View the configuration information currently in official use")
     async def info(self, event: MessageEvent) -> None:
+        # 判断是否有更新命令权限，如果没有就返回没有权限的提示
+        is_allow = self.is_allow_readonly_command(event.sender)
+        if not is_allow:
+            await event.reply(f"{event.sender} have not read permission")
+            return
+
+        show_infos = []
+        # 当前机器人名称
+        show_infos.append(f"bot name: {self.get_bot_name()}\n\n")
+        # 查询当前使用的ai平台
+        show_infos.append(f"platform: {self.get_cur_platform()}\n\n")
+        show_infos.append("platform detail: \n\n")
+        # 查询当前ai平台的配置信息
+        p_m_dict = self.get_config()
+        for k, v in p_m_dict.items():
+            show_infos.append(f"- {k}: {v}\n")
+        # 当前使用的model
+        show_infos.append(f"\nmodel: {self.config.cur_model}\n")
+        # TODO 列出model信息
+        await event.reply("".join(show_infos), markdown=True)
         pass
 
-    @ai_command.subcommand(help="")
+    """
+        获取配置信息
+    """
+    def get_config(self) -> dict:
+        platform_config_dict = dict(self.config['platforms'][self.get_cur_platform()])
+        # 移除敏感配置
+        platform_config_dict.pop('api_key')
+        platform_config_dict.pop('url')
+        return platform_config_dict
+
+    """
+        获取实际平台名称
+    """
+    def get_cur_platform(self) -> str:
+        platform_model = self.config.cur_platform
+        return platform_model.split('#')[0]
+
+    @ai_command.subcommand(help="List platforms or query current platform in use")
+    @command.argument("argus")
+    async def platform(self, event: MessageEvent, argus: str):
+        # 判断是否有更新命令权限，如果没有就返回没有权限的提示
+        is_allow = self.is_allow_readonly_command(event.sender)
+        if not is_allow:
+            await event.reply(f"{event.sender} have not read permission")
+            return
+
+        if argus == 'list':
+            p_dict = dict(self.config['platforms'])
+            platforms = [f"- {platform}" for platform in set(p_dict.keys())]
+            await event.reply("\n".join(platforms))
+            pass
+        if argus == 'current':
+            await event.reply(f"current use platform is {self.config.cur_platform}")
+            pass
+
+    @ai_command.subcommand(help="List models or query current model in use")
     @command.argument("argus")
     async def model(self, event: MessageEvent, argus: str):
+        # 判断是否有更新命令权限，如果没有就返回没有权限的提示
+        is_allow = self.is_allow_readonly_command(event.sender)
+        if not is_allow:
+            await event.reply(f"{event.sender} have not read permission")
+            return
+
         # 如果是list表示查看当前可以使用的模型列表
         if argus == 'list':
             platform = self.get_ai_platform()
-            models = platform.list_models()
-            await event.reply("\n".join(models))
+            models = await platform.list_models()
+            await event.reply("\n".join(models), markdown=True)
+            pass
+        # 如果是current，显示出当前的使用模型
+        if argus == 'current':
+            await event.reply(f"current use model is {self.config.cur_model}")
+            pass
 
-        # 如果不是，如果是其他的名称，表示这是一个模型名
+    @ai_command.subcommand(help="switch model in platform")
+    @command.argument("argus")
+    async def use(self, event: MessageEvent, argus: str):
+        # 判断是否有更新命令权限，如果没有就返回没有权限的提示
+        is_allow = self.is_allow_update_read_command(event.sender)
+        if not is_allow:
+            await event.reply(f"{event.sender} have not update permission")
+            return
+
+        platform = self.get_ai_platform()
+        # 获取模型列表，判断使用的模型是否存在于列表中
+        models = await platform.list_models()
+        if f"- {argus}" in models:
+            self.log.debug(f"switch model: {argus}")
+            self.config.cur_model = argus
+            await event.react("✅")
+        else:
+            await event.reply("not found valid model")
+
+    @ai_command.subcommand(help="switch platform")
+    @command.argument("argus")
+    async def switch(self, event: MessageEvent, argus: str):
+        # 判断是否有更新命令权限，如果没有就返回没有权限的提示
+        is_allow = self.is_allow_update_read_command(event.sender)
+        if not is_allow:
+            await event.reply(f"{event.sender} have not update permission")
+            return
+
+        # 判断是否是本地ai模型，如果是还需要解析#后的type
+        if argus == 'local_ai':
+            await event.reply("local ai platform has ollama and lmstudio. "
+                              "you can type `!ai use local_ai#{type}`. "
+                              "Example: local_ai#ollama")
+            pass
+        if argus == 'local_ai#ollama' or argus == 'local_ai#lmstudio':
+            if argus == self.config.cur_platform:
+                await event.reply(f"current ai platform has be {argus}")
+                pass
+            else:
+                self.config.cur_platform = argus
+                self.config.cur_model = self.config['platforms'][argus.split("#")[0]]['model']
+                await event.react("✅")
+        # 如果是openai或者是claude
+        elif argus == 'openai' or argus == 'anthropic' or argus == 'xai' or argus == 'deepseek' or argus == 'gemini' or argus == 'qwen':
+            if argus == self.config.cur_platform:
+                await event.reply(f"current ai platform has be {argus}")
+                pass
+            else:
+                self.config.cur_platform = argus
+                # 使用配置的默认模型
+                self.config.cur_model = self.config['platforms'][argus]['model']
+                await event.react("✅")
+        else:
+            await event.reply(f"nof found ai platform: {argus}")
+            pass
+        self.log.debug(f"switch platform: {self.config.cur_platform}")
+        self.log.debug(f"use default config model: {self.config.cur_model}")
 
     @classmethod
     def get_config_class(cls) -> Type[BaseProxyConfig]:

maubot_llmplus/local_paltform.py

@@ -1,24 +1,30 @@
+import asyncio
 import json
+
 from typing import List
 
 from aiohttp import ClientSession
-from maubot import Plugin
+
 from mautrix.types import MessageEvent
 from mautrix.util.config import BaseProxyConfig
 
 import maubot_llmplus
 import maubot_llmplus.platforms
 from maubot_llmplus.platforms import Platform, ChatCompletion
+from maubot_llmplus.plugin import AbsExtraConfigPlugin
+from maubot_llmplus.thrid_platform import _read_openai_sse
 
 
 class Ollama(Platform):
-    chat_api: str
 
-    def __init__(self, config: BaseProxyConfig, name: str, http: ClientSession) -> None:
-        super().__init__(config, name, http)
-        self.chat_api = '/api/chat'
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.streaming = self.config.get('streaming', False)
 
-    async def create_chat_completion(self, plugin: Plugin, evt: MessageEvent) -> ChatCompletion:
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
         full_context = []
         context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
         full_context.extend(list(context))
@@ -27,37 +33,123 @@ class Ollama(Platform):
         req_body = {'model': self.model, 'messages': full_context, 'stream': False}
         headers = {'Content-Type': 'application/json'}
         async with self.http.post(endpoint, headers=headers, json=req_body) as response:
-            # plugin.log.debug(f"响应内容：{response.status}, {await response.json()}")
             if response.status != 200:
                 return ChatCompletion(
+                    result=False,
                     message={},
                     finish_reason=f"http status {response.status}",
                     model=None
                 )
             response_json = await response.json()
             return ChatCompletion(
+                result=True,
                 message=response_json['message'],
                 finish_reason='success',
                 model=response_json['model']
             )
 
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        endpoint = f"{self.url}/api/chat"
+        req_body = {'model': self.model, 'messages': full_context, 'stream': True}
+        headers = {'Content-Type': 'application/json'}
+        async with self.http.post(endpoint, headers=headers, json=req_body) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: http status {response.status}")
+            while True:
+                try:
+                    line_bytes = await asyncio.wait_for(response.content.readline(), timeout=60.0)
+                except asyncio.TimeoutError:
+                    break
+                if not line_bytes:
+                    break
+                line = line_bytes.decode("utf-8").strip()
+                if not line:
+                    continue
+                try:
+                    data = json.loads(line)
+                    if data.get("done"):
+                        break
+                    content = data.get("message", {}).get("content", "")
+                    if content:
+                        yield content
+                except json.JSONDecodeError:
+                    pass
+
     async def list_models(self) -> List[str]:
         full_url = f"{self.url}/api/tags"
         async with self.http.get(full_url) as response:
             if response.status != 200:
                 return []
-            response_data = json.loads(await response.json())
-            return [model['name'] for model in response_data]
+            response_data = await response.json()
+            return [f"- {model['model']}" for model in response_data['models']]
 
     def get_type(self) -> str:
         return "local_ai"
 
 
 class LmStudio(Platform):
+    temperature: int
 
-    def __init__(self, config: BaseProxyConfig, name: str, http: ClientSession) -> None:
-        super().__init__(config, name, http)
-        pass
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.temperature = float(self.config['temperature']) if self.config.get('temperature') is not None else None
+        self.streaming = self.config.get('streaming', False)
 
-    async def create_chat_completion(self, plugin: Plugin, evt: MessageEvent) -> ChatCompletion:
-        pass
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        headers = {"content-type": "application/json"}
+        req_body = {"model": self.model, "messages": full_context, "temperature": self.temperature, "stream": False}
+        async with self.http.post(
+                endpoint, headers=headers, data=json.dumps(req_body)
+        ) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice["finish_reason"],
+                model=choice.get("model", None)
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        headers = {"content-type": "application/json"}
+        req_body = {"model": self.model, "messages": full_context, "temperature": self.temperature, "stream": True}
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(req_body)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            async for chunk in _read_openai_sse(response):
+                yield chunk
+
+    async def list_models(self) -> List[str]:
+        full_url = f"{self.url}/v1/models"
+        async with self.http.get(full_url) as response:
+            if response.status != 200:
+                return []
+            response_data = await response.json()
+            return [f"- {m['id']}" for m in response_data["data"]]
+
+    def get_type(self) -> str:
+        return "local_ai"

maubot_llmplus/platforms.py

@@ -1,12 +1,13 @@
 import json
 from collections import deque
 from datetime import datetime
-from typing import Optional, List, Generator
+from typing import Optional, List, Generator, AsyncIterator
 
 from aiohttp import ClientSession
 from maubot import Plugin
 from mautrix.types import MessageEvent, EncryptedEvent
-from mautrix.util.config import BaseProxyConfig
+
+from maubot_llmplus.plugin import AbsExtraConfigPlugin, Config
 
 """
     AI响应对象
@@ -14,7 +15,8 @@ from mautrix.util.config import BaseProxyConfig
 
 
 class ChatCompletion:
-    def __init__(self, message: dict, finish_reason: str, model: Optional[str]) -> None:
+    def __init__(self, result: bool, message: dict, finish_reason: str, model: Optional[str]) -> None:
+        self.result = result
         self.message = message
         self.finish_reason = finish_reason
         self.model = model
@@ -33,51 +35,57 @@ class Platform:
     additional_prompt: List[dict]
     system_prompt: str
     max_context_messages: int
-    name: str
 
-    def __init__(self, config: BaseProxyConfig, name: str, http: ClientSession) -> None:
+    def __init__(self, config: Config, http: ClientSession) -> None:
         self.http = http
         self.config = config['platforms'][self.get_type()]
         self.url = self.config['url']
-        self.model = self.config['model']
+        # 设置当前的使用模型，这里不直接使用config对象下的配置值，而是加入了与命令决定后的使用模型名称
+        self.model = config.cur_model
         self.max_words = self.config['max_words']
         self.api_key = self.config['api_key']
         self.max_context_messages = self.config['max_context_messages']
         self.additional_prompt = config['additional_prompt']
         self.system_prompt = config['system_prompt']
-        self.name = name
 
     """a
         调用AI对话接口, 响应结果
     """
 
-    async def create_chat_completion(self, plugin: Plugin, evt: MessageEvent) -> ChatCompletion:
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
         raise NotImplementedError()
 
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> AsyncIterator[str]:
+        raise NotImplementedError()
+
+    def is_streaming_enabled(self) -> bool:
+        return False
+
     async def list_models(self) -> List[str]:
         raise NotImplementedError()
 
     def get_type(self) -> str:
         raise NotImplementedError()
 
-
-
-async def get_context(plugin: Plugin, platform: Platform, evt: MessageEvent) -> deque:
+"""
+    获取系统提示上下文
+"""
+async def get_system_context(plugin: AbsExtraConfigPlugin, platform: Platform, evt: MessageEvent) -> deque:
     # 创建系统提示词上下文
     system_context = deque()
     # 生成当前时间
     timestamp = datetime.today().strftime('%Y-%m-%d %H:%M:%S')
     # 加入系统提示词
     system_prompt = {"role": "system",
-                     "content": plugin.config['system_prompt'].format(name=plugin.name, timestamp=timestamp)}
+                     "content": plugin.config['system_prompt'].format(name=plugin.get_bot_name(), timestamp=timestamp)}
     if plugin.config['enable_multi_user']:
         system_prompt["content"] += """
-        User messages are in the context of multiperson chatrooms.
-        Each message indicates its sender by prefixing the message with the sender's name followed by a colon, for example:
-        "username: hello world."
-        In this case, the user called "username" sent the message "hello world.". You should not follow this convention in your responses.
-        your response instead could be "hello username!" without including any colons, because you are the only one sending your responses there is no need to prefix them.
-        """
+            User messages are in the context of multiperson chatrooms.
+            Each message indicates its sender by prefixing the message with the sender's name followed by a colon, for example:
+            "username: hello world."
+            In this case, the user called "username" sent the message "hello world.". You should not follow this convention in your responses.
+            your response instead could be "hello username!" without including any colons, because you are the only one sending your responses there is no need to prefix them.
+            """
     if len(system_prompt["content"]) > 0:
         system_context.append(system_prompt)
 
@@ -89,9 +97,14 @@ async def get_context(plugin: Plugin, platform: Platform, evt: MessageEvent) ->
         # 如果 消息长度已经超过了配置的消息条数，那么就抛出错误
         if len(additional_context) > platform.max_context_messages - 1:
             raise ValueError(f"sorry, my configuration has too many additional prompts "
-                                 f"({platform.max_context_messages}) and i'll never see your message. "
-                                    f"Update my config to have fewer messages and i'll be able to answer your questions!")
+                             f"({platform.max_context_messages}) and i'll never see your message. "
+                             f"Update my config to have fewer messages and i'll be able to answer your questions!")
+    return system_context
 
+"""
+    获取聊天信息上下文
+"""
+async def get_chat_context(system_context: deque, plugin: AbsExtraConfigPlugin, platform: Platform, evt: MessageEvent, hasAssistant: bool=True) -> deque:
     # 用户历史聊天上下文
     chat_context = deque()
     # 计算系统提示词单词数
@@ -105,8 +118,16 @@ async def get_context(plugin: Plugin, platform: Platform, evt: MessageEvent) ->
         except (KeyError, AttributeError):
             continue
 
+        # 如果没有assistant的角色，那么如果当前的对话消息是机器人的，忽略不要
+        if not hasAssistant:
+            if plugin.client.mxid == next_event.sender:
+                continue
+            else :
+                role = 'user'
+        else :
+            role = 'assistant' if plugin.client.mxid == next_event.sender else 'user'
+
         # 如果当前的这条历史消息是机器人自己的，那么角色就要设置为assistant
-        role = 'assistant' if plugin.client.mxid == next_event.sender else 'user'
         message = next_event['content']['body']
         user = ''
         # 如果是允许多用户使用，那么就需要在每个历史消息前加上用户名
@@ -121,11 +142,16 @@ async def get_context(plugin: Plugin, platform: Platform, evt: MessageEvent) ->
             break
         chat_context.appendleft({"role": role, "content": user + message})
 
+    return chat_context
+
+"""
+    获取总消息上下文
+"""
+async def get_context(plugin: AbsExtraConfigPlugin, platform: Platform, evt: MessageEvent, hasAssistant: bool=True) -> deque:
+    system_context = await get_system_context(plugin, platform, evt)
+    chat_context = await get_chat_context(system_context, plugin, platform, evt, hasAssistant)
     return system_context + chat_context
 
-
-
-
 async def generate_context_messages(plugin: Plugin, platform: Platform, evt: MessageEvent) -> Generator[MessageEvent, None, None]:
     yield evt
     if plugin.config['reply_in_thread']:

maubot_llmplus/plugin.py

@@ -0,0 +1,43 @@
+from maubot import Plugin
+from mautrix.util.config import BaseProxyConfig, ConfigUpdateHelper
+
+
+class AbsExtraConfigPlugin(Plugin):
+    default_username: str
+    user_id: str
+
+    async def start(self) -> None:
+        await super().start()
+        self.default_username = await self.client.get_displayname(self.client.mxid)
+        self.user_id = self.client.parse_user_id(self.client.mxid)[0]
+
+    def get_bot_name(self) -> str:
+        return self.config['name'] or \
+            self.default_username or \
+            self.user_id
+
+
+"""
+    配置文件加载
+"""
+
+
+class Config(BaseProxyConfig):
+    cur_model: str
+    cur_platform: str
+
+    def do_update(self, helper: ConfigUpdateHelper) -> None:
+        helper.copy("allowed_users")
+        helper.copy("use_platform")
+        helper.copy("name")
+        helper.copy("reply_in_thread")
+        helper.copy("enable_multi_user")
+        helper.copy("system_prompt")
+        helper.copy("platforms")
+        helper.copy("additional_prompt")
+        helper.copy("allow_update_read_command_users")
+        helper.copy("allow_readonly_command_users")
+
+        self.cur_platform = helper.base['use_platform'] if helper.base['use_platform'] != 'local_ai' else \
+            f"{helper.base['use_platform']}#{helper.base['platforms']['local_ai']['type']}"
+        self.cur_model = helper.base['platforms'][helper.base['use_platform']]['model']

maubot_llmplus/thrid_platform.py

@@ -1,36 +1,648 @@
+import asyncio
+import json
+import logging
+from collections import deque
+
+from typing import List
+
 from aiohttp import ClientSession
-from maubot import Plugin
 from mautrix.types import MessageEvent
 from mautrix.util.config import BaseProxyConfig
 
+import maubot_llmplus.platforms
 from maubot_llmplus.platforms import Platform, ChatCompletion
+from maubot_llmplus.plugin import AbsExtraConfigPlugin
 
 
+async def _read_openai_sse(response):
+    """读取 OpenAI 兼容格式的 SSE 流，yield 每个 delta content"""
+    while True:
+        try:
+            line_bytes = await asyncio.wait_for(response.content.readline(), timeout=60.0)
+        except asyncio.TimeoutError:
+            break
+        if not line_bytes:
+            break
+        line = line_bytes.decode("utf-8").strip()
+        if not line.startswith("data: "):
+            continue
+        data_str = line[6:]
+        if data_str == "[DONE]":
+            break
+        try:
+            data = json.loads(data_str)
+            choices = data.get("choices", [])
+            if choices:
+                content = choices[0].get("delta", {}).get("content", "")
+                if content:
+                    yield content
+        except json.JSONDecodeError:
+            pass
+
+
+
+class Deepseek(Platform):
+
+    def __init__(self, config: BaseProxyConfig, http: ClientSession):
+        super().__init__(config, http)
+        self.streaming = self.config.get('streaming', False)
+
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        data = {
+            "model": self.model,
+            "messages": full_context,
+        }
+
+        endpoint = f"{self.url}/chat/completions"
+        async with self.http.post(
+            endpoint, headers=headers, data=json.dumps(data)
+        ) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice["finish_reason"],
+                model=response_json.get("model", None)
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        data = {
+            "model": self.model,
+            "messages": full_context,
+            "stream": True,
+        }
+
+        endpoint = f"{self.url}/chat/completions"
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(data)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            async for chunk in _read_openai_sse(response):
+                yield chunk
+
+    async def list_models(self) -> List[str]:
+        models = ["deepseek-chat", "deepseek-reasoner"]
+        return [f"- {m}" for m in models]
+
+    def get_type(self) -> str:
+        return "deepseek"
+
 class OpenAi(Platform):
+    max_tokens: int
+    temperature: float
 
-    def __init__(self, config: BaseProxyConfig, name: str, http: ClientSession) -> None:
-        super().__init__(config, name, http)
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.max_tokens = int(self.config['max_tokens']) if self.config.get('max_tokens') else None
+        self.temperature = float(self.config['temperature']) if self.config.get('temperature') is not None else None
+        self.streaming = self.config.get('streaming', False)
 
-    async def create_chat_completion(self, plugin: Plugin, evt: MessageEvent) -> ChatCompletion:
-        # 获取系统提示词
-        # 获取额外的其他角色的提示词： role: user role: system
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
 
-        pass
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        data = {
+            "model": self.model,
+            "messages": full_context,
+        }
+
+        if 'max_tokens' in self.config and self.max_tokens:
+            # 如果是gpt5的，就用max_completion_tokens
+            if 'gpt-5' in self.model:
+                data["max_completion_tokens"] = self.max_tokens
+            else:
+                # 如果是gpt4之前的，就是用max_tokens
+                data["max_tokens"] = self.max_tokens
+
+        if 'temperature' in self.config and self.temperature:
+            data["temperature"] = self.temperature
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        async with self.http.post(
+                endpoint, headers=headers, data=json.dumps(data)
+        ) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice["finish_reason"],
+                model=choice.get("model", None)
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        data = {
+            "model": self.model,
+            "messages": full_context,
+            "stream": True,
+        }
+
+        if 'max_tokens' in self.config and self.max_tokens:
+            if 'gpt-5' in self.model:
+                data["max_completion_tokens"] = self.max_tokens
+            else:
+                data["max_tokens"] = self.max_tokens
+
+        if 'temperature' in self.config and self.temperature:
+            data["temperature"] = self.temperature
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(data)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            async for chunk in _read_openai_sse(response):
+                yield chunk
+
+    async def list_models(self) -> List[str]:
+        # 调用openai接口获取模型列表
+        full_url = f"{self.url}/v1/models"
+        headers = {'Authorization': f"Bearer {self.api_key}"}
+        async with self.http.get(full_url, headers=headers) as response:
+            if response.status != 200:
+                return []
+            response_data = await response.json()
+            return [f"- {m['id']}" for m in response_data["data"]]
 
     def get_type(self) -> str:
         return "openai"
 
 
 class Anthropic(Platform):
+    max_tokens: int
+    streaming: bool
 
-    def __init__(self, config: BaseProxyConfig, name: str, http: ClientSession) -> None:
-        super().__init__(config, name, http)
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.max_tokens = int(self.config['max_tokens']) if self.config.get('max_tokens') else None
+        self.streaming = self.config.get('streaming', False)
 
-    async def create_chat_completion(self, plugin: Plugin, evt: MessageEvent) -> ChatCompletion:
-        # 获取系统提示词
-        # 获取额外的其他角色的提示词： role: user role: system
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
 
-        pass
+    def _build_request(self, full_chat_context: list) -> tuple:
+        endpoint = f"{self.url}/v1/messages"
+        headers = {"x-api-key": self.api_key, "anthropic-version": "2023-06-01", "content-type": "application/json"}
+        req_body = {"model": self.model, "max_tokens": self.max_tokens, "system": self.system_prompt,
+                    "messages": full_chat_context}
+        return endpoint, headers, req_body
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_chat_context = []
+        system_context = deque()
+        chat_context = await maubot_llmplus.platforms.get_chat_context(system_context, plugin, self, evt)
+        full_chat_context.extend(list(chat_context))
+
+        endpoint, headers, req_body = self._build_request(full_chat_context)
+
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(req_body)) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            text = "\n\n".join(c["text"] for c in response_json["content"])
+            return ChatCompletion(
+                result=True,
+                message=dict(role="assistant", content=text),
+                finish_reason=response_json['stop_reason'],
+                model=response_json['model']
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_chat_context = []
+        system_context = deque()
+        chat_context = await maubot_llmplus.platforms.get_chat_context(system_context, plugin, self, evt)
+        full_chat_context.extend(list(chat_context))
+
+        endpoint, headers, req_body = self._build_request(full_chat_context)
+        req_body["stream"] = True
+
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(req_body)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            while True:
+                try:
+                    line_bytes = await asyncio.wait_for(response.content.readline(), timeout=60.0)
+                except asyncio.TimeoutError:
+                    break
+                if not line_bytes:
+                    break
+                line = line_bytes.decode("utf-8").strip()
+                if not line.startswith("data: "):
+                    continue
+                data_str = line[6:]
+                try:
+                    data = json.loads(data_str)
+                    if data.get("type") == "message_stop":
+                        break
+                    if data.get("type") == "content_block_delta":
+                        delta = data.get("delta", {})
+                        if delta.get("type") == "text_delta":
+                            yield delta.get("text", "")
+                except json.JSONDecodeError:
+                    pass
+
+    async def list_models(self) -> List[str]:
+        full_url = f"{self.url}/v1/models"
+        headers = {
+            'anthropic-version': "2023-06-01",
+            'X-Api-Key': f"{self.api_key}"
+        }
+        async with self.http.get(full_url, headers=headers) as response:
+            if response.status != 200:
+                return []
+            response_data = await response.json()
+            return [f"- {m['id']}" for m in response_data['data']]
 
     def get_type(self) -> str:
         return "anthropic"
+
+
+class Gemini(Platform):
+    max_tokens: int
+    temperature: float
+
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.max_tokens = int(self.config['max_tokens']) if self.config.get('max_tokens') else None
+        self.temperature = float(self.config['temperature']) if self.config.get('temperature') is not None else None
+        self.streaming = self.config.get('streaming', False)
+
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    def _build_gemini_request(self, context) -> tuple:
+        system_parts = []
+        contents = []
+        for msg in context:
+            role = msg['role']
+            content = msg['content']
+            if role == 'system':
+                system_parts.append({"text": content})
+            elif role == 'assistant':
+                contents.append({"role": "model", "parts": [{"text": content}]})
+            else:
+                contents.append({"role": "user", "parts": [{"text": content}]})
+
+        request_body = {
+            "contents": contents,
+            "generationConfig": {}
+        }
+
+        if system_parts:
+            request_body["system_instruction"] = {"parts": system_parts}
+
+        if self.max_tokens:
+            request_body["generationConfig"]["maxOutputTokens"] = self.max_tokens
+
+        if self.temperature:
+            request_body["generationConfig"]["temperature"] = self.temperature
+
+        headers = {
+            "Content-Type": "application/json",
+            "x-goog-api-key": self.api_key
+        }
+        return request_body, headers
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        request_body, headers = self._build_gemini_request(context)
+
+        endpoint = f"{self.url}/v1beta/models/{self.model}:generateContent"
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(request_body)) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            candidate = response_json["candidates"][0]
+            text = "".join(part["text"] for part in candidate["content"]["parts"])
+            return ChatCompletion(
+                result=True,
+                message={"role": "assistant", "content": text},
+                finish_reason=candidate.get("finishReason", "STOP"),
+                model=response_json.get("modelVersion", self.model)
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        request_body, headers = self._build_gemini_request(context)
+
+        endpoint = f"{self.url}/v1beta/models/{self.model}:streamGenerateContent?alt=sse"
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(request_body)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            # 与 Anthropic 保持一致：内联 while 循环，避免双层异步生成器代理
+            while True:
+                try:
+                    line_bytes = await asyncio.wait_for(response.content.readline(), timeout=60.0)
+                except asyncio.TimeoutError:
+                    break
+                if not line_bytes:
+                    break
+                line = line_bytes.decode("utf-8").strip()
+                if not line.startswith("data: "):
+                    continue
+                data_str = line[6:]
+                try:
+                    data = json.loads(data_str)
+                    candidates = data.get("candidates", [])
+                    if not candidates:
+                        continue
+                    candidate = candidates[0]
+                    # 先 yield 文本，再判断是否结束（对齐 OpenAI [DONE] 逻辑）
+                    parts = candidate.get("content", {}).get("parts", [])
+                    for part in parts:
+                        text = part.get("text", "")
+                        if text:
+                            yield text
+                    finish_reason = candidate.get("finishReason")
+                    if finish_reason:
+                        logging.getLogger("instance/aibot").debug(
+                            f"Gemini stream finished: finishReason={finish_reason}"
+                        )
+                        break
+                except json.JSONDecodeError:
+                    pass
+
+    async def list_models(self) -> List[str]:
+        full_url = f"{self.url}/v1beta/models"
+        headers = {"x-goog-api-key": self.api_key}
+        async with self.http.get(full_url, headers=headers) as response:
+            if response.status != 200:
+                return []
+            response_data = await response.json()
+            return [
+                f"- {m['name'].replace('models/', '')}"
+                for m in response_data.get("models", [])
+                if "generateContent" in m.get("supportedGenerationMethods", [])
+            ]
+
+    def get_type(self) -> str:
+        return "gemini"
+
+
+class XAi(Platform):
+    max_tokens: int
+    temperature: int
+
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.temperature = float(self.config['temperature']) if self.config.get('temperature') is not None else None
+        self.max_tokens = int(self.config['max_tokens']) if self.config.get('max_tokens') else None
+        self.streaming = self.config.get('streaming', False)
+
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        request_body = {
+            "messages": full_context,
+            "model": self.model,
+            "stream": False
+        }
+
+        if 'max_tokens' in self.config and self.max_tokens:
+            request_body["max_tokens"] = self.max_tokens
+
+        if 'temperature' in self.config and self.temperature:
+            request_body["temperature"] = self.temperature
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        async with self.http.post(url=endpoint, data=json.dumps(request_body), headers=headers) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice["finish_reason"],
+                model=response_json["model"]
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        request_body = {
+            "messages": full_context,
+            "model": self.model,
+            "stream": True,
+        }
+
+        if 'max_tokens' in self.config and self.max_tokens:
+            request_body["max_tokens"] = self.max_tokens
+
+        if 'temperature' in self.config and self.temperature:
+            request_body["temperature"] = self.temperature
+
+        endpoint = f"{self.url}/v1/chat/completions"
+        async with self.http.post(url=endpoint, data=json.dumps(request_body), headers=headers) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            async for chunk in _read_openai_sse(response):
+                yield chunk
+
+    async def list_models(self) -> List[str]:
+        full_url = f"{self.url}/v1/models"
+        headers = {'Content-Type': 'application/json', 'Authorization': f"Bearer {self.api_key}"}
+        async with self.http.get(full_url, headers=headers) as response:
+            if response.status != 200:
+                return []
+            response_data = await response.json()
+            return [f"- {m['id']}" for m in response_data["data"]]
+
+    def get_type(self) -> str:
+        return "xai"
+
+
+class Qwen(Platform):
+    max_tokens: int
+    temperature: float
+    top_p: float
+    enable_thinking: bool
+
+    def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
+        super().__init__(config, http)
+        self.max_tokens = int(self.config['max_tokens']) if self.config.get('max_tokens') else None
+        self.temperature = float(self.config['temperature']) if self.config.get('temperature') is not None else None
+        self.top_p = float(self.config['top_p']) if self.config.get('top_p') is not None else None
+        self.enable_thinking = self.config['enable_thinking']
+        self.streaming = self.config.get('streaming', False)
+
+    def is_streaming_enabled(self) -> bool:
+        return self.streaming
+
+    def _build_qwen_request(self, full_context: list) -> tuple:
+        parameters = {
+            "result_format": "message"
+        }
+        if self.max_tokens:
+            parameters["max_tokens"] = self.max_tokens
+        if self.temperature is not None:
+            parameters["temperature"] = self.temperature
+        if self.top_p is not None:
+            parameters["top_p"] = self.top_p
+        if self.enable_thinking:
+            parameters["enable_thinking"] = True
+
+        request_body = {
+            "model": self.model,
+            "input": {
+                "messages": full_context
+            },
+            "parameters": parameters
+        }
+
+        endpoint = f"{self.url}/api/v1/services/aigc/text-generation/generation"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        return endpoint, headers, request_body
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        endpoint, headers, request_body = self._build_qwen_request(full_context)
+
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(request_body)) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["output"]["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice.get("finish_reason", "stop"),
+                model=response_json.get("model", self.model)
+            )
+
+    async def create_chat_completion_stream(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent):
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        endpoint, headers, request_body = self._build_qwen_request(full_context)
+        # DashScope SSE 流式：增加 header 和 incremental_output 参数（每次只返回增量）
+        headers["X-DashScope-SSE"] = "enable"
+        request_body["parameters"]["incremental_output"] = True
+
+        async with self.http.post(endpoint, headers=headers, data=json.dumps(request_body)) as response:
+            if response.status != 200:
+                raise ValueError(f"Error: {await response.text()}")
+            while True:
+                try:
+                    line_bytes = await asyncio.wait_for(response.content.readline(), timeout=60.0)
+                except asyncio.TimeoutError:
+                    break
+                if not line_bytes:
+                    break
+                line = line_bytes.decode("utf-8").strip()
+                if not line.startswith("data:"):
+                    continue
+                data_str = line[5:].strip()
+                try:
+                    data = json.loads(data_str)
+                    choices = data.get("output", {}).get("choices", [])
+                    if choices:
+                        content = choices[0].get("message", {}).get("content", "")
+                        if content:
+                            yield content
+                except json.JSONDecodeError:
+                    pass
+
+    async def list_models(self) -> List[str]:
+        models = [
+            "qwen-max", "qwen-max-latest",
+            "qwen-plus", "qwen-plus-latest",
+            "qwen-turbo", "qwen-turbo-latest",
+            "qwen-long",
+            "qwen3-235b-a22b", "qwen3-30b-a3b",
+            "qwq-plus", "qwq-plus-latest",
+        ]
+        return [f"- {m}" for m in models]
+
+    def get_type(self) -> str:
+        return "qwen"