ツールの戻り値

def create_image_message(self, image: str) -> ToolInvokeMessage:    """    Return an image URL message        Dify will automatically download the image from the provided URL    and display it to the user.        Args:        image: URL to an image file            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

def create_link_message(self, link: str) -> ToolInvokeMessage:    """    Return a clickable link message        Args:        link: URL to be displayed as a clickable link            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

def create_text_message(self, text: str) -> ToolInvokeMessage:    """    Return a text message        Args:        text: Text content to be displayed            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

def create_blob_message(self, blob: bytes, meta: dict = None) -> ToolInvokeMessage:    """    Return a file blob message        For returning raw file data such as images, audio, video,     or documents (PPT, Word, Excel, etc.)        Args:        blob: Raw file data in bytes        meta: File metadata dictionary. Include 'mime_type' to specify               the file type, otherwise 'octet/stream' will be used                  Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

def create_json_message(self, json: dict) -> ToolInvokeMessage:    """    Return a formatted JSON message        Useful for data transmission between workflow nodes.    In agent mode, most LLMs can read and understand JSON data.        Args:        json: Python dictionary to be serialized as JSON            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

from typing import Anydef create_variable_message(self, variable_name: str, variable_value: Any) -> ToolInvokeMessage:    """    Create a named variable for workflow integration        For non-streaming output variables. If multiple instances with the     same name are created, the latest one overrides previous values.        Args:        variable_name: Name of the variable to create        variable_value: Value of the variable (any Python data type)            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

def create_stream_variable_message(    self, variable_name: str, variable_value: str) -> ToolInvokeMessage:    """    Create a streaming variable with typewriter effect        When referenced in an answer node in a chatflow application,    the text will be output with a typewriter effect.        Args:        variable_name: Name of the variable to create        variable_value: String value to stream (only strings supported)            Returns:        ToolInvokeMessage: Message object for the tool response    """    pass

identity:  author: example_author  name: example_tool  label:    en_US: Example Tool    zh_Hans: 示例工具    ja_JP: ツール例    pt_BR: Ferramenta de exemplodescription:  human:    en_US: A simple tool that returns a name    zh_Hans: 返回名称的简单工具    ja_JP: 名前を返す簡単なツール    pt_BR: Uma ferramenta simples que retorna um nome  llm: A simple tool that returns a name variableoutput_schema:  type: object  properties:    name:      type: string      description: "The name returned by the tool"    age:      type: integer      description: "The age returned by the tool"    profile:      type: object      properties:        interests:          type: array          items:            type: string        location:          type: string

def run(self, inputs):    # Process inputs and generate a name    generated_name = "Alice"        # Return the name as a variable that matches the output_schema    return self.create_variable_message("name", generated_name)

def run(self, inputs):    # Generate complex structured data    user_data = {        "name": "Bob",        "age": 30,        "profile": {            "interests": ["coding", "reading", "hiking"],            "location": "San Francisco"        }    }        # Return individual variables    self.create_variable_message("name", user_data["name"])    self.create_variable_message("age", user_data["age"])    self.create_variable_message("profile", user_data["profile"])        # Also return a text message for display    return self.create_text_message(f"User {user_data['name']} processed successfully")

import requestsfrom typing import Anyclass WeatherForecastTool:    def run(self, inputs: dict) -> Any:        # Get location from inputs        location = inputs.get("location", "London")                try:            # Call weather API (example only)            weather_data = self._get_weather_data(location)                        # Create variables for workflow use            self.create_variable_message("temperature", weather_data["temperature"])            self.create_variable_message("conditions", weather_data["conditions"])            self.create_variable_message("forecast", weather_data["forecast"])                        # Create a JSON message for data transmission            self.create_json_message(weather_data)                        # Create an image message for the weather map            self.create_image_message(weather_data["map_url"])                        # Return a formatted text response            return self.create_text_message(                f"Weather in {location}: {weather_data['temperature']}°C, {weather_data['conditions']}. "                f"Forecast: {weather_data['forecast']}"            )                    except Exception as e:            # Handle errors gracefully            return self.create_text_message(f"Error retrieving weather data: {str(e)}")        def _get_weather_data(self, location: str) -> dict:        # Mock implementation - in a real tool, this would call a weather API        return {            "location": location,            "temperature": 22,            "conditions": "Partly Cloudy",            "forecast": "Sunny with occasional showers tomorrow",            "map_url": "https://example.com/weather-map.png"        }