本次使用到的工具：
首先介绍一下 ：
FastGPT提供开箱即用的数据处理和模型调用能力。它支持通过可视化的 Flow 模块进行工作流编排，以实现复杂的问答场景。FASTGPT基本使用教程B站有，可以去看看，这里不做讲解。
FASTGPT各个模型会优先调用用户自己的配置的接口，若无，才会消耗FASTGPT的AI积分进行调用。因此，FASTGPT基本只消耗一些索引的token，消耗极少，在免费范围内。FASTGPT配置的接口也可以选用 AFF 硅基流动 含aff的deepseekchat模型。
AFF 硅基流动 含aff 拉新双方可领取2000万token，可以调用deepseek chat，并且可以免费调用FLUX.1模型绘画。FLUX.1应该是目前最强绘画模型。
AI 绘画新标杆！一文详解最新开源模型 Flux.1
综上，无任何付费项目。
效果展示：
直接输入中文提示词即可，会生成对应英文提示词
工作流展示：
部署教程：
先在 AFF 硅基流动 含aff中注册，生成api key，复制备用。
接着去fastgpt创建工作流，并导入我的工作流如下：
{
"nodes": [
{
"nodeId": "userGuide",
"name": "core.module.template.User guide",
"intro": "core.app.tip.userGuideTip",
"avatar": "core/workflow/template/systemConfig",
"flowNodeType": "userGuide",
"position": {
"x": 638.9689284902843,
"y": 1330.8896334960516
},
"version": "481",
"inputs": [
{
"key": "welcomeText",
"renderTypeList": [
"hidden"
],
"valueType": "string",
"label": "core.app.Welcome Text",
"type": "hidden",
"showTargetInApp": false,
"showTargetInPlugin": false,
"value": "您好,我是stable-diffusion文生图像绘制助手,您可以按照下面这个格式进行提问:\n[一只赛博朋克猫咪]\n[一只黑白相间的狗在追蝴蝶]",
"connected": false,
"selectedTypeIndex": 0
},
{
"key": "variables",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "core.module.Variable",
"value": [
{
"id": "6agumx",
"key": "AI优化",
"label": "是否需要使用AI优化提示词？(默认不需要)",
"type": "select",
"required": false,
"maxLen": 50,
"enums": [
{
"value": "true"
},
{
"value": "false"
}
],
"icon": "core/app/variable/select"
}
],
"type": "hidden",
"showTargetInApp": false,
"showTargetInPlugin": false,
"connected": false,
"selectedTypeIndex": 0
},
{
"key": "questionGuide",
"valueType": "boolean",
"renderTypeList": [
"hidden"
],
"label": "",
"type": "switch",
"showTargetInApp": false,
"showTargetInPlugin": false,
"connected": false,
"selectedTypeIndex": 0
},
{
"key": "tts",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"type": "hidden",
"showTargetInApp": false,
"showTargetInPlugin": false,
"connected": false,
"selectedTypeIndex": 0
},
{
"key": "whisper",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"type": "hidden",
"showTargetInApp": false,
"showTargetInPlugin": false,
"connected": false,
"selectedTypeIndex": 0
},
{
"key": "scheduleTrigger",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": null
}
],
"outputs": []
},
{
"nodeId": "userChatInput",
"name": "流程开始",
"intro": "当用户发送一个内容后，流程将会从这个模块开始执行。",
"avatar": "core/workflow/template/workflowStart",
"flowNodeType": "workflowStart",
"position": {
"x": 1046.1768900426205,
"y": 1422.528457769088
},
"version": "481",
"inputs": [
{
"key": "userChatInput",
"renderTypeList": [
"reference",
"textarea"
],
"valueType": "string",
"label": "问题输入",
"required": true,
"toolDescription": "用户问题",
"type": "systemInput",
"showTargetInApp": false,
"showTargetInPlugin": false,
"connected": false,
"selectedTypeIndex": 0,
"value": [
"userChatInput",
"userChatInput"
]
}
],
"outputs": [
{
"id": "userChatInput",
"key": "userChatInput",
"label": "common:core.module.input.label.user question",
"type": "static",
"valueType": "string"
}
]
},
{
"nodeId": "tNbjIPgU4HWr",
"name": "AI 生成提示词",
"intro": "AI 大模型对话",
"avatar": "core/workflow/template/aiChat",
"flowNodeType": "chatNode",
"showStatus": true,
"position": {
"x": 1461.3899581366866,
"y": 1164.185941848274
},
"version": "481",
"inputs": [
{
"key": "model",
"renderTypeList": [
"settingLLMModel",
"reference"
],
"label": "core.module.input.label.aiModel",
"valueType": "string",
"value": "deepseek-chat"
},
{
"key": "temperature",
"renderTypeList": [
"hidden"
],
"label": "",
"value": 3,
"valueType": "number",
"min": 0,
"max": 10,
"step": 1
},
{
"key": "maxToken",
"renderTypeList": [
"hidden"
],
"label": "",
"value": 4000,
"valueType": "number",
"min": 100,
"max": 4000,
"step": 50
},
{
"key": "isResponseAnswerText",
"renderTypeList": [
"hidden"
],
"label": "",
"value": true,
"valueType": "boolean"
},
{
"key": "quoteTemplate",
"renderTypeList": [
"hidden"
],
"label": "",
"valueType": "string"
},
{
"key": "quotePrompt",
"renderTypeList": [
"hidden"
],
"label": "",
"valueType": "string"
},
{
"key": "aiChatVision",
"renderTypeList": [
"hidden"
],
"label": "",
"valueType": "boolean",
"value": true
},
{
"key": "systemPrompt",
"renderTypeList": [
"textarea",
"reference"
],
"max": 3000,
"valueType": "string",
"label": "core.ai.Prompt",
"description": "core.app.tip.chatNodeSystemPromptTip",
"placeholder": "core.app.tip.chatNodeSystemPromptTip",
"value": "作为 Stable Diffusion Prompt 提示词专家，您将从关键词中创建提示，通常来自 Danbooru 等数据库。\n\n提示通常描述图像，使用常见词汇，按重要性排列，并用逗号分隔。避免使用\"-\"或\".\"，但可以接受空格和自然语言。避免词汇重复。\n\n为了强调关键词，请将其放在括号中以增加其权重。例如，\"(flowers)\"将'flowers'的权重增加1.1倍，而\"(((flowers)))\"将其增加1.331倍。使用\"(flowers:1.5)\"将'flowers'的权重增加1.5倍。只为重要的标签增加权重。\n\n提示包括三个部分：**前缀**（质量标签+风格词+效果器）+ **主题**（图像的主要焦点）+ **场景**（背景、环境）。\n\n* 前缀影响图像质量。像\"masterpiece\"、\"best quality\"、\"4k\"这样的标签可以提高图像的细节。像\"illustration\"、\"lensflare\"这样的风格词定义图像的风格。像\"bestlighting\"、\"lensflare\"、\"depthoffield\"这样的效果器会影响光照和深度。\n\n* 主题是图像的主要焦点，如角色或场景。对主题进行详细描述可以确保图像丰富而详细。增加主题的权重以增强其清晰度。对于角色，描述面部、头发、身体、服装、姿势等特征。\n\n* 场景描述环境。没有场景，图像的背景是平淡的，主题显得过大。某些主题本身包含场景（例如建筑物、风景）。像\"花草草地\"、\"阳光\"、\"河流\"这样的环境词可以丰富场景。你的任务是设计图像生成的提示。请按照以下步骤进行操作：\n\n1. 我会发送给您一个图像场景。需要你生成详细的图像描述\n2. 图像描述必须是英文，输出为Positive Prompt。\n\n示例：\n\n我发送：二战时期的护士。\n您回复只回复：\nA WWII-era nurse in a German uniform, holding a wine bottle and stethoscope, sitting at a table in white attire, with a table in the background, masterpiece, best quality, 4k, illustration style, best lighting, depth of field, detailed character, detailed environment.\n"
},
{
"key": "history",
"renderTypeList": [
"numberInput",
"reference"
],
"valueType": "chatHistory",
"label": "core.module.input.label.chat history",
"description": "最多携带多少轮对话记录",
"required": true,
"min": 0,
"max": 50,
"value": 0
},
{
"key": "quoteQA",
"renderTypeList": [
"settingDatasetQuotePrompt"
],
"label": "",
"debugLabel": "知识库引用",
"description": "",
"valueType": "datasetQuote"
},
{
"key": "stringQuoteText",
"renderTypeList": [
"reference",
"textarea"
],
"label": "app:document_quote",
"debugLabel": "app:document_quote",
"description": "app:document_quote_tip",
"valueType": "string"
},
{
"key": "userChatInput",
"renderTypeList": [
"reference",
"textarea"
],
"valueType": "string",
"label": "用户问题",
"required": true,
"toolDescription": "用户问题",
"value": [
"userChatInput",
"userChatInput"
]
}
],
"outputs": [
{
"id": "history",
"key": "history",
"required": true,
"label": "core.module.output.label.New context",
"description": "core.module.output.description.New context",
"valueType": "chatHistory",
"valueDesc": "{\n obj: System | Human | AI;\n value: string;\n}[]",
"type": "static"
},
{
"id": "answerText",
"key": "answerText",
"required": true,
"label": "core.module.output.label.Ai response content",
"description": "core.module.output.description.Ai response content",
"valueType": "string",
"type": "static"
}
]
},
{
"nodeId": "szqvHMArA7rG",
"name": "FLUX.1",
"intro": "可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）",
"avatar": "core/workflow/template/httpRequest",
"flowNodeType": "httpRequest468",
"showStatus": true,
"position": {
"x": 2097.395110695174,
"y": 1268.0575222390357
},
"version": "481",
"inputs": [
{
"key": "system_addInputParam",
"renderTypeList": [
"addInputParam"
],
"valueType": "dynamic",
"label": "",
"required": false,
"description": "core.module.input.description.HTTP Dynamic Input",
"editField": {
"key": true,
"valueType": true
},
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"any",
"chatHistory",
"datasetQuote",
"dynamic",
"selectApp",
"selectDataset"
],
"showDescription": false,
"showDefaultValue": true
}
},
{
"key": "system_httpMethod",
"renderTypeList": [
"custom"
],
"valueType": "string",
"label": "",
"value": "POST",
"required": true
},
{
"key": "system_httpTimeout",
"renderTypeList": [
"custom"
],
"valueType": "number",
"label": "",
"value": 30,
"min": 5,
"max": 600,
"required": true
},
{
"key": "system_httpReqUrl",
"renderTypeList": [
"hidden"
],
"valueType": "string",
"label": "",
"description": "core.module.input.description.Http Request Url",
"placeholder": "https://api.ai.com/getInventory",
"required": false,
"value": "https://api.siliconflow.cn/v1/black-forest-labs/FLUX.1-schnell/text-to-image"
},
{
"key": "system_httpHeader",
"renderTypeList": [
"custom"
],
"valueType": "any",
"value": [
{
"key": "content-type",
"type": "string",
"value": "application/json"
},
{
"key": "authorization",
"type": "string",
"value": "Bearer sk-xxxxx"
}
],
"label": "",
"description": "core.module.input.description.Http Request Header",
"placeholder": "core.module.input.description.Http Request Header",
"required": false
},
{
"key": "system_httpParams",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"value": [],
"label": "",
"required": false
},
{
"key": "system_httpJsonBody",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"value": "{\r\n \"prompt\": \"{{prompt}}\",\r\n \"image_size\": \"1024x1024\",\r\n \"num_inference_steps\": 28\r\n}",
"label": "",
"required": false
},
{
"key": "prompt",
"valueType": "string",
"label": "prompt",
"renderTypeList": [
"reference"
],
"description": "",
"canEdit": true,
"editField": {
"key": true,
"valueType": true
},
"value": [
"tNbjIPgU4HWr",
"answerText"
],
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"any",
"chatHistory",
"datasetQuote",
"dynamic",
"selectApp",
"selectDataset"
],
"showDescription": false,
"showDefaultValue": true
}
}
],
"outputs": [
{
"id": "error",
"key": "error",
"label": "请求错误",
"description": "HTTP请求错误信息，成功时返回空",
"valueType": "object",
"type": "static"
},
{
"id": "httpRawResponse",
"key": "httpRawResponse",
"label": "原始响应",
"required": true,
"description": "HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。",
"valueType": "any",
"type": "static"
},
{
"id": "system_addOutputParam",
"key": "system_addOutputParam",
"type": "dynamic",
"valueType": "dynamic",
"label": "",
"editField": {
"key": true,
"valueType": true
}
},
{
"id": "q2mkKEFTiGJV",
"type": "dynamic",
"key": "images[0].url",
"valueType": "string",
"label": "images[0].url"
}
]
},
{
"nodeId": "vFlAtLTLYxl7",
"name": "文本拼接",
"intro": "可对固定或传入的文本进行加工后输出，非字符串类型数据最终会转成字符串类型。",
"avatar": "core/workflow/template/textConcat",
"flowNodeType": "textEditor",
"position": {
"x": 2734.785397176285,
"y": 1410.7360523031057
},
"version": "486",
"inputs": [
{
"key": "system_addInputParam",
"renderTypeList": [
"addInputParam"
],
"valueType": "dynamic",
"label": "",
"required": false,
"description": "可以引用其他节点的输出，作为文本拼接的变量，输入 / 唤起变量列表",
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"any",
"chatHistory",
"datasetQuote",
"dynamic",
"selectApp",
"selectDataset"
],
"showDescription": false,
"showDefaultValue": false
}
},
{
"key": "system_textareaInput",
"renderTypeList": [
"textarea"
],
"valueType": "string",
"required": true,
"label": "拼接文本",
"placeholder": "可输入 / 唤起变量列表",
"value": ""
},
{
"renderTypeList": [
"reference"
],
"valueType": "string",
"canEdit": true,
"key": "url",
"label": "url",
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"any",
"chatHistory",
"datasetQuote",
"dynamic",
"selectApp",
"selectDataset"
],
"showDescription": false,
"showDefaultValue": false
},
"required": true,
"value": [
"szqvHMArA7rG",
"q2mkKEFTiGJV"
]
}
],
"outputs": [
{
"id": "system_text",
"key": "system_text",
"label": "拼接结果",
"type": "static",
"valueType": "string"
}
]
},
{
"nodeId": "e6s2QseLaH23",
"name": "指定回复",
"intro": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
"avatar": "core/workflow/template/reply",
"flowNodeType": "answerNode",
"position": {
"x": 3270.1509500165303,
"y": 1596.8386061773158
},
"version": "481",
"inputs": [
{
"key": "text",
"renderTypeList": [
"textarea",
"reference"
],
"valueType": "any",
"required": true,
"label": "core.module.input.label.Response content",
"description": "core.module.input.description.Response content",
"placeholder": "core.module.input.description.Response content",
"selectedTypeIndex": 1,
"value": [
"vFlAtLTLYxl7",
"system_text"
]
}
],
"outputs": []
}
],
"edges": [
{
"source": "tNbjIPgU4HWr",
"target": "szqvHMArA7rG",
"sourceHandle": "tNbjIPgU4HWr-source-right",
"targetHandle": "szqvHMArA7rG-target-left"
},
{
"source": "userChatInput",
"target": "tNbjIPgU4HWr",
"sourceHandle": "userChatInput-source-right",
"targetHandle": "tNbjIPgU4HWr-target-left"
},
{
"source": "vFlAtLTLYxl7",
"target": "e6s2QseLaH23",
"sourceHandle": "vFlAtLTLYxl7-source-right",
"targetHandle": "e6s2QseLaH23-target-left"
},
{
"source": "szqvHMArA7rG",
"target": "vFlAtLTLYxl7",
"sourceHandle": "szqvHMArA7rG-source-right",
"targetHandle": "vFlAtLTLYxl7-target-left"
}
],
"chatConfig": {
"welcomeText": "您好,我是FLUX.1 AI绘画小助手.\n\n直接输入提示词即可使用AI绘画。AI自动优化提示词",
"variables": [],
"whisperConfig": {
"open": true,
"autoSend": false,
"autoTTSResponse": false
},
"scheduledTriggerConfig": {
"cronString": "",
"timezone": "Asia/Shanghai",
"defaultPrompt": ""
},
"_id": "66c4a5e9501b65de6749f604"
}
}
导入方式如下：
接着来到图中所示空处，将sk-xxxxxxx换成你的之前提到的api kay
（可选）以上工作流调用的是FLUX.1，如果想使用SD3绘画的话，在上图中,点击cURL导入，输入以下内容即可：
curl --request POST \
--url https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-3-medium/text-to-image \
--header 'accept: application/json' \
--header 'authorization: Bearer sk-xxxxxxxxx' \
--header 'content-type: application/json' \
--data '
{
"prompt": "{{prompt}}",
"image_size": "1024x1024",
"batch_size": 1,
"num_inference_steps": 20,
"guidance_scale": 7.5
}
'
接入NEW API
在fastgpt点击发布渠道，然后记录下图中两个红框的值,另外发布渠道中也可以直接创建我下面那样的分享链接
来到NEW API填写相关信息即可，兼容open ai接口
大功告成
这是我搭建好的，大家可以试试：效果展示 （已屏蔽nsfw的内容）
鸣谢
参考： 放一个fastgpt调用CF的SD模型并结合gpt的简单绘图工作流，让大佬们看看哪里可以进行优化 - 常规话题 / 快问快答 - LINUX DO
搭建图生图的工作流：
【2】一分钱不花！ AI图生图，AI优化生成提示词，并可接入NEW API，模型工具全免费，永久有效 - 常规话题 / 人工智能 - LINUX DO
