chore: release v3.4.1.4

fix: 下载 QQ 图片时的400问题

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -6,26 +6,19 @@ body:
   - type: dropdown
     attributes:
       label: 消息平台适配器
-      description: "连接QQ使用的框架"
+      description: "接入的消息平台类型"
       options:
+        - 其他（或暂未使用）
         - Nakuru（go-cqhttp）
         - aiocqhttp（使用 OneBot 协议接入的）
         - qq-botpy（QQ官方API）
-        - 其他
-    validations:
-      required: false
-  - type: input
-    attributes:
-      label: 运行环境
-      description: 操作系统、系统架构、**Python版本**、**主机地理位置**
-      placeholder: 例如： CentOS x64 Python 3.10.3、Docker 的直接写 Docker 就行
     validations:
       required: true
   - type: input
     attributes:
-      label: LangBot 版本
+      label: 运行环境
-      description: LangBot (QChatGPT) 版本号
+      description: LangBot 版本、操作系统、系统架构、**Python版本**、**主机地理位置**
-      placeholder: 例如：v3.3.0，可以使用`!version`命令查看，或者到 pkg/utils/constants.py 查看
+      placeholder: 例如：v3.3.0、CentOS x64 Python 3.10.3、Docker 的系统直接写 Docker 就行
     validations:
       required: true
   - type: textarea
@@ -34,6 +27,12 @@ body:
       description: 完整描述异常情况，什么时候发生的、发生了什么。**请附带日志信息。** 
     validations:
       required: true
+  - type: textarea
+    attributes:
+      label: 复现步骤
+      description: 如何重现这个问题，越详细越好
+    validations:
+      required: false
   - type: textarea
     attributes:
       label: 启用的插件

README.md

@@ -1,27 +1,16 @@
+> [!IMPORTANT]
+> 我们被人在 X.com 和 pump.fun 上冒充了，以下两个账号利用本项目和作者信息在 X.com 上发布数字货币营销信息，请勿相信！我们已向 X 官方举报！我们从未以 LangBot 名义创建任何社交媒体账号或者数字货币。  
+> We have been impersonated on X.com and pump.fun . The following two accounts are using this project and author information to post digital currency marketing information on X.com. Please do not believe that! We have reported to X official! We have never created any social media account or digital currency under the name LangBot.  
+> 1. https://x.com/RockChinQ
+> 2. https://x.com/LangBotAI
 
 <p align="center">
-<img src="https://docs.langbot.app/langbot-logo-0.5x.png" alt="QChatGPT" width="180" />
+<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
-</p>
+
 <div align="center">
 
-# LangBot
-
 <a href="https://trendshift.io/repositories/6187" target="_blank"><img src="https://trendshift.io/api/badge/repositories/6187" alt="RockChinQ%2FQChatGPT | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
- ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.qchatgpt.rockchin.top%2Fapi%2Fv2%2Fview%2Frealtime%2Fcount_query%3Fminute%3D10080&query=%24.data.count&label=%E4%BD%BF%E7%94%A8%E9%87%8F%EF%BC%887%E6%97%A5%EF%BC%89)
-![Wakapi Count](https://wakapi.rockchin.top/api/badge/RockChinQ/interval:any/project:QChatGPT)
-<br/>
-<img src="https://img.shields.io/badge/python-3.10 | 3.11 | 3.12-blue.svg" alt="python">
-<a href="http://qm.qq.com/cgi-bin/qm/qr?_wv=1027&k=66-aWvn8cbP4c1ut_1YYkvvGVeEtyTH8&authKey=pTaKBK5C%2B8dFzQ4XlENf6MHTCLaHnlKcCRx7c14EeVVlpX2nRSaS8lJm8YeM4mCU&noverify=0&group_code=195992197">
-<img alt="Static Badge" src="https://img.shields.io/badge/%E5%AE%98%E6%96%B9%E7%BE%A4-195992197-purple">
-</a>
-<a href="https://qm.qq.com/q/PClALFK242">
-<img alt="Static Badge" src="https://img.shields.io/badge/%E7%A4%BE%E5%8C%BA%E7%BE%A4-619154800-purple">
-</a>
- 
-## 使用文档
-
 <a href="https://docs.langbot.app">项目主页</a> ｜
 <a href="https://docs.langbot.app/insight/intro.htmll">功能介绍</a> ｜
 <a href="https://docs.langbot.app/insight/guide.html">部署文档</a> ｜
@@ -29,12 +18,67 @@
 <a href="https://docs.langbot.app/plugin/plugin-intro.html">插件介绍</a> ｜
 <a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
 
-## 相关链接
 
-<a href="https://github.com/RockChinQ/qcg-installer">安装器源码</a> ｜
+<div align="center">
-<a href="https://github.com/RockChinQ/qcg-tester">测试工程源码</a> ｜
+😎高稳定、🧩支持扩展、🦄多模态 - 基于大语言模型的即时通讯机器人平台🤖  
-<a href="https://github.com/RockChinQ/qcg-center">遥测服务端源码</a> ｜
+</div>
-<a href="https://github.com/the-lazy-me/QChatGPT-Wiki">官方文档储存库</a>
+
+<br/>
+
+<a href="http://qm.qq.com/cgi-bin/qm/qr?_wv=1027&k=66-aWvn8cbP4c1ut_1YYkvvGVeEtyTH8&authKey=pTaKBK5C%2B8dFzQ4XlENf6MHTCLaHnlKcCRx7c14EeVVlpX2nRSaS8lJm8YeM4mCU&noverify=0&group_code=195992197">
+<img alt="Static Badge" src="https://img.shields.io/badge/%E5%AE%98%E6%96%B9%E7%BE%A4-195992197-green">
+</a>
+<a href="https://qm.qq.com/q/PClALFK242">
+<img alt="Static Badge" src="https://img.shields.io/badge/%E7%A4%BE%E5%8C%BA%E7%BE%A4-619154800-green">
+</a>
+<br/>
+
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
+ ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.qchatgpt.rockchin.top%2Fapi%2Fv2%2Fview%2Frealtime%2Fcount_query%3Fminute%3D10080&query=%24.data.count&label=%E4%BD%BF%E7%94%A8%E9%87%8F%EF%BC%887%E6%97%A5%EF%BC%89)
+<img src="https://img.shields.io/badge/python-3.10 | 3.11 | 3.12-blue.svg" alt="python">
+</div>
+
+</p>
+
+## ✨ Features
+
+- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态能力，并深度适配 [Dify](https://dify.ai)。目前支持 QQ、QQ频道，后续还将支持微信、WhatsApp、Discord等平台。
+- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。
+- 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；丰富生态，目前已有数十个[插件](https://docs.langbot.app/plugin/plugin-intro.html)
+- 😻 [New] Web 管理面板：支持通过浏览器管理 LangBot 实例，具体支持功能，查看[文档](https://docs.langbot.app/webui/intro.html)
+
+## 📦 开始使用
+
+> [!IMPORTANT]
+>
+> 在您开始任何方式部署之前，请务必阅读[新手指引](https://docs.langbot.app/insight/guide.html)。
+
+#### Docker Compose 部署
+
+适合熟悉 Docker 的用户，查看文档[Docker 部署](https://docs.langbot.app/deploy/langbot/docker.html)。
+
+#### 宝塔面板部署
+
+已上架宝塔面板，若您已安装宝塔面板，可以根据[文档](https://docs.langbot.app/deploy/langbot/one-click/bt.html)使用。
+
+#### Zeabur 云部署
+
+社区贡献的 Zeabur 模板。
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+
+#### Railway 云部署
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### 手动部署
+
+直接使用发行版运行，查看文档[手动部署](https://docs.langbot.app/deploy/langbot/manual.html)。
+
+## 📸 效果展示
 
 <img alt="回复效果（带有联网插件）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
-</div>
+
+- WebUI Demo: https://demo.langbot.dev/
+    - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
+    - 注意：仅展示webui效果，公开环境，请不要在其中填入您的任何敏感信息。

libs/dify_service_api/test.py

@@ -10,8 +10,8 @@ class TestDifyClient:
     async def test_chat_messages(self):
         cln = client.AsyncDifyServiceClient(api_key=os.getenv("DIFY_API_KEY"), base_url=os.getenv("DIFY_BASE_URL"))
 
-        resp = await cln.chat_messages(inputs={}, query="Who are you?", user="test")
+        async for chunk in cln.chat_messages(inputs={}, query="调用工具查看现在几点？", user="test"):
-        print(json.dumps(resp, ensure_ascii=False, indent=4))
+            print(json.dumps(chunk, ensure_ascii=False, indent=4))
 
     async def test_upload_file(self):
         cln = client.AsyncDifyServiceClient(api_key=os.getenv("DIFY_API_KEY"), base_url=os.getenv("DIFY_BASE_URL"))
@@ -41,4 +41,4 @@ class TestDifyClient:
         print(json.dumps(chunks, ensure_ascii=False, indent=4))
 
 if __name__ == "__main__":
-    asyncio.run(TestDifyClient().test_workflow_run())
+    asyncio.run(TestDifyClient().test_chat_messages())

libs/dify_service_api/v1/client.py

@@ -26,21 +26,22 @@ class AsyncDifyServiceClient:
         inputs: dict[str, typing.Any],
         query: str,
         user: str,
-        response_mode: str = "blocking",  # 当前不支持 streaming
+        response_mode: str = "streaming",  # 当前不支持 blocking
         conversation_id: str = "",
         files: list[dict[str, typing.Any]] = [],
         timeout: float = 30.0,
-    ) -> dict[str, typing.Any]:
+    ) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
         """发送消息"""
-        if response_mode != "blocking":
+        if response_mode != "streaming":
-            raise DifyAPIError("当前仅支持 blocking 模式")
+            raise DifyAPIError("当前仅支持 streaming 模式")
         
         async with httpx.AsyncClient(
             base_url=self.base_url,
             trust_env=True,
             timeout=timeout,
         ) as client:
-            response = await client.post(
+            async with client.stream(
+                "POST",
                 "/chat-messages",
                 headers={"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"},
                 json={
@@ -51,12 +52,14 @@ class AsyncDifyServiceClient:
                     "conversation_id": conversation_id,
                     "files": files,
                 },
-            )
+            ) as r:
-
+                async for chunk in r.aiter_lines():
-            if response.status_code != 200:
+                    if r.status_code != 200:
-                raise DifyAPIError(f"{response.status_code} {response.text}")
+                        raise DifyAPIError(f"{r.status_code} {chunk}")
-
+                    if chunk.strip() == "":
-            return response.json()
+                        continue
+                    if chunk.startswith("data:"):
+                        yield json.loads(chunk[5:])
         
     async def workflow_run(
         self,
@@ -88,6 +91,8 @@ class AsyncDifyServiceClient:
                 },
             ) as r:
                 async for chunk in r.aiter_lines():
+                    if r.status_code != 200:
+                        raise DifyAPIError(f"{r.status_code} {chunk}")
                     if chunk.strip() == "":
                         continue
                     if chunk.startswith("data:"):
@@ -100,10 +105,6 @@ class AsyncDifyServiceClient:
         timeout: float = 30.0,
     ) -> str:
         """上传文件"""
-        # curl -X POST 'http://dify.rockchin.top/v1/files/upload' \
-        # --header 'Authorization: Bearer {api_key}' \
-        # --form 'file=@localfile;type=image/[png|jpeg|jpg|webp|gif] \
-        # --form 'user=abc-123'
         async with httpx.AsyncClient(
             base_url=self.base_url,
             trust_env=True,

pkg/core/app.py

@@ -143,9 +143,7 @@ class Application:
             self.logger.warning("WebUI 文件缺失，请根据文档获取：https://docs.langbot.app/webui/intro.html")
             return
 
-        import socket
+        host_ip = "127.0.0.1"
-
-        host_ip = socket.gethostbyname(socket.gethostname())
 
         public_ip = await ip.get_myip()
 

pkg/core/migrations/m017_dify_api_timeout_params.py

@@ -0,0 +1,24 @@
+from __future__ import annotations
+
+from .. import migration
+
+
+@migration.migration_class("dify-api-timeout-params", 17)
+class DifyAPITimeoutParamsMigration(migration.Migration):
+    """迁移"""
+
+    async def need_migrate(self) -> bool:
+        """判断当前环境是否需要运行此迁移"""
+        return 'timeout' not in self.ap.provider_cfg.data['dify-service-api']['chat'] or 'timeout' not in self.ap.provider_cfg.data['dify-service-api']['workflow'] \
+            or 'agent' not in self.ap.provider_cfg.data['dify-service-api']
+
+    async def run(self):
+        """执行迁移"""
+        self.ap.provider_cfg.data['dify-service-api']['chat']['timeout'] = 120
+        self.ap.provider_cfg.data['dify-service-api']['workflow']['timeout'] = 120
+        self.ap.provider_cfg.data['dify-service-api']['agent'] = {
+            "api-key": "app-1234567890",
+            "timeout": 120
+        }
+
+        await self.ap.provider_cfg.dump_config()

pkg/core/stages/migrate.py

@@ -7,7 +7,7 @@ from .. import migration
 from ..migrations import m001_sensitive_word_migration, m002_openai_config_migration, m003_anthropic_requester_cfg_completion, m004_moonshot_cfg_completion
 from ..migrations import m005_deepseek_cfg_completion, m006_vision_config, m007_qcg_center_url, m008_ad_fixwin_config_migrate, m009_msg_truncator_cfg
 from ..migrations import m010_ollama_requester_config, m011_command_prefix_config, m012_runner_config, m013_http_api_config, m014_force_delay_config
-from ..migrations import m015_gitee_ai_config, m016_dify_service_api
+from ..migrations import m015_gitee_ai_config, m016_dify_service_api, m017_dify_api_timeout_params
 
 
 @stage.stage_class("MigrationStage")

pkg/pipeline/preproc/preproc.py

@@ -45,7 +45,7 @@ class PreProcessor(stage.PipelineStage):
 
 
         # 检查vision是否启用，没启用就删除所有图片
-        if not self.ap.provider_cfg.data['enable-vision'] or not query.use_model.vision_supported:
+        if not self.ap.provider_cfg.data['enable-vision'] or (self.ap.provider_cfg.data['runner'] == 'local-agent' and not query.use_model.vision_supported):
             for msg in query.messages:
                 if isinstance(msg.content, list):
                     for me in msg.content:
@@ -60,13 +60,13 @@ class PreProcessor(stage.PipelineStage):
                     llm_entities.ContentElement.from_text(me.text)
                 )
             elif isinstance(me, platform_message.Image):
-                if self.ap.provider_cfg.data['enable-vision'] and query.use_model.vision_supported:
+                if self.ap.provider_cfg.data['enable-vision'] and (self.ap.provider_cfg.data['runner'] != 'local-agent' or query.use_model.vision_supported):
-                    if me.url is not None:
+                    if me.base64 is not None:
                         content_list.append(
-                            llm_entities.ContentElement.from_image_url(str(me.url))
+                            llm_entities.ContentElement.from_image_base64(me.base64)
                         )
 
-        query.user_message = llm_entities.Message(  # TODO 适配多模态输入
+        query.user_message = llm_entities.Message(
             role='user',
             content=content_list
         )

pkg/pipeline/process/handlers/chat.py

@@ -91,7 +91,7 @@ class ChatMessageHandler(handler.MessageHandler):
                 query.session.using_conversation.messages.extend(query.resp_messages)
             except Exception as e:
                 
-                self.ap.logger.error(f'对话({query.query_id})请求失败: {str(e)}')
+                self.ap.logger.error(f'对话({query.query_id})请求失败: {type(e).__name__} {str(e)}')
 
                 yield entities.StageProcessResult(
                     result_type=entities.ResultType.INTERRUPT,

pkg/platform/sources/aiocqhttp.py

@@ -6,6 +6,7 @@ import time
 import datetime
 
 import aiocqhttp
+import aiohttp
 
 from .. import adapter
 from ...pipeline.longtext.strategies import forward
@@ -13,12 +14,12 @@ from ...core import app
 from ..types import message as platform_message
 from ..types import events as platform_events
 from ..types import entities as platform_entities
-
+from ...utils import image
 
 class AiocqhttpMessageConverter(adapter.MessageConverter):
 
     @staticmethod
-    def yiri2target(message_chain: platform_message.MessageChain) -> typing.Tuple[list, int, datetime.datetime]:
+    async def yiri2target(message_chain: platform_message.MessageChain) -> typing.Tuple[list, int, datetime.datetime]:
         msg_list = aiocqhttp.Message()
 
         msg_id = 0
@@ -59,7 +60,7 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
             elif type(msg) is forward.Forward:
 
                 for node in msg.node_list:
-                    msg_list.extend(AiocqhttpMessageConverter.yiri2target(node.message_chain)[0])
+                    msg_list.extend((await AiocqhttpMessageConverter.yiri2target(node.message_chain))[0])
                 
             else:
                 msg_list.append(aiocqhttp.MessageSegment.text(str(msg)))
@@ -67,7 +68,7 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
         return msg_list, msg_id, msg_time
 
     @staticmethod
-    def target2yiri(message: str, message_id: int = -1):
+    async def target2yiri(message: str, message_id: int = -1):
         message = aiocqhttp.Message(message)
 
         yiri_msg_list = []
@@ -89,7 +90,8 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
             elif msg.type == "text":
                 yiri_msg_list.append(platform_message.Plain(text=msg.data["text"]))
             elif msg.type == "image":
-                yiri_msg_list.append(platform_message.Image(url=msg.data["url"]))
+                image_base64, image_format = await image.qq_image_url_to_base64(msg.data['url'])
+                yiri_msg_list.append(platform_message.Image(base64=f"data:image/{image_format};base64,{image_base64}"))
 
         chain = platform_message.MessageChain(yiri_msg_list)
 
@@ -99,9 +101,9 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
 class AiocqhttpEventConverter(adapter.EventConverter):
 
     @staticmethod
-    def yiri2target(event: platform_events.Event, bot_account_id: int):
+    async def yiri2target(event: platform_events.Event, bot_account_id: int):
 
-        msg, msg_id, msg_time = AiocqhttpMessageConverter.yiri2target(event.message_chain)
+        msg, msg_id, msg_time = await AiocqhttpMessageConverter.yiri2target(event.message_chain)
 
         if type(event) is platform_events.GroupMessage:
             role = "member"
@@ -164,8 +166,8 @@ class AiocqhttpEventConverter(adapter.EventConverter):
             return aiocqhttp.Event.from_payload(payload)
 
     @staticmethod
-    def target2yiri(event: aiocqhttp.Event):
+    async def target2yiri(event: aiocqhttp.Event):
-        yiri_chain = AiocqhttpMessageConverter.target2yiri(
+        yiri_chain = await AiocqhttpMessageConverter.target2yiri(
             event.message, event.message_id
         )
 
@@ -242,7 +244,7 @@ class AiocqhttpAdapter(adapter.MessageSourceAdapter):
     async def send_message(
         self, target_type: str, target_id: str, message: platform_message.MessageChain
     ):
-        aiocq_msg = AiocqhttpMessageConverter.yiri2target(message)[0]
+        aiocq_msg = (await AiocqhttpMessageConverter.yiri2target(message))[0]
 
         if target_type == "group":
             await self.bot.send_group_msg(group_id=int(target_id), message=aiocq_msg)
@@ -255,8 +257,8 @@ class AiocqhttpAdapter(adapter.MessageSourceAdapter):
         message: platform_message.MessageChain,
         quote_origin: bool = False,
     ):  
-        aiocq_event = AiocqhttpEventConverter.yiri2target(message_source, self.bot_account_id)
+        aiocq_event = await AiocqhttpEventConverter.yiri2target(message_source, self.bot_account_id)
-        aiocq_msg = AiocqhttpMessageConverter.yiri2target(message)[0]
+        aiocq_msg = (await AiocqhttpMessageConverter.yiri2target(message))[0]
         if quote_origin:
             aiocq_msg = aiocqhttp.MessageSegment.reply(aiocq_event.message_id) + aiocq_msg
 
@@ -276,7 +278,7 @@ class AiocqhttpAdapter(adapter.MessageSourceAdapter):
         async def on_message(event: aiocqhttp.Event):
             self.bot_account_id = event.self_id
             try:
-                return await callback(self.event_converter.target2yiri(event), self)
+                return await callback(await self.event_converter.target2yiri(event), self)
             except:
                 traceback.print_exc()
 

pkg/provider/entities.py

@@ -38,6 +38,8 @@ class ContentElement(pydantic.BaseModel):
 
     image_url: typing.Optional[ImageURLContentObject] = None
 
+    image_base64: typing.Optional[str] = None
+
     def __str__(self):
         if self.type == 'text':
             return self.text
@@ -54,6 +56,10 @@ class ContentElement(pydantic.BaseModel):
     def from_image_url(cls, image_url: str):
         return cls(type='image_url', image_url=ImageURLContentObject(url=image_url))
     
+    @classmethod
+    def from_image_base64(cls, image_base64: str):
+        return cls(type='image_base64', image_base64=image_base64)
+
 
 class Message(pydantic.BaseModel):
     """消息"""

pkg/provider/modelmgr/requester.py

@@ -48,6 +48,7 @@ class LLMAPIRequester(metaclass=abc.ABCMeta):
     @abc.abstractmethod
     async def call(
         self,
+        query: core_entities.Query,
         model: modelmgr_entities.LLMModelInfo,
         messages: typing.List[llm_entities.Message],
         funcs: typing.List[tools_entities.LLMFunction] = None,

pkg/provider/modelmgr/requesters/anthropicmsgs.py

@@ -2,8 +2,10 @@ from __future__ import annotations
 
 import typing
 import traceback
+import base64
 
 import anthropic
+import httpx
 
 from .. import entities, errors, requester
 
@@ -21,15 +23,24 @@ class AnthropicMessages(requester.LLMAPIRequester):
     client: anthropic.AsyncAnthropic
 
     async def initialize(self):
+
+        httpx_client = anthropic._base_client.AsyncHttpxClientWrapper(
+            base_url=self.ap.provider_cfg.data['requester']['anthropic-messages']['base-url'],
+            # cast to a valid type because mypy doesn't understand our type narrowing
+            timeout=typing.cast(httpx.Timeout, self.ap.provider_cfg.data['requester']['anthropic-messages']['timeout']),
+            limits=anthropic._constants.DEFAULT_CONNECTION_LIMITS,
+            follow_redirects=True,
+            proxies=self.ap.proxy_mgr.get_forward_proxies()
+        )
+
         self.client = anthropic.AsyncAnthropic(
             api_key="",
-            base_url=self.ap.provider_cfg.data['requester']['anthropic-messages']['base-url'],
+            http_client=httpx_client,
-            timeout=self.ap.provider_cfg.data['requester']['anthropic-messages']['timeout'],
-            proxies=self.ap.proxy_mgr.get_forward_proxies()
         )
 
     async def call(
         self,
+        query: core_entities.Query,
         model: entities.LLMModelInfo,
         messages: typing.List[llm_entities.Message],
         funcs: typing.List[tools_entities.LLMFunction] = None,
@@ -61,24 +72,20 @@ class AnthropicMessages(requester.LLMAPIRequester):
             if isinstance(m.content, str) and m.content.strip() != "":
                 req_messages.append(m.dict(exclude_none=True))
             elif isinstance(m.content, list):
-                # m.content = [
-                #     c for c in m.content if c.type == "text"
-                # ]
-
-                # if len(m.content) > 0:
-                #     req_messages.append(m.dict(exclude_none=True))
 
                 msg_dict = m.dict(exclude_none=True)
 
                 for i, ce in enumerate(m.content):
-                    if ce.type == "image_url":
+
-                        base64_image, image_format = await image.qq_image_url_to_base64(ce.image_url.url)
+                    if ce.type == "image_base64":
+                        image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
+
                         alter_image_ele = {
                             "type": "image",
                             "source": {
                                 "type": "base64",
                                 "media_type": f"image/{image_format}",
-                                "data": base64_image
+                                "data": image_b64
                             }
                         }
                         msg_dict["content"][i] = alter_image_ele

pkg/provider/modelmgr/requesters/chatcmpl.py

@@ -65,6 +65,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
 
     async def _closure(
         self,
+        query: core_entities.Query,
         req_messages: list[dict],
         use_model: entities.LLMModelInfo,
         use_funcs: list[tools_entities.LLMFunction] = None,
@@ -87,8 +88,12 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
         for msg in messages:
             if 'content' in msg and isinstance(msg["content"], list):
                 for me in msg["content"]:
-                    if me["type"] == "image_url":
+                    if me["type"] == "image_base64":
-                        me["image_url"]['url'] = await self.get_base64_str(me["image_url"]['url'])
+                        me["image_url"] = {
+                            "url": me["image_base64"]
+                        }
+                        me["type"] = "image_url"
+                        del me["image_base64"]
 
         args["messages"] = messages
 
@@ -102,6 +107,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
     
     async def call(
         self,
+        query: core_entities.Query,
         model: entities.LLMModelInfo,
         messages: typing.List[llm_entities.Message],
         funcs: typing.List[tools_entities.LLMFunction] = None,
@@ -118,7 +124,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
             req_messages.append(msg_dict)
 
         try:
-            return await self._closure(req_messages, model, funcs)
+            return await self._closure(query, req_messages, model, funcs)
         except asyncio.TimeoutError:
             raise errors.RequesterError('请求超时')
         except openai.BadRequestError as e:
@@ -134,11 +140,3 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
             raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
         except openai.APIError as e:
             raise errors.RequesterError(f'请求错误: {e.message}')
-
-    @async_lru.alru_cache(maxsize=128)
-    async def get_base64_str(
-        self,
-        original_url: str,
-    ) -> str:
-        base64_image, image_format = await image.qq_image_url_to_base64(original_url)
-        return f"data:image/{image_format};base64,{base64_image}"

pkg/provider/modelmgr/requesters/ollamachat.py

@@ -4,6 +4,9 @@ import asyncio
 import os
 import typing
 from typing import Union, Mapping, Any, AsyncIterator
+import uuid
+import json
+import base64
 
 import async_lru
 import ollama
@@ -11,7 +14,7 @@ import ollama
 from .. import entities, errors, requester
 from ... import entities as llm_entities
 from ...tools import entities as tools_entities
-from ....core import app
+from ....core import app, entities as core_entities
 from ....utils import image
 
 REQUESTER_NAME: str = "ollama-chat"
@@ -41,7 +44,7 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
             **args
         )
 
-    async def _closure(self, req_messages: list[dict], use_model: entities.LLMModelInfo,
+    async def _closure(self, query: core_entities.Query, req_messages: list[dict], use_model: entities.LLMModelInfo,
                        user_funcs: list[tools_entities.LLMFunction] = None) -> (
             llm_entities.Message):
         args: Any = self.request_cfg['args'].copy()
@@ -55,30 +58,59 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
                 for me in msg["content"]:
                     if me["type"] == "text":
                         text_content.append(me["text"])
-                    elif me["type"] == "image_url":
+                    elif me["type"] == "image_base64":
-                        image_url = await self.get_base64_str(me["image_url"]['url'])
+                        image_urls.append(me["image_base64"])
-                        image_urls.append(image_url)
+                        
                 msg["content"] = "\n".join(text_content)
                 msg["images"] = [url.split(',')[1] for url in image_urls]
+            if 'tool_calls' in msg:  # LangBot 内部以 str 存储 tool_calls 的参数，这里需要转换为 dict
+                for tool_call in msg['tool_calls']:
+                    tool_call['function']['arguments'] = json.loads(tool_call['function']['arguments'])
         args["messages"] = messages
 
-        resp: Mapping[str, Any] | AsyncIterator[Mapping[str, Any]] = await self._req(args)
+        args["tools"] = []
+        if user_funcs:
+            tools = await self.ap.tool_mgr.generate_tools_for_openai(user_funcs)
+            if tools:
+                args["tools"] = tools
+
+        resp = await self._req(args)
         message: llm_entities.Message = await self._make_msg(resp)
         return message
 
     async def _make_msg(
             self,
-            chat_completions: Union[Mapping[str, Any], AsyncIterator[Mapping[str, Any]]]) -> llm_entities.Message:
+            chat_completions: ollama.ChatResponse) -> llm_entities.Message:
-        message: Any = chat_completions.pop('message', None)
+        message: ollama.Message = chat_completions.message
         if message is None:
             raise ValueError("chat_completions must contain a 'message' field")
 
-        message.update(chat_completions)
+        ret_msg: llm_entities.Message = None
-        ret_msg: llm_entities.Message = llm_entities.Message(**message)
+
+        if message.content is not None:
+            ret_msg = llm_entities.Message(
+                role="assistant",
+                content=message.content
+            )
+        if message.tool_calls is not None and len(message.tool_calls) > 0:
+            tool_calls: list[llm_entities.ToolCall] = []
+
+            for tool_call in message.tool_calls:
+                tool_calls.append(llm_entities.ToolCall(
+                    id=uuid.uuid4().hex,
+                    type="function",
+                    function=llm_entities.FunctionCall(
+                        name=tool_call.function.name,
+                        arguments=json.dumps(tool_call.function.arguments)
+                    )
+                ))
+            ret_msg.tool_calls = tool_calls
+
         return ret_msg
 
     async def call(
             self,
+            query: core_entities.Query,
             model: entities.LLMModelInfo,
             messages: typing.List[llm_entities.Message],
             funcs: typing.List[tools_entities.LLMFunction] = None,
@@ -92,14 +124,6 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
                     msg_dict["content"] = "\n".join(part["text"] for part in content)
             req_messages.append(msg_dict)
         try:
-            return await self._closure(req_messages, model)
+            return await self._closure(query, req_messages, model, funcs)
         except asyncio.TimeoutError:
             raise errors.RequesterError('请求超时')
-
-    @async_lru.alru_cache(maxsize=128)
-    async def get_base64_str(
-            self,
-            original_url: str,
-    ) -> str:
-        base64_image, image_format = await image.qq_image_url_to_base64(original_url)
-        return f"data:image/{image_format};base64,{base64_image}"

pkg/provider/runners/difysvapi.py

@@ -3,6 +3,7 @@ from __future__ import annotations
 import typing
 import json
 import uuid
+import base64
 
 from .. import runner
 from ...core import entities as core_entities
@@ -20,64 +21,170 @@ class DifyServiceAPIRunner(runner.RequestRunner):
 
     async def initialize(self):
         """初始化"""
-        valid_app_types = ['chat', 'workflow']
+        valid_app_types = ["chat", "agent", "workflow"]
-        if self.ap.provider_cfg.data['dify-service-api']['app-type'] not in valid_app_types:
+        if (
-            raise errors.DifyAPIError(f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}")
+            self.ap.provider_cfg.data["dify-service-api"]["app-type"]
+            not in valid_app_types
+        ):
+            raise errors.DifyAPIError(
+                f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}"
+            )
 
-        api_key = self.ap.provider_cfg.data['dify-service-api'][self.ap.provider_cfg.data['dify-service-api']['app-type']]['api-key']
+        api_key = self.ap.provider_cfg.data["dify-service-api"][
+            self.ap.provider_cfg.data["dify-service-api"]["app-type"]
+        ]["api-key"]
 
         self.dify_client = client.AsyncDifyServiceClient(
             api_key=api_key,
-            base_url=self.ap.provider_cfg.data['dify-service-api']['base-url']
+            base_url=self.ap.provider_cfg.data["dify-service-api"]["base-url"],
         )
 
-    async def _preprocess_user_message(self, query: core_entities.Query) -> tuple[str, list[str]]:
+    async def _preprocess_user_message(
+        self, query: core_entities.Query
+    ) -> tuple[str, list[str]]:
         """预处理用户消息，提取纯文本，并将图片上传到 Dify 服务
 
         Returns:
             tuple[str, list[str]]: 纯文本和图片的 Dify 服务图片 ID
         """
-        plain_text = ''
+        plain_text = ""
         image_ids = []
         if isinstance(query.user_message.content, list):
             for ce in query.user_message.content:
-                if ce.type == 'text':
+                if ce.type == "text":
                     plain_text += ce.text
-                elif ce.type == 'image_url':
+                elif ce.type == "image_base64":
-                    file_bytes, image_format = await image.get_qq_image_bytes(ce.image_url.url)
+                    image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
+                    file_bytes = base64.b64decode(image_b64)
                     file = ("img.png", file_bytes, f"image/{image_format}")
-                    file_upload_resp = await self.dify_client.upload_file(file, f"{query.session.launcher_type.value}_{query.session.launcher_id}")
+                    file_upload_resp = await self.dify_client.upload_file(
-                    image_id = file_upload_resp['id']
+                        file,
+                        f"{query.session.launcher_type.value}_{query.session.launcher_id}",
+                    )
+                    image_id = file_upload_resp["id"]
                     image_ids.append(image_id)
         elif isinstance(query.user_message.content, str):
             plain_text = query.user_message.content
 
         return plain_text, image_ids
 
-    async def _chat_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def _chat_messages(
+        self, query: core_entities.Query
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
         """调用聊天助手"""
         cov_id = query.session.using_conversation.uuid or ""
 
         plain_text, image_ids = await self._preprocess_user_message(query)
 
-        files = [{
+        files = [
-            'type': 'image',
+            {
-            'transfer_method': 'local_file',
+                "type": "image",
-            'upload_file_id': image_id,
+                "transfer_method": "local_file",
-        } for image_id in image_ids]
+                "upload_file_id": image_id,
+            }
+            for image_id in image_ids
+        ]
 
-        resp = await self.dify_client.chat_messages(inputs={}, query=plain_text, user=f"{query.session.launcher_type.value}_{query.session.launcher_id}", conversation_id=cov_id, files=files)
+        mode = "basic"  # 标记是基础编排还是工作流编排
 
-        msg = llm_entities.Message(
+        basic_mode_pending_chunk = ''
-            role='assistant',
-            content=resp['answer'],
-        )
 
-        yield msg
+        async for chunk in self.dify_client.chat_messages(
+            inputs={},
+            query=plain_text,
+            user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
+            conversation_id=cov_id,
+            files=files,
+            timeout=self.ap.provider_cfg.data["dify-service-api"]["chat"]["timeout"],
+        ):
+            self.ap.logger.debug("dify-chat-chunk: ", chunk)
 
-        query.session.using_conversation.uuid = resp['conversation_id']
+            if chunk['event'] == 'workflow_started':
+                mode = "workflow"
 
-    async def _workflow_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
+            if mode == "workflow":
+                if chunk['event'] == 'node_finished':
+                    if chunk['data']['node_type'] == 'answer':
+                        yield llm_entities.Message(
+                            role="assistant",
+                            content=chunk['data']['outputs']['answer'],
+                        )
+            elif mode == "basic":
+                if chunk['event'] == 'message':
+                    basic_mode_pending_chunk += chunk['answer']
+                elif chunk['event'] == 'message_end':
+                    yield llm_entities.Message(
+                        role="assistant",
+                        content=basic_mode_pending_chunk,
+                    )
+                    basic_mode_pending_chunk = ''
+
+        query.session.using_conversation.uuid = chunk["conversation_id"]
+
+    async def _agent_chat_messages(
+        self, query: core_entities.Query
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        """调用聊天助手"""
+        cov_id = query.session.using_conversation.uuid or ""
+
+        plain_text, image_ids = await self._preprocess_user_message(query)
+
+        files = [
+            {
+                "type": "image",
+                "transfer_method": "local_file",
+                "upload_file_id": image_id,
+            }
+            for image_id in image_ids
+        ]
+
+        ignored_events = ["agent_message"]
+
+        async for chunk in self.dify_client.chat_messages(
+            inputs={},
+            query=plain_text,
+            user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
+            response_mode="streaming",
+            conversation_id=cov_id,
+            files=files,
+            timeout=self.ap.provider_cfg.data["dify-service-api"]["chat"]["timeout"],
+        ):
+            self.ap.logger.debug("dify-agent-chunk: ", chunk)
+            if chunk["event"] in ignored_events:
+                continue
+            if chunk["event"] == "agent_thought":
+
+                if chunk['tool'] != '' and chunk['observation'] != '':  # 工具调用结果，跳过
+                    continue
+
+                if chunk['thought'].strip() != '':  # 文字回复内容
+                    msg = llm_entities.Message(
+                        role="assistant",
+                        content=chunk["thought"],
+                    )
+                    yield msg
+
+                if chunk['tool']:
+                    msg = llm_entities.Message(
+                        role="assistant",
+                        tool_calls=[
+                            llm_entities.ToolCall(
+                                id=chunk['id'],
+                                type="function",
+                                function=llm_entities.FunctionCall(
+                                    name=chunk["tool"],
+                                    arguments=json.dumps({}),
+                                ),
+                            )
+                        ],
+                    )
+                    yield msg
+
+        query.session.using_conversation.uuid = chunk["conversation_id"]
+
+    async def _workflow_messages(
+        self, query: core_entities.Query
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
         """调用工作流"""
 
         if not query.session.using_conversation.uuid:
@@ -87,58 +194,85 @@ class DifyServiceAPIRunner(runner.RequestRunner):
 
         plain_text, image_ids = await self._preprocess_user_message(query)
 
-        files = [{
+        files = [
-            'type': 'image',
+            {
-            'transfer_method': 'local_file',
+                "type": "image",
-            'upload_file_id': image_id,
+                "transfer_method": "local_file",
-        } for image_id in image_ids]
+                "upload_file_id": image_id,
+            }
+            for image_id in image_ids
+        ]
 
-        ignored_events = ['text_chunk', 'workflow_started']
+        ignored_events = ["text_chunk", "workflow_started"]
 
-        async for chunk in self.dify_client.workflow_run(inputs={
+        async for chunk in self.dify_client.workflow_run(
-            "langbot_user_message_text": plain_text,
+            inputs={
-            "langbot_session_id": f"{query.session.launcher_type.value}_{query.session.launcher_id}",
+                "langbot_user_message_text": plain_text,
-            "langbot_conversation_id": cov_id,
+                "langbot_session_id": f"{query.session.launcher_type.value}_{query.session.launcher_id}",
-        }, user=f"{query.session.launcher_type.value}_{query.session.launcher_id}", files=files):
+                "langbot_conversation_id": cov_id,
-            if chunk['event'] in ignored_events:
+            },
+            user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
+            files=files,
+            timeout=self.ap.provider_cfg.data["dify-service-api"]["workflow"]["timeout"],
+        ):
+            self.ap.logger.debug("dify-workflow-chunk: ", chunk)
+            if chunk["event"] in ignored_events:
                 continue
 
-            if chunk['event'] == 'node_started':
+            if chunk["event"] == "node_started":
 
-                if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end':
+                if (
+                    chunk["data"]["node_type"] == "start"
+                    or chunk["data"]["node_type"] == "end"
+                ):
                     continue
 
                 msg = llm_entities.Message(
-                    role='assistant',
+                    role="assistant",
                     content=None,
-                    tool_calls=[llm_entities.ToolCall(
+                    tool_calls=[
-                        id=chunk['data']['node_id'],
+                        llm_entities.ToolCall(
-                        type='function',
+                            id=chunk["data"]["node_id"],
-                        function=llm_entities.FunctionCall(
+                            type="function",
-                            name=chunk['data']['title'],
+                            function=llm_entities.FunctionCall(
-                            arguments=json.dumps({}),
+                                name=chunk["data"]["title"],
-                        ),
+                                arguments=json.dumps({}),
-                    )],
+                            ),
+                        )
+                    ],
                 )
 
                 yield msg
 
-            elif chunk['event'] == 'workflow_finished':
+            elif chunk["event"] == "workflow_finished":
+                if chunk['data']['error']:
+                    raise errors.DifyAPIError(chunk['data']['error'])
 
                 msg = llm_entities.Message(
-                    role='assistant',
+                    role="assistant",
-                    content=chunk['data']['outputs'][self.ap.provider_cfg.data['dify-service-api']['workflow']['output-key']],
+                    content=chunk["data"]["outputs"][
+                        self.ap.provider_cfg.data["dify-service-api"]["workflow"][
+                            "output-key"
+                        ]
+                    ],
                 )
 
                 yield msg
 
-    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def run(
+        self, query: core_entities.Query
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
         """运行请求"""
-        if self.ap.provider_cfg.data['dify-service-api']['app-type'] == 'chat':
+        if self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "chat":
             async for msg in self._chat_messages(query):
                 yield msg
-        elif self.ap.provider_cfg.data['dify-service-api']['app-type'] == 'workflow':
+        elif self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "agent":
+            async for msg in self._agent_chat_messages(query):
+                yield msg
+        elif self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "workflow":
             async for msg in self._workflow_messages(query):
                 yield msg
         else:
-            raise errors.DifyAPIError(f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}")
+            raise errors.DifyAPIError(
+                f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}"
+            )

pkg/provider/runners/localagent.py

@@ -23,7 +23,7 @@ class LocalAgentRunner(runner.RequestRunner):
         req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
 
         # 首次请求
-        msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+        msg = await query.use_model.requester.call(query, query.use_model, req_messages, query.use_funcs)
 
         yield msg
 
@@ -61,7 +61,7 @@ class LocalAgentRunner(runner.RequestRunner):
                     req_messages.append(err_msg)
 
             # 处理完所有调用，再次请求
-            msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+            msg = await query.use_model.requester.call(query, query.use_model, req_messages, query.use_funcs)
 
             yield msg
 

pkg/utils/constants.py

@@ -1,4 +1,4 @@
-semantic_version = "v3.4.1"
+semantic_version = "v3.4.1.4"
 
 debug_mode = False
 

pkg/utils/image.py

@@ -1,9 +1,11 @@
 import base64
 import typing
+import io
 from urllib.parse import urlparse, parse_qs
 import ssl
 
 import aiohttp
+import PIL.Image
 
 
 def get_qq_image_downloadable_url(image_url: str) -> tuple[str, dict]:
@@ -13,9 +15,10 @@ def get_qq_image_downloadable_url(image_url: str) -> tuple[str, dict]:
     return f"http://{parsed.netloc}{parsed.path}", query
 
 
-async def get_qq_image_bytes(image_url: str) -> tuple[bytes, str]:
+async def get_qq_image_bytes(image_url: str, query: dict={}) -> tuple[bytes, str]:
-    """获取QQ图片的bytes"""
+    """[弃用]获取QQ图片的bytes"""
-    image_url, query = get_qq_image_downloadable_url(image_url)
+    image_url, query_in_url = get_qq_image_downloadable_url(image_url)
+    query = {**query, **query_in_url}
     ssl_context = ssl.create_default_context()
     ssl_context.check_hostname = False
     ssl_context.verify_mode = ssl.CERT_NONE
@@ -24,8 +27,11 @@ async def get_qq_image_bytes(image_url: str) -> tuple[bytes, str]:
             resp.raise_for_status()
             file_bytes = await resp.read()
             content_type = resp.headers.get('Content-Type')
-            if not content_type or not content_type.startswith('image/'):
+            if not content_type:
                 image_format = 'jpeg'
+            elif not content_type.startswith('image/'):
+                pil_img = PIL.Image.open(io.BytesIO(file_bytes))
+                image_format = pil_img.format.lower()
             else: 
                 image_format = content_type.split('/')[-1]
             return file_bytes, image_format
@@ -34,7 +40,7 @@ async def get_qq_image_bytes(image_url: str) -> tuple[bytes, str]:
 async def qq_image_url_to_base64(
     image_url: str
 ) -> typing.Tuple[str, str]:
-    """将QQ图片URL转为base64，并返回图片格式
+    """[弃用]将QQ图片URL转为base64，并返回图片格式
 
     Args:
         image_url (str): QQ图片URL
@@ -47,8 +53,18 @@ async def qq_image_url_to_base64(
     # Flatten the query dictionary
     query = {k: v[0] for k, v in query.items()}
 
-    file_bytes, image_format = await get_qq_image_bytes(image_url)
+    file_bytes, image_format = await get_qq_image_bytes(image_url, query)
 
     base64_str = base64.b64encode(file_bytes).decode()
 
     return base64_str, image_format
+
+async def extract_b64_and_format(image_base64_data: str) -> typing.Tuple[str, str]:
+    """提取base64编码和图片格式
+    
+    data:image/jpeg;base64,xxx
+    提取出base64编码和图片格式
+    """
+    base64_str = image_base64_data.split(',')[-1]
+    image_format = image_base64_data.split(':')[-1].split(';')[0].split('/')[-1]
+    return base64_str, image_format

pkg/utils/ip.py

@@ -2,7 +2,7 @@ import aiohttp
 
 async def get_myip() -> str:
     try:
-        async with aiohttp.ClientSession() as session:
+        async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=10)) as session:
             async with session.get("https://ip.useragentinfo.com/myip") as response:
                 return await response.text()
     except Exception as e:

pkg/utils/pkgmgr.py

@@ -22,13 +22,3 @@ def install_requirements(file):
     pipmain(['install', '-r', file, "-i", "https://pypi.tuna.tsinghua.edu.cn/simple",
                     "--trusted-host", "pypi.tuna.tsinghua.edu.cn"])
     # log.reset_logging()
-
-
-if __name__ == "__main__":
-    try:
-        install("openai11")
-    except Exception as e:
-        print(111)
-        print(e)
-
-    print(222)

requirements.txt

@@ -1,3 +1,4 @@
+# direct
 requests
 openai>1.0.0
 anthropic
@@ -23,3 +24,6 @@ aiofiles
 aioshutil
 argon2-cffi
 pyjwt
+
+# indirect
+taskgroup==0.0.0a4

templates/provider.json

@@ -62,11 +62,17 @@
         "base-url": "https://api.dify.ai/v1",
         "app-type": "chat",
         "chat": {
-            "api-key": "app-1234567890"
+            "api-key": "app-1234567890",
+            "timeout": 120
+        },
+        "agent": {
+            "api-key": "app-1234567890",
+            "timeout": 120
         },
         "workflow": {
             "api-key": "app-1234567890",
-            "output-key": "summary"
+            "output-key": "summary",
+            "timeout": 120
         }
     }
 }

templates/schema/provider.json

@@ -255,6 +255,24 @@
                         "api-key": {
                             "type": "string",
                             "title": "API 密钥"
+                        },
+                        "timeout": {
+                            "type": "number",
+                            "title":"API 请求超时时间"
+                        }
+                    }
+                },
+                "agent": {
+                    "type": "object",
+                    "title": "Agent API 参数",
+                    "properties": {
+                        "api-key": {
+                            "type": "string",
+                            "title": "API 密钥"
+                        },
+                        "timeout": {
+                            "type": "number",
+                            "title":"API 请求超时时间"
                         }
                     }
                 },
@@ -271,6 +289,10 @@
                             "title": "工作流输出键",
                             "description": "设置工作流输出键，用于从 Dify Workflow 结束节点返回的 JSON 数据中提取输出内容",
                             "default": "summary"
+                        },
+                        "timeout": {
+                            "type": "number",
+                            "title": "API 请求超时时间"
                         }
                     }
                 }