From 3e0a2e571900c22644a773e9e7dac9ff25474ee2 Mon Sep 17 00:00:00 2001 From: ai-business-hql Date: Mon, 4 Aug 2025 16:21:06 +0800 Subject: [PATCH 01/15] =?UTF-8?q?feat:=20=E9=98=B2=E6=AD=A2=E7=94=A8?= =?UTF-8?q?=E6=88=B7=E4=B8=8A=E4=BC=A0=E4=B8=80=E5=BC=A0=E8=B4=BC=E5=A4=A7?= =?UTF-8?q?=E7=9A=84=E5=9B=BE=E7=89=87?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ui/src/apis/workflowChatApi.ts | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/ui/src/apis/workflowChatApi.ts b/ui/src/apis/workflowChatApi.ts index a184d5e..ebe121c 100644 --- a/ui/src/apis/workflowChatApi.ts +++ b/ui/src/apis/workflowChatApi.ts @@ -2,7 +2,7 @@ * @Author: ai-business-hql qingli.hql@alibaba-inc.com * @Date: 2025-06-24 16:29:05 * @LastEditors: ai-business-hql qingli.hql@alibaba-inc.com - * @LastEditTime: 2025-08-02 11:33:35 + * @LastEditTime: 2025-08-04 16:20:04 * @FilePath: /comfyui_copilot/ui/src/apis/workflowChatApi.ts * @Description: 这是默认设置,请设置`customMade`, 打开koroFileHeader查看配置 进行设置: https://github.com/OBKoro1/koro1FileHeader/wiki/%E9%85%8D%E7%BD%AE */ @@ -192,6 +192,7 @@ export namespace WorkflowChatAPI { if (image.url) { content.push({ type: 'input_image', + detail: 'low', image_url: image.url }); From 5a2361a0a67aa9f57b3813af7f732b6a4acb5b99 Mon Sep 17 00:00:00 2001 From: ai-business-hql Date: Mon, 4 Aug 2025 17:20:39 +0800 Subject: [PATCH 02/15] =?UTF-8?q?feat:=20rewrite=E4=B8=8A=E4=B8=8B?= =?UTF-8?q?=E6=96=87=E6=8E=A7=E5=88=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/data/workflow_rewrite_expert.json | 37 + backend/service/workflow_rewrite_agent.py | 827 +----------------- .../{App-DT2fOvHP.js => App-BVbKTtsg.js} | 4 +- ...ide-CqUJVeP7.js => DebugGuide-BQ7towRD.js} | 2 +- ...lt-BPVOJwqc.js => DebugResult-CdvyVrc1.js} | 2 +- ...BRKJ_AoR.js => WorkflowOption-39wfPDLn.js} | 2 +- dist/copilot_web/input.js | 6 +- ...kzGi.js => message-components-BrrLmtj_.js} | 2 +- ...t-Bp01CH2d.js => workflowChat-B_xZb6og.js} | 6 +- 9 files changed, 81 insertions(+), 807 deletions(-) create mode 100644 backend/data/workflow_rewrite_expert.json rename dist/copilot_web/{App-DT2fOvHP.js => App-BVbKTtsg.js} (87%) rename dist/copilot_web/{DebugGuide-CqUJVeP7.js => DebugGuide-BQ7towRD.js} (98%) rename dist/copilot_web/{DebugResult-BPVOJwqc.js => DebugResult-CdvyVrc1.js} (98%) rename dist/copilot_web/{WorkflowOption-BRKJ_AoR.js => WorkflowOption-39wfPDLn.js} (99%) rename dist/copilot_web/{message-components-DmxYkzGi.js => message-components-BrrLmtj_.js} (99%) rename dist/copilot_web/{workflowChat-Bp01CH2d.js => workflowChat-B_xZb6og.js} (99%) diff --git a/backend/data/workflow_rewrite_expert.json b/backend/data/workflow_rewrite_expert.json new file mode 100644 index 0000000..df62c7b --- /dev/null +++ b/backend/data/workflow_rewrite_expert.json @@ -0,0 +1,37 @@ +[ + { + "name": "添加LoRA", + "description": "在现有工作流中添加LoRA节点", + "content": "在现有工作流中添加LoRA节点，确保与现有模型和提示词节点正确连接\n 在checkpoint节点后添加LoRA节点。\n {\n \"1\": {\n \"inputs\": {\n \"lora_name\": \"DOG.safetensors\",\n \"strength_model\": 1,\n \"strength_clip\": 1,\n \"model\": [\n \"2\",\n 0\n ],\n \"clip\": [\n \"2\",\n 1\n ]\n },\n \"class_type\": \"LoraLoader\",\n \"_meta\": {\n \"title\": \"Load LoRA\"\n }\n }" + }, + { + "name": "后处理增强", + "description": "后处理增强，例如在Preview Image或Save Image节点后添加高清放大功能（如Real-ESRGAN、ESRGAN等）; 或者添加图像缩放节点", + "content": "- 在Preview Image或Save Image节点后添加高清放大功能（如Real-ESRGAN、ESRGAN等）\n - 添加图像缩放节点\n {\n \"1\": {\n \"inputs\": {\n \"width\": 512,\n \"height\": 512,\n \"interpolation\": \"nearest\",\n \"method\": \"stretch\",\n \"condition\": \"always\",\n \"multiple_of\": 0\n },\n \"class_type\": \"ImageResize+\",\n \"_meta\": {\n \"title\": \"🔧 Image Resize\"\n }\n }\n}\n - 添加图像尺寸调整节点\n {\n \"2\": {\n \"inputs\": {\n \"aspect_ratio\": \"original\",\n \"proportional_width\": 2,\n \"proportional_height\": 1,\n \"fit\": \"letterbox\",\n \"method\": \"lanczos\",\n \"round_to_multiple\": \"8\",\n \"scale_to_longest_side\": false,\n \"longest_side\": 1024\n },\n \"class_type\": \"LayerUtility: ImageScaleByAspectRatio\",\n \"_meta\": {\n \"title\": \"LayerUtility: ImageScaleByAspectRatio\"\n }\n }\n}\n -添加图像放大节点\n \"11\": {\n \"inputs\": {\n \"width\": 512,\n \"height\": 512,\n \"upscale_method\": \"nearest-exact\",\n \"keep_proportion\": false,\n \"divisible_by\": 2,\n \"crop\": \"disabled\",\n \"image\": [\n \"12\",\n 0\n ]\n },\n \"class_type\": \"ImageResizeKJ\",\n \"_meta\": {\n \"title\": \"Resize Image\"\n }\n },\n -添加VAEdecode节点\n \"12\": {\n \"inputs\": {},\n \"class_type\": \"VAEDecode\",\n \"_meta\": {\n \"title\": \"VAE Decode\"\n }\n }\n}" + }, + { + "name": "提示词优化", + "description": "修改现有提示词节点的内容(提示词应该在(CLIP Text Encode Prompt或Text _O节点内编辑); 添加单独的提示词输入节点", + "content": "{\n \"12\": {\n \"inputs\": {\n \"text\": [\n \"13\",\n 0\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"13\": {\n \"inputs\": {\n \"delimiter\": \", \",\n \"clean_whitespace\": \"true\",\n \"text_a\": [\n \"15\",\n 0\n ],\n \"text_b\": [\n \"16\",\n 0\n ]\n },\n \"class_type\": \"Text Concatenate\",\n \"_meta\": {\n \"title\": \"Text Concatenate\"\n }\n },\n \"15\": {\n \"inputs\": {\n \"text\": \"\"\n },\n \"class_type\": \"Text _O\",\n \"_meta\": {\n \"title\": \"Text _O\"\n }\n },\n \"16\": {\n \"inputs\": {\n \"text\": \"\"\n },\n \"class_type\": \"Text _O\",\n \"_meta\": {\n \"title\": \"Text _O\"\n }\n }\n}" + }, + { + "name": "图像反推", + "description": "理解图片信息并用文字表达出来", + "content": "添加图像反推节点（如CLIP Interrogator）\n{\n \"11\": {\n \"inputs\": {\n \"prompt_mode\": \"fast\",\n \"image_analysis\": \"off\"\n },\n \"class_type\": \"ClipInterrogator\",\n \"_meta\": {\n \"title\": \"Clip Interrogator ♾️Mixlab\"\n }\n }\n}\n - 添加更复杂或者更好用的图像反推节点(加载图片使用florence2进行反推)\n {\n \"6\": {\n \"inputs\": {\n \"image\": \"06.JPG\"\n },\n \"class_type\": \"LoadImage\",\n \"_meta\": {\n \"title\": \"$image.image!:The image to analyze, must be a url\"\n }\n },\n \"10\": {\n \"inputs\": {\n \"model\": \"microsoft/Florence-2-large\",\n \"precision\": \"fp16\",\n \"attention\": \"sdpa\"\n },\n \"class_type\": \"DownloadAndLoadFlorence2Model\",\n \"_meta\": {\n \"title\": \"DownloadAndLoadFlorence2Model\"\n }\n },\n \"11\": {\n \"inputs\": {\n \"text_input\": \"\",\n \"task\": \"more_detailed_caption\",\n \"fill_mask\": true,\n \"keep_model_loaded\": false,\n \"max_new_tokens\": 1024,\n \"num_beams\": 3,\n \"do_sample\": true,\n \"output_mask_select\": \"\",\n \"seed\": 1098631327477633,\n \"image\": [\n \"6\",\n 0\n ],\n \"florence2_model\": [\n \"10\",\n 0\n ]\n },\n \"class_type\": \"Florence2Run\",\n \"_meta\": {\n \"title\": \"Florence2Run\"\n }\n },\n \"18\": {\n \"inputs\": {\n \"anything\": [\n \"11\",\n 2\n ]\n },\n \"class_type\": \"easy showAnything\",\n \"_meta\": {\n \"title\": \"Show Any\"\n }\n },\n \"20\": {\n \"inputs\": {\n \"value\": \"Generate high-quality text descriptions from images using local Florence model.\\n \\n Main use cases:\\n 1. **Reverse image prompt generation**:\\n - When users upload an image and want to get prompts for AI art generation\\n - Analyzes visual elements, style, composition, etc. to generate prompts for Stable Diffusion, DALL-E, and other models\\n - In this case, return the tool's raw output directly to users without any modification or summary\\n - Users can directly use these prompts for image generation\\n 2. **Image content understanding**:\\n - When users ask about specific content, objects, scenes, people, etc. in the image\\n - Need to understand the semantic content of the image and answer users' specific questions\\n - In this case, combine tool output with conversation context to give users contextually appropriate natural responses\\n - Don't return raw output directly, but provide targeted replies based on understanding results\"\n },\n \"class_type\": \"PrimitiveStringMultiline\",\n \"_meta\": {\n \"title\": \"MCP\"\n }\n }\n}" + }, + { + "name": "添加ControlNet", + "description": "在使用风格迁移保持主体结构不变、保持主体形状、重新绘制背景、控制人物角色姿态、保持场景的深度和空间结构、基于线稿或者草图生成图像等场景下，可以用添加ControlNet节点来实现", + "content": "**ControlNet集成**：(preprocessor可选canny、depth等参数,模型样式选择，Controlnet开始、结束权重)\n {\n \"22\": {\n \"inputs\": {\n \"strength\": 1,\n \"start_percent\": 0,\n \"end_percent\": 1,\n \"control_net\": [\n \"23\",\n 0\n ],\n \"image\": [\n \"24\",\n 0\n ]\n },\n \"class_type\": \"ControlNetApplyAdvanced\",\n \"_meta\": {\n \"title\": \"Apply ControlNet\"\n }\n },\n \"23\": {\n \"inputs\": {\n \"control_net_name\": \"ControlNet-Standard-Lineart-for-SDXL.safetensors\"\n },\n \"class_type\": \"ControlNetLoader\",\n \"_meta\": {\n \"title\": \"Load ControlNet Model\"\n }\n },\n \"24\": {\n \"inputs\": {\n \"preprocessor\": \"none\",\n \"resolution\": 512\n },\n \"class_type\": \"AIO_Preprocessor\",\n \"_meta\": {\n \"title\": \"AIO Aux Preprocessor\"\n }\n }\n}" + }, + { + "name": "扩图", + "description": "给我一个扩图链路(包括图像加载和图像输出)", + "content": "{\n \"1\": {\n \"inputs\": {\n \"image\": \"01.JPG\"\n },\n \"class_type\": \"LoadImage\",\n \"_meta\": {\n \"title\": \"$image.image!:The image to analyze, must be a url\"\n }\n },\n \"2\": {\n \"inputs\": {\n \"model\": \"runwayml/stable-diffusion-xl-base-1.0\",\n \"precision\": \"fp16\",\n \"attention\": \"sdpa\"\n },\n \"class_type\": \"DownloadAndLoadModel\",\n \"_meta\": {\n \"title\": \"DownloadAndLoadModel\"\n }\n },\n \"3\": {\n \"inputs\": {\n \"prompt\": \"A beautiful girl with long hair and a white dress\",\n \"image\": [\n \"1\",\n 0\n ],\n \"model\": [\n \"2\",\n 0\n ]\n },\n \"class_type\": \"StableDiffusionXLRun\",\n \"_meta\": {\n \"title\": \"StableDiffusionXLRun\"\n }\n },\n \"4\": {\n \"inputs\": {\n \"image\": [\n \"3\",\n 0\n ]\n },\n \"class_type\": \"easy showImage\",\n \"_meta\": {\n \"title\": \"Show Image\"\n }\n }\n}" + }, + { + "name": "智能抠图", + "description": "添加背景移除节点（如SAM、U²-Net等）", + "content": "- 添加背景移除或抠图节点\n {\n \"7\": {\n \"inputs\": {\n \"rem_mode\": \"RMBG-1.4\",\n \"image_output\": \"Preview\",\n \"save_prefix\": \"ComfyUI\",\n \"torchscript_jit\": false,\n \"add_background\": \"none\",\n \"refine_foreground\": false\n },\n \"class_type\": \"easy imageRemBg\",\n \"_meta\": {\n \"title\": \"Image Remove Bg\"\n }\n }\n}\n - 添加SAM抠图节点\n {\n \"8\": {\n \"inputs\": {\n \"prompt\": \"\",\n \"threshold\": 0.3,\n \"sam_model\": [\n \"9\",\n 0\n ],\n \"grounding_dino_model\": [\n \"10\",\n 0\n ]\n },\n \"class_type\": \"GroundingDinoSAMSegment (segment anything)\",\n \"_meta\": {\n \"title\": \"GroundingDinoSAMSegment (segment anything)\"\n }\n },\n \"9\": {\n \"inputs\": {\n \"model_name\": \"sam_vit_h (2.56GB)\"\n },\n \"class_type\": \"SAMModelLoader (segment anything)\",\n \"_meta\": {\n \"title\": \"SAMModelLoader (segment anything)\"\n }\n },\n \"10\": {\n \"inputs\": {\n \"model_name\": \"GroundingDINO_SwinT_OGC (694MB)\"\n },\n \"class_type\": \"GroundingDinoModelLoader (segment anything)\",\n \"_meta\": {\n \"title\": \"GroundingDinoModelLoader (segment anything)\"\n }\n }\n}" + } +] \ No newline at end of file diff --git a/backend/service/workflow_rewrite_agent.py b/backend/service/workflow_rewrite_agent.py index f1d2934..ef4acbe 100644 --- a/backend/service/workflow_rewrite_agent.py +++ b/backend/service/workflow_rewrite_agent.py @@ -2,7 +2,7 @@ Author: ai-business-hql qingli.hql@alibaba-inc.com Date: 2025-07-24 17:10:23 LastEditors: ai-business-hql qingli.hql@alibaba-inc.com -LastEditTime: 2025-07-31 11:20:37 +LastEditTime: 2025-08-04 17:13:43 FilePath: /comfyui_copilot/backend/service/workflow_rewrite_agent.py Description: 这是默认设置,请设置`customMade`, 打开koroFileHeader查看配置 进行设置: https://github.com/OBKoro1/koro1FileHeader/wiki/%E9%85%8D%E7%BD%AE ''' @@ -11,12 +11,38 @@ from agents.tool import function_tool import json import time import uuid +from agents.tool import function_tool +import os from ..agent_factory import create_agent from ..utils.globals import get_language from ..service.workflow_rewrite_tools import * +@function_tool +def get_rewrite_expert_by_name(name_list: list[str]) -> str: + """根据经验名称来获取工作流改写专家经验""" + result = "" + with open(os.path.join(os.path.dirname(__file__), "..", "data", "workflow_rewrite_expert.json"), "r") as f: + data = json.load(f) + for name in name_list: + for item in data: + if item["name"] == name: + result += f'### {name}({item["description"]})：\n{item["content"]}\n' + return result + +def get_rewrite_export_schema() -> dict: + """获取工作流改写专家经验schema""" + expert_schema = [] + with open(os.path.join(os.path.dirname(__file__), "..", "data", "workflow_rewrite_expert.json"), "r") as f: + data = json.load(f) + for item in data: + expert_schema.append({ + "name": item["name"], + "description": item["description"] + }) + return expert_schema + def create_workflow_rewrite_agent(session_id: str): """创建带有session_id的workflow_rewrite_agent实例""" @@ -35,799 +61,10 @@ def create_workflow_rewrite_agent(session_id: str): **当前Session ID:** {}""".format(language, session_id) + """ ## 主要处理场景 - - ### 文生图场景优化 - 1. **LoRA集成**：在现有工作流中添加LoRA节点，确保与现有模型和提示词节点正确连接 - 在checkpoint节点后添加LoRA节点。 - { - "1": { - "inputs": { - "lora_name": "DOG.safetensors", - "strength_model": 1, - "strength_clip": 1, - "model": [ - "2", - 0 - ], - "clip": [ - "2", - 1 - ] - }, - "class_type": "LoraLoader", - "_meta": { - "title": "Load LoRA" - } - } - - 在checkpoint节点后添加vae encode节点 - - { - "2": { - "inputs": { - "ckpt_name": "Flux_Kontext_dev_.safetensors" - }, - "class_type": "CheckpointLoaderSimple", - "_meta": { - "title": "Load Checkpoint" - } - }, - "5": { - "inputs": { - "vae": [ - "2", - 2 - ] - }, - "class_type": "VAEEncode", - "_meta": { - "title": "VAE Encode" - } - } -} - - 2. **后处理增强**： - - 在Preview Image或Save Image节点后添加高清放大功能（如Real-ESRGAN、ESRGAN等） - - 添加图像缩放节点 - { - "1": { - "inputs": { - "width": 512, - "height": 512, - "interpolation": "nearest", - "method": "stretch", - "condition": "always", - "multiple_of": 0 - }, - "class_type": "ImageResize+", - "_meta": { - "title": "🔧 Image Resize" - } - } -} - - 添加图像尺寸调整节点 - { - "2": { - "inputs": { - "aspect_ratio": "original", - "proportional_width": 2, - "proportional_height": 1, - "fit": "letterbox", - "method": "lanczos", - "round_to_multiple": "8", - "scale_to_longest_side": false, - "longest_side": 1024 - }, - "class_type": "LayerUtility: ImageScaleByAspectRatio", - "_meta": { - "title": "LayerUtility: ImageScaleByAspectRatio" - } - } -} - -添加图像放大节点 - "11": { - "inputs": { - "width": 512, - "height": 512, - "upscale_method": "nearest-exact", - "keep_proportion": false, - "divisible_by": 2, - "crop": "disabled", - "image": [ - "12", - 0 - ] - }, - "class_type": "ImageResizeKJ", - "_meta": { - "title": "Resize Image" - } - }, - -添加VAEdecode节点 - "12": { - "inputs": {}, - "class_type": "VAEDecode", - "_meta": { - "title": "VAE Decode" - } - } -} - - 3. **提示词优化**： - - 修改现有提示词节点的内容(提示词应该在(CLIP Text Encode Prompt或Text _O节点内编辑) - - 添加单独的提示词输入节点 - { - "12": { - "inputs": { - "text": [ - "13", - 0 - ] - }, - "class_type": "CLIPTextEncode", - "_meta": { - "title": "CLIP Text Encode (Prompt)" - } - }, - "13": { - "inputs": { - "delimiter": ", ", - "clean_whitespace": "true", - "text_a": [ - "15", - 0 - ], - "text_b": [ - "16", - 0 - ] - }, - "class_type": "Text Concatenate", - "_meta": { - "title": "Text Concatenate" - } - }, - "15": { - "inputs": { - "text": "" - }, - "class_type": "Text _O", - "_meta": { - "title": "Text _O" - } - }, - "16": { - "inputs": { - "text": "" - }, - "class_type": "Text _O", - "_meta": { - "title": "Text _O" - } - } -} - - ### 图生图场景优化 - 1. **LoRA增强**：为图生图工作流添加LoRA支持，保证与图像输入节点兼容 - -在checkpoint节点后添加LoRA节点。(与文生图添加lora节点的方式保持一致) - 2. **图像反推功能**： - - 添加图像反推节点（如CLIP Interrogator） -{ - "11": { - "inputs": { - "prompt_mode": "fast", - "image_analysis": "off" - }, - "class_type": "ClipInterrogator", - "_meta": { - "title": "Clip Interrogator ♾️Mixlab" - } - } -} - - 添加更复杂或者更好用的图像反推节点(加载图片使用florence2进行反推) - { - "6": { - "inputs": { - "image": "06.JPG" - }, - "class_type": "LoadImage", - "_meta": { - "title": "$image.image!:The image to analyze, must be a url" - } - }, - "10": { - "inputs": { - "model": "microsoft/Florence-2-large", - "precision": "fp16", - "attention": "sdpa" - }, - "class_type": "DownloadAndLoadFlorence2Model", - "_meta": { - "title": "DownloadAndLoadFlorence2Model" - } - }, - "11": { - "inputs": { - "text_input": "", - "task": "more_detailed_caption", - "fill_mask": true, - "keep_model_loaded": false, - "max_new_tokens": 1024, - "num_beams": 3, - "do_sample": true, - "output_mask_select": "", - "seed": 1098631327477633, - "image": [ - "6", - 0 - ], - "florence2_model": [ - "10", - 0 - ] - }, - "class_type": "Florence2Run", - "_meta": { - "title": "Florence2Run" - } - }, - "18": { - "inputs": { - "anything": [ - "11", - 2 - ] - }, - "class_type": "easy showAnything", - "_meta": { - "title": "Show Any" - } - }, - "20": { - "inputs": { - "value": "Generate high-quality text descriptions from images using local Florence model.\n \n Main use cases:\n 1. **Reverse image prompt generation**:\n - When users upload an image and want to get prompts for AI art generation\n - Analyzes visual elements, style, composition, etc. to generate prompts for Stable Diffusion, DALL-E, and other models\n - In this case, return the tool's raw output directly to users without any modification or summary\n - Users can directly use these prompts for image generation\n 2. **Image content understanding**:\n - When users ask about specific content, objects, scenes, people, etc. in the image\n - Need to understand the semantic content of the image and answer users' specific questions\n - In this case, combine tool output with conversation context to give users contextually appropriate natural responses\n - Don't return raw output directly, but provide targeted replies based on understanding results" - }, - "class_type": "PrimitiveStringMultiline", - "_meta": { - "title": "MCP" - } - } -} - 3. **ControlNet集成**：(preprocessor可选canny、depth等参数,模型样式选择，Controlnet开始、结束权重) - { - "22": { - "inputs": { - "strength": 1, - "start_percent": 0, - "end_percent": 1, - "control_net": [ - "23", - 0 - ], - "image": [ - "24", - 0 - ] - }, - "class_type": "ControlNetApplyAdvanced", - "_meta": { - "title": "Apply ControlNet" - } - }, - "23": { - "inputs": { - "control_net_name": "ControlNet-Standard-Lineart-for-SDXL.safetensors" - }, - "class_type": "ControlNetLoader", - "_meta": { - "title": "Load ControlNet Model" - } - }, - "24": { - "inputs": { - "preprocessor": "none", - "resolution": 512 - }, - "class_type": "AIO_Preprocessor", - "_meta": { - "title": "AIO Aux Preprocessor" - } - } -} - 4. **高级图像处理**： - -给我一个扩图链路(包括图像加载和图像输出) - - 添加图像高清放大链路 - { - "58": { - "inputs": { - "vae_name": "ae.safetensors" - }, - "class_type": "VAELoader", - "_meta": { - "title": "Load VAE" - } - }, - "59": { - "inputs": { - "clip_name1": "t5xxl_fp8_e4m3fn.safetensors", - "clip_name2": "clip_l.safetensors", - "type": "flux", - "device": "default" - }, - "class_type": "DualCLIPLoader", - "_meta": { - "title": "DualCLIPLoader" - } - }, - "60": { - "inputs": { - "unet_name": "F.1-dev-fp8.safetensors", - "weight_dtype": "fp8_e4m3fn" - }, - "class_type": "UNETLoader", - "_meta": { - "title": "Load Diffusion Model" - } - }, - "175": { - "inputs": { - "upscale_by": 2.0000000000000004, - "seed": 203184385867926, - "steps": 10, - "cfg": 3, - "sampler_name": "dpmpp_2m", - "scheduler": "karras", - "denoise": 0.34, - "mode_type": "Linear", - "tile_width": 512, - "tile_height": 512, - "mask_blur": 8, - "tile_padding": 32, - "seam_fix_mode": "None", - "seam_fix_denoise": 1, - "seam_fix_width": 64, - "seam_fix_mask_blur": 8, - "seam_fix_padding": 16, - "force_uniform_tiles": true, - "tiled_decode": false, - "image": [ - "263", - 0 - ], - "model": [ - "266", - 0 - ], - "positive": [ - "267", - 0 - ], - "negative": [ - "271", - 0 - ], - "vae": [ - "269", - 0 - ], - "upscale_model": [ - "270", - 0 - ] - }, - "class_type": "UltimateSDUpscale", - "_meta": { - "title": "Ultimate SD Upscale" - } - }, - "176": { - "inputs": { - "text": [ - "226", - 2 - ], - "clip": [ - "59", - 0 - ] - }, - "class_type": "CLIPTextEncode", - "_meta": { - "title": "CLIP Text Encode (Prompt)" - } - }, - "178": { - "inputs": { - "model_name": "4xNomos8kSCHAT-L.pth" - }, - "class_type": "UpscaleModelLoader", - "_meta": { - "title": "Load Upscale Model" - } - }, - "188": { - "inputs": { - "guidance": 30, - "conditioning": [ - "213", - 0 - ] - }, - "class_type": "FluxGuidance", - "_meta": { - "title": "FluxGuidance" - } - }, - "189": { - "inputs": { - "conditioning": [ - "176", - 0 - ] - }, - "class_type": "ConditioningZeroOut", - "_meta": { - "title": "ConditioningZeroOut" - } - }, - "212": { - "inputs": { - "type": "tile", - "control_net": [ - "214", - 0 - ] - }, - "class_type": "SetUnionControlNetType", - "_meta": { - "title": "SetUnionControlNetType" - } - }, - "213": { - "inputs": { - "strength": 0.30000000000000004, - "start_percent": 0, - "end_percent": 1, - "positive": [ - "176", - 0 - ], - "negative": [ - "189", - 0 - ], - "control_net": [ - "212", - 0 - ], - "image": [ - "215", - 0 - ], - "vae": [ - "58", - 0 - ] - }, - "class_type": "ControlNetApplyAdvanced", - "_meta": { - "title": "Apply ControlNet" - } - }, - "214": { - "inputs": { - "control_net_name": "FLUX.1-dev-ControlNet-Union-Pro.safetensors" - }, - "class_type": "ControlNetLoader", - "_meta": { - "title": "Load ControlNet Model" - } - }, - "215": { - "inputs": { - "preprocessor": "TTPlanet_TileSimple_Preprocessor", - "resolution": [ - "217", - 0 - ], - "image": [ - "272", - 0 - ] - }, - "class_type": "AIO_Preprocessor", - "_meta": { - "title": "AIO Aux Preprocessor" - } - }, - "216": { - "inputs": { - "image": [ - "272", - 0 - ] - }, - "class_type": "GetImageSize+", - "_meta": { - "title": "🔧 Get Image Size" - } - }, - "217": { - "inputs": { - "image_gen_width": [ - "216", - 0 - ], - "image_gen_height": [ - "216", - 1 - ], - "resize_mode": "Just Resize", - "original_image": [ - "272", - 0 - ] - }, - "class_type": "PixelPerfectResolution", - "_meta": { - "title": "Pixel Perfect Resolution" - } - }, - "226": { - "inputs": { - "text_input": "", - "task": "region_caption", - "fill_mask": true, - "keep_model_loaded": false, - "max_new_tokens": 1024, - "num_beams": 3, - "do_sample": true, - "output_mask_select": "", - "seed": 204052510973001, - "image": [ - "272", - 0 - ], - "florence2_model": [ - "227", - 0 - ] - }, - "class_type": "Florence2Run", - "_meta": { - "title": "Florence2Run" - } - }, - "227": { - "inputs": { - "model": "Florence-2-large", - "precision": "fp16", - "attention": "sdpa" - }, - "class_type": "Florence2ModelLoader", - "_meta": { - "title": "Florence2ModelLoader" - } - }, - "230": { - "inputs": { - "text": "home appliance", - "anything": [ - "226", - 2 - ] - }, - "class_type": "easy showAnything", - "_meta": { - "title": "Show Any" - } - }, - "240": { - "inputs": { - "filename_prefix": "ComfyUI", - "images": [ - "175", - 0 - ] - }, - "class_type": "SaveImage", - "_meta": { - "title": "Save Image" - } - }, - "263": { - "inputs": { - "anything": [ - "272", - 0 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "266": { - "inputs": { - "anything": [ - "60", - 0 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "267": { - "inputs": { - "anything": [ - "188", - 0 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "269": { - "inputs": { - "anything": [ - "58", - 0 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "270": { - "inputs": { - "anything": [ - "178", - 0 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "271": { - "inputs": { - "anything": [ - "213", - 1 - ] - }, - "class_type": "easy cleanGpuUsed", - "_meta": { - "title": "Clean VRAM Used" - } - }, - "272": { - "inputs": { - "image": "234.png" - }, - "class_type": "LoadImage", - "_meta": { - "title": "Load Image" - } - } -} - - 配置图像缩放和裁剪功能 - { - "46": { - "inputs": { - "width": [ - "47", - 1 - ], - "height": [ - "47", - 2 - ], - "position": "top-left", - "x_offset": 0, - "y_offset": 0, - "image": [ - "47", - 0 - ] - }, - "class_type": "ImageCrop+", - "_meta": { - "title": "🔧 Image Crop" - } - }, - "47": { - "inputs": { - "width": 512, - "height": 512, - "interpolation": "nearest", - "method": "stretch", - "condition": "always", - "multiple_of": 0 - }, - "class_type": "ImageResize+", - "_meta": { - "title": "🔧 Image Resize" - } - }, - "49": { - "inputs": { - "images": [ - "46", - 0 - ] - }, - "class_type": "PreviewImage", - "_meta": { - "title": "Preview Image" - } - } -} - 5. **智能抠图**： - - 添加背景移除节点（如SAM、U²-Net等） - - 添加背景移除或抠图节点 - { - "7": { - "inputs": { - "rem_mode": "RMBG-1.4", - "image_output": "Preview", - "save_prefix": "ComfyUI", - "torchscript_jit": false, - "add_background": "none", - "refine_foreground": false - }, - "class_type": "easy imageRemBg", - "_meta": { - "title": "Image Remove Bg" - } - } -} - - 添加SAM抠图节点 - { - "8": { - "inputs": { - "prompt": "", - "threshold": 0.3, - "sam_model": [ - "9", - 0 - ], - "grounding_dino_model": [ - "10", - 0 - ] - }, - "class_type": "GroundingDinoSAMSegment (segment anything)", - "_meta": { - "title": "GroundingDinoSAMSegment (segment anything)" - } - }, - "9": { - "inputs": { - "model_name": "sam_vit_h (2.56GB)" - }, - "class_type": "SAMModelLoader (segment anything)", - "_meta": { - "title": "SAMModelLoader (segment anything)" - } - }, - "10": { - "inputs": { - "model_name": "GroundingDINO_SwinT_OGC (694MB)" - }, - "class_type": "GroundingDinoModelLoader (segment anything)", - "_meta": { - "title": "GroundingDinoModelLoader (segment anything)" - } - } -} - + {} + """.format(json.dumps(get_rewrite_export_schema())) + """ + 你可以根据用户的需求，从上面的专家经验中选择一个或多个经验，并根据经验内容进行工作流改写。 + ## 操作原则 - **保持兼容性**：确保修改后的工作流与现有节点兼容 - **优化连接**：正确设置节点间的输入输出连接 @@ -845,7 +82,7 @@ def create_workflow_rewrite_agent(session_id: str): 始终以用户的实际需求为导向，提供专业、准确、高效的工作流改写服务。 """, - tools=[get_current_workflow, get_node_info, update_workflow, remove_node], + tools=[get_rewrite_expert_by_name, get_current_workflow, get_node_info, update_workflow, remove_node], ) # 保持向后兼容性的默认实例 diff --git a/dist/copilot_web/App-DT2fOvHP.js b/dist/copilot_web/App-BVbKTtsg.js similarity index 87% rename from dist/copilot_web/App-DT2fOvHP.js rename to dist/copilot_web/App-BVbKTtsg.js index 528cae3..132899c 100644 --- a/dist/copilot_web/App-DT2fOvHP.js +++ b/dist/copilot_web/App-BVbKTtsg.js @@ -1,7 +1,7 @@ function getImportPath(filename) { return `./${filename}`; } - const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["copilot_web/workflowChat-Bp01CH2d.js","copilot_web/vendor-markdown-CBmlBP6m.js","copilot_web/vendor-react-Dixhfmvb.js","copilot_web/message-components-DmxYkzGi.js","copilot_web/input.js","copilot_web/assets/input-CWoNegTl.css","copilot_web/fonts.css"].map(path => { + const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["copilot_web/workflowChat-B_xZb6og.js","copilot_web/vendor-markdown-CBmlBP6m.js","copilot_web/vendor-react-Dixhfmvb.js","copilot_web/message-components-BrrLmtj_.js","copilot_web/input.js","copilot_web/assets/input-CWoNegTl.css","copilot_web/fonts.css"].map(path => { const apiBase = window.comfyAPI?.api?.api?.api_base; if (apiBase) { // 有 API base 时，使用完整路径 @@ -11,4 +11,4 @@ function getImportPath(filename) { return `./${path}`; } }))))=>i.map(i=>d[i]); -import{_ as a}from"./input.js";import{j as e}from"./vendor-markdown-CBmlBP6m.js";import{r as t,R as i}from"./vendor-react-Dixhfmvb.js";import{C as n}from"./message-components-DmxYkzGi.js";const s={EXPLAIN_NODE:"copilot:explain-node",TOOLBOX_USAGE:"copilot:toolbox-usage",TOOLBOX_PARAMETERS:"copilot:toolbox-parameters",TOOLBOX_DOWNSTREAMNODES:"copilot:toolbox-downstreamnodes"},d=i.lazy(()=>a(()=>import(getImportPath("workflowChat-Bp01CH2d.js")),__vite__mapDeps([0,1,2,3,4,5,6])).then(o=>({default:o.default})));function c(){const[o,r]=t.useState(!1);return t.useEffect(()=>{const l=()=>{r(!0)};return window.addEventListener(s.EXPLAIN_NODE,l),()=>window.removeEventListener(s.EXPLAIN_NODE,l)},[]),e.jsx(n,{children:e.jsx("div",{className:"h-full w-full flex flex-col",children:e.jsx(t.Suspense,{fallback:e.jsx("div",{className:"h-full w-full flex items-center justify-center",children:"Loading..."}),children:e.jsx(d,{visible:!0,triggerUsage:o,onUsageTriggered:()=>r(!1)})})})})}const O=Object.freeze(Object.defineProperty({__proto__:null,default:c},Symbol.toStringTag,{value:"Module"}));export{O as A,s as C}; +import{_ as a}from"./input.js";import{j as e}from"./vendor-markdown-CBmlBP6m.js";import{r as t,R as i}from"./vendor-react-Dixhfmvb.js";import{C as n}from"./message-components-BrrLmtj_.js";const s={EXPLAIN_NODE:"copilot:explain-node",TOOLBOX_USAGE:"copilot:toolbox-usage",TOOLBOX_PARAMETERS:"copilot:toolbox-parameters",TOOLBOX_DOWNSTREAMNODES:"copilot:toolbox-downstreamnodes"},d=i.lazy(()=>a(()=>import(getImportPath("workflowChat-B_xZb6og.js")),__vite__mapDeps([0,1,2,3,4,5,6])).then(o=>({default:o.default})));function c(){const[o,r]=t.useState(!1);return t.useEffect(()=>{const l=()=>{r(!0)};return window.addEventListener(s.EXPLAIN_NODE,l),()=>window.removeEventListener(s.EXPLAIN_NODE,l)},[]),e.jsx(n,{children:e.jsx("div",{className:"h-full w-full flex flex-col",children:e.jsx(t.Suspense,{fallback:e.jsx("div",{className:"h-full w-full flex items-center justify-center",children:"Loading..."}),children:e.jsx(d,{visible:!0,triggerUsage:o,onUsageTriggered:()=>r(!1)})})})})}const O=Object.freeze(Object.defineProperty({__proto__:null,default:c},Symbol.toStringTag,{value:"Module"}));export{O as A,s as C}; diff --git a/dist/copilot_web/DebugGuide-CqUJVeP7.js b/dist/copilot_web/DebugGuide-BQ7towRD.js similarity index 98% rename from dist/copilot_web/DebugGuide-CqUJVeP7.js rename to dist/copilot_web/DebugGuide-BQ7towRD.js index f1f5e8a..96bfe9c 100644 --- a/dist/copilot_web/DebugGuide-CqUJVeP7.js +++ b/dist/copilot_web/DebugGuide-BQ7towRD.js @@ -1,5 +1,5 @@ function getImportPath(filename) { return `./${filename}`; } - import{j as r}from"./vendor-markdown-CBmlBP6m.js";import{r as a}from"./vendor-react-Dixhfmvb.js";import{B as I,R as E,h as f,a as h,W as x}from"./message-components-DmxYkzGi.js";function B({content:g,name:m="Assistant",avatar:A,onAddMessage:b,onUpdateMessage:c,onFinishLoad:k,messageId:y}){const[d,_]=a.useState(!1),[D,O]=a.useState(""),[J,w]=a.useState(!1),[S,v]=a.useState(null);a.useEffect(()=>{k?.()},[]);const s=a.useMemo(()=>{try{return JSON.parse(g)}catch(e){return console.error("Failed to parse message content:",e),null}},[g]),p=a.useMemo(()=>{if(!s||!s.ext)return null;const e=s.ext.find(t=>t.type==="debug_start_checkpoint"||t.type==="debug_checkpoint"&&t.data?.checkpoint_type==="debug_start");return e&&e.data&&e.data.checkpoint_id?e.data.checkpoint_id:null},[s])||S,j=async()=>{if(d)return;const e=f(),t={id:e,role:"ai",content:JSON.stringify({text:`🔍 Starting workflow analysis... + import{j as r}from"./vendor-markdown-CBmlBP6m.js";import{r as a}from"./vendor-react-Dixhfmvb.js";import{B as I,R as E,h as f,a as h,W as x}from"./message-components-BrrLmtj_.js";function B({content:g,name:m="Assistant",avatar:A,onAddMessage:b,onUpdateMessage:c,onFinishLoad:k,messageId:y}){const[d,_]=a.useState(!1),[D,O]=a.useState(""),[J,w]=a.useState(!1),[S,v]=a.useState(null);a.useEffect(()=>{k?.()},[]);const s=a.useMemo(()=>{try{return JSON.parse(g)}catch(e){return console.error("Failed to parse message content:",e),null}},[g]),p=a.useMemo(()=>{if(!s||!s.ext)return null;const e=s.ext.find(t=>t.type==="debug_start_checkpoint"||t.type==="debug_checkpoint"&&t.data?.checkpoint_type==="debug_start");return e&&e.data&&e.data.checkpoint_id?e.data.checkpoint_id:null},[s])||S,j=async()=>{if(d)return;const e=f(),t={id:e,role:"ai",content:JSON.stringify({text:`🔍 Starting workflow analysis... `,ext:[]}),format:"markdown",name:"Assistant",finished:!1,debugGuide:!0};b?.(t);try{await N(),await C(e)}finally{_(!1)}},N=async()=>{try{const e=await h.graphToPrompt(),t=localStorage.getItem("sessionId")||"";if(t&&e){const o=await x.saveWorkflowCheckpoint(t,e.output,e.workflow,"debug_start");if(v(o.version_id),console.log(`Saved debug start checkpoint: ${o.version_id}`),c&&s){const n=[...s.ext||[]].filter(u=>u.type!=="debug_start_checkpoint"&&!(u.type==="debug_checkpoint"&&u.data?.checkpoint_type==="debug_start"));n.push({type:"debug_start_checkpoint",data:{checkpoint_id:o.version_id,checkpoint_type:"debug_start"}});const l={id:y||f(),role:"ai",content:JSON.stringify({text:s.text,ext:n}),format:"debug_guide",name:"Assistant"};c(l)}}}catch(e){console.error("Failed to save checkpoint before debug:",e)}},C=async e=>{try{const t=await h.graphToPrompt();let o="",i=null;for await(const n of x.streamDebugAgent(t))if(n.text){o=n.text,n.ext&&(i=n.ext);const l={id:e,role:"ai",content:JSON.stringify({text:o,ext:i||[]}),format:"markdown",name:"Assistant",finished:!1,debugGuide:!0};c?.(l)}c?.({id:e,role:"ai",content:JSON.stringify({text:o,ext:i||[]}),format:"markdown",name:"Assistant",finished:!0,debugGuide:!0})}catch(t){console.error("Error calling debug agent:",t),w(!1);const i={id:e,role:"ai",content:JSON.stringify({text:`I encountered an error while analyzing your workflow: ${t.message||"Unknown error"}`,ext:[]}),format:"markdown",name:"Assistant",finished:!0};c?.(i)}};return s?r.jsx(I,{name:m,children:r.jsxs("div",{className:"bg-gray-100 pt-4 px-4 pb-3 rounded-lg",children:[r.jsx("div",{className:"flex justify-between items-start",children:r.jsx("p",{className:"text-gray-700 text-sm flex-1",children:s.text})}),r.jsx("div",{className:"flex justify-end mt-4",children:r.jsx("button",{onClick:j,disabled:d,className:`px-4 py-2 text-[#fff] text-sm rounded-md shadow-[0_2px_8px_rbga(79, 140, 255, 0.15)] hover:!shadow-[0_4px_16px_rbga(79, 140, 255, 0.25)] hover:!scale-[1.05] transition-colors ${d?"bg-gray-400 cursor-not-allowed":"bg-debug-btn hover:!bg-debug-btn-hover"}`,children:d?"Analyzing...":"Debug Errors"})}),r.jsx("div",{className:"flex justify-end mt-2",children:!!p&&r.jsx("div",{className:"ml-2 flex-shrink-0",children:r.jsx(E,{checkpointId:p,onRestore:()=>{console.log("Workflow restored from checkpoint")}})})})]})}):null}export{B as DebugGuide}; diff --git a/dist/copilot_web/DebugResult-BPVOJwqc.js b/dist/copilot_web/DebugResult-CdvyVrc1.js similarity index 98% rename from dist/copilot_web/DebugResult-BPVOJwqc.js rename to dist/copilot_web/DebugResult-CdvyVrc1.js index 0de0544..84a1b52 100644 --- a/dist/copilot_web/DebugResult-BPVOJwqc.js +++ b/dist/copilot_web/DebugResult-CdvyVrc1.js @@ -1,4 +1,4 @@ function getImportPath(filename) { return `./${filename}`; } - import{j as e}from"./vendor-markdown-CBmlBP6m.js";import{r as o}from"./vendor-react-Dixhfmvb.js";import{b as j,c as b,B as y,R as N}from"./message-components-DmxYkzGi.js";const _=c=>{const{title:i="",isWorkflowUpdate:h=!1,className:d="",children:x}=c,[a,u]=o.useState(!1),l=h?"#166534":"#E5E7EB";return e.jsxs("div",{className:`relative shadow-gray-200 dark:shadow-gray-600 rounded-lg p-2 overflow-hidden ${d} ${a?"h-auto":"h-[200px]"}`,children:[e.jsxs("div",{className:"flex justify-between items-center",children:[e.jsx("div",{children:typeof i=="string"?e.jsx("h3",{className:"text-sm text-gray-900 dark:text-white font-medium",children:i}):i}),e.jsx("button",{onClick:()=>{console.log("setOpen--->"),u(!a)},children:a?e.jsx(j,{color:l}):e.jsx(b,{color:l})})]}),e.jsx("div",{className:"dark:border-gray-700",children:x}),!a&&e.jsx("div",{className:"absolute bottom-0 left-0 right-0 h-40 w-full z-5 bg-gradient-to-t from-[#fff] to-transparent pointer-events-none"})]})};function D({content:c,name:i="Assistant",avatar:h,format:d="markdown",onFinishLoad:x}){o.useEffect(()=>{x?.()},[]);const[a,u]=o.useState(null),[l,f]=o.useState(null),[s,p]=o.useState(!1);o.useEffect(()=>{try{const r=JSON.parse(c);if(u(r),r.ext){let t=r.ext.find(n=>n.type==="workflow_rewrite_checkpoint"||n.type==="debug_checkpoint"&&n.data?.checkpoint_type==="workflow_rewrite_start");t&&t.data&&t.data.checkpoint_id?(f(t.data.checkpoint_id),p(!0)):(t=r.ext.find(n=>n.type==="workflow_rewrite_complete"),t&&t.data&&t.data.version_id?(f(t.data.version_id),p(!0)):(t=r.ext.find(n=>n.type==="debug_checkpoint"),t&&t.data&&t.data.checkpoint_id&&(f(t.data.checkpoint_id),p(!1)))),r.ext.find(n=>n.type==="workflow_update")&&p(!0)}}catch(r){console.error("Failed to parse DebugResult content:",r)}},[c]);const g=r=>d==="markdown"?r.replace(/\*\*(.*?)\*\*/g,"$1").replace(/\*(.*?)\*/g,"$1").replace(/`(.*?)`/g,'$1').replace(/\n/g,"
"):r,w=o.useMemo(()=>s?"bg-green-50 border border-green-200":"bg-gray-100",[s]),m=o.useMemo(()=>s?"text-green-700 text-sm leading-relaxed":"text-gray-700 text-sm leading-relaxed",[s]),k=o.useMemo(()=>s?e.jsxs("div",{className:"flex items-center",children:[e.jsx("svg",{className:"w-5 h-5 text-green-600 mr-2",fill:"currentColor",viewBox:"0 0 20 20",children:e.jsx("path",{fillRule:"evenodd",d:"M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z",clipRule:"evenodd"})}),e.jsx("h4",{className:"text-green-800 font-medium",children:"Workflow Updated Successfully"})]}):null,[s]),v=o.useMemo(()=>s?e.jsx("div",{className:"mt-3 text-xs text-green-600",children:"💡 If you're not satisfied with the changes, click the restore button to revert to the previous version."}):null,[s]);return console.log("responseData-",a),a?e.jsx(y,{name:i,children:e.jsxs("div",{className:"bg-gray-100 p-4 rounded-lg",children:[e.jsx(_,{title:k,isWorkflowUpdate:s,className:w,children:e.jsxs("div",{className:"flex-1 prose prose-sm max-w-none",children:[d==="markdown"?e.jsx("div",{className:m,dangerouslySetInnerHTML:{__html:g(a.text||"")}}):e.jsx("pre",{className:`whitespace-pre-wrap ${m}`,children:a.text||""}),v]})}),e.jsx("div",{className:"flex justify-end mt-2",children:!!l&&e.jsx("div",{className:"ml-2 flex-shrink-0",children:e.jsx(N,{checkpointId:l,onRestore:()=>{console.log(`Workflow restored from ${s?"workflow update":"debug"} checkpoint`)},title:s?`Restore to this version (Version ${l})`:`Restore checkpoint ${l}`})})})]})}):null}export{D as DebugResult}; + import{j as e}from"./vendor-markdown-CBmlBP6m.js";import{r as o}from"./vendor-react-Dixhfmvb.js";import{b as j,c as b,B as y,R as N}from"./message-components-BrrLmtj_.js";const _=c=>{const{title:i="",isWorkflowUpdate:h=!1,className:d="",children:x}=c,[a,u]=o.useState(!1),l=h?"#166534":"#E5E7EB";return e.jsxs("div",{className:`relative shadow-gray-200 dark:shadow-gray-600 rounded-lg p-2 overflow-hidden ${d} ${a?"h-auto":"h-[200px]"}`,children:[e.jsxs("div",{className:"flex justify-between items-center",children:[e.jsx("div",{children:typeof i=="string"?e.jsx("h3",{className:"text-sm text-gray-900 dark:text-white font-medium",children:i}):i}),e.jsx("button",{onClick:()=>{console.log("setOpen--->"),u(!a)},children:a?e.jsx(j,{color:l}):e.jsx(b,{color:l})})]}),e.jsx("div",{className:"dark:border-gray-700",children:x}),!a&&e.jsx("div",{className:"absolute bottom-0 left-0 right-0 h-40 w-full z-5 bg-gradient-to-t from-[#fff] to-transparent pointer-events-none"})]})};function D({content:c,name:i="Assistant",avatar:h,format:d="markdown",onFinishLoad:x}){o.useEffect(()=>{x?.()},[]);const[a,u]=o.useState(null),[l,f]=o.useState(null),[s,p]=o.useState(!1);o.useEffect(()=>{try{const r=JSON.parse(c);if(u(r),r.ext){let t=r.ext.find(n=>n.type==="workflow_rewrite_checkpoint"||n.type==="debug_checkpoint"&&n.data?.checkpoint_type==="workflow_rewrite_start");t&&t.data&&t.data.checkpoint_id?(f(t.data.checkpoint_id),p(!0)):(t=r.ext.find(n=>n.type==="workflow_rewrite_complete"),t&&t.data&&t.data.version_id?(f(t.data.version_id),p(!0)):(t=r.ext.find(n=>n.type==="debug_checkpoint"),t&&t.data&&t.data.checkpoint_id&&(f(t.data.checkpoint_id),p(!1)))),r.ext.find(n=>n.type==="workflow_update")&&p(!0)}}catch(r){console.error("Failed to parse DebugResult content:",r)}},[c]);const g=r=>d==="markdown"?r.replace(/\*\*(.*?)\*\*/g,"$1").replace(/\*(.*?)\*/g,"$1").replace(/`(.*?)`/g,'$1').replace(/\n/g,"
"):r,w=o.useMemo(()=>s?"bg-green-50 border border-green-200":"bg-gray-100",[s]),m=o.useMemo(()=>s?"text-green-700 text-sm leading-relaxed":"text-gray-700 text-sm leading-relaxed",[s]),k=o.useMemo(()=>s?e.jsxs("div",{className:"flex items-center",children:[e.jsx("svg",{className:"w-5 h-5 text-green-600 mr-2",fill:"currentColor",viewBox:"0 0 20 20",children:e.jsx("path",{fillRule:"evenodd",d:"M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z",clipRule:"evenodd"})}),e.jsx("h4",{className:"text-green-800 font-medium",children:"Workflow Updated Successfully"})]}):null,[s]),v=o.useMemo(()=>s?e.jsx("div",{className:"mt-3 text-xs text-green-600",children:"💡 If you're not satisfied with the changes, click the restore button to revert to the previous version."}):null,[s]);return console.log("responseData-",a),a?e.jsx(y,{name:i,children:e.jsxs("div",{className:"bg-gray-100 p-4 rounded-lg",children:[e.jsx(_,{title:k,isWorkflowUpdate:s,className:w,children:e.jsxs("div",{className:"flex-1 prose prose-sm max-w-none",children:[d==="markdown"?e.jsx("div",{className:m,dangerouslySetInnerHTML:{__html:g(a.text||"")}}):e.jsx("pre",{className:`whitespace-pre-wrap ${m}`,children:a.text||""}),v]})}),e.jsx("div",{className:"flex justify-end mt-2",children:!!l&&e.jsx("div",{className:"ml-2 flex-shrink-0",children:e.jsx(N,{checkpointId:l,onRestore:()=>{console.log(`Workflow restored from ${s?"workflow update":"debug"} checkpoint`)},title:s?`Restore to this version (Version ${l})`:`Restore checkpoint ${l}`})})})]})}):null}export{D as DebugResult}; diff --git a/dist/copilot_web/WorkflowOption-BRKJ_AoR.js b/dist/copilot_web/WorkflowOption-39wfPDLn.js similarity index 99% rename from dist/copilot_web/WorkflowOption-BRKJ_AoR.js rename to dist/copilot_web/WorkflowOption-39wfPDLn.js index c0626b0..103d599 100644 --- a/dist/copilot_web/WorkflowOption-BRKJ_AoR.js +++ b/dist/copilot_web/WorkflowOption-39wfPDLn.js @@ -1,7 +1,7 @@ function getImportPath(filename) { return `./${filename}`; } - import{j as ue}from"./vendor-markdown-CBmlBP6m.js";import{W as Si,h as Ba,a as Bt}from"./message-components-DmxYkzGi.js";import{g as _u,R as Oe,b as Wa,r as g,d as Ca,a as Ou}from"./vendor-react-Dixhfmvb.js";var ns={exports:{}};/*! + import{j as ue}from"./vendor-markdown-CBmlBP6m.js";import{W as Si,h as Ba,a as Bt}from"./message-components-BrrLmtj_.js";import{g as _u,R as Oe,b as Wa,r as g,d as Ca,a as Ou}from"./vendor-react-Dixhfmvb.js";var ns={exports:{}};/*! Copyright (c) 2018 Jed Watson. Licensed under the MIT License (MIT), see http://jedwatson.github.io/classnames diff --git a/dist/copilot_web/input.js b/dist/copilot_web/input.js index 3a34f61..712df53 100644 --- a/dist/copilot_web/input.js +++ b/dist/copilot_web/input.js @@ -1,7 +1,7 @@ function getImportPath(filename) { return `./${filename}`; } - const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["copilot_web/App-DT2fOvHP.js","copilot_web/vendor-markdown-CBmlBP6m.js","copilot_web/vendor-react-Dixhfmvb.js","copilot_web/message-components-DmxYkzGi.js"].map(path => { + const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["copilot_web/App-BVbKTtsg.js","copilot_web/vendor-markdown-CBmlBP6m.js","copilot_web/vendor-react-Dixhfmvb.js","copilot_web/message-components-BrrLmtj_.js"].map(path => { const apiBase = window.comfyAPI?.api?.api?.api_base; if (apiBase) { // 有 API base 时，使用完整路径 @@ -11,7 +11,7 @@ function getImportPath(filename) { return `./${path}`; } }))))=>i.map(i=>d[i]); -import{j as Fu}from"./vendor-markdown-CBmlBP6m.js";import{r as d0,a as Pv,g as ly,R as s0}from"./vendor-react-Dixhfmvb.js";import{w as ay,a as ty}from"./message-components-DmxYkzGi.js";/* empty css */const uy="modulepreload",ey=function(l){return"/"+l},Jc={},ny=function(a,t,u){let e=Promise.resolve();if(t&&t.length>0){document.getElementsByTagName("link");const f=document.querySelector("meta[property=csp-nonce]"),c=f?.nonce||f?.getAttribute("nonce");e=Promise.allSettled(t.map(i=>{if(i=ey(i),i in Jc)return;Jc[i]=!0;const h=i.endsWith(".css"),b=h?'[rel="stylesheet"]':"";if(document.querySelector(`link[href="${i}"]${b}`))return;const S=document.createElement("link");if(S.rel=h?"stylesheet":uy,h||(S.as="script"),S.crossOrigin="",S.href=i,c&&S.setAttribute("nonce",c),document.head.appendChild(S),h)return new Promise((d,m)=>{S.addEventListener("load",d),S.addEventListener("error",()=>m(new Error(`Unable to preload CSS for ${i}`)))})}))}function n(f){const c=new Event("vite:preloadError",{cancelable:!0});if(c.payload=f,window.dispatchEvent(c),!c.defaultPrevented)throw f}return e.then(f=>{for(const c of f||[])c.status==="rejected"&&n(c.reason);return a().catch(n)})};var m0={exports:{}},an={},S0={exports:{}},b0={};/** +import{j as Fu}from"./vendor-markdown-CBmlBP6m.js";import{r as d0,a as Pv,g as ly,R as s0}from"./vendor-react-Dixhfmvb.js";import{w as ay,a as ty}from"./message-components-BrrLmtj_.js";/* empty css */const uy="modulepreload",ey=function(l){return"/"+l},Jc={},ny=function(a,t,u){let e=Promise.resolve();if(t&&t.length>0){document.getElementsByTagName("link");const f=document.querySelector("meta[property=csp-nonce]"),c=f?.nonce||f?.getAttribute("nonce");e=Promise.allSettled(t.map(i=>{if(i=ey(i),i in Jc)return;Jc[i]=!0;const h=i.endsWith(".css"),b=h?'[rel="stylesheet"]':"";if(document.querySelector(`link[href="${i}"]${b}`))return;const S=document.createElement("link");if(S.rel=h?"stylesheet":uy,h||(S.as="script"),S.crossOrigin="",S.href=i,c&&S.setAttribute("nonce",c),document.head.appendChild(S),h)return new Promise((d,m)=>{S.addEventListener("load",d),S.addEventListener("error",()=>m(new Error(`Unable to preload CSS for ${i}`)))})}))}function n(f){const c=new Event("vite:preloadError",{cancelable:!0});if(c.payload=f,window.dispatchEvent(c),!c.defaultPrevented)throw f}return e.then(f=>{for(const c of f||[])c.status==="rejected"&&n(c.reason);return a().catch(n)})};var m0={exports:{}},an={},S0={exports:{}},b0={};/** * @license React * scheduler.production.js * @@ -35,4 +35,4 @@ import{j as Fu}from"./vendor-markdown-CBmlBP6m.js";import{r as d0,a as Pv,g as l `+i[u].replace(" at new "," at ");return l.displayName&&b.includes("")&&(b=b.replace("",l.displayName)),b}while(1<=u&&0<=e);break}}}finally{Mn=!1,Error.prepareStackTrace=t}return(t=l?l.displayName||l.name:"")?ft(t):""}function Ny(l){switch(l.tag){case 26:case 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e=a.type._context,u=a.pendingProps.children,Fa(a),e=sl(e),u=u(e),a.flags|=1,vl(l,a,u,t),a.child;case 14:return Gi(l,a,a.type,a.pendingProps,t);case 15:return F1(l,a,a.type,a.pendingProps,t);case 19:return lv(l,a,t);case 31:return u=a.pendingProps,t=a.mode,u={mode:u.mode,children:u.children},l===null?(t=Ce(u,t),t.ref=a.ref,a.child=t,t.return=a,a=t):(t=na(l.child,u),t.ref=a.ref,a.child=t,t.return=a,a=t),a;case 22:return I1(l,a,t);case 24:return Fa(a),u=sl(al),l===null?(e=mc(),e===null&&(e=C,n=sc(),e.pooledCache=n,n.refCount++,n!==null&&(e.pooledCacheLanes|=t),e=n),a.memoizedState={parent:u,cache:e},Sc(a),ga(a,al,e)):(l.lanes&t&&(Mf(l,a),hu(a,null,null,t),yu()),e=l.memoizedState,n=a.memoizedState,e.parent!==u?(e={parent:u,cache:u},a.memoizedState=e,a.lanes===0&&(a.memoizedState=a.updateQueue.baseState=e),ga(a,al,u)):(u=n.cache,ga(a,al,u),u!==e.cache&&Af(a,[al],t,!0))),vl(l,a,a.pendingProps.children,t),a.child;case 29:throw a.pendingProps}throw Error(o(156,a.tag))}function 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for(e=l.child;e!==null;)t|=e.lanes|e.childLanes,u|=e.subtreeFlags,u|=e.flags,e.return=l,e=e.sibling;return l.subtreeFlags|=u,l.childLanes=t,a}function Qh(l,a,t){var u=a.pendingProps;switch(dc(a),a.tag){case 31:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return r(a),null;case 1:return r(a),null;case 3:return t=a.stateNode,u=null,l!==null&&(u=l.memoizedState.cache),a.memoizedState.cache!==u&&(a.flags|=2048),fa(al),Nt(),t.pendingContext&&(t.context=t.pendingContext,t.pendingContext=null),(l===null||l.child===null)&&($t(a)?Fl(a):l===null||l.memoizedState.isDehydrated&&!(a.flags&256)||(a.flags|=1024,gi())),r(a),null;case 26:return t=a.memoizedState,l===null?(Fl(a),t!==null?(r(a),Ki(a,t)):(r(a),a.flags&=-16777217)):t?t!==l.memoizedState?(Fl(a),r(a),Ki(a,t)):(r(a),a.flags&=-16777217):(l.memoizedProps!==u&&Fl(a),r(a),a.flags&=-16777217),null;case 27:He(a),t=Oa.current;var 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