feat(lzwcai-demp-tool-server-dify-to-mcp): 初始化 Dify 集成工具模块

新增 Dify 到 MCP 的集成工具，支持通过 Dify API 将模型部署到 MCP 平台并进行推理。
该模块包含完整的服务器实现、依赖配置和命令行启动脚本。

主要功能：
- 支持 Workflow 和 Completion 模式的调用
- 自动翻译工具名称为驼峰命名格式
- 提供文件上传与任务停止接口
- 兼容流式与非流式响应处理

README.md

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+# lzwcai-mcp-server-package
+
+MCP (Model Context Protocol) 服务器工具集，为 AI 助手提供企业级业务能力扩展。
+
+## 📦 包含模块
+
+| 模块 | 版本 | 说明 |
+|------|------|------|
+| [lzwcai-mcp-iot](./lzwcai_mcp_iot) | 0.3.3 | IoT 设备控制服务器，支持设备查询、定位和控制 |
+| [lzwcai-mcp-sqlexecutor](./lzwcai_mcp_sqlexecutor) | 0.1.8 | SQL 查询执行服务器，支持动态工具生成 |
+| [lzwcai-mcp-api-converter](./lzwcai_mcp_api_converter) | 0.1.30 | API 转换服务器，将业务 API 转换为 MCP 工具 |
+| [lzwcai-demp-tool-server-dify-to-mcp](./lzwcai_demp_tool_server_dify_to_mcp) | 0.1.4 | Dify 集成工具，将 Dify 模型部署到 MCP |
+| [lzwcai-demp-tool-server-dify-to-mcp-test](./lzwcai_demp_tool_server_dify_to_mcp_test) | 0.1.0 | Dify 集成工具测试版 |
+
+## 🚀 快速安装
+
+```bash
+# IoT 设备控制
+pip install lzwcai-mcp-iot
+
+# SQL 查询执行
+pip install lzwcai-mcp-sqlexecutor
+
+# API 转换器
+pip install lzwcai-mcp-api-converter
+
+# Dify 集成
+pip install lzwcai-demp-tool-server-dify-to-mcp
+```
+
+## <20>️ 打包 与发布
+
+```bash
+# 进入子模块目录
+cd lzwcai_mcp_iot
+
+# 使用 uv 打包
+uv build
+
+# 上传到管理端技能广场
+# 将 dist/ 目录下的 .tar.gz 文件上传至技能广场
+```
+
+## 🔧 MCP 客户端配置示例
+
+```json
+{
+  "mcpServers": {
+    "iot": {
+      "command": "lzwcai-mcp-iot"
+    },
+    "sql": {
+      "command": "lzwcai-mcp-sqlexecutor"
+    },
+    "api": {
+      "command": "lzwcai-mcp-api-converter"
+    }
+  }
+}
+```
+
+## 📄 许可证
+
+专有软件 - 版权所有 © LZWCAI开发团队
+
+## 📧 联系方式
+
+- 邮箱：dev@lzwcai.com

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/PKG-INFO

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+Metadata-Version: 2.4
+Name: lzwcai-demp-tool-server-dify-to-mcp
+Version: 0.1.0
+Summary: 这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。
+Requires-Python: >=3.10
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: mcp>=1.1.2
+Requires-Dist: omegaconf>=2.3.0
+Requires-Dist: pip>=24.3.1
+Requires-Dist: python-dotenv>=1.0.1
+Requires-Dist: requests
+Requires-Dist: pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/README.md

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+# lzwcai-mcp-server-package
+
+#### 介绍
+lzwcai-mcp-server-package
+
+#### 软件架构
+软件架构说明
+
+
+#### 安装教程
+
+1.  xxxx
+2.  xxxx
+3.  xxxx
+
+#### 使用说明
+
+1.  xxxx
+2.  xxxx
+3.  xxxx
+
+#### 参与贡献
+
+1.  Fork 本仓库
+2.  新建 Feat_xxx 分支
+3.  提交代码
+4.  新建 Pull Request
+
+
+#### 特技
+
+1.  使用 Readme\_XXX.md 来支持不同的语言，例如 Readme\_en.md, Readme\_zh.md
+2.  Gitee 官方博客 [blog.gitee.com](https://blog.gitee.com)
+3.  你可以 [https://gitee.com/explore](https://gitee.com/explore) 这个地址来了解 Gitee 上的优秀开源项目
+4.  [GVP](https://gitee.com/gvp) 全称是 Gitee 最有价值开源项目，是综合评定出的优秀开源项目
+5.  Gitee 官方提供的使用手册 [https://gitee.com/help](https://gitee.com/help)
+6.  Gitee 封面人物是一档用来展示 Gitee 会员风采的栏目 [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/PKG-INFO

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+Metadata-Version: 2.4
+Name: lzwcai-demp-tool-server-dify-to-mcp
+Version: 0.1.4
+Summary: 这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。
+Requires-Python: >=3.10
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: mcp>=1.1.2
+Requires-Dist: omegaconf>=2.3.0
+Requires-Dist: pip>=24.3.1
+Requires-Dist: python-dotenv>=1.0.1
+Requires-Dist: requests
+Requires-Dist: pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/SOURCES.txt

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+README.md
+pyproject.toml
+setup.cfg
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/PKG-INFO
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/SOURCES.txt
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/dependency_links.txt
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/entry_points.txt
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/requires.txt
+lzwcai_demp_tool_server_dify_to_mcp.egg-info/top_level.txt
+src/__init__.py
+src/create_mcp.py
+src/create_mcp_util.py
+src/chat/__init__.py
+src/chat/chat_server.py
+src/completion/completion_server.py
+src/completion/test.py
+src/core/__init__.py
+src/core/core_server.py
+src/difyTaskCall/task_instance.py
+src/utils/tool_translation.py
+src/utils/translator.py
+src/workflow/__init__.py
+src/workflow/workflow_server.py

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/entry_points.txt

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+[console_scripts]
+lzwcai-demp-tool-server-dify-to-mcp = src.create_mcp:run_main

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/requires.txt

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+httpx>=0.28.1
+mcp>=1.1.2
+omegaconf>=2.3.0
+pip>=24.3.1
+python-dotenv>=1.0.1
+requests
+pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp.egg-info/top_level.txt

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+src

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/main.py

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+#!/usr/bin/env python3
+"""
+主入口文件
+用于启动 Dify MCP 服务器，并配置命令行参数
+"""
+import os
+import sys
+
+# Mock 配置参数
+def setup_mock_arguments():
+    """
+    设置模拟命令行参数
+    这些参数可以根据实际需求进行修改
+    """
+    # 默认配置
+    default_config = {
+        "base_url": "http://192.168.2.236:3001/v1",
+        "app_sks": ["app-YFHByB4whARWVqXN2LcuPudq"],
+        "mode_type": "workflow",
+        "transport": "stdio"
+    }
+    
+    # 如果没有提供命令行参数，则添加默认参数
+    if len(sys.argv) == 1:
+        sys.argv.extend([
+            "--base-url", default_config["base_url"],
+            "--app-sks", *default_config["app_sks"],
+            "--mode-type", default_config["mode_type"]
+        ])
+    
+    return default_config
+
+
+def main():
+    """
+    主函数：设置命令行参数并启动服务器
+    """
+    # 设置模拟命令行参数
+    config = setup_mock_arguments()
+    
+    # 导入并运行 MCP 服务器
+    try:
+        from src.create_mcp import run_main
+        
+        # 获取传输模式
+        transport_mode = config.get("transport", "stdio")
+        
+        # 运行服务器（不输出额外信息，避免干扰 STDIO 通信）
+        run_main(transport=transport_mode)
+        
+    except ImportError as e:
+        print(f"[ERROR] 导入错误: {e}", file=sys.stderr)
+        print("请确保已正确安装所有依赖包", file=sys.stderr)
+        sys.exit(1)
+    except Exception as e:
+        print(f"[ERROR] 运行错误: {e}", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/pyproject.toml

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+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "lzwcai-demp-tool-server-dify-to-mcp"
+version = "0.1.4"
+description = "这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。"
+requires-python = ">=3.10"
+dependencies = [
+    "httpx>=0.28.1",
+    "mcp>=1.1.2",
+    "omegaconf>=2.3.0",
+    "pip>=24.3.1",
+    "python-dotenv>=1.0.1",
+    "requests",
+    "pypinyin>=0.54.0",
+]
+
+[tool.setuptools]
+packages = {find = {where = ["."], include = ["src*"]}}
+include-package-data = true
+
+[project.scripts]
+lzwcai-demp-tool-server-dify-to-mcp = "src.create_mcp:run_main"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.setuptools.package-data]
+"*" = ["*.env"]
+"src" = ["**/*.env"] 

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/setup.cfg

@@ -0,0 +1,4 @@
+[egg_info]
+tag_build = 
+tag_date = 0
+

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/chat/chat_server.py

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+class ChatDifyAPI:
+    def __init__(self, base_url: str, app_sks: str):
+        self.base_url = base_url
+        self.app_sks = app_sks
+
+    def process_task(self, task_id: str, **kwargs):
+        pass

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/completion/completion_server.py

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+import requests
+from abc import ABC
+import logging
+import json
+import re
+import pypinyin
+
+logger = logging.getLogger(__name__)
+
+
+def pinyin_to_camel(pinyin):
+    """
+    将拼音列表转换为驼峰命名
+    例如: ['ni', 'hao', 'a'] -> 'NiHaoA'
+    所有非字母数字字符会被替换为下划线
+    """
+    # 使用正则表达式将所有非字母数字字符（包括所有标点符号）替换为下划线
+    cleaned = re.sub(r'[^\w\s]', '_', pinyin)
+    # 将空格也替换为下划线
+    cleaned = re.sub(r'\s+', '_', cleaned)
+    # 移除连续的下划线并去除首尾下划线
+    cleaned = re.sub(r'_+', '_', cleaned).strip('_')
+    
+    # 转换为拼音并生成驼峰命名
+    pinyin_list = pypinyin.lazy_pinyin(cleaned)
+    return "tool_" + "".join(word.capitalize() for word in pinyin_list)
+
+
+class CompletionDifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        userId="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/completion-messages"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": userId,
+        }
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+
+        if response_mode == "streaming":
+            response = requests.post(url, headers=headers, json=data, stream=True)
+
+            # 处理流式响应
+            full_answer = ""
+            for line in response.iter_lines():
+                if line:
+                    # 跳过 "data:" 前缀
+                    decoded_line = line.decode("utf-8")
+                    if decoded_line.startswith("data:"):
+                        try:
+                            json_str = decoded_line[5:].strip()
+                            data = json.loads(json_str)
+                            if data.get("event") == "message" and "answer" in data:
+                                # 累积完整答案
+                                full_answer += data["answer"]
+                                # 这里也可以选择处理每个部分响应，例如返回生成器
+                                # yield data
+                        except json.JSONDecodeError:
+                            logger.warning(f"无法解析JSON数据: {decoded_line}")
+
+            # 创建一个符合非流式响应格式的结果
+            response_data = {"answer": full_answer}
+            # 处理可能包含代码块的数据
+            processed_data = self.process_answer_code_block(response_data)
+            return processed_data
+        else:
+            response = requests.post(url, headers=headers, json=data)
+            response_data = response.json()
+            # 处理可能包含代码块的数据
+            processed_data = self.process_answer_code_block(response_data)
+            return processed_data
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        # params = {"user": user}
+        response = requests.get(url, headers=headers)
+        response.raise_for_status()
+
+        response_map = response.json()
+        # 翻译工具名称
+        from src.utils.tool_translation import TranslationService
+
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+
+        # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # if tool_description:
+        #     translated_description = TranslationService.translate_tool_description(
+        #         tool_description
+        #     )
+        #     response_map["description"] = (
+        #         f"{tool_description} ({translated_description})"
+        #     )
+
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        return {
+            "user_input_form": [
+                {"string": {"variable": "query", "label": "查询内容", "required": True}}
+            ]
+        }
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    @staticmethod
+    def process_answer_code_block(data):
+        try:
+            # 获取answer字段
+            answer = data.get("answer", "")
+
+            # 构造符合workflow_finished格式的输出
+            formatted_response = [
+                {"event": "workflow_finished", "data": {"outputs": {"result": answer}}}
+            ]
+
+            # 尝试处理可能的代码块
+            if answer.startswith("```") and answer.endswith("```"):
+                try:
+                    # 移除代码块标记并解析JSON
+                    code_content = answer.strip("```").strip()
+                    json_data = json.loads(code_content)
+
+                    # 如果包含description字段，用它替换answer
+                    if "description" in json_data:
+                        formatted_response[0]["data"]["outputs"]["result"] = json_data[
+                            "description"
+                        ]
+                except json.JSONDecodeError:
+                    # 如果不是有效的JSON，保留原始代码块内容
+                    pass
+
+            return formatted_response
+        except Exception as e:
+            logger.warning(f"处理答案代码块时出错: {str(e)}")
+            # 发生错误时返回符合格式的基础响应
+            return [
+                {
+                    "event": "workflow_finished",
+                    "data": {
+                        "outputs": {
+                            "error": str(e),
+                            "fallback": data.get("answer", str(data)),
+                        }
+                    },
+                }
+            ]

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/completion/test.py

@@ -0,0 +1,104 @@
+import requests
+from abc import ABC
+import logging
+import json
+
+logger = logging.getLogger(__name__)
+
+res = {
+    "event": "message",
+    "task_id": "49c9ea1b-7b43-475b-a680-d769fb238a45",
+    "id": "432ab98e-5e36-4a29-abe5-e01281c3678c",
+    "message_id": "432ab98e-5e36-4a29-abe5-e01281c3678c",
+    "mode": "completion",
+    "answer": '```\n{\n  "description": "该API的具体功能描述暂时不明确，因为提供的API信息 \'今天打老虎啊按时啊啊\' 并不是有效的API名称或描述。请提供正确的API名称和相关输入输出信息，以便我能为其补充完善的API描述。"\n}\n```',
+    "metadata": {
+        "usage": {
+            "prompt_tokens": 73,
+            "prompt_unit_price": "0.0",
+            "prompt_price_unit": "0.0",
+            "prompt_price": "0.0",
+            "completion_tokens": 61,
+            "completion_unit_price": "0.0",
+            "completion_price_unit": "0.0",
+            "completion_price": "0.0",
+            "total_tokens": 134,
+            "total_price": "0.0",
+            "currency": "USD",
+            "latency": 1.896302318200469,
+        }
+    },
+    "created_at": 1747233054,
+}
+
+
+def process_answer_code_block(data):
+    try:
+        # 获取answer字段
+        answer = data.get("answer", "")
+
+        # 检查answer是否是代码块格式
+        if answer.startswith("```") and answer.endswith("```"):
+            # 移除代码块标记并解析JSON
+            code_content = answer.strip("```").strip()
+            json_data = json.loads(code_content)
+
+            # 获取description字段
+            if "description" in json_data:
+                return json_data["description"]
+
+        # 如果不是预期格式，则返回原始answer
+        return data.get("answer", data)
+    except Exception as e:
+        logger.warning(f"处理答案代码块时出错: {str(e)}")
+        # 发生错误时返回原始数据
+        return data.get("answer", data)
+
+
+def chat_message_test(
+    api_key,
+    inputs={},
+    response_mode="blocking",
+    conversation_id=None,
+    userId="pp666",
+    files=None,
+):
+    url = "https://ops.lzwcai.com/v1/completion-messages"
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json",
+    }
+    data = {
+        "inputs": inputs,
+        "response_mode": response_mode,
+        "user": userId,
+    }
+    if conversation_id:
+        data["conversation_id"] = conversation_id
+    if response_mode == "streaming":
+        response = requests.post(
+            url, headers=headers, json=data, stream=response_mode == "streaming"
+        )
+        return response
+    else:
+        response = requests.post(url, headers=headers, json=data)
+        return response.json()
+
+
+if __name__ == "__main__":
+    print("开始执行主程序")
+    try:
+        print("准备调用chat_message方法")
+        res = chat_message_test(
+            api_key="app-Ppemii3c0ROPoLvRwskgZ7Il",
+            inputs={"query": "今天打老虎啊按时啊啊"},
+            response_mode="streaming",
+            userId="abc-123",
+        )
+        print("chat_message方法调用完成")
+
+        # 打印响应内容
+        print("响应内容:", res)
+        # print(process_answer_code_block(res))
+    except Exception as e:
+        print(f"执行过程中出现错误: {e}")

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/core/core_server.py

@@ -0,0 +1,172 @@
+import requests
+from abc import ABC
+import logging
+import json
+import re
+import pypinyin
+
+logger = logging.getLogger(__name__)
+
+
+def pinyin_to_camel(pinyin):
+    """
+    将拼音列表转换为驼峰命名
+    例如: ['ni', 'hao', 'a'] -> 'NiHaoA'
+    所有非字母数字字符会被替换为下划线
+    """
+    # 使用正则表达式将所有非字母数字字符（包括所有标点符号）替换为下划线
+    cleaned = re.sub(r'[^\w\s]', '_', pinyin)
+    # 将空格也替换为下划线
+    cleaned = re.sub(r'\s+', '_', cleaned)
+    # 移除连续的下划线并去除首尾下划线
+    cleaned = re.sub(r'_+', '_', cleaned).strip('_')
+    
+    # 转换为拼音并生成驼峰命名
+    pinyin_list = pypinyin.lazy_pinyin(cleaned)
+    return "tool_" + "".join(word.capitalize() for word in pinyin_list)
+
+
+class DifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        print("dify_app_params", dify_app_params)
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        user="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/workflows/run"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": user,
+        }
+        logger.info("Sending data to Dify API: %s", data)
+        logger.info("Sending headers to Dify API: %s", headers)
+        logger.info("Sending url to Dify API: %s", url)
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+        if files:
+            files_data = []
+            for file_info in files:
+                file_path = file_info.get("path")
+                transfer_method = file_info.get("transfer_method")
+                if transfer_method == "local_file":
+                    files_data.append(("file", open(file_path, "rb")))
+                elif transfer_method == "remote_url":
+                    pass
+            response = requests.post(
+                url,
+                headers=headers,
+                data=data,
+                files=files_data,
+                stream=response_mode == "streaming",
+            )
+        else:
+            response = requests.post(
+                url, headers=headers, json=data, stream=response_mode == "streaming"
+            )
+        response.raise_for_status()
+        if response_mode == "streaming":
+            for line in response.iter_lines():
+                if line:
+                    if line.startswith(b"data:"):
+                        try:
+                            json_data = json.loads(line[5:].decode("utf-8"))
+                            yield json_data
+                        except json.JSONDecodeError:
+                            print(f"Error decoding JSON: {line}")
+        else:
+            return response.json()
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+
+        from src.utils.tool_translation import TranslationService
+
+        response_map = response.json()
+        # 翻译工具名称
+        # tool_name = response_map.get("name")
+        # translated_name = TranslationService.translate_tool_name(tool_name)
+        # response_map["name"] = translated_name
+        # # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # translated_description = TranslationService.translate_tool_description(
+        #     tool_description
+        # )
+        # response_map["description"] = translated_description
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/parameters"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/create_mcp.py

@@ -0,0 +1,318 @@
+import asyncio
+import json
+import os
+import logging
+import argparse
+from abc import ABC
+
+import mcp.server.stdio
+import mcp.types as types
+import requests
+from mcp.server import NotificationOptions, Server
+from mcp.server.models import InitializationOptions
+from omegaconf import OmegaConf
+
+# from src.workflow.workflow_server import WorkflowDifyAPI
+from src.difyTaskCall.task_instance import TaskInstance
+
+# 配置日志记录
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger(__name__)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Dify MCP服务器配置")
+    parser.add_argument(
+        "--base-url",
+        type=str,
+        help="API基础URL",
+        default="http://192.168.11.24:3001/v1",
+    )
+    parser.add_argument(
+        "--app-sks",
+        nargs="+",
+        help="应用秘钥列表",
+        default=["app-d7s00CJ2NY4LJzUEiZsVDnPN"],
+    )
+    parser.add_argument(
+        "--mode-type",
+        type=str,
+        help="Dify应用模式类型 (workflow, chat, completion)",
+        default="workflow",
+        choices=["workflow", "chat", "completion"],
+    )
+    return parser.parse_args()
+
+
+def get_app_info(base_url=None, app_sks=None, mode_type=None):
+    # 获取命令行参数
+    args = parse_arguments()
+    # 命令行参数优先，其次是函数参数，最后是默认值
+    if args.base_url is not None:
+        base_url = args.base_url
+    if base_url is None:
+        base_url = "http://192.168.11.24:3001/v1"
+
+    if args.app_sks is not None:
+        app_sks = args.app_sks
+    if app_sks is None:
+        app_sks = ["app-d7s00CJ2NY4LJzUEiZsVDnPN"]
+    
+    # 确保 app_sks 始终是列表类型
+    if isinstance(app_sks, str):
+        # 如果是字符串，转换为列表
+        app_sks = [app_sks]
+
+    if args.mode_type is not None:
+        mode_type = args.mode_type
+    if mode_type is None:
+        mode_type = "workflow"
+    return base_url, app_sks, mode_type
+    # return "https://dempdify.lzwcai.com/v1", ["app-X6wAy5nkvWB3hR69cgvIjC3r"], "workflow"
+
+
+
+# 初始化服务器和Dify API
+base_url, dify_app_sks, dify_app_mode_type = get_app_info()
+server = Server("dify_mcp_server")
+task_instance = TaskInstance(base_url, dify_app_sks, dify_app_mode_type)
+dify_api = task_instance.get_task_instance(dify_app_mode_type)
+
+
+def process_user_input_form(user_input_form):
+    """
+    处理Dify应用的用户输入表单，转换为JSON Schema格式
+
+    参数:
+        user_input_form: Dify应用的用户输入表单配置
+
+    返回:
+        处理后的inputSchema字典
+    """
+    inputSchema = dict(
+        type="object",
+        properties={},
+        required=[],
+    )
+
+    property_num = len(user_input_form)
+    if property_num > 0:
+        for j in range(property_num):
+            param = user_input_form[j]
+            param_type = list(param.keys())[0]
+            param_info = param[param_type]
+            property_name = param_info["variable"]
+
+            # 根据不同控件类型处理
+            if param_type == "text-input":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "paragraph":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                    "format": "paragraph",
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "select":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                    "enum": param_info["options"],
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "file_upload":
+                # 文件上传控件处理
+                file_type_schema = {
+                    "type": "object",
+                    "description": param_info["label"],
+                    "properties": {
+                        "file_url": {"type": "string", "description": "文件URL"},
+                        "file_name": {"type": "string", "description": "文件名称"},
+                    },
+                    "required": ["file_url"],
+                }
+
+                # 处理图片上传配置
+                if "image" in param_info and param_info["image"]["enabled"]:
+                    image_config = param_info["image"]
+                    file_type_schema["properties"]["type"] = {
+                        "type": "string",
+                        "description": "文件类型，支持png、jpg、jpeg、webp、gif",
+                        "enum": ["png", "jpg", "jpeg", "webp", "gif"],
+                    }
+
+                    # 处理数量限制
+                    number_limits = image_config.get("number_limits", 3)
+                    if number_limits > 1:
+                        # 如果允许多个文件，则使用数组
+                        inputSchema["properties"][property_name] = {
+                            "type": "array",
+                            "description": param_info["label"],
+                            "items": file_type_schema,
+                            "maxItems": number_limits,
+                        }
+                    else:
+                        # 如果只允许单个文件
+                        inputSchema["properties"][property_name] = file_type_schema
+                else:
+                    # 如果没有特定的图片配置，使用一般文件配置
+                    inputSchema["properties"][property_name] = file_type_schema
+
+            else:
+                # 默认处理为字符串类型
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                }
+
+            # 处理必填字段
+            if param_info.get("required", False):
+                inputSchema["required"].append(property_name)
+
+    # 添加必填的userId参数，支持数字或字符串类型
+    # inputSchema["properties"]["userId"] = dict(
+    #     oneOf=[{"type": "number"}, {"type": "string"}],
+    #     description="您的员工ID，用于识别您的员工身份",
+    # )
+    # inputSchema["required"].append("userId")
+
+    return inputSchema
+
+
+@server.list_tools()
+async def handle_list_tools() -> list[types.Tool]:
+    """
+    列出可用的工具
+    返回:
+        工具列表，每个工具都使用JSON Schema验证其参数
+    """
+    tools = []
+    tool_names = dify_api.dify_app_names
+    tool_infos = dify_api.dify_app_infos
+    tool_params = dify_api.dify_app_params
+    tool_num = len(tool_names)
+    for i in range(tool_num):
+        # 加载每个工具的应用信息
+        app_info = tool_infos[i]
+        # 加载每个工具的应用参数
+        app_param = tool_params[i]
+        # 处理用户输入表单
+        inputSchema = process_user_input_form(app_param["user_input_form"])
+
+        tools.append(
+            types.Tool(
+                name=app_info["name"],
+                description=app_info["description"],
+                inputSchema=inputSchema,
+            )
+        )
+    return tools
+
+
+@server.call_tool()
+async def handle_call_tool(
+    name: str, arguments: dict | None
+) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
+    """
+    调用工具处理请求
+    参数:
+        name: 工具名称
+        arguments: 工具参数
+    返回:
+        处理结果列表
+    """
+    tool_names = dify_api.dify_app_names
+    if name in tool_names:
+        tool_idx = tool_names.index(name)
+        tool_sk = dify_api.dify_app_sks[tool_idx]
+        responses = dify_api.chat_message(
+            tool_sk,
+            inputs=arguments,
+            userId=arguments.get("userId", "pp666"),
+        )
+        for res in responses:
+            if res["event"] == "workflow_finished":
+                outputs = res["data"]["outputs"]
+        mcp_out = []
+        for _, v in outputs.items():
+            mcp_out.append(types.TextContent(type="text", text=v))
+        return mcp_out
+    else:
+        raise ValueError(f"Unknown tool: {name}")
+
+
+def run_main(transport="stdio"):
+    """
+    主函数：使用stdin/stdout流运行服务器
+    """
+    if transport == "stdio":
+        import anyio
+        from mcp.server.stdio import stdio_server
+
+        async def arun():
+            async with stdio_server() as streams:
+                await server.run(
+                    streams[0],
+                    streams[1],
+                    InitializationOptions(
+                        server_name="dify_mcp_server",
+                        server_version="0.0.6",
+                        capabilities=server.get_capabilities(
+                            notification_options=NotificationOptions(),
+                            experimental_capabilities={},
+                        ),
+                    ),
+                )
+
+        anyio.run(arun)
+
+    else:
+        from mcp.server.sse import SseServerTransport
+        from starlette.applications import Starlette
+        from starlette.responses import Response
+        from starlette.routing import Mount, Route
+
+        sse = SseServerTransport("/messages/")
+
+        async def handle_sse(request):
+            async with sse.connect_sse(
+                request.scope, request.receive, request._send
+            ) as streams:
+                await server.run(
+                    streams[0], streams[1], server.create_initialization_options()
+                )
+            return Response()
+
+        starlette_app = Starlette(
+            debug=True,
+            routes=[
+                Route("/sse", endpoint=handle_sse, methods=["GET"]),
+                Mount("/messages/", app=sse.handle_post_message),
+            ],
+        )
+
+        import uvicorn
+
+        uvicorn.run(starlette_app, host="0.0.0.0", port=8080, log_level="info")
+
+
+if __name__ == "__main__":
+    run_main()

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/create_mcp_util.py

@@ -0,0 +1,373 @@
+import json
+from typing import Dict, List, Any, Tuple, Optional
+import logging
+from pathlib import Path
+
+
+# 常量定义
+DEFAULT_NUMBER_LIMITS = 3  # 默认文件数量限制
+
+
+def process_user_input_form(
+    user_input_form: List[Dict[str, Any]],
+) -> Tuple[Dict[str, Any], List[str]]:
+    """
+    处理Dify用户输入表单，生成对应的JSON Schema properties和required列表
+
+    参数:
+        user_input_form: Dify应用的用户输入表单配置
+
+    返回:
+        properties: 表单字段的properties字典
+        required: 必填字段列表
+    """
+    properties = {}
+    required = []
+
+    if not user_input_form:
+        return properties, required
+
+    for param in user_input_form:
+        try:
+            # 直接获取字典的第一个键,而不是通过list转换
+            param_type = next(iter(param))
+            param_info = param[param_type]
+            property_name = param_info["variable"]
+
+            properties[property_name] = {
+                "type": param_type,
+                "description": param_info["label"],
+            }
+
+            if param_info.get("required", False):
+                required.append(property_name)
+        except (KeyError, StopIteration) as e:
+            logging.warning(f"处理用户输入表单项时出错: {e}, 跳过此项")
+            continue
+
+    return properties, required
+
+
+def process_file_upload(file_upload: Optional[Dict[str, Any]]) -> Dict[str, Any]:
+    """
+    处理Dify文件上传配置，生成对应的JSON Schema properties
+
+    设计为通用实现，支持任意文件类型配置
+
+    参数:
+        file_upload: Dify应用的文件上传配置
+
+    返回:
+        file_properties: 文件上传的properties字典
+    """
+    # 检查是否存在文件上传配置
+    if not file_upload:
+        return {}
+
+    # 收集所有启用的文件类型信息
+    enabled_types = []
+    max_items = 0
+    supported_transfer_methods = set()
+    file_type_configs = {}
+
+    for file_type, config in file_upload.items():
+        if not config.get("enabled", False):
+            continue
+
+        enabled_types.append(file_type)
+        number_limits = config.get("number_limits", DEFAULT_NUMBER_LIMITS)
+        max_items += number_limits
+        type_transfer_methods = config.get("transfer_methods", [])
+        supported_transfer_methods.update(type_transfer_methods)
+
+        # 存储每种文件类型的详细配置
+        file_type_configs[file_type] = {
+            "number_limits": number_limits,
+            "transfer_methods": type_transfer_methods,
+        }
+
+    # 如果没有启用的文件类型，返回空字典
+    if not enabled_types:
+        return {}
+
+    # 构建文件项的JSON Schema
+    file_item_schema = _build_file_item_schema(
+        enabled_types, supported_transfer_methods, file_type_configs
+    )
+
+    # 构建最终的files属性
+    file_properties = {
+        "files": {
+            "type": "array",
+            "items": file_item_schema,
+            "description": "支持多种文件类型的文件列表",
+            "maxItems": max_items,
+        }
+    }
+
+    return file_properties
+
+
+def _build_file_item_schema(
+    enabled_types: List[str],
+    supported_transfer_methods: set,
+    file_type_configs: Dict[str, Dict[str, Any]],
+) -> Dict[str, Any]:
+    """
+    构建文件项的JSON Schema
+
+    参数:
+        enabled_types: 启用的文件类型列表
+        supported_transfer_methods: 支持的传输方式集合
+        file_type_configs: 每种文件类型的配置信息
+
+    返回:
+        file_item_schema: 文件项的JSON Schema
+    """
+    file_item_schema = {
+        "type": "object",
+        "properties": {
+            "type": {
+                "type": "string",
+                "enum": enabled_types,
+                "description": "文件类型",
+            },
+            "transfer_method": {
+                "type": "string",
+                "enum": list(supported_transfer_methods),
+                "description": "传输方式",
+            },
+        },
+    }
+
+    # 添加条件属性
+    if "remote_url" in supported_transfer_methods:
+        file_item_schema["properties"]["url"] = {
+            "type": "string",
+            "format": "uri",
+            "description": "文件URL (当传输方式为remote_url时使用)",
+        }
+
+    if "local_file" in supported_transfer_methods:
+        file_item_schema["properties"]["upload_file_id"] = {
+            "type": "string",
+            "description": "上传文件ID (当传输方式为local_file时使用)",
+        }
+
+    # 添加条件验证逻辑
+    file_item_schema["allOf"] = []
+
+    # 为每种文件类型添加验证规则
+    for file_type, type_config in file_type_configs.items():
+        type_methods = type_config["transfer_methods"]
+
+        # 基本验证
+        file_item_schema["allOf"].append(
+            {
+                "if": {"properties": {"type": {"const": file_type}}},
+                "then": {
+                    "properties": {
+                        "transfer_method": {
+                            "enum": type_methods,
+                            "description": f"{file_type}类型支持的传输方式: {', '.join(type_methods)}",
+                        }
+                    }
+                },
+            }
+        )
+
+        # 为每种传输方法添加类型特定的验证
+        _add_transfer_method_validations(file_item_schema, file_type, type_methods)
+
+    return file_item_schema
+
+
+def _add_transfer_method_validations(
+    file_item_schema: Dict[str, Any], file_type: str, type_methods: List[str]
+) -> None:
+    """
+    为每种传输方法添加类型特定的验证
+
+    参数:
+        file_item_schema: 文件项JSON Schema
+        file_type: 文件类型
+        type_methods: 该类型支持的传输方法列表
+    """
+    for method in type_methods:
+        if method == "remote_url":
+            file_item_schema["allOf"].append(
+                {
+                    "if": {
+                        "properties": {
+                            "type": {"const": file_type},
+                            "transfer_method": {"const": "remote_url"},
+                        },
+                        "required": ["type", "transfer_method"],
+                    },
+                    "then": {"required": ["url"]},
+                }
+            )
+        elif method == "local_file":
+            file_item_schema["allOf"].append(
+                {
+                    "if": {
+                        "properties": {
+                            "type": {"const": file_type},
+                            "transfer_method": {"const": "local_file"},
+                        },
+                        "required": ["type", "transfer_method"],
+                    },
+                    "then": {"required": ["upload_file_id"]},
+                }
+            )
+
+
+def convert_dify_params_to_schema(tool_params: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    将用户输入表单和文件上传配置组合成新的结构
+
+    参数:
+        tool_params: 包含user_input_form和file_upload的参数字典
+
+    返回:
+        组合后的结构
+    """
+    # 参数验证
+    if not isinstance(tool_params, dict):
+        raise TypeError("tool_params 必须是字典类型")
+
+    # 处理用户输入表单
+    properties, required = process_user_input_form(
+        tool_params.get("user_input_form", [])
+    )
+
+    # 处理文件上传配置
+    file_properties = process_file_upload(tool_params.get("file_upload"))
+
+    # 创建新的结构
+    result = {
+        "inputs": {"type": "object", "properties": properties, "required": required},
+        # "userId": {
+        #     "oneOf": [{"type": "number"}, {"type": "string"}],
+        #     "description": "您的员工ID，用于识别您的员工身份",
+        #     "required": True,
+        # },
+    }
+
+    # 如果有文件上传配置，添加files字段
+    if file_properties:
+        result["files"] = file_properties.get("files", {})
+
+    return result
+
+
+def finalize_schema_structure(mock_result: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    将mock_result构建为符合要求的map_mock_result格式
+
+    参数:
+        mock_result: 通过convert_dify_params_to_schema函数获取的结果
+
+    返回:
+        构建后的map_mock_result字典
+    """
+    # 确定required字段
+    # required_fields = ["userId"]
+    required_fields = []
+
+    # 只有当inputs的required有值时，才添加inputs到顶层required
+    if (
+        mock_result.get("inputs", {}).get("required")
+        and len(mock_result["inputs"]["required"]) > 0
+    ):
+        required_fields.append("inputs")
+
+    # 如果有文件上传，也可以考虑添加files到required
+    if "files" in mock_result:
+        # 可以根据需求决定是否将files添加到required
+        # required_fields.append("files")
+        pass
+
+    return {
+        "type": "object",
+        "properties": mock_result,
+        "required": required_fields,
+    }
+
+
+def create_json_file(data: Dict[str, Any], filename: str = "output.json") -> None:
+    """
+    将数据保存为JSON文件
+
+    参数:
+        data: 要保存的数据
+        filename: 保存的文件名
+    """
+    try:
+        # 获取mock数据
+        mock_result = convert_dify_params_to_schema(data)
+
+        # 使用封装的方法构建map_mock_result
+        map_mock_result = finalize_schema_structure(mock_result)
+
+        # 确保目标目录存在
+        output_path = Path(filename)
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+
+        # 将结果写入JSON文件
+        with open(filename, "w", encoding="utf-8") as f:
+            json.dump(map_mock_result, f, ensure_ascii=False, indent=4)
+
+        logging.info(f"已成功将数据保存至 {filename}")
+        print(f"已成功将数据保存至 {filename}")
+
+    except Exception as e:
+        error_msg = f"保存JSON文件时出错: {e}"
+        logging.error(error_msg)
+        raise IOError(error_msg)
+
+
+if __name__ == "__main__":
+    # 配置日志
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    )
+
+    # 示例数据
+    api_data = {
+        "opening_statement": "",
+        "suggested_questions": [],
+        "suggested_questions_after_answer": {"enabled": False},
+        "speech_to_text": {"enabled": False},
+        "text_to_speech": {"enabled": False, "language": "", "voice": ""},
+        "retriever_resource": {"enabled": False},
+        "annotation_reply": {"enabled": False},
+        "more_like_this": {"enabled": False},
+        "user_input_form": [
+            {
+                "paragraph": {
+                    "label": "文案内容",
+                    "max_length": 33024,
+                    "options": [],
+                    "required": True,
+                    "type": "paragraph",
+                    "variable": "content",
+                }
+            }
+        ],
+        "sensitive_word_avoidance": {"enabled": False},
+        "file_upload": {
+            "image": {
+                "enabled": False,
+                "number_limits": 3,
+                "transfer_methods": ["local_file", "remote_url"],
+            }
+        },
+        "system_parameters": {"image_file_size_limit": "10"},
+    }
+
+    try:
+        create_json_file(api_data)
+    except Exception as e:
+        logging.error(f"程序执行失败: {e}")

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/difyTaskCall/task_instance.py

@@ -0,0 +1,53 @@
+from abc import ABC
+
+
+# class   WorkflowDifyAPI和chatDifyApi和completionDifyApi
+# dify_app_mode_type  ：workflow, chat, completion
+
+
+class TaskInstance(ABC):
+    def __init__(self, base_url, dify_app_sks, dify_app_mode_type):
+        self.base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.dify_app_mode_type = dify_app_mode_type
+
+    def get_task_instance(self, task_id: str):
+        """
+        根据dify_app_mode_type返回相应的API实例
+
+        Args:
+            task_id: 任务ID
+
+        Returns:
+            返回对应的API实例
+
+        Raises:
+            ValueError: 当dify_app_mode_type无效时抛出异常
+        """
+        from src.workflow.workflow_server import WorkflowDifyAPI
+        from src.completion.completion_server import CompletionDifyAPI
+        from src.chat.chat_server import ChatDifyAPI
+
+        # 使用字典映射提高代码灵活性和可维护性
+        api_classes = {
+            "workflow": WorkflowDifyAPI,
+            "chat": ChatDifyAPI,
+            "completion": CompletionDifyAPI,
+        }
+
+        # 检查mode_type是否有效
+        if self.dify_app_mode_type.lower() not in api_classes:
+            supported_types = ", ".join(api_classes.keys())
+            raise ValueError(
+                f"不支持的dify_app_mode_type: {self.dify_app_mode_type}，支持的类型: {supported_types}"
+            )
+
+        # 获取对应的API类
+        api_class = api_classes[self.dify_app_mode_type.lower()]
+
+        # 这里假设所有API类都接受相同的参数集
+        # 如果各API类构造函数参数不同，需要针对每种类型单独处理
+        return api_class(
+            self.base_url,
+            self.dify_app_sks,
+        )

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/utils/tool_translation.py

@@ -0,0 +1,153 @@
+import os
+import sys
+from typing import Dict, Any, Optional
+
+
+# 导入翻译函数
+from .translator import translate
+
+
+class TranslationService:
+    """翻译服务类，用于处理各种翻译需求"""
+
+    @staticmethod
+    def create_prompt(
+        content: str,
+        target_lang: str,
+        use_case: str,
+        style: str,
+        prompt_type: str = "general",
+        keep_terms_desc: str = "核心术语",
+    ) -> str:
+        """
+        创建翻译提示
+
+        Args:
+            content: 待翻译内容
+            target_lang: 目标语言
+            use_case: 使用场景
+            style: 翻译风格
+            prompt_type: 提示类型，可选值: "general", "tool_name", "tool_description"
+            keep_terms_desc: 保留术语的描述
+
+        Returns:
+            str: 格式化的翻译提示
+        """
+        if prompt_type == "tool_name":
+            keep_terms_desc = "核心术语（如 小写，词语需要用下划线连接）"
+        elif prompt_type == "tool_description":
+            keep_terms_desc = "核心术语（这是一段话）"
+
+        return f"""
+角色：专业本地化翻译专家
+任务：将以下内容翻译为{target_lang}（目标用途：{use_case}）
+要求：
+1. 仅返回译文，不含解释或原文；
+2. 保留{keep_terms_desc}；
+3. 符合{style}风格；
+4. 特殊符号保持原样。
+
+示例输出格式：
+Translated Text
+
+待翻译内容：
+{content}
+"""
+
+    @staticmethod
+    def translate_text(
+        content: str,
+        target_lang: str,
+        use_case: str = "",
+        style: str = "正式且符合技术品牌调性",
+        prompt_type: str = "general",
+    ) -> Dict[str, Any]:
+        """
+        翻译文本
+
+        Args:
+            content: 待翻译内容
+            target_lang: 目标语言
+            use_case: 使用场景，默认为空
+            style: 翻译风格，默认为"正式且符合技术品牌调性"
+            prompt_type: 提示类型，可选值: "general", "tool_name", "tool_description"
+
+        Returns:
+            Dict: 包含翻译结果的字典
+        """
+        prompt = TranslationService.create_prompt(
+            content=content,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type=prompt_type,
+        )
+
+        try:
+            result = translate(prompt, target_lang)
+            return result
+        except Exception as e:
+            print(f"翻译出错: {str(e)}")
+            return {"translated_text": "", "error": str(e)}
+
+    @staticmethod
+    def translate_tool_name(
+        name: str,
+        target_lang: str = "英语",
+        use_case: str = "工具名称",
+        style: str = "正式且符合技术品牌调性，大模型能理解",
+    ) -> str:
+        """
+        翻译工具名称的便捷方法
+
+        Returns:
+            str: 翻译后的工具名称
+        """
+        result = TranslationService.translate_text(
+            content=name,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type="tool_name",
+        )
+        return result.get("translated_text", "")
+
+    @staticmethod
+    def translate_tool_description(
+        description: str,
+        target_lang: str = "英语",
+        use_case: str = "工具描述",
+        style: str = "正式且符合技术品牌调性，大模型能理解",
+    ) -> str:
+        """
+        翻译工具描述的便捷方法
+
+        Returns:
+            str: 翻译后的工具描述
+        """
+        result = TranslationService.translate_text(
+            content=description,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type="tool_description",
+        )
+        return result.get("translated_text", "")
+
+
+def translation_example():
+    """翻译功能使用示例"""
+
+    # 示例1: 翻译工具名称
+    tool_name = "万川AI新媒体平台【测试环境】"
+    translated_name = TranslationService.translate_tool_name(tool_name)
+    print(f"工具名称翻译: {translated_name}")
+
+    # 示例2: 翻译工具描述
+    description = "21日，辛柏青发布讣告宣布妻子朱媛媛抗癌五年后离世。此前在一次路演现场，当观众问及朱媛媛时辛柏青2秒停顿藏着"
+    translated_desc = TranslationService.translate_tool_description(description)
+    print(f"工具描述翻译: {translated_desc}")
+
+
+if __name__ == "__main__":
+    translation_example()

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/utils/translator.py

@@ -0,0 +1,64 @@
+import os
+import requests
+import json
+from dotenv import load_dotenv
+
+# 加载环境变量
+load_dotenv()
+# ========== 模型相关 ==========
+# 从.env文件获取模型API配置
+BASE_URL = os.getenv("BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")
+API_KEY = os.getenv("OPENAI_API_KEY", "sk-c5a912a6bc8e4c9cbdbdf68232352a03")
+TEMPERATURE = float(os.getenv("MODEL_TEMPERATURE", "0.7"))
+
+
+def translate(content, target_language):
+    """
+    翻译文本内容到目标语言
+
+    :param content: 要翻译的内容
+    :param target_language: 目标语言，如'en'(英语), 'zh'(中文), 'ja'(日语), 'fr'(法语)等
+    :return: 翻译后的内容，如果翻译失败则返回原文和错误信息
+    """
+    if not content or not target_language:
+        return {"error": "内容或目标语言不能为空", "translated_text": content}
+
+    # 确保API密钥已设置
+    if not API_KEY:
+        return {"error": "API密钥未设置，请检查.env文件", "translated_text": content}
+
+    try:
+        # 构建API请求头
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {API_KEY}",
+        }
+
+        # 构建翻译提示
+        prompt = f"请将以下内容翻译成{target_language}，只返回翻译结果，不要包含任何解释或原文：\n\n{content}"
+
+        # 构建API请求体
+        data = {
+            "model": "qwen-max",  # 使用通义千问模型，可以根据实际需要更改
+            "messages": [{"role": "user", "content": prompt}],
+            "temperature": TEMPERATURE,
+        }
+
+        # 发送API请求
+        response = requests.post(
+            f"{BASE_URL}/chat/completions", headers=headers, json=data
+        )
+
+        # 解析响应
+        if response.status_code == 200:
+            result = response.json()
+            translated_text = result["choices"][0]["message"]["content"].strip()
+            return {"translated_text": translated_text}
+        else:
+            error_message = (
+                f"翻译失败，状态码: {response.status_code}, 响应: {response.text}"
+            )
+            return {"error": error_message, "translated_text": content}
+
+    except Exception as e:
+        return {"error": f"翻译过程中发生错误: {str(e)}", "translated_text": content}

lzwcai_demp_tool_server_dify_to_mcp/lzwcai_demp_tool_server_dify_to_mcp/src/workflow/workflow_server.py

@@ -0,0 +1,175 @@
+import requests
+from abc import ABC
+import logging
+import json
+import re
+
+logger = logging.getLogger(__name__)
+
+import pypinyin
+
+
+def pinyin_to_camel(pinyin):
+    """
+    将拼音列表转换为驼峰命名
+    例如: ['ni', 'hao', 'a'] -> 'NiHaoA'
+    所有非字母数字字符会被替换为下划线
+    """
+    # 使用正则表达式将所有非字母数字字符（包括所有标点符号）替换为下划线
+    cleaned = re.sub(r'[^\w\s]', '_', pinyin)
+    # 将空格也替换为下划线
+    cleaned = re.sub(r'\s+', '_', cleaned)
+    # 移除连续的下划线并去除首尾下划线
+    cleaned = re.sub(r'_+', '_', cleaned).strip('_')
+    
+    # 转换为拼音并生成驼峰命名
+    pinyin_list = pypinyin.lazy_pinyin(cleaned)
+    return "tool_" + "".join(word.capitalize() for word in pinyin_list)
+
+
+class WorkflowDifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        userId="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/workflows/run"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": userId,
+        }
+        logger.info("Sending data to Dify API: %s", data)
+        logger.info("Sending headers to Dify API: %s", headers)
+        logger.info("Sending url to Dify API: %s", url)
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+        if files:
+            files_data = []
+            for file_info in files:
+                file_path = file_info.get("path")
+                transfer_method = file_info.get("transfer_method")
+                if transfer_method == "local_file":
+                    files_data.append(("file", open(file_path, "rb")))
+                elif transfer_method == "remote_url":
+                    pass
+            response = requests.post(
+                url,
+                headers=headers,
+                data=data,
+                files=files_data,
+                stream=response_mode == "streaming",
+            )
+        else:
+            response = requests.post(
+                url, headers=headers, json=data, stream=response_mode == "streaming"
+            )
+        response.raise_for_status()
+        if response_mode == "streaming":
+            for line in response.iter_lines():
+                if line:
+                    if line.startswith(b"data:"):
+                        try:
+                            json_data = json.loads(line[5:].decode("utf-8"))
+                            yield json_data
+                        except json.JSONDecodeError:
+                            print(f"Error decoding JSON: {line}")
+        else:
+            return response.json()
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+
+        from src.utils.tool_translation import TranslationService
+
+        response_map = response.json()
+
+        # 翻译工具名称
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+
+        # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # if tool_description:
+        #     translated_description = TranslationService.translate_tool_description(
+        #         tool_description
+        #     )
+        #     response_map["description"] = (
+        #         f"{tool_description} ({translated_description})"
+        #     )
+
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/parameters"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/PKG-INFO

@@ -0,0 +1,12 @@
+Metadata-Version: 2.4
+Name: lzwcai-demp-tool-server-dify-to-mcp-test
+Version: 0.0.15
+Summary: 这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。
+Requires-Python: >=3.10
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: mcp>=1.1.2
+Requires-Dist: omegaconf>=2.3.0
+Requires-Dist: pip>=24.3.1
+Requires-Dist: python-dotenv>=1.0.1
+Requires-Dist: requests
+Requires-Dist: pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/dify-api.md

@@ -0,0 +1,267 @@
+# Dify Workflow API 文档
+
+## 概述
+
+Workflow 应用无会话支持,适合用于翻译、文章写作、总结等 AI 场景。
+
+**Base URL:** `http://192.168.2.236:3001/v1`
+
+## 认证
+
+所有 API 请求需在 HTTP Header 中包含 API-Key:
+
+```
+Authorization: Bearer {API_KEY}
+```
+
+## 1. 执行 Workflow
+
+**接口:** `POST /workflows/run`
+
+### 请求参数
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| inputs | object | ✓ | 允许传入 App 定义的各变量值。inputs 参数包含了多组键值对,每组的键对应一个特定变量,每组的值则是该变量的具体值 |
+| response_mode | string | ✓ | 返回响应模式:`streaming`(流式,推荐)或`blocking`(阻塞,Cloudflare 限制 100 秒超时) |
+| user | string | ✓ | 用户标识,用于定义终端用户的身份,方便检索、统计。需保证用户标识在应用内唯一 |
+
+### 文件列表类型变量
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| type | string | 文件类型:document/image/audio/video/custom |
+| transfer_method | string | 传递方式:remote_url(图片地址)或local_file(上传文件) |
+| url | string | 图片地址(仅当传递方式为 remote_url 时) |
+| upload_file_id | string | 上传文件 ID(仅当传递方式为 local_file 时) |
+
+**支持的文件类型:**
+- **document**: TXT, MD, PDF, HTML, XLSX, DOCX, CSV, PPTX, XML, EPUB
+- **image**: JPG, PNG, GIF, WEBP, SVG
+- **audio**: MP3, WAV, M4A, WEBM, AMR
+- **video**: MP4, MOV, MPEG
+
+### 响应格式
+
+#### CompletionResponse(阻塞模式)
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| workflow_run_id | string | workflow 执行 ID |
+| task_id | string | 任务 ID,用于请求跟踪和停止响应接口 |
+| data.id | string | workflow 执行 ID |
+| data.workflow_id | string | 关联 Workflow ID |
+| data.status | string | 执行状态:running/succeeded/failed/stopped |
+| data.outputs | json | 可选,输出内容 |
+| data.error | string | 可选,错误原因 |
+| data.elapsed_time | float | 可选,耗时(秒) |
+| data.total_tokens | int | 可选,总使用 tokens |
+| data.total_steps | int | 总步数,默认 0 |
+| data.created_at | timestamp | 开始时间 |
+| data.finished_at | timestamp | 结束时间 |
+
+#### ChunkCompletionResponse(流式模式)
+
+**事件类型:**
+
+**1. workflow_started**
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| task_id | string | 任务 ID |
+| workflow_run_id | string | workflow 执行 ID |
+| event | string | 固定为 workflow_started |
+| data.id | string | workflow 执行 ID |
+| data.workflow_id | string | 关联 Workflow ID |
+| data.sequence_number | int | 自增序号,从 1 开始 |
+| data.created_at | timestamp | 开始时间 |
+
+**2. node_started**
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| data.node_id | string | 节点 ID |
+| data.node_type | string | 节点类型 |
+| data.title | string | 节点名称 |
+| data.index | int | 执行序号 |
+| data.predecessor_node_id | string | 前置节点 ID |
+| data.inputs | object | 节点中所有使用到的前置节点变量内容 |
+
+**3. node_finished**
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| data.node_id | string | 节点 ID |
+| data.status | string | 执行状态:running/succeeded/failed/stopped |
+| data.outputs | json | 可选,输出内容 |
+| data.error | string | 可选,错误原因 |
+| data.elapsed_time | float | 可选,耗时(秒) |
+| data.execution_metadata.total_tokens | int | 可选,总使用 tokens |
+| data.execution_metadata.total_price | decimal | 可选,总费用 |
+| data.execution_metadata.currency | string | 可选,货币(USD/RMB) |
+
+**4. workflow_finished**
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| data.status | string | 执行状态:running/succeeded/failed/stopped |
+| data.outputs | json | 可选,输出内容 |
+| data.error | string | 可选,错误原因 |
+| data.total_tokens | int | 可选,总使用 tokens |
+| data.finished_at | timestamp | 结束时间 |
+
+**5. tts_message** - TTS 音频流事件(Mp3 格式,base64 编码)
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| task_id | string | 任务 ID |
+| message_id | string | 消息唯一 ID |
+| audio | string | Base64 编码的音频内容 |
+| created_at | int | 创建时间戳 |
+
+**6. tts_message_end** - TTS 音频流结束
+
+**7. ping** - 每 10 秒心跳保活
+
+### 错误码
+
+| 状态码 | 错误码 | 说明 |
+|--------|--------|------|
+| 400 | invalid_param | 传入参数异常 |
+| 400 | app_unavailable | App 配置不可用 |
+| 400 | provider_not_initialize | 无可用模型凭据配置 |
+| 400 | provider_quota_exceeded | 模型调用额度不足 |
+| 400 | workflow_request_error | workflow 执行失败 |
+| 500 | - | 服务内部异常 |
+
+---
+
+## 2. 查询 Workflow 执行状态
+
+**接口:** `GET /workflows/run/:workflow_run_id`
+
+### 响应字段
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| id | string | workflow 执行 ID |
+| workflow_id | string | 关联的 Workflow ID |
+| status | string | 执行状态:running/succeeded/failed/stopped |
+| inputs | json | 任务输入内容 |
+| outputs | json | 任务输出内容 |
+| error | string | 错误原因 |
+| total_steps | int | 任务执行总步数 |
+| total_tokens | int | 任务执行总 tokens |
+| created_at | timestamp | 任务开始时间 |
+| finished_at | timestamp | 任务结束时间 |
+| elapsed_time | float | 耗时(秒) |
+
+---
+
+## 3. 停止 Workflow 执行
+
+**接口:** `POST /workflows/tasks/:task_id/stop`
+
+### 请求参数
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| user | string | ✓ | 用户标识,必须和发送消息接口传入 user 保持一致 |
+
+---
+
+## 4. 上传文件
+
+**接口:** `POST /files/upload`
+
+### 请求参数
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| file | file | ✓ | 要上传的文件 |
+| user | string | ✓ | 用户标识 |
+
+### 响应字段
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| id | uuid | ID |
+| name | string | 文件名 |
+| size | int | 文件大小(byte) |
+| extension | string | 文件后缀 |
+| mime_type | string | 文件 mime-type |
+| created_by | uuid | 上传人 ID |
+| created_at | timestamp | 上传时间 |
+
+### 错误码
+
+| 状态码 | 错误码 | 说明 |
+|--------|--------|------|
+| 400 | no_file_uploaded | 必须提供文件 |
+| 413 | file_too_large | 文件太大 |
+| 415 | unsupported_file_type | 不支持的文件类型 |
+| 503 | s3_connection_failed | 无法连接到 S3 服务 |
+
+---
+
+## 5. 获取 Workflow 日志
+
+**接口:** `GET /workflows/logs`
+
+### 查询参数
+
+| 参数 | 类型 | 说明 | 默认值 |
+|------|------|------|--------|
+| keyword | string | 关键字 | - |
+| status | string | 执行状态:succeeded/failed/stopped | - |
+| page | int | 当前页码 | 1 |
+| limit | int | 每页条数 | 20 |
+
+### 响应字段
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| page | int | 当前页码 |
+| limit | int | 每页条数 |
+| total | int | 总条数 |
+| has_more | bool | 是否还有更多数据 |
+| data[].workflow_run.id | string | 标识 |
+| data[].workflow_run.status | string | 执行状态 |
+| data[].workflow_run.elapsed_time | float | 耗时(秒) |
+| data[].workflow_run.total_tokens | int | 消耗的 token 数量 |
+
+---
+
+## 6. 获取应用信息
+
+**接口:** `GET /info`
+
+### 响应字段
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| name | string | 应用名称 |
+| description | string | 应用描述 |
+| tags | array[string] | 应用标签 |
+
+---
+
+## 7. 获取应用参数
+
+**接口:** `GET /parameters`
+
+### 响应字段
+
+| 字段 | 类型 | 说明 |
+|------|------|------|
+| user_input_form[].text-input.label | string | 控件展示标签名 |
+| user_input_form[].text-input.variable | string | 控件 ID |
+| user_input_form[].text-input.required | bool | 是否必填 |
+| user_input_form[].text-input.default | string | 默认值 |
+| file_upload.image.enabled | bool | 是否开启 |
+| file_upload.image.number_limits | int | 图片数量限制,默认 3 |
+| file_upload.image.transfer_methods | array[string] | 传递方式:remote_url/local_file |
+| system_parameters.file_size_limit | int | 文档上传大小限制(MB) |
+| system_parameters.image_file_size_limit | int | 图片文件上传大小限制(MB) |
+| system_parameters.audio_file_size_limit | int | 音频文件上传大小限制(MB) |
+| system_parameters.video_file_size_limit | int | 视频文件上传大小限制(MB) |

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/logs/.gitkeep

@@ -0,0 +1,2 @@
+# 此文件用于确保 logs 目录被 Git 跟踪
+# 日志文件会自动生成在此目录中

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/PKG-INFO

@@ -0,0 +1,12 @@
+Metadata-Version: 2.4
+Name: lzwcai-demp-tool-server-dify-to-mcp-test
+Version: 0.1.0
+Summary: 这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。
+Requires-Python: >=3.10
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: mcp>=1.1.2
+Requires-Dist: omegaconf>=2.3.0
+Requires-Dist: pip>=24.3.1
+Requires-Dist: python-dotenv>=1.0.1
+Requires-Dist: requests
+Requires-Dist: pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/SOURCES.txt

@@ -0,0 +1,27 @@
+README.md
+pyproject.toml
+setup.cfg
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/PKG-INFO
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/SOURCES.txt
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/dependency_links.txt
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/entry_points.txt
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/requires.txt
+lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/top_level.txt
+src/__init__.py
+src/create_mcp.py
+src/create_mcp_update.py
+src/create_mcp_utils.py
+src/chat/__init__.py
+src/chat/chat_server.py
+src/completion/completion_server.py
+src/completion/test.py
+src/core/__init__.py
+src/core/core_server.py
+src/difyTaskCall/task_instance.py
+src/utils/dify_workflow_schema.py
+src/utils/logger_config.py
+src/utils/tool_translation.py
+src/utils/translator.py
+src/utils/upload_file.py
+src/workflow/__init__.py
+src/workflow/workflow_server.py

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/entry_points.txt

@@ -0,0 +1,2 @@
+[console_scripts]
+lzwcai-demp-tool-server-dify-to-mcp-test = src.create_mcp:run_main

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/requires.txt

@@ -0,0 +1,7 @@
+httpx>=0.28.1
+mcp>=1.1.2
+omegaconf>=2.3.0
+pip>=24.3.1
+python-dotenv>=1.0.1
+requests
+pypinyin>=0.54.0

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test.egg-info/top_level.txt

@@ -0,0 +1 @@
+src

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/main.py

@@ -0,0 +1,86 @@
+#!/usr/bin/env python3
+"""
+主入口文件
+用于启动 Dify MCP 服务器，并配置命令行参数
+"""
+import os
+import sys
+import logging
+
+# 导入日志配置
+from src.utils.logger_config import setup_logging, get_logger
+
+# Mock 配置参数
+def setup_mock_arguments():
+    """
+    设置模拟命令行参数
+    这些参数可以根据实际需求进行修改
+    """
+    # 默认配置
+    default_config = {
+        "base_url": "http://192.168.2.236:3001/v1",
+        "app_sks": ["app-Oo0QRJismgQADRSt8Bj0RXWB"],
+        "mode_type": "workflow",
+        "transport": "stdio"
+    }
+    
+    # 如果没有提供命令行参数，则添加默认参数
+    if len(sys.argv) == 1:
+        sys.argv.extend([
+            "--base-url", default_config["base_url"],
+            "--app-sks", *default_config["app_sks"],
+            "--mode-type", default_config["mode_type"]
+        ])
+    
+    return default_config
+
+
+def main():
+    """
+    主函数：设置命令行参数并启动服务器
+    """
+    # 初始化日志系统（MCP模式下禁用控制台输出，避免干扰stdio通信）
+    try:
+        log_file_path = setup_logging(
+            log_level=logging.INFO,
+            console_output=False,  # MCP模式下禁用控制台输出
+            file_output=True
+        )
+        logger = get_logger(__name__)
+        logger.info("=" * 80)
+        logger.info("Dify MCP 服务器启动")
+        logger.info(f"日志文件: {log_file_path}")
+        logger.info("=" * 80)
+    except Exception as e:
+        # 如果日志初始化失败，使用stderr输出错误
+        print(f"[ERROR] 日志系统初始化失败: {e}", file=sys.stderr)
+    
+    # 设置模拟命令行参数
+    config = setup_mock_arguments()
+    
+    # 导入并运行 MCP 服务器
+    try:
+        from src.create_mcp import run_main
+        
+        # 获取传输模式
+        transport_mode = config.get("transport", "stdio")
+        
+        logger.info(f"传输模式: {transport_mode}")
+        logger.info(f"配置参数: {config}")
+        
+        # 运行服务器（不输出额外信息，避免干扰 STDIO 通信）
+        run_main(transport=transport_mode)
+        
+    except ImportError as e:
+        logger.error(f"导入错误: {e}", exc_info=True)
+        print(f"[ERROR] 导入错误: {e}", file=sys.stderr)
+        print("请确保已正确安装所有依赖包", file=sys.stderr)
+        sys.exit(1)
+    except Exception as e:
+        logger.error(f"运行错误: {e}", exc_info=True)
+        print(f"[ERROR] 运行错误: {e}", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/pyproject.toml

@@ -0,0 +1,32 @@
+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "lzwcai-demp-tool-server-dify-to-mcp-test"
+version = "0.1.0"
+description = "这是一个Dify to MCP的集成工具；通过Dify的API接口，将Dify的模型部署到MCP平台，并进行推理。"
+requires-python = ">=3.10"
+dependencies = [
+    "httpx>=0.28.1",
+    "mcp>=1.1.2",
+    "omegaconf>=2.3.0",
+    "pip>=24.3.1",
+    "python-dotenv>=1.0.1",
+    "requests",
+    "pypinyin>=0.54.0",
+]
+
+[tool.setuptools]
+packages = {find = {where = ["."], include = ["src*"]}}
+include-package-data = true
+
+[project.scripts]
+lzwcai-demp-tool-server-dify-to-mcp-test = "src.create_mcp:run_main"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.setuptools.package-data]
+"*" = ["*.env"]
+"src" = ["**/*.env"] 

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/setup.cfg

@@ -0,0 +1,4 @@
+[egg_info]
+tag_build = 
+tag_date = 0
+

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/chat/chat_server.py

@@ -0,0 +1,7 @@
+class ChatDifyAPI:
+    def __init__(self, base_url: str, app_sks: str):
+        self.base_url = base_url
+        self.app_sks = app_sks
+
+    def process_task(self, task_id: str, **kwargs):
+        pass

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/completion/completion_server.py

@@ -0,0 +1,203 @@
+import requests
+from abc import ABC
+import logging
+import json
+import pypinyin
+from src.utils.logger_config import get_logger
+
+logger = get_logger(__name__)
+
+
+def pinyin_to_camel(pinyin):
+    """
+    将拼音列表转换为驼峰命名
+    例如: ['ni', 'hao', 'a'] -> 'NiHaoA'
+    """
+    pinyin_list = pypinyin.lazy_pinyin(pinyin)
+    return "tool_" + "".join(word.capitalize() for word in pinyin_list)
+
+
+class CompletionDifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        userId="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/completion-messages"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": userId,
+        }
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+
+        if response_mode == "streaming":
+            response = requests.post(url, headers=headers, json=data, stream=True)
+
+            # 处理流式响应
+            full_answer = ""
+            for line in response.iter_lines():
+                if line:
+                    # 跳过 "data:" 前缀
+                    decoded_line = line.decode("utf-8")
+                    if decoded_line.startswith("data:"):
+                        try:
+                            json_str = decoded_line[5:].strip()
+                            data = json.loads(json_str)
+                            if data.get("event") == "message" and "answer" in data:
+                                # 累积完整答案
+                                full_answer += data["answer"]
+                                # 这里也可以选择处理每个部分响应，例如返回生成器
+                                # yield data
+                        except json.JSONDecodeError:
+                            logger.warning(f"无法解析JSON数据: {decoded_line}")
+
+            # 创建一个符合非流式响应格式的结果
+            response_data = {"answer": full_answer}
+            # 处理可能包含代码块的数据
+            processed_data = self.process_answer_code_block(response_data)
+            return processed_data
+        else:
+            response = requests.post(url, headers=headers, json=data)
+            response_data = response.json()
+            # 处理可能包含代码块的数据
+            processed_data = self.process_answer_code_block(response_data)
+            return processed_data
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        # params = {"user": user}
+        response = requests.get(url, headers=headers)
+        response.raise_for_status()
+
+        response_map = response.json()
+        # 翻译工具名称
+        from src.utils.tool_translation import TranslationService
+
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+
+        # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # if tool_description:
+        #     translated_description = TranslationService.translate_tool_description(
+        #         tool_description
+        #     )
+        #     response_map["description"] = (
+        #         f"{tool_description} ({translated_description})"
+        #     )
+
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        return {
+            "user_input_form": [
+                {"string": {"variable": "query", "label": "查询内容", "required": True}}
+            ]
+        }
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    @staticmethod
+    def process_answer_code_block(data):
+        try:
+            # 获取answer字段
+            answer = data.get("answer", "")
+
+            # 构造符合workflow_finished格式的输出
+            formatted_response = [
+                {"event": "workflow_finished", "data": {"outputs": {"result": answer}}}
+            ]
+
+            # 尝试处理可能的代码块
+            if answer.startswith("```") and answer.endswith("```"):
+                try:
+                    # 移除代码块标记并解析JSON
+                    code_content = answer.strip("```").strip()
+                    json_data = json.loads(code_content)
+
+                    # 如果包含description字段，用它替换answer
+                    if "description" in json_data:
+                        formatted_response[0]["data"]["outputs"]["result"] = json_data[
+                            "description"
+                        ]
+                except json.JSONDecodeError:
+                    # 如果不是有效的JSON，保留原始代码块内容
+                    pass
+
+            return formatted_response
+        except Exception as e:
+            logger.warning(f"处理答案代码块时出错: {str(e)}")
+            # 发生错误时返回符合格式的基础响应
+            return [
+                {
+                    "event": "workflow_finished",
+                    "data": {
+                        "outputs": {
+                            "error": str(e),
+                            "fallback": data.get("answer", str(data)),
+                        }
+                    },
+                }
+            ]

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/completion/test.py

@@ -0,0 +1,104 @@
+import requests
+from abc import ABC
+import logging
+import json
+
+logger = logging.getLogger(__name__)
+
+res = {
+    "event": "message",
+    "task_id": "49c9ea1b-7b43-475b-a680-d769fb238a45",
+    "id": "432ab98e-5e36-4a29-abe5-e01281c3678c",
+    "message_id": "432ab98e-5e36-4a29-abe5-e01281c3678c",
+    "mode": "completion",
+    "answer": '```\n{\n  "description": "该API的具体功能描述暂时不明确，因为提供的API信息 \'今天打老虎啊按时啊啊\' 并不是有效的API名称或描述。请提供正确的API名称和相关输入输出信息，以便我能为其补充完善的API描述。"\n}\n```',
+    "metadata": {
+        "usage": {
+            "prompt_tokens": 73,
+            "prompt_unit_price": "0.0",
+            "prompt_price_unit": "0.0",
+            "prompt_price": "0.0",
+            "completion_tokens": 61,
+            "completion_unit_price": "0.0",
+            "completion_price_unit": "0.0",
+            "completion_price": "0.0",
+            "total_tokens": 134,
+            "total_price": "0.0",
+            "currency": "USD",
+            "latency": 1.896302318200469,
+        }
+    },
+    "created_at": 1747233054,
+}
+
+
+def process_answer_code_block(data):
+    try:
+        # 获取answer字段
+        answer = data.get("answer", "")
+
+        # 检查answer是否是代码块格式
+        if answer.startswith("```") and answer.endswith("```"):
+            # 移除代码块标记并解析JSON
+            code_content = answer.strip("```").strip()
+            json_data = json.loads(code_content)
+
+            # 获取description字段
+            if "description" in json_data:
+                return json_data["description"]
+
+        # 如果不是预期格式，则返回原始answer
+        return data.get("answer", data)
+    except Exception as e:
+        logger.warning(f"处理答案代码块时出错: {str(e)}")
+        # 发生错误时返回原始数据
+        return data.get("answer", data)
+
+
+def chat_message_test(
+    api_key,
+    inputs={},
+    response_mode="blocking",
+    conversation_id=None,
+    userId="pp666",
+    files=None,
+):
+    url = "https://ops.lzwcai.com/v1/completion-messages"
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json",
+    }
+    data = {
+        "inputs": inputs,
+        "response_mode": response_mode,
+        "user": userId,
+    }
+    if conversation_id:
+        data["conversation_id"] = conversation_id
+    if response_mode == "streaming":
+        response = requests.post(
+            url, headers=headers, json=data, stream=response_mode == "streaming"
+        )
+        return response
+    else:
+        response = requests.post(url, headers=headers, json=data)
+        return response.json()
+
+
+if __name__ == "__main__":
+    print("开始执行主程序")
+    try:
+        print("准备调用chat_message方法")
+        res = chat_message_test(
+            api_key="app-Ppemii3c0ROPoLvRwskgZ7Il",
+            inputs={"query": "今天打老虎啊按时啊啊"},
+            response_mode="streaming",
+            userId="abc-123",
+        )
+        print("chat_message方法调用完成")
+
+        # 打印响应内容
+        print("响应内容:", res)
+        # print(process_answer_code_block(res))
+    except Exception as e:
+        print(f"执行过程中出现错误: {e}")

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/core/core_server.py

@@ -0,0 +1,213 @@
+import requests
+from abc import ABC
+import logging
+import json
+
+# 导入 pypinyin 用于中文转拼音
+try:
+    import pypinyin
+except ImportError:
+    pypinyin = None
+    logging.warning("pypinyin 模块未安装，将使用简化的命名方式")
+
+logger = logging.getLogger(__name__)
+
+
+def pinyin_to_camel(pinyin):
+    """
+    将中文名称转换为工具名称
+    
+    处理逻辑：
+    1. 如果安装了 pypinyin，将中文转换为拼音，然后转为驼峰命名
+    2. 如果未安装 pypinyin，将所有非字母数字字符替换为下划线
+    3. 所有符号都会被替换成下划线
+    
+    示例:
+        "你好啊" -> "tool_NiHaoA" (有pypinyin)
+        "测试-工具" -> "tool_测试_工具" (无pypinyin)
+        "Hello World!" -> "tool_Hello_World_" (无pypinyin)
+    
+    Args:
+        pinyin: 输入的字符串（可能包含中文、英文、符号等）
+    
+    Returns:
+        str: 格式化后的工具名称，以 "tool_" 开头
+    """
+    import re
+    
+    if pypinyin is None:
+        # 如果 pypinyin 未安装，使用简化的命名方式
+        # 将所有非字母数字字符（包括空格、符号等）替换为下划线
+        cleaned = re.sub(r'[^\w]', '_', str(pinyin))
+        # 移除连续的下划线
+        cleaned = re.sub(r'_+', '_', cleaned)
+        # 移除首尾的下划线
+        cleaned = cleaned.strip('_')
+        return "tool_" + cleaned if cleaned else "tool_unnamed"
+    
+    # 使用 pypinyin 转换中文为拼音
+    pinyin_list = pypinyin.lazy_pinyin(pinyin)
+    
+    # 处理每个拼音单词
+    processed_words = []
+    for word in pinyin_list:
+        # 将所有非字母数字字符替换为下划线
+        cleaned_word = re.sub(r'[^\w]', '_', word)
+        # 移除连续的下划线
+        cleaned_word = re.sub(r'_+', '_', cleaned_word)
+        # 移除首尾的下划线
+        cleaned_word = cleaned_word.strip('_')
+        
+        if cleaned_word:
+            # 首字母大写（驼峰命名）
+            processed_words.append(cleaned_word.capitalize())
+    
+    # 拼接所有单词
+    result = "".join(processed_words) if processed_words else "Unnamed"
+    return "tool_" + result
+
+
+class DifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        logger.info(f"Dify应用参数: {dify_app_params}")
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        user="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/workflows/run"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": user,
+        }
+        logger.info("Sending data to Dify API: %s", data)
+        logger.info("Sending headers to Dify API: %s", headers)
+        logger.info("Sending url to Dify API: %s", url)
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+        if files:
+            files_data = []
+            for file_info in files:
+                file_path = file_info.get("path")
+                transfer_method = file_info.get("transfer_method")
+                if transfer_method == "local_file":
+                    files_data.append(("file", open(file_path, "rb")))
+                elif transfer_method == "remote_url":
+                    pass
+            response = requests.post(
+                url,
+                headers=headers,
+                data=data,
+                files=files_data,
+                stream=response_mode == "streaming",
+            )
+        else:
+            response = requests.post(
+                url, headers=headers, json=data, stream=response_mode == "streaming"
+            )
+        response.raise_for_status()
+        if response_mode == "streaming":
+            for line in response.iter_lines():
+                if line:
+                    if line.startswith(b"data:"):
+                        try:
+                            json_data = json.loads(line[5:].decode("utf-8"))
+                            yield json_data
+                        except json.JSONDecodeError:
+                            logger.error(f"JSON解码错误: {line}")
+        else:
+            return response.json()
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+
+        from src.utils.tool_translation import TranslationService
+
+        response_map = response.json()
+        # 翻译工具名称
+        # tool_name = response_map.get("name")
+        # translated_name = TranslationService.translate_tool_name(tool_name)
+        # response_map["name"] = translated_name
+        # # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # translated_description = TranslationService.translate_tool_description(
+        #     tool_description
+        # )
+        # response_map["description"] = translated_description
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/parameters"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/create_mcp.py

@@ -0,0 +1,233 @@
+import asyncio
+import json
+import os
+import logging
+import argparse
+from abc import ABC
+
+import mcp.server.stdio
+import mcp.types as types
+import requests
+from mcp.server import NotificationOptions, Server
+from mcp.server.models import InitializationOptions
+from omegaconf import OmegaConf
+
+# from src.workflow.workflow_server import WorkflowDifyAPI
+from src.difyTaskCall.task_instance import TaskInstance
+from src.utils.dify_workflow_schema import process_user_input_form, extract_file_fields
+from src.create_mcp_utils import process_file_arguments
+from src.utils.logger_config import get_logger
+
+# 使用统一的日志配置
+logger = get_logger(__name__)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Dify MCP服务器配置")
+    parser.add_argument(
+        "--base-url",
+        type=str,
+        help="API基础URL",
+        default="http://192.168.2.236:3001/v1",
+    )
+    parser.add_argument(
+        "--app-sks",
+        nargs="+",
+        help="应用秘钥列表",
+        default=["app-RBS0TuYEnqm8Q1cRQingkuhf"],
+    )
+    parser.add_argument(
+        "--mode-type",
+        type=str,
+        help="Dify应用模式类型 (workflow, chat, completion)",
+        default="workflow",
+        choices=["workflow", "chat", "completion"],
+    )
+    return parser.parse_args()
+
+
+def get_app_info(base_url=None, app_sks=None, mode_type=None):
+    # 获取命令行参数
+    args = parse_arguments()
+    # 命令行参数优先，其次是函数参数，最后是默认值
+    if args.base_url is not None:
+        base_url = args.base_url
+    if base_url is None:
+        base_url = "http://192.168.2.236:3001/v1"
+
+    if args.app_sks is not None:
+        app_sks = args.app_sks
+    if app_sks is None:
+        app_sks = ["app-RBS0TuYEnqm8Q1cRQingkuhf"]
+
+    if args.mode_type is not None:
+        mode_type = args.mode_type
+    if mode_type is None:
+        mode_type = "workflow"
+
+    return base_url, app_sks, mode_type
+
+
+# 初始化服务器和Dify API
+base_url, dify_app_sks, dify_app_mode_type = get_app_info()
+server = Server("dify_mcp_server")
+task_instance = TaskInstance(base_url, dify_app_sks, dify_app_mode_type)
+dify_api = task_instance.get_task_instance(dify_app_mode_type)
+
+# 创建工具
+file_config = {
+    "file_fields": {},  # 字典，key为工具名称，value为该工具的文件字段列表
+    "file_type_dicts": {}  # 字典，key为工具名称，value为该工具的文件类型字典
+}
+
+
+@server.list_tools()
+async def handle_list_tools() -> list[types.Tool]:
+    """
+    列出可用的工具
+    返回:
+        工具列表，每个工具都使用JSON Schema验证其参数
+    """
+    tools = []
+    tool_names = dify_api.dify_app_names
+    tool_infos = dify_api.dify_app_infos
+    tool_params = dify_api.dify_app_params
+    tool_num = len(tool_names)
+    for i in range(tool_num):
+        # 加载每个工具的应用信息
+        app_info = tool_infos[i]
+        # 加载每个工具的应用参数
+        app_param = tool_params[i]
+        
+        # 记录 parameters API 返回的原始数据
+        logger.info(f"工具 {app_info['name']} 的 parameters 数据: {app_param}")
+        
+        # 处理用户输入表单
+        inputSchema = process_user_input_form(app_param["user_input_form"])
+        # 提取所有文件字段并存储到全局字典中
+        tool_file_fields = extract_file_fields(app_param["user_input_form"])
+        logger.info(f"工具 {app_info['name']} 提取的文件字段: {tool_file_fields}")
+        file_config["file_fields"][app_info["name"]] = tool_file_fields
+
+        
+
+        tools.append(
+            types.Tool(
+                name=app_info["name"],
+                description=app_info["description"],
+                inputSchema=inputSchema,
+            )
+        )
+    return tools
+
+
+@server.call_tool()
+async def handle_call_tool(
+    name: str, arguments: dict | None
+) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
+    """
+    调用工具处理请求
+    参数:
+        name: 工具名称
+        arguments: 工具参数
+    返回:
+        处理结果列表
+    """
+    tool_names = dify_api.dify_app_names
+    if name in tool_names:
+        tool_idx = tool_names.index(name)
+        tool_sk = dify_api.dify_app_sks[tool_idx]
+
+        # 获取当前工具的文件字段信息
+        current_tool_file_fields = file_config["file_fields"].get(name, [])
+        logger.info(f"工具 {name} 的文件字段信息: {current_tool_file_fields}")
+        logger.info(f"工具 {name} 调用前的 arguments: {arguments}")
+
+        # 使用工具函数处理文件字段
+        processed_arguments = process_file_arguments(arguments, current_tool_file_fields, dify_api, name)
+        logger.info(f"工具 {name} 处理后的 arguments: {processed_arguments}")
+
+        responses = dify_api.chat_message(
+            tool_sk,
+            inputs=processed_arguments,
+        )
+
+        # 初始化 outputs 变量，避免未定义错误
+        outputs = {}
+        for res in responses:
+            if res["event"] == "workflow_finished":
+                outputs = res["data"]["outputs"]
+                break  # 找到 workflow_finished 事件后退出循环
+        
+        # 构建 MCP 输出
+        mcp_out = []
+        if outputs:
+            for _, v in outputs.items():
+                mcp_out.append(types.TextContent(type="text", text=v))
+        else:
+            # 如果没有获取到 outputs，返回错误信息
+            logger.warning(f"工具 {name} 未获取到 workflow_finished 事件或 outputs 为空")
+            mcp_out.append(types.TextContent(type="text", text="工具执行完成，但未返回输出结果"))
+        
+        return mcp_out
+    else:
+        raise ValueError(f"Unknown tool: {name}")
+
+
+def run_main(transport="stdio"):
+    """
+    主函数：使用stdin/stdout流运行服务器
+    """
+    if transport == "stdio":
+        import anyio
+        from mcp.server.stdio import stdio_server
+
+        async def arun():
+            async with stdio_server() as streams:
+                await server.run(
+                    streams[0],
+                    streams[1],
+                    InitializationOptions(
+                        server_name="dify_mcp_server",
+                        server_version="0.0.6",
+                        capabilities=server.get_capabilities(
+                            notification_options=NotificationOptions(),
+                            experimental_capabilities={},
+                        ),
+                    ),
+                )
+
+        anyio.run(arun)
+
+    else:
+        from mcp.server.sse import SseServerTransport
+        from starlette.applications import Starlette
+        from starlette.responses import Response
+        from starlette.routing import Mount, Route
+
+        sse = SseServerTransport("/messages/")
+
+        async def handle_sse(request):
+            async with sse.connect_sse(
+                request.scope, request.receive, request._send
+            ) as streams:
+                await server.run(
+                    streams[0], streams[1], server.create_initialization_options()
+                )
+            return Response()
+
+        starlette_app = Starlette(
+            debug=True,
+            routes=[
+                Route("/sse", endpoint=handle_sse, methods=["GET"]),
+                Mount("/messages/", app=sse.handle_post_message),
+            ],
+        )
+
+        import uvicorn
+
+        uvicorn.run(starlette_app, host="0.0.0.0", port=8080, log_level="info")
+
+
+if __name__ == "__main__":
+    run_main()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/create_mcp_update.py

@@ -0,0 +1,320 @@
+import asyncio
+import json
+import os
+import logging
+import argparse
+from abc import ABC
+
+import mcp.server.stdio
+import mcp.types as types
+import requests
+from mcp.server import NotificationOptions, Server
+from mcp.server.models import InitializationOptions
+from omegaconf import OmegaConf
+
+# from src.workflow.workflow_server import WorkflowDifyAPI
+from src.difyTaskCall.task_instance import TaskInstance
+from src.utils.dify_workflow_schema import process_user_input_form
+# 配置日志记录
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger(__name__)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Dify MCP服务器配置")
+    parser.add_argument(
+        "--base-url",
+        type=str,
+        help="API基础URL",
+        default="http://192.168.2.236:3001/v1",
+    )
+    parser.add_argument(
+        "--app-sks",
+        nargs="+",
+        help="应用秘钥列表",
+        default=["app-XaRWpeL2Yfdguc5ul3ScXvPE"],
+    )
+    parser.add_argument(
+        "--mode-type",
+        type=str,
+        help="Dify应用模式类型 (workflow, chat, completion)",
+        default="workflow",
+        choices=["workflow", "chat", "completion"],
+    )
+    return parser.parse_args()
+
+
+def get_app_info(base_url=None, app_sks=None, mode_type=None):
+    # 获取命令行参数
+    args = parse_arguments()
+    # 命令行参数优先，其次是函数参数，最后是默认值
+    if args.base_url is not None:
+        base_url = args.base_url
+    if base_url is None:
+        base_url = "http://192.168.2.236:3001/v1"
+
+    if args.app_sks is not None:
+        app_sks = args.app_sks
+    if app_sks is None:
+        app_sks = ["app-XaRWpeL2Yfdguc5ul3ScXvPE"]
+
+    if args.mode_type is not None:
+        mode_type = args.mode_type
+    if mode_type is None:
+        mode_type = "workflow"
+
+    return base_url, app_sks, mode_type
+
+
+# 初始化服务器和Dify API
+base_url, dify_app_sks, dify_app_mode_type = get_app_info()
+server = Server("dify_mcp_server")
+task_instance = TaskInstance(base_url, dify_app_sks, dify_app_mode_type)
+dify_api = task_instance.get_task_instance(dify_app_mode_type)
+
+
+def process_user_input_form1(user_input_form):
+    """
+    处理Dify应用的用户输入表单，转换为JSON Schema格式
+
+    参数:
+        user_input_form: Dify应用的用户输入表单配置
+
+    返回:
+        处理后的inputSchema字典
+    """
+    inputSchema = dict(
+        type="object",
+        properties={},
+        required=[],
+    )
+
+    property_num = len(user_input_form)
+    if property_num > 0:
+        for j in range(property_num):
+            param = user_input_form[j]
+            param_type = list(param.keys())[0]
+            param_info = param[param_type]
+            property_name = param_info["variable"]
+
+            # 根据不同控件类型处理
+            if param_type == "text-input":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "paragraph":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                    "format": "paragraph",
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "select":
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                    "enum": param_info["options"],
+                }
+                if "default" in param_info:
+                    inputSchema["properties"][property_name]["default"] = param_info[
+                        "default"
+                    ]
+
+            elif param_type == "file_upload":
+                # 文件上传控件处理
+                file_type_schema = {
+                    "type": "object",
+                    "description": param_info["label"],
+                    "properties": {
+                        "file_url": {"type": "string", "description": "文件URL"},
+                        "file_name": {"type": "string", "description": "文件名称"},
+                    },
+                    "required": ["file_url"],
+                }
+
+                # 处理图片上传配置
+                if "image" in param_info and param_info["image"]["enabled"]:
+                    image_config = param_info["image"]
+                    file_type_schema["properties"]["type"] = {
+                        "type": "string",
+                        "description": "文件类型，支持png、jpg、jpeg、webp、gif",
+                        "enum": ["png", "jpg", "jpeg", "webp", "gif"],
+                    }
+
+                    # 处理数量限制
+                    number_limits = image_config.get("number_limits", 3)
+                    if number_limits > 1:
+                        # 如果允许多个文件，则使用数组
+                        inputSchema["properties"][property_name] = {
+                            "type": "array",
+                            "description": param_info["label"],
+                            "items": file_type_schema,
+                            "maxItems": number_limits,
+                        }
+                    else:
+                        # 如果只允许单个文件
+                        inputSchema["properties"][property_name] = file_type_schema
+                else:
+                    # 如果没有特定的图片配置，使用一般文件配置
+                    inputSchema["properties"][property_name] = file_type_schema
+
+            else:
+                # 默认处理为字符串类型
+                inputSchema["properties"][property_name] = {
+                    "type": "string",
+                    "description": param_info["label"],
+                }
+
+            # 处理必填字段
+            if param_info.get("required", False):
+                inputSchema["required"].append(property_name)
+
+    # 添加必填的userId参数，支持数字或字符串类型
+    inputSchema["properties"]["userId"] = dict(
+        oneOf=[{"type": "number"}, {"type": "string"}],
+        description="您的员工ID，用于识别您的员工身份",
+    )
+    inputSchema["required"].append("userId")
+
+    return inputSchema
+
+
+@server.list_tools()
+async def handle_list_tools() -> list[types.Tool]:
+    """
+    列出可用的工具
+    返回:
+        工具列表，每个工具都使用JSON Schema验证其参数
+    """
+    tools = []
+    tool_names = dify_api.dify_app_names
+    tool_infos = dify_api.dify_app_infos
+    tool_params = dify_api.dify_app_params
+    tool_num = len(tool_names)
+    for i in range(tool_num):
+        # 加载每个工具的应用信息
+        app_info = tool_infos[i]
+        # 加载每个工具的应用参数
+        app_param = tool_params[i]
+        # 处理用户输入表单
+        inputSchema = process_user_input_form(app_param["user_input_form"])
+
+        tools.append(
+            types.Tool(
+                name=app_info["name"],
+                description=app_info["description"],
+                inputSchema=inputSchema,
+            )
+        )
+    return tools
+
+
+@server.call_tool()
+async def handle_call_tool(
+    name: str, arguments: dict | None
+) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
+    """
+    调用工具处理请求
+    参数:
+        name: 工具名称
+        arguments: 工具参数
+    返回:
+        处理结果列表
+    """
+    tool_names = dify_api.dify_app_names
+    if name in tool_names:
+        tool_idx = tool_names.index(name)
+        tool_sk = dify_api.dify_app_sks[tool_idx]
+
+        # 提取files参数，并创建不包含files的inputs对象
+        files = arguments.get("files", None) if arguments else None
+        inputs = {k: v for k, v in (arguments or {}).items() if k != "files"}
+
+        responses = dify_api.chat_message(
+            tool_sk,
+            inputs=inputs,
+            userId=arguments.get("userId", "pp666") if arguments else "pp666",
+            files=files,
+        )
+
+  
+        for res in responses:
+            if res["event"] == "workflow_finished":
+                outputs = res["data"]["outputs"]
+        mcp_out = []
+        for _, v in outputs.items():
+            mcp_out.append(types.TextContent(type="text", text=v))
+        return mcp_out
+    else:
+        raise ValueError(f"Unknown tool: {name}")
+
+
+def run_main(transport="stdio"):
+    """
+    主函数：使用stdin/stdout流运行服务器
+    """
+    if transport == "stdio":
+        import anyio
+        from mcp.server.stdio import stdio_server
+
+        async def arun():
+            async with stdio_server() as streams:
+                await server.run(
+                    streams[0],
+                    streams[1],
+                    InitializationOptions(
+                        server_name="dify_mcp_server",
+                        server_version="0.0.6",
+                        capabilities=server.get_capabilities(
+                            notification_options=NotificationOptions(),
+                            experimental_capabilities={},
+                        ),
+                    ),
+                )
+
+        anyio.run(arun)
+
+    else:
+        from mcp.server.sse import SseServerTransport
+        from starlette.applications import Starlette
+        from starlette.responses import Response
+        from starlette.routing import Mount, Route
+
+        sse = SseServerTransport("/messages/")
+
+        async def handle_sse(request):
+            async with sse.connect_sse(
+                request.scope, request.receive, request._send
+            ) as streams:
+                await server.run(
+                    streams[0], streams[1], server.create_initialization_options()
+                )
+            return Response()
+
+        starlette_app = Starlette(
+            debug=True,
+            routes=[
+                Route("/sse", endpoint=handle_sse, methods=["GET"]),
+                Mount("/messages/", app=sse.handle_post_message),
+            ],
+        )
+
+        import uvicorn
+
+        uvicorn.run(starlette_app, host="0.0.0.0", port=8080, log_level="info")
+
+
+if __name__ == "__main__":
+    run_main()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/create_mcp_utils.py

@@ -0,0 +1,326 @@
+"""
+MCP创建工具的辅助函数模块
+
+包含文件字段处理、参数预处理等功能
+"""
+
+import logging
+import re
+from urllib.parse import urlparse
+import os
+from src.utils.logger_config import get_logger
+
+logger = get_logger(__name__)
+
+file_type_details = {
+        "document": {
+            "extensions": "TXT, MD, MARKDOWN, PDF, HTML, XLSX, XLS, DOCX, CSV, EML, MSG, PPTX, PPT, XML, EPUB",
+            "description": "文档文件"
+        },
+        "image": {
+            "extensions": "JPG, JPEG, PNG, GIF, WEBP, SVG",
+            "description": "图片文件"
+        },
+        "audio": {
+            "extensions": "MP3, M4A, WAV, WEBM, AMR",
+            "description": "音频文件"
+        },
+        "video": {
+            "extensions": "MP4, MOV, MPEG, MPGA",
+            "description": "视频文件"
+        },
+        "custom": {
+            "extensions": "",
+            "description": "其他文件类型"
+        }
+    }
+
+def process_file_arguments(arguments, current_tool_file_fields, dify_api, tool_name):
+    """
+    处理arguments中的文件类型字段
+
+    Args:
+        arguments (dict): 工具调用的参数字典
+        current_tool_file_fields (list): 当前工具的文件字段信息列表
+            数据结构: [{'variable': 'txt', 'label': '输入', 'required': True, 'max_length': 48,
+                      'allowed_file_types': ['document'], 'allowed_file_upload_methods': ['local_file', 'remote_url'],
+                      'allowed_file_extensions': []}]
+        dify_api: Dify API实例，包含file_parameter_pretreatment方法
+        tool_name (str): 工具名称，用于日志记录
+
+    Returns:
+        dict: 处理后的arguments字典
+
+    Raises:
+        Exception: 当文件处理过程中发生严重错误时抛出
+    """
+    if not arguments or not current_tool_file_fields:
+        logger.info(f"工具 {tool_name}: 无需处理文件字段 (arguments={bool(arguments)}, file_fields={len(current_tool_file_fields) if current_tool_file_fields else 0})")
+        return arguments
+
+    # 创建文件字段变量名的集合，用于快速查找
+    file_field_variables = {field['variable'] for field in current_tool_file_fields}
+    logger.info(f"工具 {tool_name} 的文件字段变量名: {file_field_variables}")
+
+    # 创建arguments的副本，避免修改原始数据
+    processed_arguments = arguments.copy()
+
+    # 处理arguments中的文件字段
+    for arg_name, arg_value in arguments.items():
+        # 检查参数名是否是文件字段
+        if arg_name in file_field_variables:
+            logger.info(f"工具 {tool_name}: 发现文件字段 {arg_name}，值: {arg_value}")
+
+            # 检查参数值是否包含文件信息
+            files_to_process = _extract_files_from_argument(arg_value, arg_name, tool_name)
+
+            if not files_to_process:
+                logger.info(f"工具 {tool_name}: 字段 {arg_name} 不是文件格式，跳过处理")
+                continue
+
+            # 调用文件预处理方法
+            try:
+
+                logger.info(f"工具 {tool_name}: 准备处理文件列表: {files_to_process}")
+
+                # 为每个文件对象添加必要的字段
+                for file_obj in files_to_process:
+                    # 设置传输方式为 remote_url（从URL下载并上传）
+                    if 'transfer_method' not in file_obj:
+                        file_obj['transfer_method'] = 'remote_url'
+                    
+                    # 自动识别文件类型
+                    if 'type' not in file_obj and 'url' in file_obj:
+                        file_obj['type'] = get_file_type_from_url(file_obj['url'])
+                        logger.info(f"工具 {tool_name}: 自动识别文件类型为 {file_obj['type']}")
+
+                # 调用文件预处理：下载文件并上传到Dify，获取upload_file_id
+                processed_files = dify_api.file_parameter_pretreatment(files_to_process)
+
+                if not processed_files or len(processed_files) == 0:
+                    logger.error(f"工具 {tool_name}: 文件预处理失败，未返回有效结果")
+                    continue
+
+                # 取第一个处理后的文件对象
+                processed_files_item = processed_files[0]
+                logger.info(f"工具 {tool_name}: 文件预处理完成，upload_file_id: {processed_files_item.get('upload_file_id', 'N/A')}")
+
+                # 更新processed_arguments中的值
+                _update_processed_argument(processed_arguments, arg_name, arg_value, processed_files_item, tool_name)
+
+            except Exception as e:
+                logger.error(f"工具 {tool_name}: 处理文件字段 {arg_name} 时发生错误: {str(e)}")
+                # 继续执行，不中断整个流程
+                continue
+
+    return processed_arguments
+
+
+def _extract_files_from_argument(arg_value, arg_name, tool_name):
+    """
+    从参数值中提取文件信息
+
+    Args:
+        arg_value: 参数值（可以是字符串URL、文件对象或文件列表）
+        arg_name (str): 参数名称
+        tool_name (str): 工具名称
+
+    Returns:
+        list: 文件列表，如果不是文件格式则返回None
+    """
+    # 情况1: 单个字符串URL
+    if isinstance(arg_value, str):
+        # 检查是否是有效的URL
+        if arg_value.startswith(('http://', 'https://')):
+            file_obj = {'url': arg_value}
+            logger.info(f"工具 {tool_name}: 将字符串URL转换为文件对象: {file_obj}")
+            return [file_obj]
+        else:
+            logger.warning(f"工具 {tool_name}: 字符串不是有效的URL: {arg_value}")
+            return None
+    
+    # 情况2: 单个文件对象
+    if isinstance(arg_value, dict) and _is_file_object(arg_value):
+        files_to_process = [arg_value]
+        logger.info(f"工具 {tool_name}: 处理单个文件对象: {files_to_process}")
+        return files_to_process
+
+    # 情况3: 文件列表
+    elif isinstance(arg_value, list) and len(arg_value) > 0:
+        # 检查列表中是否包含文件对象或URL字符串
+        valid_files = []
+        for item in arg_value:
+            if isinstance(item, dict) and _is_file_object(item):
+                valid_files.append(item)
+            elif isinstance(item, str) and item.startswith(('http://', 'https://')):
+                valid_files.append({'url': item})
+        
+        if valid_files:
+            logger.info(f"工具 {tool_name}: 处理文件列表: {valid_files}")
+            return valid_files
+
+    return None
+
+
+def _is_file_object(obj):
+    """
+    判断对象是否是文件对象
+
+    Args:
+        obj (dict): 要检查的对象
+
+    Returns:
+        bool: 如果是文件对象返回True，否则返回False
+    """
+    if not isinstance(obj, dict):
+        return False
+
+    # 检查是否包含文件对象的关键字段
+    file_indicators = ['type', 'transfer_method', 'url', 'upload_file_id', 'file_url', 'file_name']
+    return any(key in obj for key in file_indicators)
+
+
+def _update_processed_argument(processed_arguments, arg_name, original_value, processed_files, tool_name):
+    """
+    更新处理后的参数值
+    
+    重要：Dify API 的文件字段始终需要一个文件对象列表，即使只有一个文件
+
+    Args:
+        processed_arguments (dict): 处理后的参数字典
+        arg_name (str): 参数名称
+        original_value: 原始参数值（可以是字符串URL、文件对象或文件列表）
+        processed_files: 处理后的文件对象（单个对象，不是列表）
+        tool_name (str): 工具名称
+    """
+    # 注意：processed_files 是单个文件对象，需要转换为列表
+    # 因为 Dify API 要求文件字段必须是列表格式
+    if processed_files:
+        # 始终将文件对象包装成列表
+        processed_arguments[arg_name] = [processed_files]
+        logger.info(f"工具 {tool_name}: 已更新文件字段 {arg_name} 为列表格式: {processed_arguments[arg_name]}")
+    else:
+        logger.warning(f"工具 {tool_name}: 文件处理后为空，保持原值")
+
+    logger.info(f"工具 {tool_name}: 字段 {arg_name} 最终值: {processed_arguments[arg_name]}")
+
+
+def validate_file_field_configuration(file_fields, tool_name):
+    """
+    验证文件字段配置的有效性
+
+    Args:
+        file_fields (list): 文件字段配置列表
+        tool_name (str): 工具名称
+
+    Returns:
+        bool: 配置是否有效
+    """
+    if not file_fields:
+        return True
+
+    for field in file_fields:
+        if not isinstance(field, dict):
+            logger.warning(f"工具 {tool_name}: 文件字段配置不是字典格式: {field}")
+            return False
+
+        if 'variable' not in field or not field['variable']:
+            logger.warning(f"工具 {tool_name}: 文件字段缺少variable字段: {field}")
+            return False
+
+    return True
+
+
+def get_file_field_summary(file_fields, tool_name):
+    """
+    获取文件字段的摘要信息
+
+    Args:
+        file_fields (list): 文件字段配置列表
+        tool_name (str): 工具名称
+
+    Returns:
+        dict: 文件字段摘要信息
+    """
+    if not file_fields:
+        return {
+            'count': 0,
+            'variables': [],
+            'required_count': 0,
+            'optional_count': 0
+        }
+
+    variables = [field.get('variable', '') for field in file_fields if field.get('variable')]
+    required_count = sum(1 for field in file_fields if field.get('required', False))
+    optional_count = len(file_fields) - required_count
+
+    summary = {
+        'count': len(file_fields),
+        'variables': variables,
+        'required_count': required_count,
+        'optional_count': optional_count
+    }
+
+    logger.info(f"工具 {tool_name} 文件字段摘要: {summary}")
+    return summary
+
+
+def get_file_type_from_url(url):
+    """
+    根据URL地址返回文件类型
+
+    Args:
+        url (str): 文件的URL地址
+
+    Returns:
+        str: 文件类型 ('document', 'image', 'audio', 'video', 'custom')
+
+    Examples:
+        >>> get_file_type_from_url("http://example.com/file.pdf")
+        'document'
+        >>> get_file_type_from_url("http://example.com/image.jpg")
+        'image'
+        >>> get_file_type_from_url("http://example.com/video.mp4")
+        'video'
+    """
+    if not url or not isinstance(url, str):
+        logger.warning(f"无效的URL: {url}")
+        return 'custom'
+
+    try:
+        # 解析URL获取路径
+        parsed_url = urlparse(url)
+        path = parsed_url.path
+
+        # 从路径中提取文件扩展名
+        file_extension = os.path.splitext(path)[1].lower().lstrip('.')
+
+        # 如果没有扩展名，尝试从查询参数中提取
+        if not file_extension:
+            # 使用正则表达式匹配常见的文件扩展名模式
+            extension_pattern = r'\.([a-zA-Z0-9]{2,5})(?:\?|$|&)'
+            match = re.search(extension_pattern, url)
+            if match:
+                file_extension = match.group(1).lower()
+
+        logger.info(f"从URL {url} 提取的文件扩展名: {file_extension}")
+
+        # 根据扩展名判断文件类型
+        for file_type, details in file_type_details.items():
+            if file_type == 'custom':
+                continue
+
+            # 将支持的扩展名转换为小写列表
+            supported_extensions = [ext.strip().lower() for ext in details['extensions'].split(',')]
+
+            if file_extension in supported_extensions:
+                logger.info(f"URL {url} 匹配文件类型: {file_type}")
+                return file_type
+
+        # 如果没有匹配到任何类型，返回custom
+        logger.info(f"URL {url} 未匹配到已知文件类型，返回custom")
+        return 'custom'
+
+    except Exception as e:
+        logger.error(f"解析URL {url} 时发生错误: {str(e)}")
+        return 'custom'

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/difyTaskCall/task_instance.py

@@ -0,0 +1,53 @@
+from abc import ABC
+
+
+# class   WorkflowDifyAPI和chatDifyApi和completionDifyApi
+# dify_app_mode_type  ：workflow, chat, completion
+
+
+class TaskInstance(ABC):
+    def __init__(self, base_url, dify_app_sks, dify_app_mode_type):
+        self.base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.dify_app_mode_type = dify_app_mode_type
+
+    def get_task_instance(self, task_id: str):
+        """
+        根据dify_app_mode_type返回相应的API实例
+
+        Args:
+            task_id: 任务ID
+
+        Returns:
+            返回对应的API实例
+
+        Raises:
+            ValueError: 当dify_app_mode_type无效时抛出异常
+        """
+        from src.workflow.workflow_server import WorkflowDifyAPI
+        from src.completion.completion_server import CompletionDifyAPI
+        from src.chat.chat_server import ChatDifyAPI
+
+        # 使用字典映射提高代码灵活性和可维护性
+        api_classes = {
+            "workflow": WorkflowDifyAPI,
+            "chat": ChatDifyAPI,
+            "completion": CompletionDifyAPI,
+        }
+
+        # 检查mode_type是否有效
+        if self.dify_app_mode_type.lower() not in api_classes:
+            supported_types = ", ".join(api_classes.keys())
+            raise ValueError(
+                f"不支持的dify_app_mode_type: {self.dify_app_mode_type}，支持的类型: {supported_types}"
+            )
+
+        # 获取对应的API类
+        api_class = api_classes[self.dify_app_mode_type.lower()]
+
+        # 这里假设所有API类都接受相同的参数集
+        # 如果各API类构造函数参数不同，需要针对每种类型单独处理
+        return api_class(
+            self.base_url,
+            self.dify_app_sks,
+        )

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/utils/dify_workflow_schema.py

@@ -0,0 +1,399 @@
+
+
+import json
+import logging
+
+# 获取日志器
+logger = logging.getLogger(__name__)
+
+data={
+    "user_input_form": [
+        {
+            "file": {
+                "variable": "files",
+                "label": "files",
+                "type": "file",
+                "max_length": 48,
+                "required": True,
+                "options": [],
+                "allowed_file_upload_methods": [
+                    "local_file",
+                    "remote_url"
+                ],
+                "allowed_file_types": [
+                    "image",
+                    "document"
+                ],
+                "allowed_file_extensions": []
+            }
+        }
+    ],
+
+}
+
+
+data2={
+    "user_input_form": [
+        {
+            "paragraph": {
+                "label": "产品名称",
+                "max_length": 33024,
+                "options": [],
+                "required": True,
+                "type": "paragraph",
+                "variable": "name"
+            }
+        },
+        {
+            "paragraph": {
+                "label": "补充描述",
+                "max_length": 33024,
+                "options": [],
+                "required": False,
+                "type": "paragraph",
+                "variable": "desc"
+            }
+        }
+    ],
+}
+
+data3={
+    "user_input_form": [
+        {
+            "file": {
+                "allowed_file_extensions": [],
+                "allowed_file_types": [
+                    "document","image"
+                ],
+                "allowed_file_upload_methods": [
+                    "local_file",
+                    "remote_url"
+                ],
+                "label": "输入",
+                "max_length": 48,
+                "options": [],
+                "required": True,
+                "type": "file",
+                "variable": "txt"
+            }
+        }
+    ]
+}
+
+def generate_file_type_description(allowed_file_types):
+    """
+    根据allowed_file_types生成文件类型描述
+
+    参数:
+        allowed_file_types (list): 允许的文件类型列表
+
+    返回:
+        str: 生成的文件类型描述
+    """
+    # 定义各种文件类型的具体格式和中文描述
+    file_type_details = {
+        "document": {
+            "extensions": "TXT, MD, MARKDOWN, PDF, HTML, XLSX, XLS, DOCX, CSV, EML, MSG, PPTX, PPT, XML, EPUB",
+            "description": "文档文件"
+        },
+        "image": {
+            "extensions": "JPG, JPEG, PNG, GIF, WEBP, SVG",
+            "description": "图片文件"
+        },
+        "audio": {
+            "extensions": "MP3, M4A, WAV, WEBM, AMR",
+            "description": "音频文件"
+        },
+        "video": {
+            "extensions": "MP4, MOV, MPEG, MPGA",
+            "description": "视频文件"
+        },
+        "custom": {
+            "extensions": "",
+            "description": "其他文件类型"
+        }
+    }
+
+    if not allowed_file_types or len(allowed_file_types) == 0:
+        return "请提供有效的文件URL地址"
+
+    # 生成描述
+    descriptions = []
+    all_extensions = []
+
+    for file_type in allowed_file_types:
+        if file_type in file_type_details:
+            detail = file_type_details[file_type]
+            if detail["extensions"]:
+                descriptions.append(f"{detail['description']}({detail['extensions']})")
+                all_extensions.extend(detail["extensions"].split(", "))
+            else:
+                descriptions.append(detail["description"])
+
+    if descriptions:
+        if len(descriptions) == 1:
+            return f"请提供{descriptions[0]}的URL地址"
+        else:
+            return f"请提供文件URL地址，支持的文件类型：{' | '.join(descriptions)}"
+    else:
+        return "请提供有效的文件URL地址"
+
+
+def process_user_input_form(user_input_form):
+    """
+    处理Dify应用的用户输入表单，转换为JSON Schema格式
+
+    支持的控件类型:
+    - text-input (object): 文本输入控件
+      * label (string): 控件展示标签名
+      * variable (string): 控件 ID
+      * required (bool): 是否必填
+      * default (string): 默认值
+
+    - paragraph (object): 段落文本输入控件
+      * label (string): 控件展示标签名
+      * variable (string): 控件 ID
+      * required (bool): 是否必填
+      * default (string): 默认值
+
+    - select (object): 下拉控件
+      * label (string): 控件展示标签名
+      * variable (string): 控件 ID
+      * required (bool): 是否必填
+      * default (string): 默认值
+      * options (array[string]): 选项值
+
+    - file (object): 文件上传控件 (支持复杂的文件处理逻辑)
+
+    参数:
+        user_input_form (array[object]): 用户输入表单配置
+
+    返回:
+        dict: 处理后的inputSchema字典，符合JSON Schema规范
+    """
+    # 初始化基础schema结构
+    inputSchema = {
+        "type": "object",
+        "properties": {},
+        "required": [],
+    }
+
+    # 如果没有用户输入表单配置，跳过处理
+    if not user_input_form or len(user_input_form) == 0:
+        pass
+    else:
+        # 遍历处理每个表单控件
+        for form_item in user_input_form:
+            # 检查form_item是否为None或空
+            if not form_item or not isinstance(form_item, dict):
+                continue
+
+            # 获取控件类型和配置信息
+            control_type = list(form_item.keys())[0]
+            logger.debug(f"处理控件类型: {control_type}")
+            control_config = form_item[control_type]
+
+            # 检查control_config是否为None
+            if not control_config or not isinstance(control_config, dict):
+                continue
+
+            # 提取控件基础属性
+            variable = control_config.get("variable", "")
+            label = control_config.get("label", "")
+            required = control_config.get("required", False)
+            default_value = control_config.get("default")
+
+            # 跳过没有variable的无效控件
+            if not variable:
+                continue
+
+            # 根据控件类型进行相应处理
+            property_schema = None
+
+            if control_type == "text-input":
+                # 文本输入控件处理
+                property_schema = {
+                    "type": "string",
+                    "description": label or f"文本输入字段: {variable}",
+                }
+                # 设置默认值
+                if default_value is not None:
+                    property_schema["default"] = str(default_value)
+
+            elif control_type == "paragraph":
+                # 段落文本输入控件处理
+                property_schema = {
+                    "type": "string",
+                    "description": label or f"段落文本字段: {variable}",
+                    "format": "textarea",  # 标识为多行文本输入
+                }
+                # 设置默认值
+                if default_value is not None:
+                    property_schema["default"] = str(default_value)
+
+            elif control_type == "select":
+                # 下拉控件处理
+                options = control_config.get("options", [])
+                property_schema = {
+                    "type": "string",
+                    "description": label or f"下拉选择字段: {variable}",
+                }
+
+                # 设置选项枚举值
+                if options and len(options) > 0:
+                    property_schema["enum"] = options
+
+                # 设置默认值
+                if default_value is not None:
+                    property_schema["default"] = str(default_value)
+
+            elif control_type == "file":
+                # 文件上传控件处理 - 简化版本，仅支持remote_url
+                # 获取允许的文件类型
+                allowed_file_types = control_config.get("allowed_file_types", [])
+
+                # 生成动态的URL描述
+                url_description = generate_file_type_description(allowed_file_types)
+
+                file_schema = {
+                    "type": "object",
+                    "description": label or f"文件上传字段: {variable}",
+                    "properties": {
+                        # "type": {
+                        #     "type": "string",
+                        #     "description": file_type_desc
+                        # },
+                        # "transfer_method": {
+                        #     "type": "string",
+                        #     "description": "文件传输方式",
+                        #     "enum": ["remote_url"],
+                        #     "default": "remote_url"
+                        # },
+                        "url": {
+                            "type": "string",
+                            "description": url_description
+                        }
+                    },
+                    "required": [ "url"]
+                }
+
+                # 处理文件数量限制
+                max_length = control_config.get("max_length", 1)
+                if max_length > 1:
+                    # 多文件上传场景
+                    property_schema = {
+                        "type": "array",
+                        "description": label or f"多文件上传字段: {variable}",
+                        "items": file_schema,
+                        "maxItems": max_length,
+                        "minItems": 1 if required else 0
+                    }
+                else:
+                    # 单文件上传场景
+                    property_schema = file_schema
+
+            else:
+                # 未知控件类型的默认处理
+                property_schema = {
+                    "type": "string",
+                    "description": label or f"未知类型字段: {variable} (类型: {control_type})",
+                }
+                if default_value is not None:
+                    property_schema["default"] = str(default_value)
+
+            # 将处理后的属性添加到schema中
+            if property_schema:
+                inputSchema["properties"][variable] = property_schema
+
+            # 处理必填字段约束
+            if required:
+                inputSchema["required"].append(variable)
+
+
+
+    return inputSchema
+
+
+def extract_file_fields(user_input_form):
+    """
+    从用户输入表单中提取所有type为file的字段信息
+
+    参数:
+        user_input_form (array[object]): 用户输入表单配置
+
+    返回:
+        list: 包含所有file类型字段信息的列表，每个元素包含：
+            - variable (str): 字段变量名
+            - label (str): 字段标签
+            - required (bool): 是否必填
+            - max_length (int): 最大文件数量
+            - allowed_file_types (list): 允许的文件类型
+            - allowed_file_upload_methods (list): 允许的上传方式
+            - allowed_file_extensions (list): 允许的文件扩展名
+    """
+    file_fields = []
+
+    # 如果没有用户输入表单配置，返回空列表
+    if not user_input_form or len(user_input_form) == 0:
+        return file_fields
+
+    # 遍历处理每个表单控件
+    for form_item in user_input_form:
+        # 检查form_item是否为None或空
+        if not form_item or not isinstance(form_item, dict):
+            continue
+
+        # 获取控件类型和配置信息
+        control_type = list(form_item.keys())[0]
+        control_config = form_item[control_type]
+
+        # 检查control_config是否为None
+        if not control_config or not isinstance(control_config, dict):
+            continue
+
+        # 只处理type为file或file-list的字段
+        if control_type in ["file", "file-list"] or control_config.get("type") in ["file", "file-list"]:
+            # 提取文件字段的详细信息
+            file_field_info = {
+                "variable": control_config.get("variable", ""),
+                "label": control_config.get("label", ""),
+                "required": control_config.get("required", False),
+                "max_length": control_config.get("max_length", 1),
+                "allowed_file_types": control_config.get("allowed_file_types", []),
+                "allowed_file_upload_methods": control_config.get("allowed_file_upload_methods", []),
+                "allowed_file_extensions": control_config.get("allowed_file_extensions", [])
+            }
+
+            # 只添加有效的字段（必须有variable）
+            if file_field_info["variable"]:
+                file_fields.append(file_field_info)
+
+    return file_fields
+
+
+if __name__ == "__main__":
+    # run_main()
+    result = process_user_input_form(data3["user_input_form"])
+    print("开始生成 Schema...", result)
+
+    # 保存到当前目录下的JSON文件
+    output_file = "process_user_input_form_output.json"
+    with open(output_file, 'w', encoding='utf-8') as f:
+        json.dump(result, f, ensure_ascii=False, indent=2)
+
+    # print(f"结果已保存到: {output_file}")
+
+    # # 测试新的extract_file_fields方法
+    # print("\n=== 测试 extract_file_fields 方法 ===")
+
+    # # 测试data（包含file字段）
+    # file_fields_data = extract_file_fields(data["user_input_form"])
+    # print("data中的file字段:", file_fields_data)
+
+    # # 测试data2（不包含file字段）
+    # file_fields_data2 = extract_file_fields(data2["user_input_form"])
+    # print("data2中的file字段:", file_fields_data2)
+
+    # 测试data3（包含file字段）
+    # file_fields_data3 = extract_file_fields(data3["user_input_form"])
+    # print("data3中的file字段:", file_fields_data3)

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/utils/logger_config.py

@@ -0,0 +1,552 @@
+"""
+统一日志配置模块
+
+这个模块提供了整个项目的统一日志配置和管理功能，确保所有组件使用一致的日志格式和输出方式。
+
+主要功能:
+1. 统一的日志格式配置
+2. 支持控制台和文件双重输出
+3. 日志文件轮转管理
+4. MCP模式下的特殊处理（禁用控制台输出）
+5. 便捷的日志器获取接口
+6. 丰富的日志工具函数
+
+设计特点:
+- 单例模式确保配置一致性
+- 支持动态配置调整
+- 异常安全的编码处理
+- 详细的调试信息记录
+
+作者: lzwcai
+版本: 1.0.0
+"""
+
+import logging
+import logging.handlers
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import Optional
+
+
+class LoggerConfig:
+    """
+    日志配置管理器
+
+    这个类采用单例模式管理整个项目的日志配置。
+    它提供了统一的日志格式、文件轮转、编码处理等功能。
+
+    主要特性:
+    - 单例模式：确保全局日志配置一致
+    - 双重输出：同时支持控制台和文件输出
+    - 文件轮转：自动管理日志文件大小和数量
+    - 编码安全：正确处理中文字符
+    - MCP兼容：支持MCP模式下的特殊需求
+
+    配置参数:
+        DEFAULT_LOG_LEVEL: 默认日志级别（INFO）
+        DEFAULT_LOG_FORMAT: 日志格式模板
+        DEFAULT_DATE_FORMAT: 时间格式
+        LOG_FILE_NAME: 日志文件名
+        MAX_LOG_SIZE: 单个日志文件最大大小（10MB）
+        BACKUP_COUNT: 保留的备份文件数量（5个）
+    """
+
+    # ==================== 默认配置常量 ====================
+
+    # 默认日志级别：INFO级别平衡了信息量和性能
+    DEFAULT_LOG_LEVEL = logging.INFO
+
+    # 默认日志格式：包含时间、模块名、级别、文件位置、消息内容
+    DEFAULT_LOG_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - [%(filename)s:%(lineno)d] - %(message)s"
+
+    # 默认时间格式：标准的年-月-日 时:分:秒格式
+    DEFAULT_DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
+
+    # ==================== 日志文件配置 ====================
+
+    # 日志文件名：使用项目名称作为前缀
+    LOG_FILE_NAME = "lzwcai_demp_tool_server_dify_to_mcp_test.log"
+
+    # 单个日志文件最大大小：10MB
+    MAX_LOG_SIZE = 10 * 1024 * 1024  # 10MB
+
+    # 保留的备份文件数量：5个（总共约50MB的日志存储）
+    BACKUP_COUNT = 5
+
+    # ==================== 单例模式状态 ====================
+
+    # 初始化标志：确保只初始化一次
+    _initialized = False
+
+    # 日志文件路径：记录当前使用的日志文件路径
+    _log_file_path = None
+    
+    @classmethod
+    def setup_logging(
+        cls,
+        log_level: int = DEFAULT_LOG_LEVEL,
+        log_file: Optional[str] = None,
+        console_output: bool = True,
+        file_output: bool = True
+    ) -> str:
+        """
+        设置项目统一日志配置
+
+        这是日志系统的核心初始化方法，负责配置整个项目的日志输出。
+        采用单例模式，确保在整个应用生命周期中只初始化一次。
+
+        配置流程:
+        1. 检查是否已经初始化（单例模式）
+        2. 确定日志文件路径（自动或手动指定）
+        3. 创建必要的目录结构
+        4. 配置根日志器和处理器
+        5. 设置日志格式化器
+        6. 添加控制台和文件处理器
+        7. 记录初始化信息
+
+        特殊处理:
+        - MCP模式下通常禁用控制台输出，避免干扰stdio通信
+        - Windows系统下的UTF-8编码处理
+        - 日志文件的自动轮转管理
+
+        参数:
+            log_level: 日志级别（DEBUG, INFO, WARNING, ERROR, CRITICAL）
+            log_file: 日志文件路径，None时使用默认路径
+            console_output: 是否输出到控制台（MCP模式下通常为False）
+            file_output: 是否输出到文件（通常为True）
+
+        返回:
+            str: 实际使用的日志文件路径
+
+        注意事项:
+        - 这个方法是线程安全的
+        - 重复调用会直接返回已配置的路径
+        - 日志文件会自动创建必要的目录
+        """
+        # 单例模式检查：如果已经初始化，直接返回
+        if cls._initialized:
+            return cls._log_file_path
+
+        # ==================== 日志文件路径配置 ====================
+
+        if log_file is None:
+            # 自动确定日志文件路径：项目根目录/logs/ + 默认文件名
+            project_root = cls._get_project_root()
+            logs_dir = project_root / "logs"
+            logs_dir.mkdir(parents=True, exist_ok=True)
+            log_file = logs_dir / cls.LOG_FILE_NAME
+        else:
+            # 使用指定的日志文件路径
+            log_file = Path(log_file)
+
+        # 确保日志目录存在（递归创建）
+        log_file.parent.mkdir(parents=True, exist_ok=True)
+        cls._log_file_path = str(log_file)
+
+        # ==================== 根日志器配置 ====================
+
+        # 配置根日志器，这样可以捕获所有模块的日志
+        root_logger = logging.getLogger()
+        root_logger.setLevel(log_level)
+
+        # 清除根日志器上现有的处理器，避免重复配置
+        for handler in root_logger.handlers[:]:
+            root_logger.removeHandler(handler)
+
+        # ==================== 日志格式化器 ====================
+
+        # 创建统一的日志格式化器
+        formatter = logging.Formatter(
+            fmt=cls.DEFAULT_LOG_FORMAT,      # 日志格式模板
+            datefmt=cls.DEFAULT_DATE_FORMAT  # 时间格式
+        )
+        
+        # ==================== 控制台处理器配置 ====================
+
+        if console_output:
+            # 控制台输出处理器，支持彩色输出和UTF-8编码
+            import io
+
+            # 处理Windows系统的编码问题
+            if hasattr(sys.stdout, 'buffer'):
+                # 在Windows上强制使用UTF-8编码，避免中文乱码
+                # errors='replace'确保即使有编码问题也不会崩溃
+                console_stream = io.TextIOWrapper(
+                    sys.stdout.buffer,
+                    encoding='utf-8',
+                    errors='replace'
+                )
+            else:
+                # Unix/Linux系统通常默认支持UTF-8
+                console_stream = sys.stdout
+
+            # 创建控制台处理器
+            console_handler = logging.StreamHandler(console_stream)
+            console_handler.setLevel(log_level)
+            console_handler.setFormatter(formatter)
+            root_logger.addHandler(console_handler)
+
+        # ==================== 文件处理器配置 ====================
+
+        if file_output:
+            # 文件输出处理器，支持自动轮转
+            file_handler = logging.handlers.RotatingFileHandler(
+                filename=cls._log_file_path,        # 日志文件路径
+                maxBytes=cls.MAX_LOG_SIZE,          # 单文件最大大小
+                backupCount=cls.BACKUP_COUNT,       # 备份文件数量
+                encoding='utf-8'                    # 文件编码
+            )
+            file_handler.setLevel(log_level)
+            file_handler.setFormatter(formatter)
+            root_logger.addHandler(file_handler)
+
+        # ==================== 初始化完成标记 ====================
+
+        # 标记为已初始化，防止重复配置
+        cls._initialized = True
+
+        # ==================== 记录初始化信息 ====================
+
+        # 获取当前模块的日志器并记录初始化信息
+        logger = logging.getLogger(__name__)
+        logger.info("=" * 80)
+        logger.info(f"日志系统初始化完成 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+        logger.info(f"日志级别: {logging.getLevelName(log_level)}")
+        logger.info(f"日志文件: {cls._log_file_path}")
+        logger.info(f"控制台输出: {console_output}")
+        logger.info(f"文件输出: {file_output}")
+        logger.info(f"文件轮转: 最大{cls.MAX_LOG_SIZE // (1024*1024)}MB, 保留{cls.BACKUP_COUNT}个备份")
+        logger.info("=" * 80)
+
+        return cls._log_file_path
+    
+    @classmethod
+    def _get_project_root(cls) -> Path:
+        """
+        获取项目根目录
+
+        这个方法通过向上遍历目录树来查找项目根目录。
+        它会寻找常见的项目标识文件来确定根目录位置。
+
+        查找策略:
+        1. 从当前文件所在目录开始向上查找
+        2. 寻找项目标识文件：pyproject.toml, setup.py, main.py
+        3. 找到任一标识文件的目录即为项目根目录
+        4. 如果都找不到，使用当前文件的上级目录作为备选
+
+        返回:
+            Path: 项目根目录的路径对象
+
+        注意事项:
+        - 这个方法假设项目结构相对标准
+        - 在特殊的部署环境中可能需要调整
+        - 备选方案确保总是返回有效路径
+        """
+        # 从当前文件向上查找项目根目录
+        current_path = Path(__file__).parent
+
+        # 向上遍历目录树
+        while current_path.parent != current_path:  # 避免到达文件系统根目录
+            # 检查常见的项目标识文件
+            if (current_path / "pyproject.toml").exists() or \
+               (current_path / "setup.py").exists() or \
+               (current_path / "main.py").exists():
+                return current_path
+            current_path = current_path.parent
+
+        # 备选方案：如果找不到标识文件，使用预设的相对路径
+        # 这个路径基于当前的项目结构：utils -> src -> 项目根
+        return Path(__file__).parent.parent.parent
+
+    @classmethod
+    def get_logger(cls, name: str) -> logging.Logger:
+        """
+        获取配置好的日志器
+
+        这是获取日志器的标准方法，确保返回的日志器使用统一的配置。
+        如果日志系统尚未初始化，会自动进行初始化。
+
+        参数:
+            name: 日志器名称，通常使用模块的 __name__ 变量
+
+        返回:
+            logging.Logger: 配置好的日志器实例
+
+        使用示例:
+            logger = LoggerConfig.get_logger(__name__)
+            logger.info("这是一条信息日志")
+
+        特性:
+        - 自动初始化：首次调用时自动配置日志系统（MCP模式下禁用控制台输出）
+        - 层次化命名：支持Python日志器的层次化命名
+        - 统一配置：所有日志器使用相同的格式和输出配置
+        """
+        # 检查是否已初始化，未初始化则使用默认配置初始化
+        # 重要：在MCP模式下禁用控制台输出，避免干扰stdio通信
+        if not cls._initialized:
+            cls.setup_logging(console_output=False, file_output=True)
+
+        # 返回指定名称的日志器
+        return logging.getLogger(name)
+    
+    # ==================== 日志工具方法 ====================
+
+    @classmethod
+    def log_function_entry(cls, logger: logging.Logger, func_name: str, **kwargs):
+        """
+        记录函数入口日志
+
+        用于调试和性能分析，记录函数被调用时的参数信息。
+        通常在DEBUG级别输出，不会影响生产环境的性能。
+
+        参数:
+            logger: 日志器实例
+            func_name: 函数名称
+            **kwargs: 函数参数（键值对形式）
+
+        使用示例:
+            LoggerConfig.log_function_entry(logger, "process_data", user_id=123, action="login")
+        """
+        args_str = ", ".join([f"{k}={v}" for k, v in kwargs.items()])
+        logger.debug(f"进入函数 {func_name}({args_str})")
+
+    @classmethod
+    def log_function_exit(cls, logger: logging.Logger, func_name: str, result=None):
+        """
+        记录函数出口日志
+
+        与log_function_entry配对使用，记录函数执行完成和返回值。
+        有助于跟踪函数执行流程和调试返回值问题。
+
+        参数:
+            logger: 日志器实例
+            func_name: 函数名称
+            result: 函数返回值（可选）
+
+        使用示例:
+            LoggerConfig.log_function_exit(logger, "process_data", result={"status": "success"})
+        """
+        if result is not None:
+            logger.debug(f"退出函数 {func_name}，返回值: {result}")
+        else:
+            logger.debug(f"退出函数 {func_name}")
+
+    @classmethod
+    def log_api_request(cls, logger: logging.Logger, method: str, url: str, **kwargs):
+        """
+        记录API请求日志
+
+        标准化API请求的日志记录，包含HTTP方法、URL和请求参数。
+        有助于API调用的监控和调试。
+
+        参数:
+            logger: 日志器实例
+            method: HTTP方法（GET, POST, PUT, DELETE等）
+            url: 请求URL
+            **kwargs: 请求参数（可选）
+
+        使用示例:
+            LoggerConfig.log_api_request(logger, "POST", "https://api.example.com/users",
+                                       headers={"Authorization": "Bearer xxx"})
+        """
+        logger.info(f"API请求 - {method} {url}")
+        if kwargs:
+            logger.debug(f"请求参数: {kwargs}")
+
+    @classmethod
+    def log_api_response(cls, logger: logging.Logger, status_code: int, response_time: float = None):
+        """
+        记录API响应日志
+
+        记录API响应的状态码和响应时间，用于性能监控和问题诊断。
+
+        参数:
+            logger: 日志器实例
+            status_code: HTTP状态码
+            response_time: 响应时间（秒，可选）
+
+        使用示例:
+            LoggerConfig.log_api_response(logger, 200, 0.156)
+        """
+        if response_time:
+            logger.info(f"API响应 - 状态码: {status_code}, 响应时间: {response_time:.3f}s")
+        else:
+            logger.info(f"API响应 - 状态码: {status_code}")
+
+    @classmethod
+    def log_error_with_context(cls, logger: logging.Logger, error: Exception, context: str = ""):
+        """
+        记录带上下文的错误日志
+
+        提供丰富的错误信息记录，包含异常类型、错误消息、上下文信息和详细堆栈。
+        这是错误处理的标准方法。
+
+        参数:
+            logger: 日志器实例
+            error: 异常对象
+            context: 错误发生的上下文描述（可选）
+
+        使用示例:
+            try:
+                risky_operation()
+            except Exception as e:
+                LoggerConfig.log_error_with_context(logger, e, "处理用户请求时")
+        """
+        if context:
+            logger.error(f"错误发生在 {context}: {type(error).__name__}: {str(error)}")
+        else:
+            logger.error(f"错误: {type(error).__name__}: {str(error)}")
+        # 记录详细的异常堆栈信息（仅在DEBUG级别显示）
+        logger.debug("错误详情:", exc_info=True)
+
+
+# ==================== 便捷函数 ====================
+
+def get_logger(name: str) -> logging.Logger:
+    """
+    获取日志器的便捷函数
+
+    这是LoggerConfig.get_logger的简化版本，提供更简洁的调用方式。
+    推荐在模块级别使用这个函数获取日志器。
+
+    参数:
+        name: 日志器名称，通常使用 __name__
+
+    返回:
+        logging.Logger: 配置好的日志器实例
+
+    使用示例:
+        logger = get_logger(__name__)
+    """
+    return LoggerConfig.get_logger(name)
+
+
+def setup_logging(**kwargs) -> str:
+    """
+    设置日志的便捷函数
+
+    这是LoggerConfig.setup_logging的简化版本，支持所有相同的参数。
+
+    参数:
+        **kwargs: 传递给LoggerConfig.setup_logging的所有参数
+
+    返回:
+        str: 日志文件路径
+
+    使用示例:
+        log_file = setup_logging(log_level=logging.DEBUG, console_output=False)
+    """
+    return LoggerConfig.setup_logging(**kwargs)
+
+
+# ==================== 装饰器 ====================
+
+def log_function_calls(logger: Optional[logging.Logger] = None):
+    """
+    函数调用日志装饰器
+
+    这个装饰器自动记录函数的调用和返回，包括参数和返回值。
+    主要用于调试和性能分析，在生产环境中通常设置为DEBUG级别。
+
+    特性:
+    - 自动记录函数入口和出口
+    - 记录函数参数（kwargs）
+    - 记录返回值
+    - 自动处理异常并记录错误上下文
+    - 支持自定义日志器或自动获取
+
+    参数:
+        logger: 可选的日志器实例，None时自动获取函数所在模块的日志器
+
+    返回:
+        装饰器函数
+
+    使用示例:
+        @log_function_calls()
+        def process_user_data(user_id, action="login"):
+            # 函数实现
+            return {"status": "success"}
+
+        # 或者指定日志器
+        @log_function_calls(logger=my_logger)
+        def another_function():
+            pass
+
+    注意事项:
+    - 会记录所有kwargs参数，注意不要记录敏感信息
+    - 返回值也会被记录，大对象可能影响性能
+    - 异常会被重新抛出，不会被吞掉
+    """
+    def decorator(func):
+        def wrapper(*args, **kwargs):
+            nonlocal logger
+            # 如果没有提供日志器，自动获取函数所在模块的日志器
+            if logger is None:
+                logger = get_logger(func.__module__)
+
+            func_name = func.__name__
+
+            # 记录函数入口（只记录kwargs，避免记录过多信息）
+            LoggerConfig.log_function_entry(logger, func_name, **kwargs)
+
+            try:
+                # 执行原函数
+                result = func(*args, **kwargs)
+
+                # 记录函数出口和返回值
+                LoggerConfig.log_function_exit(logger, func_name, result)
+                return result
+
+            except Exception as e:
+                # 记录异常信息并重新抛出
+                LoggerConfig.log_error_with_context(logger, e, f"函数 {func_name}")
+                raise
+
+        return wrapper
+    return decorator
+
+
+# ==================== 测试代码 ====================
+
+if __name__ == "__main__":
+    """
+    日志配置测试代码
+
+    这个测试代码演示了日志系统的基本功能，包括：
+    1. 日志系统初始化
+    2. 不同级别的日志输出
+    3. 日志文件路径获取
+    4. 装饰器功能测试
+
+    运行方式:
+        python -m src.utils.logger_config
+    """
+    # 初始化日志系统（DEBUG级别，同时输出到控制台和文件）
+    log_file = setup_logging(log_level=logging.DEBUG)
+    test_logger = get_logger(__name__)
+    
+    test_logger.info("开始测试日志配置...")
+
+    # 测试不同级别的日志输出
+    test_logger.debug("这是一个调试消息 - 用于开发调试")
+    test_logger.info("这是一个信息消息 - 记录重要信息")
+    test_logger.warning("这是一个警告消息 - 提醒注意事项")
+    test_logger.error("这是一个错误消息 - 记录错误情况")
+
+    # 测试工具方法
+    LoggerConfig.log_api_request(test_logger, "GET", "https://api.example.com/test")
+    LoggerConfig.log_api_response(test_logger, 200, 0.123)
+
+    # 测试装饰器
+    @log_function_calls()
+    def test_function(param1, param2="default"):
+        """测试函数"""
+        return {"result": "success", "param1": param1}
+
+    # 调用测试函数
+    result = test_function("test_value", param2="custom")
+
+    # 输出日志文件位置
+    test_logger.info(f"日志文件位置: {log_file}")
+    test_logger.info("日志配置测试完成！")

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/utils/tool_translation.py

@@ -0,0 +1,153 @@
+import os
+import sys
+from typing import Dict, Any, Optional
+
+
+# 导入翻译函数
+from .translator import translate
+
+
+class TranslationService:
+    """翻译服务类，用于处理各种翻译需求"""
+
+    @staticmethod
+    def create_prompt(
+        content: str,
+        target_lang: str,
+        use_case: str,
+        style: str,
+        prompt_type: str = "general",
+        keep_terms_desc: str = "核心术语",
+    ) -> str:
+        """
+        创建翻译提示
+
+        Args:
+            content: 待翻译内容
+            target_lang: 目标语言
+            use_case: 使用场景
+            style: 翻译风格
+            prompt_type: 提示类型，可选值: "general", "tool_name", "tool_description"
+            keep_terms_desc: 保留术语的描述
+
+        Returns:
+            str: 格式化的翻译提示
+        """
+        if prompt_type == "tool_name":
+            keep_terms_desc = "核心术语（如 小写，词语需要用下划线连接）"
+        elif prompt_type == "tool_description":
+            keep_terms_desc = "核心术语（这是一段话）"
+
+        return f"""
+角色：专业本地化翻译专家
+任务：将以下内容翻译为{target_lang}（目标用途：{use_case}）
+要求：
+1. 仅返回译文，不含解释或原文；
+2. 保留{keep_terms_desc}；
+3. 符合{style}风格；
+4. 特殊符号保持原样。
+
+示例输出格式：
+Translated Text
+
+待翻译内容：
+{content}
+"""
+
+    @staticmethod
+    def translate_text(
+        content: str,
+        target_lang: str,
+        use_case: str = "",
+        style: str = "正式且符合技术品牌调性",
+        prompt_type: str = "general",
+    ) -> Dict[str, Any]:
+        """
+        翻译文本
+
+        Args:
+            content: 待翻译内容
+            target_lang: 目标语言
+            use_case: 使用场景，默认为空
+            style: 翻译风格，默认为"正式且符合技术品牌调性"
+            prompt_type: 提示类型，可选值: "general", "tool_name", "tool_description"
+
+        Returns:
+            Dict: 包含翻译结果的字典
+        """
+        prompt = TranslationService.create_prompt(
+            content=content,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type=prompt_type,
+        )
+
+        try:
+            result = translate(prompt, target_lang)
+            return result
+        except Exception as e:
+            print(f"翻译出错: {str(e)}")
+            return {"translated_text": "", "error": str(e)}
+
+    @staticmethod
+    def translate_tool_name(
+        name: str,
+        target_lang: str = "英语",
+        use_case: str = "工具名称",
+        style: str = "正式且符合技术品牌调性，大模型能理解",
+    ) -> str:
+        """
+        翻译工具名称的便捷方法
+
+        Returns:
+            str: 翻译后的工具名称
+        """
+        result = TranslationService.translate_text(
+            content=name,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type="tool_name",
+        )
+        return result.get("translated_text", "")
+
+    @staticmethod
+    def translate_tool_description(
+        description: str,
+        target_lang: str = "英语",
+        use_case: str = "工具描述",
+        style: str = "正式且符合技术品牌调性，大模型能理解",
+    ) -> str:
+        """
+        翻译工具描述的便捷方法
+
+        Returns:
+            str: 翻译后的工具描述
+        """
+        result = TranslationService.translate_text(
+            content=description,
+            target_lang=target_lang,
+            use_case=use_case,
+            style=style,
+            prompt_type="tool_description",
+        )
+        return result.get("translated_text", "")
+
+
+def translation_example():
+    """翻译功能使用示例"""
+
+    # 示例1: 翻译工具名称
+    tool_name = "万川AI新媒体平台【测试环境】"
+    translated_name = TranslationService.translate_tool_name(tool_name)
+    print(f"工具名称翻译: {translated_name}")
+
+    # 示例2: 翻译工具描述
+    description = "21日，辛柏青发布讣告宣布妻子朱媛媛抗癌五年后离世。此前在一次路演现场，当观众问及朱媛媛时辛柏青2秒停顿藏着"
+    translated_desc = TranslationService.translate_tool_description(description)
+    print(f"工具描述翻译: {translated_desc}")
+
+
+if __name__ == "__main__":
+    translation_example()

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/utils/translator.py

@@ -0,0 +1,64 @@
+import os
+import requests
+import json
+from dotenv import load_dotenv
+
+# 加载环境变量
+load_dotenv()
+# ========== 模型相关 ==========
+# 从.env文件获取模型API配置
+BASE_URL = os.getenv("BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")
+API_KEY = os.getenv("OPENAI_API_KEY", "sk-c5a912a6bc8e4c9cbdbdf68232352a03")
+TEMPERATURE = float(os.getenv("MODEL_TEMPERATURE", "0.7"))
+
+
+def translate(content, target_language):
+    """
+    翻译文本内容到目标语言
+
+    :param content: 要翻译的内容
+    :param target_language: 目标语言，如'en'(英语), 'zh'(中文), 'ja'(日语), 'fr'(法语)等
+    :return: 翻译后的内容，如果翻译失败则返回原文和错误信息
+    """
+    if not content or not target_language:
+        return {"error": "内容或目标语言不能为空", "translated_text": content}
+
+    # 确保API密钥已设置
+    if not API_KEY:
+        return {"error": "API密钥未设置，请检查.env文件", "translated_text": content}
+
+    try:
+        # 构建API请求头
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {API_KEY}",
+        }
+
+        # 构建翻译提示
+        prompt = f"请将以下内容翻译成{target_language}，只返回翻译结果，不要包含任何解释或原文：\n\n{content}"
+
+        # 构建API请求体
+        data = {
+            "model": "qwen-max",  # 使用通义千问模型，可以根据实际需要更改
+            "messages": [{"role": "user", "content": prompt}],
+            "temperature": TEMPERATURE,
+        }
+
+        # 发送API请求
+        response = requests.post(
+            f"{BASE_URL}/chat/completions", headers=headers, json=data
+        )
+
+        # 解析响应
+        if response.status_code == 200:
+            result = response.json()
+            translated_text = result["choices"][0]["message"]["content"].strip()
+            return {"translated_text": translated_text}
+        else:
+            error_message = (
+                f"翻译失败，状态码: {response.status_code}, 响应: {response.text}"
+            )
+            return {"error": error_message, "translated_text": content}
+
+    except Exception as e:
+        return {"error": f"翻译过程中发生错误: {str(e)}", "translated_text": content}

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/utils/upload_file.py

@@ -0,0 +1,461 @@
+"""
+Dify文件上传工具 - 优化版
+
+主要功能：
+- 从URL下载文件并自动上传到Dify API
+- 支持常见文件类型：JPG、PNG、GIF、PDF、DOCX、TXT等
+- 自动处理文件大小检查、MIME类型识别、临时文件清理
+
+使用方法：
+    from upload_file import upload_file_from_url
+
+    result = upload_file_from_url(
+        file_url="http://example.com/image.jpg",
+        base_url="http://192.168.2.236:3001/v1",
+        api_key="app-QdfDKqHAI3dlB6tvnibuh6rv"
+    )
+
+    file_id = result['id']  # 获取上传后的文件ID
+"""
+
+import os
+import tempfile
+import requests
+import logging
+from urllib.parse import urlparse, unquote
+from typing import Optional
+
+# 获取模块级别的logger，避免影响全局日志配置
+logger = logging.getLogger(__name__)
+
+# 常用MIME类型映射
+MIME_TYPE_MAP = {
+    '.jpg': 'image/jpeg',
+    '.jpeg': 'image/jpeg',
+    '.png': 'image/png',
+    '.gif': 'image/gif',
+    '.webp': 'image/webp',
+    '.svg': 'image/svg+xml',
+    '.pdf': 'application/pdf',
+    '.txt': 'text/plain',
+    '.docx': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document'
+}
+
+
+def download_file_from_url(
+    url: str,
+    download_dir: Optional[str] = None,
+    filename: Optional[str] = None,
+    timeout: int = 30,
+    max_retries: int = 3
+) -> str:
+    """
+    从URL下载文件到本地并返回文件路径
+
+    Args:
+        url: 文件的URL地址
+        download_dir: 下载目录，如果为None则使用系统临时目录
+        filename: 指定文件名，如果为None则从URL中提取
+        timeout: 请求超时时间（秒）
+        max_retries: 最大重试次数
+
+    Returns:
+        str: 下载后的本地文件路径
+
+    Raises:
+        Exception: 下载失败时抛出异常
+    """
+
+    # 设置下载目录
+    if download_dir is None:
+        download_dir = tempfile.gettempdir()
+
+    # 确保下载目录存在
+    os.makedirs(download_dir, exist_ok=True)
+
+    # 提取文件名
+    if filename is None:
+        filename = _extract_filename_from_url(url)
+
+    # 构建完整的文件路径
+    file_path = os.path.join(download_dir, filename)
+
+    # 下载文件（带重试机制）
+    for attempt in range(max_retries):
+        try:
+            logger.info(f"正在下载文件: {url} (尝试 {attempt + 1}/{max_retries})")
+
+            # 发送GET请求下载文件
+            response = requests.get(url, timeout=timeout, stream=True)
+            response.raise_for_status()
+
+            # 写入文件
+            with open(file_path, 'wb') as f:
+                for chunk in response.iter_content(chunk_size=8192):
+                    if chunk:
+                        f.write(chunk)
+
+            # 验证文件是否下载成功
+            if os.path.exists(file_path) and os.path.getsize(file_path) > 0:
+                logger.info(f"文件下载成功: {file_path} (大小: {os.path.getsize(file_path)} 字节)")
+                return file_path
+            else:
+                raise Exception("下载的文件为空或不存在")
+
+        except requests.exceptions.Timeout:
+            error_msg = f"请求超时 (超过 {timeout} 秒)"
+            logger.warning(f"{error_msg}, 尝试 {attempt + 1}/{max_retries}")
+            if attempt == max_retries - 1:
+                raise Exception(f"下载失败：{error_msg}")
+
+        except requests.exceptions.RequestException as e:
+            error_msg = f"请求异常: {str(e)}"
+            logger.warning(f"{error_msg}, 尝试 {attempt + 1}/{max_retries}")
+            if attempt == max_retries - 1:
+                raise Exception(f"下载失败：{error_msg}")
+
+        except Exception as e:
+            error_msg = f"下载过程中发生错误: {str(e)}"
+            logger.warning(f"{error_msg}, 尝试 {attempt + 1}/{max_retries}")
+            if attempt == max_retries - 1:
+                raise Exception(f"下载失败：{error_msg}")
+
+    raise Exception("下载失败：已达到最大重试次数")
+
+
+def _extract_filename_from_url(url: str) -> str:
+    """
+    从URL中提取文件名
+
+    Args:
+        url: 文件URL
+
+    Returns:
+        str: 提取的文件名
+    """
+    try:
+        # 解析URL
+        parsed_url = urlparse(url)
+        path = unquote(parsed_url.path)
+
+        # 从路径中提取文件名
+        filename = os.path.basename(path)
+
+        # 如果没有找到文件名或文件名为空，使用默认名称
+        if not filename or filename == '/':
+            filename = "downloaded_file"
+
+        # 移除查询参数（如果文件名中包含）
+        if '?' in filename:
+            filename = filename.split('?')[0]
+
+        return filename
+
+    except Exception as e:
+        logger.warning(f"无法从URL提取文件名: {str(e)}, 使用默认文件名")
+        return "downloaded_file"
+
+
+def upload_file_to_dify(
+    file_path: str,
+    base_url: str,
+    api_key: str,
+    user: str = "default_user",
+    verify_ssl: bool = False
+) -> dict:
+    """
+    上传文件到Dify API
+
+    Args:
+        file_path: 本地文件路径
+        base_url: Dify API基础URL (例如: http://192.168.2.236:3001/v1)
+        api_key: API密钥
+        user: 用户标识
+        verify_ssl: 是否验证SSL证书
+
+    Returns:
+        dict: 上传响应结果
+
+    Raises:
+        Exception: 上传失败时抛出异常
+    """
+    # 检查文件是否存在
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"文件不存在: {file_path}")
+
+    # 检查文件大小
+    file_size = os.path.getsize(file_path)
+    file_size_mb = file_size / (1024 * 1024)
+    logger.info(f"准备上传文件: {file_path} (大小: {file_size_mb:.2f} MB)")
+
+    # 检查文件大小是否超过限制
+    if file_size_mb > 10:
+        logger.warning(f"文件大小 {file_size_mb:.2f} MB 可能超过服务器限制 (10 MB)")
+
+    upload_url = f"{base_url}/files/upload"
+    headers = {"Authorization": f"Bearer {api_key}"}
+
+    try:
+        with open(file_path, "rb") as f:
+            # 获取文件扩展名和MIME类型
+            file_ext = os.path.splitext(file_path)[1].lower()
+            mime_type = MIME_TYPE_MAP.get(file_ext, "application/octet-stream")
+
+            # 构建文件上传数据
+            files = {"file": (os.path.basename(file_path), f, mime_type)}
+            data = {"user": user}
+
+            # 发送上传请求
+            response = requests.post(
+                upload_url,
+                headers=headers,
+                files=files,
+                data=data,
+                verify=verify_ssl
+            )
+
+            # 检查响应
+            if response.status_code == 201:
+                result = response.json()
+                logger.info(f"文件上传成功: {result.get('name', 'unknown')} (ID: {result.get('id', 'unknown')})")
+                return result
+            else:
+                error_msg = f"上传失败 (状态码: {response.status_code}): {response.text}"
+                logger.error(error_msg)
+                raise requests.exceptions.HTTPError(error_msg)
+
+    except requests.exceptions.RequestException as e:
+        logger.error(f"上传文件请求失败: {str(e)}")
+        raise
+    except Exception as e:
+        logger.error(f"上传文件失败: {str(e)}")
+        raise
+
+
+
+def check_app_config(base_url: str, api_key: str):
+    """
+    检查Dify应用的文件上传配置
+
+    Args:
+        base_url: Dify API基础URL
+        api_key: API密钥
+    """
+    try:
+        # 获取应用参数配置
+        config_url = f"{base_url}/parameters"
+        headers = {"Authorization": f"Bearer {api_key}"}
+
+        response = requests.get(config_url, headers=headers, verify=False)
+        response.raise_for_status()
+
+        config = response.json()
+        logger.info(f"应用配置获取成功")
+
+        # 检查文件上传配置
+        file_upload = config.get("file_upload", {})
+        if file_upload.get("enabled", False):
+            logger.info("✓ 文件上传功能已启用")
+            logger.info(f"  - 允许的文件类型: {file_upload.get('allowed_file_types', [])}")
+            logger.info(f"  - 允许的文件扩展名: {file_upload.get('allowed_file_extensions', [])}")
+            logger.info(f"  - 文件大小限制: {file_upload.get('fileUploadConfig', {}).get('image_file_size_limit', 'N/A')} MB")
+        else:
+            logger.warning("✗ 文件上传功能未启用")
+
+        return config
+
+    except Exception as e:
+        logger.error(f"检查应用配置失败: {str(e)}")
+        return None
+
+
+def test_download_and_upload():
+    """
+    测试下载和上传功能的示例
+    """
+    # 测试用的文件URL
+    file_url = "http://192.168.2.236:9000/lzwcai/upload/2025-07-29/34b28da03f3c43b0921ba1b76857bbc0/34b28da03f3c43b0921ba1b76857bbc0.JPG?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=minio%2F20250729%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20250729T075242Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=80f58d37c3bd52fb2b25efa36b5df0d73c8da7c773e7a7066dd6563710c619d6"
+
+    # 上传API配置
+    base_url = "http://192.168.2.236:3001/v1"
+    upload_url = f"{base_url}/files/upload"
+    api_key = "app-QdfDKqHAI3dlB6tvnibuh6rv"
+    headers = {"Authorization": f"Bearer {api_key}"}
+    user = "abc-123"
+
+    try:
+        logger.info("开始测试下载和上传流程...")
+
+        # 0. 检查应用配置
+        logger.info("检查Dify应用配置...")
+        config = check_app_config(base_url, api_key)
+        if not config:
+            logger.error("无法获取应用配置，终止测试")
+            return
+
+        # 1. 下载文件
+        logger.info(f"正在下载文件: {file_url}")
+        file_path = download_file_from_url(file_url)
+        logger.info(f"文件下载成功，保存路径: {file_path}")
+
+        # 2. 上传文件
+        logger.info(f"正在上传文件到: {upload_url}")
+
+        # 检查文件大小
+        file_size = os.path.getsize(file_path)
+        file_size_mb = file_size / (1024 * 1024)
+        logger.info(f"文件大小: {file_size_mb:.2f} MB")
+
+        # 检查文件大小是否超过限制（通常为10MB对于图片）
+        if file_size_mb > 10:
+            logger.warning(f"文件大小 {file_size_mb:.2f} MB 可能超过服务器限制")
+
+        with open(file_path, "rb") as f:
+            # 获取文件扩展名来确定MIME类型
+            file_ext = os.path.splitext(file_path)[1].lower()
+            mime_type = "image/jpeg" if file_ext in ['.jpg', '.jpeg'] else "application/octet-stream"
+
+            # 构建文件上传数据，指定正确的MIME类型
+            files = {"file": (os.path.basename(file_path), f, mime_type)}
+            data = {"user": user}
+
+            # 不要在headers中设置Content-Type，让requests自动处理multipart/form-data
+            upload_headers = headers.copy()
+            if "Content-Type" in upload_headers:
+                del upload_headers["Content-Type"]
+
+            # 添加SSL验证跳过选项，用于自签名证书
+            response = requests.post(upload_url, headers=upload_headers, files=files, data=data, verify=False)
+
+            # 打印详细的响应信息用于调试
+            logger.info(f"响应状态码: {response.status_code}")
+            logger.info(f"响应头: {response.headers}")
+            logger.info(f"响应内容: {response.text}")
+
+            response.raise_for_status()
+
+        result = response.json()
+        logger.info(f"文件上传成功，响应: {result}")
+
+        # 3. 清理临时文件
+        try:
+            os.remove(file_path)
+            logger.info(f"已清理临时文件: {file_path}")
+        except Exception as e:
+            logger.warning(f"清理临时文件失败: {str(e)}")
+
+        return result
+
+    except Exception as e:
+        logger.error(f"测试失败: {str(e)}")
+        raise
+
+
+def upload_file_from_url(
+    file_url: str,
+    base_url: str,
+    api_key: str,
+    user: str = "default_user",
+    verify_ssl: bool = False
+) -> dict:
+    """
+    从URL下载文件并上传到Dify API - 一站式解决方案
+
+    这是一个优化后的方法，只需要提供URL地址、base_url和api_key，就能自动完成下载和上传。
+    支持常见的文件类型：JPG、PNG、GIF、PDF、DOCX、TXT等。
+    自动处理文件大小检查、MIME类型识别、临时文件清理等。
+
+    Args:
+        file_url: 要下载的文件URL
+        base_url: Dify API基础URL (例如: http://192.168.2.236:3001/v1)
+        api_key: API密钥 (例如: app-QdfDKqHAI3dlB6tvnibuh6rv)
+        user: 用户标识 (可选，默认为 default_user)
+        verify_ssl: 是否验证SSL证书 (可选，默认为 False)
+
+    Returns:
+        dict: 上传成功后的结果，包含文件ID、名称、大小等信息
+        示例: {
+            'id': 'a239b623-40a8-482c-859f-bb8368d5b1fe',
+            'name': 'example.jpg',
+            'size': 495240,
+            'extension': 'jpg',
+            'mime_type': 'image/jpeg',
+            'created_by': '92c4b250-e0e7-4123-900d-f5c2187679a2',
+            'created_at': 1753777420
+        }
+
+    使用示例:
+        result = upload_file_from_url(
+            file_url="http://example.com/image.jpg",
+            base_url="http://192.168.2.236:3001/v1",
+            api_key="app-QdfDKqHAI3dlB6tvnibuh6rv"
+        )
+        file_id = result['id']  # 获取上传后的文件ID
+
+    Raises:
+        Exception: 下载或上传失败时抛出异常
+    """
+    temp_file_path = None
+    try:
+        logger.info(f"开始处理文件: {file_url}")
+
+        # 1. 下载文件到临时目录
+        temp_file_path = download_file_from_url(file_url)
+
+        # 2. 上传文件到Dify (复用已有的上传函数)
+        result = upload_file_to_dify(temp_file_path, base_url, api_key, user, verify_ssl)
+        return result
+
+    except Exception as e:
+        logger.error(f"处理文件失败: {str(e)}")
+        raise
+    finally:
+        # 清理临时文件
+        if temp_file_path and os.path.exists(temp_file_path):
+            try:
+                os.remove(temp_file_path)
+                logger.info(f"已清理临时文件: {temp_file_path}")
+            except Exception as e:
+                logger.warning(f"清理临时文件失败: {str(e)}")
+
+
+def test_upload_functionality():
+    """
+    测试文件上传功能的示例
+    注意：这个函数包含示例配置，实际使用时请替换为真实的配置
+    """
+    # 示例配置 - 实际使用时请替换为真实的配置
+    file_url = "https://example.com/test-image.jpg"  # 替换为实际的文件URL
+    base_url = "http://localhost:3001/v1"  # 替换为实际的Dify API地址
+    api_key = "your-api-key-here"  # 替换为实际的API密钥
+
+    try:
+        logger.info("=== 开始测试文件上传功能 ===")
+
+        # 检查应用配置
+        logger.info("检查Dify应用配置...")
+        config = check_app_config(base_url, api_key)
+        if not config:
+            logger.warning("无法获取应用配置，但继续测试上传功能")
+
+        # 调用上传方法
+        result = upload_file_from_url(file_url, base_url, api_key)
+
+        logger.info("=== 上传成功！结果如下 ===")
+        logger.info(f"文件ID: {result.get('id')}")
+        logger.info(f"文件名: {result.get('name')}")
+        logger.info(f"文件大小: {result.get('size')} 字节")
+        logger.info(f"文件类型: {result.get('mime_type')}")
+        logger.info(f"扩展名: {result.get('extension')}")
+
+        return result
+
+    except Exception as e:
+        logger.error(f"测试失败: {str(e)}")
+        raise
+
+
+if __name__ == "__main__":
+    # 运行测试 - 注意：需要先配置正确的URL和API密钥
+    print("警告：测试函数包含示例配置，请先修改为实际配置后再运行")
+    # test_upload_functionality()  # 取消注释并配置后运行

lzwcai_demp_tool_server_dify_to_mcp_test/lzwcai_demp_tool_server_dify_to_mcp_test/src/workflow/workflow_server.py

@@ -0,0 +1,315 @@
+import requests
+from abc import ABC
+import logging
+import json
+from src.utils.logger_config import get_logger
+
+# 导入 pypinyin 用于中文转拼音
+try:
+    import pypinyin
+except ImportError:
+    pypinyin = None
+    logging.warning("pypinyin 模块未安装，将使用简化的命名方式")
+
+logger = get_logger(__name__)
+
+def pinyin_to_camel(pinyin):
+    """
+    将中文名称转换为工具名称
+    
+    处理逻辑：
+    1. 如果安装了 pypinyin，将中文转换为拼音，然后转为驼峰命名
+    2. 如果未安装 pypinyin，将所有非字母数字字符替换为下划线
+    3. 所有符号都会被替换成下划线
+    
+    示例:
+        "你好啊" -> "tool_NiHaoA" (有pypinyin)
+        "测试-工具" -> "tool_测试_工具" (无pypinyin)
+        "Hello World!" -> "tool_Hello_World_" (无pypinyin)
+    
+    Args:
+        pinyin: 输入的字符串（可能包含中文、英文、符号等）
+    
+    Returns:
+        str: 格式化后的工具名称，以 "tool_" 开头
+    """
+    import re
+    
+    if pypinyin is None:
+        # 如果 pypinyin 未安装，使用简化的命名方式
+        # 将所有非字母数字字符（包括空格、符号等）替换为下划线
+        cleaned = re.sub(r'[^\w]', '_', str(pinyin))
+        # 移除连续的下划线
+        cleaned = re.sub(r'_+', '_', cleaned)
+        # 移除首尾的下划线
+        cleaned = cleaned.strip('_')
+        return "tool_" + cleaned if cleaned else "tool_unnamed"
+    
+    # 使用 pypinyin 转换中文为拼音
+    pinyin_list = pypinyin.lazy_pinyin(pinyin)
+    
+    # 处理每个拼音单词
+    processed_words = []
+    for word in pinyin_list:
+        # 将所有非字母数字字符替换为下划线
+        cleaned_word = re.sub(r'[^\w]', '_', word)
+        # 移除连续的下划线
+        cleaned_word = re.sub(r'_+', '_', cleaned_word)
+        # 移除首尾的下划线
+        cleaned_word = cleaned_word.strip('_')
+        
+        if cleaned_word:
+            # 首字母大写（驼峰命名）
+            processed_words.append(cleaned_word.capitalize())
+    
+    # 拼接所有单词
+    result = "".join(processed_words) if processed_words else "Unnamed"
+    return "tool_" + result
+
+
+class WorkflowDifyAPI(ABC):
+    def __init__(self, base_url: str, dify_app_sks: list, user="pp666"):
+        # dify configs
+        self.dify_base_url = base_url
+        self.dify_app_sks = dify_app_sks
+        self.user = user
+
+        # dify app infos
+        dify_app_infos = []
+        dify_app_params = []
+        dify_app_metas = []
+        for key in self.dify_app_sks:
+            dify_app_infos.append(self.get_app_info(key))
+            dify_app_params.append(self.get_app_parameters(key))
+            dify_app_metas.append(self.get_app_meta(key))
+
+        self.dify_app_infos = dify_app_infos
+        self.dify_app_params = dify_app_params
+        self.dify_app_metas = dify_app_metas
+        self.dify_app_names = [x["name"] for x in dify_app_infos]
+
+    def chat_message(
+        self,
+        api_key,
+        inputs={},
+        response_mode="streaming",
+        conversation_id=None,
+        userId="pp666",
+        files=None,
+    ):
+        url = f"{self.dify_base_url}/workflows/run"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {
+            "inputs": inputs,
+            "response_mode": response_mode,
+            "user": userId,
+        }
+        logger.info("Sending data to Dify API: %s", data)
+        logger.info("Sending headers to Dify API: %s", headers)
+        logger.info("Sending url to Dify API: %s", url)
+        if conversation_id:
+            data["conversation_id"] = conversation_id
+        if files:
+            files_data = self.file_parameter_pretreatment(files)
+            if files_data and len(files_data) > 0:
+                data["inputs"]["files"] = files_data[0]
+            # For workflow API, we send files data in the JSON payload, not as multipart files
+            response = requests.post(
+                url, headers=headers, json=data, stream=response_mode == "streaming"
+            )
+        else:
+            response = requests.post(
+                url, headers=headers, json=data, stream=response_mode == "streaming"
+            )
+            logger.info(f"Response1:{data} {response.status_code} {response.reason}")
+
+        # Add debugging for error responses
+        if response.status_code != 200:
+            logger.error(f"API request failed with status {response.status_code}")
+            logger.error(f"Response content: {response.text}")
+            logger.error(f"Request data: {data}")
+
+        response.raise_for_status()
+        if response_mode == "streaming":
+            def stream_generator():
+                for line in response.iter_lines():
+                    if line:
+                        if line.startswith(b"data:"):
+                            try:
+                                json_data = json.loads(line[5:].decode("utf-8"))
+                                yield json_data
+                            except json.JSONDecodeError:
+                                logger.error(f"Error decoding JSON: {line}")
+            return stream_generator()
+        else:
+            return response.json()
+
+    def upload_file(self, api_key, file_path, user="pp666"):
+
+        url = f"{self.dify_base_url}/files/upload"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        files = {"file": open(file_path, "rb")}
+        data = {"user": user}
+        response = requests.post(url, headers=headers, files=files, data=data)
+        response.raise_for_status()
+        return response.json()
+    def upload_file_remote_url(self, file_url):
+        from src.utils.upload_file import upload_file_from_url
+        base_url = self.dify_base_url
+        api_key = self.dify_app_sks[0]
+        return upload_file_from_url(file_url, base_url, api_key)
+
+    def file_parameter_pretreatment(self, files):
+        """
+        文件参数预处理方法
+
+        传入的"files"数据结构是这样的: [
+            {
+                "type": "image",
+                "transfer_method": "remote_url",
+                "url": "http://example.com/image.jpg"
+            }
+        ]
+
+        处理逻辑：
+        1. 遍历files列表中的每个文件对象
+        2. 对于transfer_method为"remote_url"的文件，调用upload_file_remote_url方法
+        3. 将返回的对象的id字段存入原对象的upload_file_id字段
+        4. 设置transfer_method为"local_file"（因为已经上传到Dify服务器）
+        5. 返回处理好的files列表
+
+        Args:
+            files (list): 文件列表，每个元素包含type、transfer_method、url等字段
+
+        Returns:
+            list: 处理后的文件列表，每个文件对象包含upload_file_id和transfer_method字段
+        """
+        if not files or not isinstance(files, list):
+            logger.warning("文件参数为空或格式不正确")
+            return files
+
+        processed_files = []
+
+        for file_obj in files:
+            # 创建文件对象的副本，避免修改原始数据
+            processed_file = file_obj.copy()
+
+            # 检查是否需要处理远程URL文件
+            if (processed_file.get("transfer_method") == "remote_url" and
+                processed_file.get("url")):
+
+                try:
+                    logger.info(f"开始上传远程文件: {processed_file['url']}")
+                    
+                    # 调用upload_file_remote_url方法：下载文件并上传到Dify
+                    upload_result = self.upload_file_remote_url(processed_file["url"])
+
+                    # 将返回的对象的id存入upload_file_id字段
+                    if upload_result and "id" in upload_result:
+                        processed_file["upload_file_id"] = upload_result["id"]
+                        # 修改transfer_method为local_file，因为文件已经上传到Dify服务器
+                        processed_file["transfer_method"] = "local_file"
+                        # 移除url字段，因为已经不需要了
+                        processed_file.pop("url", None)
+                        
+                        logger.info(f"文件上传成功 - ID: {upload_result['id']}, "
+                                  f"名称: {upload_result.get('name', 'N/A')}, "
+                                  f"大小: {upload_result.get('size', 'N/A')} bytes")
+                    else:
+                        logger.error(f"文件上传失败，未获取到有效的文件ID，响应: {upload_result}")
+                        processed_file["upload_error"] = "未获取到有效的文件ID"
+
+                except Exception as e:
+                    logger.error(f"文件上传过程中发生错误: {str(e)}", exc_info=True)
+                    # 记录错误信息，但继续处理其他文件
+                    processed_file["upload_error"] = str(e)
+
+            elif processed_file.get("transfer_method") == "local_file":
+                # 如果已经是local_file，确保有upload_file_id
+                if not processed_file.get("upload_file_id"):
+                    logger.warning("local_file类型的文件缺少upload_file_id字段")
+            
+            processed_files.append(processed_file)
+
+        logger.info(f"文件预处理完成，共处理 {len(processed_files)} 个文件")
+        return processed_files
+    def stop_response(self, api_key, task_id, user="pp666"):
+
+        url = f"{self.dify_base_url}/chat-messages/{task_id}/stop"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+        data = {"user": user}
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        return response.json()
+
+    def get_app_info(self, api_key, user="pp666"):
+
+        url = f"{self.dify_base_url}/info"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+
+        response_map = response.json()
+
+        # 翻译工具名称
+        tool_name = response_map.get("name")
+        if tool_name:
+            # translated_name = TranslationService.translate_tool_name(tool_name)
+            translated_name = pinyin_to_camel(tool_name)
+            response_map["name"] = translated_name
+
+        # 翻译工具描述
+        # tool_description = response_map.get("description")
+        # if tool_description:
+        #     translated_description = TranslationService.translate_tool_description(
+        #         tool_description
+        #     )
+        #     response_map["description"] = (
+        #         f"{tool_description} ({translated_description})"
+        #     )
+
+        return response_map
+
+    def get_app_parameters(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/parameters"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        
+        logger.info(f"调用 /parameters API: {url}")
+        logger.info(f"请求头: {headers}")
+        logger.info(f"请求参数: {params}")
+        
+        response = requests.get(url, headers=headers, params=params)
+        
+        logger.info(f"/parameters API 响应状态码: {response.status_code}")
+        
+        response.raise_for_status()
+        
+        response_data = response.json()
+        logger.info(f"/parameters API 响应数据: {response_data}")
+        
+        return response_data
+
+    def get_app_meta(self, api_key, user="pp666"):
+        url = f"{self.dify_base_url}/meta"
+        headers = {"Authorization": f"Bearer {api_key}"}
+        params = {"user": user}
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        return response.json()
+
+
+
+if __name__ == "__main__":
+    dify_api = WorkflowDifyAPI(
+        "https://ops.lzwcai.com/v1",
+        ["app-ZmLuBlRmViseUdOonqLyNSku", "app-AHjfp8k4nawQSJi0us8x3J5Q"],
+    )
+    dify_api.upload_file_remote_url("http://192.168.2.236:9000/lzwcai/upload/2025-07-29/34b28da03f3c43b0921ba1b76857bbc0/34b28da03f3c43b0921ba1b76857bbc0.JPG?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=minio%2F20250729%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20250729T075242Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=80f58d37c3bd52fb2b25efa36b5df0d73c8da7c773e7a7066dd6563710c619d6")

lzwcai_mcp_api_converter/PKG-INFO

@@ -0,0 +1,12 @@
+Metadata-Version: 2.4
+Name: lzwcai-mcp-dyntoolapi
+Version: 0.1.27
+Summary: 基于FastMCP框架的动态API工具服务器，自动将企业业务API配置转换为MCP协议工具，支持多种传输方式、企业认证和参数验证，为AI助手提供标准化的业务接口访问能力。
+Requires-Python: >=3.10
+Description-Content-Type: text/markdown
+Requires-Dist: dynaconf>=3.2.11
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: jinja2==3.1.6
+Requires-Dist: mcp[cli]>=1.8.0
+Requires-Dist: requests>=2.31.0
+Requires-Dist: pypinyin>=0.54.0

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/PKG-INFO

@@ -0,0 +1,12 @@
+Metadata-Version: 2.4
+Name: lzwcai-mcp-api-converter
+Version: 0.1.30
+Summary: 基于FastMCP框架的动态API工具服务器，自动将企业业务API配置转换为MCP协议工具，支持多种传输方式、企业认证和参数验证，为AI助手提供标准化的业务接口访问能力。
+Requires-Python: >=3.10
+Description-Content-Type: text/markdown
+Requires-Dist: dynaconf>=3.2.11
+Requires-Dist: httpx>=0.28.1
+Requires-Dist: jinja2==3.1.6
+Requires-Dist: mcp[cli]>=1.8.0
+Requires-Dist: requests>=2.31.0
+Requires-Dist: pypinyin>=0.54.0

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/SOURCES.txt

@@ -0,0 +1,25 @@
+pyproject.toml
+setup.cfg
+lzwcai_mcp_api_converter/__init__.py
+lzwcai_mcp_api_converter.egg-info/PKG-INFO
+lzwcai_mcp_api_converter.egg-info/SOURCES.txt
+lzwcai_mcp_api_converter.egg-info/dependency_links.txt
+lzwcai_mcp_api_converter.egg-info/entry_points.txt
+lzwcai_mcp_api_converter.egg-info/requires.txt
+lzwcai_mcp_api_converter.egg-info/top_level.txt
+lzwcai_mcp_api_converter/src/__init__.py
+lzwcai_mcp_api_converter/src/api_config.json
+lzwcai_mcp_api_converter/src/create_mcp.py
+lzwcai_mcp_api_converter/src/business/__init__.py
+lzwcai_mcp_api_converter/src/business/business_util.py
+lzwcai_mcp_api_converter/src/business/get_business_api.py
+lzwcai_mcp_api_converter/src/core/__init__.py
+lzwcai_mcp_api_converter/src/core/api_auth_service.py
+lzwcai_mcp_api_converter/src/core/api_base.py
+lzwcai_mcp_api_converter/src/core/core_server.py
+lzwcai_mcp_api_converter/src/core/get_auth.py
+lzwcai_mcp_api_converter/src/core/plugin_base.py
+lzwcai_mcp_api_converter/src/util/__init__.py
+lzwcai_mcp_api_converter/src/util/api_helper.py
+lzwcai_mcp_api_converter/src/util/logger_config.py
+lzwcai_mcp_api_converter/src/util/nested_value.py

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/entry_points.txt

@@ -0,0 +1,2 @@
+[console_scripts]
+lzwcai-mcp-api-converter = lzwcai_mcp_api_converter.src.create_mcp:run_main

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/requires.txt

@@ -0,0 +1,6 @@
+dynaconf>=3.2.11
+httpx>=0.28.1
+jinja2==3.1.6
+mcp[cli]>=1.8.0
+requests>=2.31.0
+pypinyin>=0.54.0

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter.egg-info/top_level.txt

@@ -0,0 +1 @@
+lzwcai_mcp_api_converter

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter/src/api_config.json

@@ -0,0 +1 @@
+{}

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter/src/business/business_util.py

@@ -0,0 +1,712 @@
+"""
+业务工具模块 - API参数处理和JSON Schema操作
+
+这个模块提供了API参数到JSON Schema转换、参数验证、API配置操作等核心业务功能。
+它是连接业务API配置和MCP工具定义的桥梁。
+
+主要功能:
+1. API参数列表转换为JSON Schema
+2. 参数验证和默认值处理
+3. Schema提示文本生成
+4. API配置数组操作
+5. 必填参数检查
+
+核心组件:
+- 参数类型常量定义
+- JSON Schema生成器
+- 参数验证器
+- 配置操作工具
+
+设计原则:
+- 类型安全：严格的类型检查和转换
+- 容错性：完善的异常处理机制
+- 可扩展性：支持新的参数类型和验证规则
+- 标准化：符合JSON Schema规范
+
+作者: lzwcai
+版本: 1.0.0
+"""
+
+import json
+import copy
+from typing import Dict, List, Any, Optional, Union
+from ..util.logger_config import get_logger
+
+# 获取日志器实例
+logger = get_logger(__name__)
+
+
+# ==================== 常量定义 ====================
+
+class ParamType:
+    """
+    API参数类型常量
+
+    定义业务平台API参数的所有支持类型。
+    这些类型会被映射到对应的JSON Schema类型。
+    """
+    STRING = "STRING"      # 字符串类型
+    NUMBER = "NUMBER"      # 数字类型（浮点数）
+    INTEGER = "INTEGER"    # 整数类型
+    BOOLEAN = "BOOLEAN"    # 布尔类型
+    ARRAY = "ARRAY"        # 数组类型
+    OBJECT = "OBJECT"      # 对象类型
+
+
+class JsonSchemaType:
+    """
+    JSON Schema类型常量
+
+    定义JSON Schema规范中的标准类型。
+    用于将业务参数类型转换为标准Schema类型。
+    """
+    STRING = "string"      # 字符串
+    NUMBER = "number"      # 数字
+    BOOLEAN = "boolean"    # 布尔值
+    ARRAY = "array"        # 数组
+    OBJECT = "object"      # 对象
+
+
+class RequestType:
+    """
+    请求类型常量
+
+    定义API参数在HTTP请求中的位置类型。
+    用于将参数正确分组到请求的不同部分。
+    """
+    HEADER = "header"              # 请求头参数
+    QUERY = "query"                # 查询参数（URL参数）
+    BODY = "body"                  # 请求体参数
+    LZWCAI_CONFIG = "lzwcaiConfig" # lzwcaiConfig参数（新的用户ID存储位置）
+
+
+# ==================== 类型映射配置 ====================
+
+# 参数类型映射表：业务参数类型 -> JSON Schema类型
+PARAM_TYPE_MAPPING = {
+    ParamType.STRING: JsonSchemaType.STRING,    # 字符串 -> string
+    ParamType.NUMBER: JsonSchemaType.NUMBER,    # 数字 -> number
+    ParamType.INTEGER: JsonSchemaType.NUMBER,   # 整数 -> number（JSON Schema中整数也是number）
+    ParamType.BOOLEAN: JsonSchemaType.BOOLEAN,  # 布尔 -> boolean
+    ParamType.ARRAY: JsonSchemaType.ARRAY,      # 数组 -> array
+    ParamType.OBJECT: JsonSchemaType.OBJECT,    # 对象 -> object
+}
+
+# ==================== 默认参数配置 ====================
+
+# 默认用户ID参数配置
+# 这个参数会自动添加到所有API的Schema中，用于标识当前用户
+DEFAULT_USER_ID_PARAM = {
+    "paramName": "userId",                                    # 参数名称
+    "paramType": ParamType.STRING,                           # 参数类型：字符串
+    "paramPrompts": "当前与您对话的用户信息的用户ID",          # 参数描述
+    "requestType": RequestType.LZWCAI_CONFIG,                # 请求类型：lzwcaiConfig类型
+    "required": 1,                                           # 必填参数
+}
+
+
+# ==================== 核心函数 ====================
+
+def generate_json_schema(api_params: List[Dict[str, Any]]) -> Dict[str, Any]:
+    """
+    API参数列表转JSON Schema格式
+
+    这是模块的核心函数，负责将业务平台的API参数列表转换为符合JSON Schema规范的对象。
+    生成的Schema用于MCP工具的参数定义和验证。
+
+    转换流程:
+    1. 验证输入参数类型
+    2. 过滤掉header类型的参数（header参数单独处理）
+    3. 添加默认的userId参数（存储在lzwcaiConfig中）
+    4. 按请求类型分组参数（query, body, lzwcaiConfig等）
+    5. 为每个分组创建Schema属性
+    6. 清理空的required列表
+
+    Schema结构:
+    {
+        "type": "object",
+        "properties": {
+            "query": {
+                "type": "object",
+                "properties": {...},
+                "required": [...]
+            },
+            "body": {
+                "type": "object",
+                "properties": {...},
+                "required": [...]
+            },
+            "lzwcaiConfig": {
+                "type": "object",
+                "properties": {
+                    "userId": {
+                        "type": "string",
+                        "description": "当前与您对话的用户信息的用户ID"
+                    }
+                },
+                "required": ["userId"]
+            }
+        },
+        "required": ["query", "body", "lzwcaiConfig"]  // 只包含有参数的分组
+    }
+
+    参数:
+        api_params: API参数对象列表，每个对象包含：
+            - paramName: 参数名称
+            - paramType: 参数类型（STRING, NUMBER等）
+            - paramPrompts: 参数描述
+            - requestType: 请求类型（header, query, body等）
+            - required: 是否必填（1为必填，0为可选）
+            - defaultValue: 默认值（可选）
+
+    返回:
+        dict: 符合JSON Schema规范的对象
+
+    异常处理:
+        TypeError: 如果api_params不是列表类型
+
+    设计考虑:
+        - header参数被过滤掉，因为它们在HTTP请求中单独处理
+        - 自动添加userId参数到lzwcaiConfig分组，确保所有API都能获取用户信息
+        - 按请求类型分组，便于后续的参数处理和验证
+        - 清理空的required列表，保持Schema的简洁性
+    """
+    # 参数类型验证
+    if not isinstance(api_params, list):
+        raise TypeError("api_params must be a list")
+
+    logger.debug(f"生成JSON Schema，参数数量: {len(api_params)}")
+
+    # 创建基础Schema结构
+    schema = {
+        "type": JsonSchemaType.OBJECT,  # 根类型为对象
+        "properties": {},               # 属性定义
+        "required": []                  # 必填字段列表
+    }
+
+    # 过滤参数并添加默认userId参数
+    # header参数在HTTP请求中单独处理，不包含在Schema中
+    filtered_params = [
+        param for param in api_params
+        if param.get("requestType") != RequestType.HEADER
+    ]
+
+    # 添加默认的userId参数到lzwcaiConfig分组，确保所有API都能获取用户信息
+    filtered_params.append(DEFAULT_USER_ID_PARAM)
+
+    logger.debug(f"过滤后参数数量: {len(filtered_params)}")
+
+    # 按请求类型分组参数
+    param_groups = _group_parameters_by_type(filtered_params)
+    logger.debug(f"参数分组: {list(param_groups.keys())}")
+
+    # 为每个请求类型创建Schema属性
+    for req_type, params in param_groups.items():
+        logger.debug(f"处理参数组 {req_type}，包含 {len(params)} 个参数")
+        _add_request_type_to_schema(schema, req_type, params)
+
+    # 清理空的required列表，保持Schema简洁
+    _cleanup_empty_required_lists(schema)
+
+    logger.debug("JSON Schema生成完成")
+    return schema
+
+
+# ==================== 辅助函数 ====================
+
+def _group_parameters_by_type(
+    params: List[Dict[str, Any]],
+) -> Dict[str, List[Dict[str, Any]]]:
+    """
+    按请求类型分组参数
+
+    将参数列表按照requestType字段进行分组，便于后续按类型处理。
+    如果参数没有指定requestType，默认归类为query类型。
+
+    参数:
+        params: 参数字典列表
+
+    返回:
+        Dict[str, List[Dict[str, Any]]]: 按类型分组的参数字典
+        格式: {"query": [...], "body": [...], "lzwcaiConfig": [...]}
+    """
+    param_groups = {}
+    for param in params:
+        # 获取请求类型，默认为query
+        req_type = param.get("requestType", RequestType.QUERY)
+        
+        # 记录参数名和类型，便于调试
+        param_name = param.get("paramName", "未命名参数")
+        logger.debug(f"参数 '{param_name}' 归类为 {req_type} 类型")
+
+        # 初始化分组
+        if req_type not in param_groups:
+            param_groups[req_type] = []
+            logger.debug(f"创建新的参数分组: {req_type}")
+
+        # 添加参数到对应分组
+        param_groups[req_type].append(param)
+
+    logger.debug(f"参数分组完成，共 {len(param_groups)} 个分组")
+    return param_groups
+
+
+def _add_request_type_to_schema(
+    schema: Dict[str, Any], req_type: str, params: List[Dict[str, Any]]
+) -> None:
+    """
+    向Schema添加请求类型分组
+
+    为指定的请求类型创建Schema属性，并处理该类型下的所有参数。
+    每个请求类型都会成为根Schema的一个属性。
+
+    参数:
+        schema: 根Schema对象
+        req_type: 请求类型（如"query", "body", "lzwcaiConfig"）
+        params: 该类型下的参数列表
+    """
+    # 如果该请求类型还没有在Schema中定义，创建它
+    if req_type not in schema["properties"]:
+        schema["properties"][req_type] = {
+            "type": JsonSchemaType.OBJECT,  # 每个请求类型都是对象类型
+            "properties": {},               # 该类型下的参数定义
+            "required": [],                 # 该类型下的必填参数
+        }
+
+    # 如果该类型有参数，将其标记为根级别的必填字段
+    if params:
+        schema["required"].append(req_type)
+
+    # 处理该类型下的每个参数
+    for param in params:
+        _add_parameter_to_schema(schema["properties"][req_type], param)
+
+
+def _add_parameter_to_schema(
+    type_schema: Dict[str, Any], param: Dict[str, Any]
+) -> None:
+    """
+    向类型Schema添加单个参数
+
+    将单个参数的定义添加到指定类型的Schema中，包括参数类型、描述、
+    默认值、示例等信息。
+
+    参数处理:
+    1. 提取参数基本信息（名称、类型、描述）
+    2. 处理默认值（添加到描述中并设置default字段）
+    3. 映射参数类型到JSON Schema类型
+    4. 创建参数定义对象
+    5. 添加到Schema的properties中
+    6. 处理必填参数标记
+
+    参数:
+        type_schema: 类型Schema对象（如query、body的Schema）
+        param: 参数定义字典
+    """
+    # 获取参数名称，如果没有名称则跳过
+    param_name = param.get("paramName")
+    if not param_name:
+        logger.warning(f"参数缺少名称，跳过: {param}")
+        return
+
+    # 获取参数类型和描述
+    param_type = param.get("paramType", ParamType.STRING)
+    param_desc = param.get("paramPrompts", "")
+    is_required = param.get("required") == 1
+    
+    logger.debug(f"添加参数: {param_name}, 类型: {param_type}, 必填: {is_required}")
+
+    # 如果有默认值，添加到描述中
+    if param.get("defaultValue") is not None:
+        param_desc += f"（默认值为{param['defaultValue']}）"
+        logger.debug(f"参数 {param_name} 有默认值: {param['defaultValue']}")
+
+    # 将业务参数类型映射到JSON Schema类型
+    json_type = PARAM_TYPE_MAPPING.get(param_type, JsonSchemaType.STRING)
+    if param_type not in PARAM_TYPE_MAPPING:
+        logger.warning(f"未知的参数类型 {param_type}，使用默认类型 string")
+
+    # 创建参数定义对象
+    param_def = {
+        "type": json_type,          # JSON Schema类型
+        "description": param_desc,  # 参数描述
+    }
+
+    # 添加可选字段
+    if param.get("defaultValue") is not None:
+        param_def["default"] = param["defaultValue"]  # 默认值
+    if param.get("example") is not None:
+        param_def["example"] = param["example"]       # 示例值
+
+    # 添加到类型Schema的properties中
+    type_schema["properties"][param_name] = param_def
+
+    # 如果是必填参数，添加到required列表中
+    if is_required:
+        type_schema["required"].append(param_name)
+        logger.debug(f"参数 {param_name} 标记为必填")
+
+
+def _cleanup_empty_required_lists(schema: Dict[str, Any]) -> None:
+    """
+    清理Schema中的空required列表
+
+    移除Schema中所有空的required数组，保持Schema的简洁性。
+    这包括嵌套属性中的required列表和顶级的required列表。
+
+    清理规则:
+    1. 遍历所有请求类型的Schema
+    2. 如果某个类型的required列表为空，删除该字段
+    3. 如果顶级required列表为空，删除该字段
+
+    参数:
+        schema: 要清理的Schema对象
+    """
+    # 清理嵌套属性中的空required列表
+    for req_type in list(schema["properties"].keys()):
+        type_schema = schema["properties"][req_type]
+        if not type_schema.get("required"):
+            # 如果required列表为空，删除该字段
+            type_schema.pop("required", None)
+
+    # 清理顶级的空required列表
+    if not schema.get("required"):
+        schema.pop("required", None)
+
+
+def create_structured_data(
+    schema: Dict[str, Any], params: Dict[str, Any]
+) -> Dict[str, Any]:
+    """
+    Generate data structure based on schema and input parameters.
+
+    Automatically matches input parameters to schema fields and creates
+    a properly structured data object.
+
+    Args:
+        schema: JSON schema object defining the data structure
+        params: Parameter values to fill
+
+    Returns:
+        dict: Structured data object conforming to schema
+
+    Raises:
+        TypeError: If schema or params are not dictionaries
+    """
+    if not isinstance(schema, dict):
+        raise TypeError("schema must be a dictionary")
+    if not isinstance(params, dict):
+        raise TypeError("params must be a dictionary")
+
+    result = {}
+
+    # Process each top-level schema property
+    for field_name, field_schema in schema.get("properties", {}).items():
+        result[field_name] = {}
+        field_properties = field_schema.get("properties", {})
+
+        # Find matching parameters for this field
+        matched_params = {
+            param_name: param_value
+            for param_name, param_value in params.items()
+            if param_name in field_properties
+        }
+
+        # Only include field if there are matching parameters
+        if matched_params:
+            result[field_name] = matched_params
+
+    return result
+
+
+def generate_schema_prompt(schema: Dict[str, Any]) -> str:
+    """
+    Generate descriptive prompt from JSON Schema for LLM guidance.
+
+    Args:
+        schema: JSON Schema object returned by generate_json_schema
+
+    Returns:
+        str: Structured prompt text for guiding LLM parameter generation
+
+    Raises:
+        TypeError: If schema is not a dictionary
+    """
+    if not isinstance(schema, dict):
+        raise TypeError("schema must be a dictionary")
+
+    prompt_parts = ["当前工具所需参数：\n"]
+
+    # Process each parameter group
+    for group_name, group_schema in schema.get("properties", {}).items():
+        prompt_parts.append(f"## {group_name} 参数组：")
+
+        required_params = set(group_schema.get("required", []))
+
+        # Process each parameter in the group
+        for param_name, param_info in group_schema.get("properties", {}).items():
+            param_type = param_info.get("type", JsonSchemaType.STRING)
+            param_desc = param_info.get("description", "")
+            required_mark = "（必填）" if param_name in required_params else "（可选）"
+
+            prompt_parts.append(
+                f"- {param_name}{required_mark}: {param_desc}, 类型: {param_type}"
+            )
+
+        prompt_parts.append("")
+
+    # Add output format guidance
+    prompt_parts.extend(
+        [
+            "参数格式要求：JSON对象，包含所有必填字段。",
+            "示例格式:",
+            "```json",
+            "{",
+        ]
+    )
+
+    for group_name in schema.get("properties", {}):
+        prompt_parts.append(f'  "{group_name}": {{')
+        prompt_parts.append("    // 相关参数")
+        prompt_parts.append("  },")
+
+    prompt_parts.extend(["}", "```"])
+
+    return "\n".join(prompt_parts)
+
+
+def _remove_property_from_schema(schema: Dict[str, Any], property_name: str) -> None:
+    """
+    Remove a property from schema (helper function to reduce code duplication).
+
+    Args:
+        schema: Schema object to modify
+        property_name: Name of property to remove
+    """
+    # Remove from properties
+    if isinstance(schema.get("properties"), dict):
+        schema["properties"].pop(property_name, None)
+
+    # Remove from required list
+    if isinstance(schema.get("required"), list):
+        try:
+            schema["required"].remove(property_name)
+        except ValueError:
+            pass  # Property not in required list, ignore
+
+        # Remove empty required list
+        if not schema["required"]:
+            schema.pop("required", None)
+
+
+def remove_property_from_api_item(
+    api_item: Dict[str, Any], property_name: str
+) -> Dict[str, Any]:
+    """
+    Remove specified property from a single API object.
+
+    Args:
+        api_item: API object (single element from generate_api_array result)
+        property_name: Name of property to remove
+
+    Returns:
+        dict: Processed API object with property removed
+
+    Raises:
+        ValueError: When input parameters are invalid
+        TypeError: When input types are incorrect
+    """
+    if not isinstance(api_item, dict) or not api_item:
+        raise ValueError("api_item must be a non-empty dictionary")
+
+    if not isinstance(property_name, str) or not property_name.strip():
+        raise ValueError("property_name must be a non-empty string")
+
+    # Create deep copy to avoid modifying original
+    new_api = copy.deepcopy(api_item)
+
+    if "schema" in new_api and isinstance(new_api["schema"], dict):
+        _remove_property_from_schema(new_api["schema"], property_name)
+
+    return new_api
+
+
+def remove_property_from_api_array(
+    api_array: List[Dict[str, Any]], property_name: str
+) -> List[Dict[str, Any]]:
+    """
+    Remove specified property from all API objects in array.
+
+    Args:
+        api_array: API array returned by generate_api_array
+        property_name: Name of property to remove
+
+    Returns:
+        list: Processed API array with property removed from all items
+
+    Raises:
+        ValueError: When input parameters are invalid
+        TypeError: When input types are incorrect
+    """
+    if not isinstance(api_array, list) or not api_array:
+        raise ValueError("api_array must be a non-empty list")
+
+    if not isinstance(property_name, str) or not property_name.strip():
+        raise ValueError("property_name must be a non-empty string")
+
+    result = []
+
+    for api_item in api_array:
+        try:
+            processed_item = remove_property_from_api_item(api_item, property_name)
+            result.append(processed_item)
+        except Exception as e:
+            result.append(copy.deepcopy(api_item))  # Keep original if processing fails
+
+    return result
+
+
+def fill_default_values_by_schema(
+    schema: Dict[str, Any], arguments: Dict[str, Any]
+) -> Dict[str, Any]:
+    """
+    Auto-fill default values in arguments based on JSON Schema.
+
+    Only fills missing parameters or those with None/empty string values.
+
+    Args:
+        schema: JSON Schema object with grouped structure (body/query/lzwcaiConfig)
+        arguments: User input parameter dictionary
+
+    Returns:
+        dict: Parameter dictionary with default values filled
+
+    Raises:
+        TypeError: When input types are incorrect
+    """
+    if not isinstance(schema, dict):
+        raise TypeError("schema must be a dictionary")
+
+    if not isinstance(arguments, dict):
+        arguments = {}
+    else:
+        arguments = copy.deepcopy(arguments)
+
+    for group_name, group_schema in schema.get("properties", {}).items():
+        if not isinstance(arguments.get(group_name), dict):
+            arguments[group_name] = {}
+
+        for param_name, param_schema in group_schema.get("properties", {}).items():
+            default_value = param_schema.get("default")
+            current_value = arguments[group_name].get(param_name)
+
+            # Fill default only if parameter is missing, None, or empty string
+            if (
+                current_value is None or current_value == ""
+            ) and default_value is not None:
+                arguments[group_name][param_name] = default_value
+
+    return arguments
+
+
+def generate_api_array(api_params: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+    """
+    Generate API array with JSON Schema for each API.
+
+    Args:
+        api_params: List of API parameter definitions
+
+    Returns:
+        list: API array with schema attached to each item
+
+    Raises:
+        TypeError: If api_params is not a list
+    """
+    if not isinstance(api_params, list):
+        raise TypeError("api_params must be a list")
+
+    api_array = []
+    for param in api_params:
+        try:
+            schema = generate_json_schema(param.get("parameters", []))
+            api_array.append({**param, "schema": schema})
+        except Exception as e:
+            logger.error(f"Error processing config: {str(e)}")
+            api_array.append(param)  # Add without schema if generation fails
+
+    return api_array
+
+
+def check_required_arguments(
+    schema: Dict[str, Any], arguments: Dict[str, Any]
+) -> List[str]:
+    """
+    Validate that arguments contain all required parameters from schema.
+
+    Args:
+        schema: JSON Schema object with grouped structure (body/query/lzwcaiConfig)
+        arguments: User input parameter dictionary
+
+    Returns:
+        list: Missing required parameters with group names, e.g., ['body.username', 'lzwcaiConfig.userId']
+
+    Raises:
+        TypeError: When input types are incorrect
+    """
+    if not isinstance(schema, dict):
+        raise TypeError("schema must be a dictionary")
+
+    if not isinstance(arguments, dict):
+        arguments = {}
+
+    missing_params = []
+
+    for group_name, group_schema in schema.get("properties", {}).items():
+        group_args = arguments.get(group_name, {})
+        required_params = group_schema.get("required", [])
+
+        for param_name in required_params:
+            param_value = group_args.get(param_name) if group_args else None
+
+            # Consider missing if not provided, None, or empty string
+            if param_value is None or param_value == "":
+                # Try to get parameter description
+                description = ""
+                try:
+                    param_properties = group_schema.get("properties", {})
+                    param_info = param_properties.get(param_name, {})
+                    description = param_info.get("description", "")
+                except Exception:
+                    pass
+
+                # Format missing parameter name
+                if description:
+                    missing_params.append(f"{group_name}.{param_name}（{description}）")
+                else:
+                    missing_params.append(f"{group_name}.{param_name}")
+
+    return missing_params
+
+
+if __name__ == "__main__":
+    # Example usage and testing
+    try:
+        with open(
+            "E:/yh-ai/project/lzwcai-szyg/lzwcai-demp-tool-server/src/"
+            "lzwcai_demp_tool_server_business_to_mcp/mcp_generator/src/parameters.json",
+            "r",
+            encoding="utf-8",
+        ) as f:
+            api_params = json.load(f)
+
+        api_array = generate_api_array(api_params)
+        result = remove_property_from_api_array(api_array, "userId")
+
+        # Write results to JSON file
+        with open("schema1.json", "w", encoding="utf-8") as f:
+            json.dump(result, f, ensure_ascii=False, indent=4)
+
+    except FileNotFoundError:
+        logger.error(f"Warning: Test data file not found. Skipping example execution.")
+    except Exception as e:
+        logger.error(f"Error in example execution: {str(e)}")

lzwcai_mcp_api_converter/lzwcai_mcp_api_converter/src/business/get_business_api.py

@@ -0,0 +1,204 @@
+"""
+Business API configuration utility functions.
+
+This module provides utilities for fetching and processing business API configurations.
+"""
+
+import json
+import os
+import requests
+from typing import Dict, List, Any
+from ..util.logger_config import get_logger
+
+# 配置日志
+logger = get_logger(__name__)
+
+
+
+
+def get_business_api_details(api_ids: List[int], auth_token: str = None) -> List[Dict[str, Any]]:
+    """
+    获取业务平台API详情
+
+    调用业务平台接口获取指定API ID列表的详细信息
+
+    Args:
+        api_ids: API ID列表，例如 [1925128743899111425, 1925128744524062721]
+        auth_token: 认证token，如果不提供则使用默认token
+
+    Returns:
+        List[Dict[str, Any]]: API详情列表，返回接口响应中的data字段内容
+
+    Raises:
+        requests.RequestException: 当网络请求失败时抛出
+        ValueError: 当响应格式不正确或返回错误时抛出
+
+    Example:
+        >>> api_ids = [1925128743899111425, 1925128744524062721]
+        >>> details = get_business_api_details(api_ids)
+        >>> print(len(details))
+        2
+    """
+    if not isinstance(api_ids, list) or not api_ids:
+        raise ValueError("api_ids must be a non-empty list")
+
+    # 默认认证token
+    default_token = "eyJhbGciOiJIUzUxMiJ9.eyJsb2dpbl91c2VyX2tleSI6ImM3OGU0M2NlLTJhZjQtNGRjYy1iMWE1LTU3YjM5YTdkNTA1OSJ9.5f1lSJJdLUunZIwCfneT1DiagGN4jD-QCnFCffWmrnvEcLfpuSMWRpY7fF-6H3yZ2N5ICZ4ZQN6cx7iqwF6jKw"
+    token = auth_token or default_token
+
+    # 接口URL - 支持环境变量配置
+    # 默认URL
+    default_url = "http://lzwcai-demp-corp-manager:8086/system/mcpServer/bizSys/api/getByIds"
+    # 从环境变量获取URL，如果没有设置则使用默认URL
+    url = os.getenv("lzwcai_mcp_dyntoolapi_auth_url", default_url)
+
+    # 请求头
+    headers = {
+        "Authorization": f"Bearer {token}",
+        # "User-Agent": "Apifox/1.0.0 (https://apifox.com)",
+        "Content-Type": "application/json",
+        # "Accept": "*/*",
+        # "Host": "192.168.2.236:8088",
+        "Connection": "keep-alive"
+    }
+
+    try:
+        # 发送POST请求
+        response = requests.post(url, headers=headers, json=api_ids, timeout=30)
+        response.raise_for_status()  # 检查HTTP状态码
+
+        # 解析响应JSON
+        response_data = response.json()
+
+        # 检查响应格式
+        if not isinstance(response_data, dict):
+            raise ValueError("响应格式不正确：期望JSON对象")
+
+        # 检查业务状态码
+        code = response_data.get("code")
+        if code != 200:
+            msg = response_data.get("msg", "未知错误")
+            raise ValueError(f"业务接口返回错误：code={code}, msg={msg}")
+
+        # 获取data字段
+        data = response_data.get("data", [])
+        if not isinstance(data, list):
+            logger.warning("响应中的data字段不是列表类型，将转换为列表")
+            data = [data] if data is not None else []
+
+        logger.info(f"成功获取 {len(data)} 个API详情")
+        return data
+
+    except requests.exceptions.Timeout:
+        raise requests.RequestException("请求超时：接口响应时间过长")
+    except requests.exceptions.ConnectionError:
+        raise requests.RequestException("连接错误：无法连接到业务平台服务器")
+    except requests.exceptions.HTTPError as e:
+        raise requests.RequestException(f"HTTP错误：{e}")
+    except json.JSONDecodeError:
+        raise ValueError("响应格式错误：无法解析JSON数据")
+    except Exception as e:
+        logger.error(f"获取API详情时发生未知错误：{str(e)}")
+        raise
+
+
+def map_api_details_to_config(api_details: List[Dict[str, Any]]) -> Dict[str, Any]:
+    """
+    将API详情数据映射为api_config.json格式
+
+    Args:
+        api_details: get_business_api_details方法返回的API详情列表
+
+    Returns:
+        Dict[str, Any]: 符合api_config.json格式的配置对象
+
+    Raises:
+        ValueError: 当输入数据格式不正确时抛出
+
+    Example:
+        >>> api_details = get_business_api_details([1925128743899111425])
+        >>> config = map_api_details_to_config(api_details)
+        >>> print(config["serverName"])
+        lzwcai_mcp_api_converter
+    """
+    if not isinstance(api_details, list):
+        raise ValueError("api_details must be a list")
+
+    if not api_details:
+        raise ValueError("api_details cannot be empty")
+
+    # 获取第一个API的domainUrl作为全局domainUrl
+    domain_url = ""
+    if api_details and isinstance(api_details[0], dict):
+        domain_url = api_details[0].get("domainUrl", "")
+
+    # 收集所有businessPrompts用于生成description
+    business_prompts = []
+    for api in api_details:
+        if isinstance(api, dict) and api.get("businessPrompts"):
+            business_prompts.append(api["businessPrompts"])
+
+    # 生成description
+    description = "、".join(business_prompts) if business_prompts else "业务API集合"
+
+    # 构建配置对象
+    config = {
+        "serverName": "lzwcai_mcp_api_converter",
+        "description": description,
+        "domainUrl": domain_url,
+        "packageName": "lzwcai-mcp-dyntoolapi",
+        "version": "1.0.0",
+        "apiConfig": api_details  # 直接使用原始API详情数据
+    }
+
+    logger.info(f"成功映射 {len(api_details)} 个API到配置格式")
+    logger.info(f"服务名称: {config['serverName']}")
+    logger.info(f"域名URL: {config['domainUrl']}")
+    logger.info(f"描述: {config['description']}")
+
+    return config
+
+
+def get_business_api_config(api_ids: List[int], auth_token: str = None) -> Dict[str, Any]:
+    """
+    一步到位获取业务平台API配置
+
+    传入API ID列表，直接返回处理好的api_config.json格式配置
+
+    Args:
+        api_ids: API ID列表，例如 [1925128743899111425, 1925128744524062721]
+        auth_token: 认证token，如果不提供则使用默认token
+
+    Returns:
+        Dict[str, Any]: 符合api_config.json格式的完整配置对象
+
+    Raises:
+        requests.RequestException: 当网络请求失败时抛出
+        ValueError: 当响应格式不正确或返回错误时抛出
+
+    Example:
+        >>> api_ids = [1925128743899111425, 1925128744524062721]
+        >>> config = get_business_api_config(api_ids)
+        >>> print(config["serverName"])
+        lzwcai_mcp_api_converter
+        >>> print(len(config["apiConfig"]))
+        2
+    """
+    try:
+        # 步骤1: 获取API详情
+        logger.info(f"开始获取 {len(api_ids)} 个API的详情...")
+        api_details = get_business_api_details(api_ids, auth_token)
+
+        # 步骤2: 映射为配置格式
+        logger.info("开始映射为配置格式...")
+        config = map_api_details_to_config(api_details)
+
+        logger.info(f"[SUCCESS] 成功生成API配置！包含 {len(config['apiConfig'])} 个API")
+        return config
+
+    except Exception as e:
+        logger.error(f"获取业务API配置时发生错误: {str(e)}")
+        raise
+
+
+