{ "workflow": { "id": 2467, "name": "Narrating over a video using multimodal AI", "views": 9667, "recentViews": 0, "totalViews": 9667, "createdAt": "2024-10-17T10:45:39.624Z", "description": "This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip.\n\nThis template was inspired by [Processing and narrating a video with GPT's visual capabilities and the TTS API](https://cookbook.openai.com/examples/gpt_with_vision_for_video_understanding)\n\n## How it works\n* Video is downloaded using the HTTP node.\n* Python code node is used to extract the frames using OpenCV.\n* Loop node is used o batch the frames for the LLM to generate partial scripts.\n* All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it.\n* The finished voiceover clip is uploaded to Google Drive.\n\nSample the finished product here: [https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing](https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing)\n\n## Requirements\n\n* OpenAI for LLM\n* Ideally, a mid-range (16GB RAM) machine for acceptable performance!\n\n## Customising this workflow\n\n* For larger videos, consider splitting into smaller clips for better performance\n* Use a multimodal LLM which supports fully video such as Google's Gemini.\n", "workflow": { "meta": { "instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9" }, "nodes": [ { "id": "6d16b5be-8f7b-49f2-8523-9b84c62f2759", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 1960, 660 ], "parameters": { "model": "gpt-4o-2024-08-06", "options": {} }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1 }, { "id": "a6084f09-9a4f-478a-ac1a-ab1413628c1f", "name": "Capture Frames", "type": "n8n-nodes-base.code", "position": [ 720, 460 ], "parameters": { "mode": "runOnceForEachItem", "language": "python", "pythonCode": "import cv2\nimport numpy as np\nimport base64\n\ndef extract_evenly_distributed_frames_from_base64(base64_string, max_frames=90):\n # Decode the Base64 string into bytes\n video_bytes = base64.b64decode(base64_string)\n \n # Write the bytes to a temporary file\n video_path = '/tmp/temp_video.mp4'\n with open(video_path, 'wb') as video_file:\n video_file.write(video_bytes)\n \n # Open the video file using OpenCV\n video_capture = cv2.VideoCapture(video_path)\n \n # Get the total number of frames in the video\n total_frames = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT))\n \n # Calculate the step size to take 'max_frames' evenly distributed frames\n step_size = max(1, total_frames // (max_frames - 1))\n \n # List to store selected frames as base64\n selected_frames_base64 = []\n \n for i in range(0, total_frames, step_size):\n # Set the current frame position\n video_capture.set(cv2.CAP_PROP_POS_FRAMES, i)\n \n # Read the frame\n ret, frame = video_capture.read()\n if ret:\n # Convert frame (NumPy array) to a Base64 string\n frame_base64 = convert_frame_to_base64(frame)\n selected_frames_base64.append(frame_base64)\n if len(selected_frames_base64) >= max_frames:\n break\n \n # Release the video capture object\n video_capture.release()\n\n return selected_frames_base64\n\ndef convert_frame_to_base64(frame):\n # Convert the frame (NumPy array) to JPEG format\n ret, buffer = cv2.imencode('.jpg', frame)\n if not ret:\n return None\n\n # Encode JPEG image to Base64\n frame_base64 = base64.b64encode(buffer).decode('utf-8')\n return frame_base64\n\nbase64_video = _input.item.binary.data.data\nframes_base64 = extract_evenly_distributed_frames_from_base64(base64_video, max_frames=90)\n\nreturn { \"output\": frames_base64 }" }, "typeVersion": 2 }, { "id": "b45e82a4-f304-4733-a9cf-07cae6df13ea", "name": "Split Out Frames", "type": "n8n-nodes-base.splitOut", "position": [ 920, 460 ], "parameters": { "options": {}, "fieldToSplitOut": "output" }, "typeVersion": 1 }, { "id": "83d29c51-a415-476d-b380-1ca5f0d4f521", "name": "Download Video", "type": "n8n-nodes-base.httpRequest", "position": [ 329, 346 ], "parameters": { "url": "=https://cdn.pixabay.com/video/2016/05/12/3175-166339863_small.mp4", "options": {} }, "typeVersion": 4.2 }, { "id": "0304ebb5-945d-4b0b-9597-f83ae8c1fe31", "name": "Convert to Binary", "type": "n8n-nodes-base.convertToFile", "position": [ 1480, 500 ], "parameters": { "options": {}, "operation": "toBinary", "sourceProperty": "output" }, "typeVersion": 1.1 }, { "id": "32a21e1d-1d8b-411e-8281-8d0e68a06889", "name": "When clicking ‘Test workflow’", "type": "n8n-nodes-base.manualTrigger", "position": [ 149, 346 ], "parameters": {}, "typeVersion": 1 }, { "id": "0ad2ea6a-e1f4-4b26-a4de-9103ecbb3831", "name": "Combine Script", "type": "n8n-nodes-base.aggregate", "position": [ 2640, 360 ], "parameters": { "options": {}, "aggregate": "aggregateAllItemData" }, "typeVersion": 1 }, { "id": "2d9bb91a-3369-4268-882f-f97e73897bb8", "name": "Upload to GDrive", "type": "n8n-nodes-base.googleDrive", "position": [ 3040, 360 ], "parameters": { "name": "=narrating-video-using-vision-ai-{{ $now.format('yyyyMMddHHmmss') }}.mp3", "driveId": { "__rl": true, "mode": "list", "value": "My Drive", "cachedResultUrl": "https://drive.google.com/drive/my-drive", "cachedResultName": "My Drive" }, "options": {}, "folderId": { "__rl": true, "mode": "id", "value": "1dBJZL_SCh6F2U7N7kIMsnSiI4QFxn2xD" } }, "credentials": { "googleDriveOAuth2Api": { "id": "credential-id", "name": "googleDriveOAuth2Api Credential" } }, "typeVersion": 3 }, { "id": "137185f6-ba32-4c68-844f-f50c7a5a261d", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -440, 0 ], "parameters": { "width": 476.34074202271484, "height": 586.0597334122469, "content": "## Try It Out!\n\n### This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip.\n\nThis template was inspired by [Processing and narrating a video with GPT's visual capabilities and the TTS API](https://cookbook.openai.com/examples/gpt_with_vision_for_video_understanding)\n\n* Video is downloaded using the HTTP node.\n* Python code node is used to extract the frames using OpenCV.\n* Loop node is used o batch the frames for the LLM to generate partial scripts.\n* All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it.\n* The finished voiceover clip is uploaded to Google Drive.\n\nSample the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing\n\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!" }, "typeVersion": 1 }, { "id": "23700b04-2549-4121-b442-4b92adf7f6d6", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 60, 120 ], "parameters": { "color": 7, "width": 459.41860465116287, "height": 463.313953488372, "content": "## 1. Download Video\n[Learn more about the HTTP Request node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.httprequest/)\n\nIn this demonstration, we'll download a stock video from pixabay using the HTTP Request node. Feel free to use other sources but ensure they are in a format support by OpenCV ([See docs](https://docs.opencv.org/3.4/dd/d43/tutorial_py_video_display.html))" }, "typeVersion": 1 }, { "id": "0a42aeb0-96cd-401c-abeb-c50e0f04f7ad", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 560, 120 ], "parameters": { "color": 7, "width": 605.2674418604653, "height": 522.6860465116279, "content": "## 2. Split Video into Frames\n[Learn more about the Code node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/)\n\nWe need to think of videos are a sum of 2 parts; a visual track and an audio track. The visual track is technically just a collection of images displayed one after the other and are typically referred to as frames. When we want LLM to understand videos, most of the time we can do so by giving it a series of frames as images to process.\n\nHere, we use the Python Code node to extract the frames from the video using OpenCV, a computer vision library. For performance reasons, we'll also capture only a max of 90 frames from the video but ensure they are evenly distributed across the video. This step takes about 1-2 mins to complete on a 3mb video." }, "typeVersion": 1 }, { "id": "b518461c-13f1-45ae-a156-20ae6051fc19", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 560, 660 ], "parameters": { "color": 3, "width": 418.11627906976724, "height": 132.89534883720933, "content": "### 🚨 PERFORMANCE WARNING!\nUsing large videos or capturing a large number of frames is really memory intensive and could crash your n8n instance. Be sure you have sufficient memory and to optimise the video beforehand! " }, "typeVersion": 1 }, { "id": "585f7a7f-1676-4bc3-a6fb-eace443aa5da", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ 1200, 118.69767441860472 ], "parameters": { "color": 7, "width": 1264.8139534883715, "height": 774.3720930232558, "content": "## 3. Use Vision AI to Narrate on Batches of Frames\n[Read more about the Basic LLM node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/)\n\nTo keep within token limits of our LLM, we'll need to send our frames in sequential batches to represent chunks of our original video. We'll use the loop node to create batches of 15 frames - this is because of our max of 90 frames, this fits perfectly for a total of 6 loops. Next, we'll convert each frame to a binary image so we can resize for and attach to the Basic LLM node. One trick to point out is that within the Basic LLM node, previous iterations of the generation are prepended to form a cohesive script. Without, the LLM will assume it needs to start fresh for each batch of frames.\n\nA wait node is used to stay within service rate limits. This is useful for new users who are still on lower tiers. If you do not have such restrictions, feel free to remove this wait node!" }, "typeVersion": 1 }, { "id": "42c002a3-37f6-4dd7-af14-20391b19cb5a", "name": "Stay Within Service Limits", "type": "n8n-nodes-base.wait", "position": [ 2280, 640 ], "webhookId": "677fa706-b4dd-4fe3-ba17-feea944c3193", "parameters": {}, "typeVersion": 1.1 }, { "id": "5beb17fa-8a57-4c72-9c3b-b7fdf41b545a", "name": "For Every 15 Frames", "type": "n8n-nodes-base.splitInBatches", "position": [ 1320, 380 ], "parameters": { "options": {}, "batchSize": 15 }, "typeVersion": 3 }, { "id": "9a57256a-076a-4823-8cad-3b64a17ff705", "name": "Resize Frame", "type": "n8n-nodes-base.editImage", "position": [ 1640, 500 ], "parameters": { "width": 768, "height": 768, "options": { "format": "jpeg" }, "operation": "resize" }, "typeVersion": 1 }, { "id": "3e776939-1a25-4ea0-8106-c3072d108106", "name": "Aggregate Frames", "type": "n8n-nodes-base.aggregate", "position": [ 1800, 500 ], "parameters": { "options": { "includeBinaries": true }, "aggregate": "aggregateAllItemData" }, "typeVersion": 1 }, { "id": "3a973a9c-2c7a-43c5-9c45-a14d49b56622", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 2500, 120.6860465116277 ], "parameters": { "color": 7, "width": 769.1860465116274, "height": 487.83720930232533, "content": "## 4. Generate Voice Over Clip Using TTS\n[Read more about the OpenAI node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai)\n\nFinally with our generated script parts, we can combine them into one and use OpenAI's Audio generation capabilities to generate a voice over from the full script. Once we have the output mp3, we can upload it to somewhere like Google Drive for later use.\n\nHave a listen to the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing" }, "typeVersion": 1 }, { "id": "92e07c18-4058-4098-a448-13451bd8a17a", "name": "Use Text-to-Speech", "type": "@n8n/n8n-nodes-langchain.openAi", "position": [ 2840, 360 ], "parameters": { "input": "={{ $json.data.map(item => item.text).join('\\n') }}", "options": { "response_format": "mp3" }, "resource": "audio" }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.5 }, { "id": "0696c336-1814-4ad4-aa5e-b86489a4231e", "name": "Sticky Note6", "type": "n8n-nodes-base.stickyNote", "position": [ 61, 598 ], "parameters": { "color": 7, "width": 458.1279069767452, "height": 296.8139534883723, "content": "**The video used in this demonstration is**\n© [Coverr-Free-Footage](https://pixabay.com/users/coverr-free-footage-1281706/) via [Pixabay](https://pixabay.com/videos/india-street-busy-rickshaw-people-3175/)\n![](https://res.cloudinary.com/daglih2g8/image/upload/f_auto,q_auto/v1/n8n-workflows/jhx2tma2gxaabkeiqlgp#full-width)" }, "typeVersion": 1 }, { "id": "81185ac4-c7fd-4921-937f-109662d5dfa5", "name": "Generate Narration Script", "type": "@n8n/n8n-nodes-langchain.chainLlm", "position": [ 1960, 500 ], "parameters": { "text": "=These are frames of a video. Create a short voiceover script in the style of David Attenborough. Only include the narration.\n{{\n$('Generate Narration Script').isExecuted\n ? `Continue from this script:\\n${$('Generate Narration Script').all().map(item => item.json.text.replace(/\\n/g,'')).join('\\n')}`\n : ''\n}}", "messages": { "messageValues": [ { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_1" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_2" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_3" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_4" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_5" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_6" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_7" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_8" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_9" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_10" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_11" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_12" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_13" }, { "type": "HumanMessagePromptTemplate", "messageType": "imageBinary", "binaryImageDataKey": "data_14" } ] }, "promptType": "define" }, "typeVersion": 1.4 } ], "pinData": {}, "connections": { "Resize Frame": { "main": [ [ { "node": "Aggregate Frames", "type": "main", "index": 0 } ] ] }, "Capture Frames": { "main": [ [ { "node": "Split Out Frames", "type": "main", "index": 0 } ] ] }, "Combine Script": { "main": [ [ { "node": "Use Text-to-Speech", "type": "main", "index": 0 } ] ] }, "Download Video": { "main": [ [ { "node": "Capture Frames", "type": "main", "index": 0 } ] ] }, "Aggregate Frames": { "main": [ [ { "node": "Generate Narration Script", "type": "main", "index": 0 } ] ] }, "Split Out Frames": { "main": [ [ { "node": "For Every 15 Frames", "type": "main", "index": 0 } ] ] }, "Convert to Binary": { "main": [ [ { "node": "Resize Frame", "type": "main", "index": 0 } ] ] }, "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "Generate Narration Script", "type": "ai_languageModel", "index": 0 } ] ] }, "Use Text-to-Speech": { "main": [ [ { "node": "Upload to GDrive", "type": "main", "index": 0 } ] ] }, "For Every 15 Frames": { "main": [ [ { "node": "Combine Script", "type": "main", "index": 0 } ], [ { "node": "Convert to Binary", "type": "main", "index": 0 } ] ] }, "Generate Narration Script": { "main": [ [ { "node": "Stay Within Service Limits", "type": "main", "index": 0 } ] ] }, "Stay Within Service Limits": { "main": [ [ { "node": "For Every 15 Frames", "type": "main", "index": 0 } ] ] }, "When clicking ‘Test workflow’": { "main": [ [ { "node": "Download Video", "type": "main", "index": 0 } ] ] } } }, "lastUpdatedBy": 16, "workflowInfo": { "nodeCount": 21, "nodeTypes": { "n8n-nodes-base.code": { "count": 1 }, "n8n-nodes-base.wait": { "count": 1 }, "n8n-nodes-base.splitOut": { "count": 1 }, "n8n-nodes-base.aggregate": { "count": 2 }, "n8n-nodes-base.editImage": { "count": 1 }, "n8n-nodes-base.stickyNote": { "count": 7 }, "n8n-nodes-base.googleDrive": { "count": 1 }, "n8n-nodes-base.httpRequest": { "count": 1 }, "n8n-nodes-base.convertToFile": { "count": 1 }, "n8n-nodes-base.manualTrigger": { "count": 1 }, "n8n-nodes-base.splitInBatches": { "count": 1 }, "@n8n/n8n-nodes-langchain.openAi": { "count": 1 }, "@n8n/n8n-nodes-langchain.chainLlm": { "count": 1 }, "@n8n/n8n-nodes-langchain.lmChatOpenAi": { "count": 1 } } }, "status": "published", "user": { "name": "Jimleuk", "username": "jimleuk", "bio": "Founder @ Subworkflow.ai - the fastest way to build durable RAG applications.\n\nFreelance AI Automation Engineer based in London, UK. Since 2024, my n8n templates have documented my journey into applied AI and have helped hundreds of businesses and organisations get up to speed with AI automation. Today, I continue to explore use-cases as AI evolves and occasionally upload templates which I find novel and interesting.\n\nSubscribe to the RSS Feed: https://cdn.subworkflow.ai/n8n-templates/rss.xml", "verified": true, "links": [ "https://linkedin.com/in/jimleuk" ], "avatar": "https://gravatar.com/avatar/4ab99e51473df76838beeaac908747f7928c625f869794815cabe34016967d51?r=pg&d=retro&size=200" }, "nodes": [ { "id": 9, "icon": "fa:image", "name": "n8n-nodes-base.editImage", "codex": { "data": { "details": "The Edit Image node allows you to manipulate and edit images. Use this node when you want to:\n\n- Blur an image\n- Add a border to an image\n- Create a new image\n- Crop an image\n- Composite an image on top of another\n- Draw on an image\n- Get information about the image\n- Rotate an image\n- Change the size of an image\n- Shear an image along the X or Y axis\n- Add text to the image", "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.editimage/" } ] }, "categories": [ "Marketing", "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Files", "Data Transformation" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "Edit Image", "color": "#553399" }, "iconData": { "icon": "image", "type": "icon" }, "displayName": "Edit Image", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" }, { "id": 27, "name": "Marketing" } ] }, { "id": 19, "icon": "file:httprequest.svg", "name": "n8n-nodes-base.httpRequest", "codex": { "data": { "alias": [ "API", "Request", "URL", "Build", "cURL" ], "resources": { "generic": [ { "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/", "icon": "☀️", "label": "2021: The Year to Automate the New You with n8n" }, { "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/", "icon": "🧬", "label": "Why business process automation with n8n can change your daily life" }, { "url": "https://n8n.io/blog/automatically-pulling-and-visualizing-data-with-n8n/", "icon": "📈", "label": "Automatically pulling and visualizing data with n8n" }, { "url": "https://n8n.io/blog/learn-how-to-automatically-cross-post-your-content-with-n8n/", "icon": "✍️", "label": "Learn how to automatically cross-post your content with n8n" }, { "url": "https://n8n.io/blog/automatically-adding-expense-receipts-to-google-sheets-with-telegram-mindee-twilio-and-n8n/", "icon": "🧾", "label": "Automatically Adding Expense Receipts to Google Sheets with Telegram, Mindee, Twilio, and n8n" }, { "url": "https://n8n.io/blog/running-n8n-on-ships-an-interview-with-maranics/", "icon": "🛳", "label": "Running n8n on ships: An interview with Maranics" }, { "url": "https://n8n.io/blog/what-are-apis-how-to-use-them-with-no-code/", "icon": " 🪢", "label": "What are APIs and how to use them with no code" }, { "url": "https://n8n.io/blog/5-tasks-you-can-automate-with-notion-api/", "icon": "⚡️", "label": "5 tasks you can automate with the new Notion API " }, { "url": "https://n8n.io/blog/world-poetry-day-workflow/", "icon": "📜", "label": "Celebrating World Poetry Day with a daily poem in Telegram" }, { "url": "https://n8n.io/blog/automate-google-apps-for-productivity/", "icon": "💡", "label": "15 Google apps you can combine and automate to increase productivity" }, { "url": "https://n8n.io/blog/automate-designs-with-bannerbear-and-n8n/", "icon": "🎨", "label": "Automate Designs with Bannerbear and n8n" }, { "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/", "icon": " 🕸️", "label": "How uProc scraped a multi-page website with a low-code workflow" }, { "url": "https://n8n.io/blog/building-an-expense-tracking-app-in-10-minutes/", "icon": "📱", "label": "Building an expense tracking app in 10 minutes" }, { "url": "https://n8n.io/blog/5-workflow-automations-for-mattermost-that-we-love-at-n8n/", "icon": "🤖", "label": "5 workflow automations for Mattermost that we love at n8n" }, { "url": "https://n8n.io/blog/how-to-use-the-http-request-node-the-swiss-army-knife-for-workflow-automation/", "icon": "🧰", "label": "How to use the HTTP Request Node - The Swiss Army Knife for Workflow Automation" }, { "url": "https://n8n.io/blog/learn-how-to-use-webhooks-with-mattermost-slash-commands/", "icon": "🦄", "label": "Learn how to use webhooks with Mattermost slash commands" }, { "url": "https://n8n.io/blog/how-a-membership-development-manager-automates-his-work-and-investments/", "icon": "📈", "label": "How a Membership Development Manager automates his work and investments" }, { "url": "https://n8n.io/blog/a-low-code-bitcoin-ticker-built-with-questdb-and-n8n-io/", "icon": "📈", "label": "A low-code bitcoin ticker built with QuestDB and n8n.io" }, { "url": "https://n8n.io/blog/how-to-set-up-a-ci-cd-pipeline-with-no-code/", "icon": "🎡", "label": "How to set up a no-code CI/CD pipeline with GitHub and TravisCI" }, { "url": "https://n8n.io/blog/automations-for-activists/", "icon": "✨", "label": "How Common Knowledge use workflow automation for activism" }, { "url": "https://n8n.io/blog/creating-scheduled-text-affirmations-with-n8n/", "icon": "🤟", "label": "Creating scheduled text affirmations with n8n" }, { "url": "https://n8n.io/blog/how-goomer-automated-their-operations-with-over-200-n8n-workflows/", "icon": "🛵", "label": "How Goomer automated their operations with over 200 n8n workflows" }, { "url": "https://n8n.io/blog/aws-workflow-automation/", "label": "7 no-code workflow automations for Amazon Web Services" } ], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.httprequest/" } ] }, "categories": [ "Development", "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Helpers" ] } } }, "group": "[\"output\"]", "defaults": { "name": "HTTP Request", "color": "#0004F5" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "HTTP Request", "typeVersion": 4, "nodeCategories": [ { "id": 5, "name": "Development" }, { "id": 9, "name": "Core Nodes" } ] }, { "id": 39, "icon": "fa:sync", "name": "n8n-nodes-base.splitInBatches", "codex": { "data": { "alias": [ "Loop", "Concatenate", "Batch", "Split", "Split In Batches" ], "resources": { "generic": [ { "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/", "icon": " 🕸️", "label": "How uProc scraped a multi-page website with a low-code workflow" }, { "url": "https://n8n.io/blog/benefits-of-automation-and-n8n-an-interview-with-hubspots-hugh-durkin/", "icon": "🎖", "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin" } ], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.splitinbatches/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Flow" ] } } }, "group": "[\"organization\"]", "defaults": { "name": "Loop Over Items", "color": "#007755" }, "iconData": { "icon": "sync", "type": "icon" }, "displayName": "Loop Over Items (Split in Batches)", "typeVersion": 3, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 58, "icon": "file:googleDrive.svg", "name": "n8n-nodes-base.googleDrive", "codex": { "data": { "resources": { "generic": [ { "url": "https://n8n.io/blog/your-business-doesnt-need-you-to-operate/", "icon": " 🖥️", "label": "Hey founders! Your business doesn't need you to operate" }, { "url": "https://n8n.io/blog/why-this-product-manager-loves-workflow-automation-with-n8n/", "icon": "🧠", "label": "Why this Product Manager loves workflow automation with n8n" }, { "url": "https://n8n.io/blog/aws-workflow-automation/", "label": "7 no-code workflow automations for Amazon Web Services" } ], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.googledrive/" } ], "credentialDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/" } ] }, "categories": [ "Data & Storage" ], "nodeVersion": "1.0", "codexVersion": "1.0" } }, "group": "[\"input\"]", "defaults": { "name": "Google Drive" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "Google Drive", "typeVersion": 3, "nodeCategories": [ { "id": 3, "name": "Data & Storage" } ] }, { "id": 514, "icon": "fa:pause-circle", "name": "n8n-nodes-base.wait", "codex": { "data": { "alias": [ "pause", "sleep", "delay", "timeout" ], "resources": { "generic": [ { "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/", "icon": "👥", "label": "How to get started with CRM automation (with 3 no-code workflow ideas" }, { "url": "https://n8n.io/blog/aws-workflow-automation/", "label": "7 no-code workflow automations for Amazon Web Services" } ], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.wait/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Helpers", "Flow" ] } } }, "group": "[\"organization\"]", "defaults": { "name": "Wait", "color": "#804050" }, "iconData": { "icon": "pause-circle", "type": "icon" }, "displayName": "Wait", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 565, "icon": "fa:sticky-note", "name": "n8n-nodes-base.stickyNote", "codex": { "data": { "alias": [ "Comments", "Notes", "Sticky" ], "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Helpers" ] } } }, "group": "[\"input\"]", "defaults": { "name": "Sticky Note", "color": "#FFD233" }, "iconData": { "icon": "sticky-note", "type": "icon" }, "displayName": "Sticky Note", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 834, "icon": "file:code.svg", "name": "n8n-nodes-base.code", "codex": { "data": { "alias": [ "cpde", "Javascript", "JS", "Python", "Script", "Custom Code", "Function" ], "details": "The Code node allows you to execute JavaScript in your workflow.", "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/" } ] }, "categories": [ "Development", "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Helpers", "Data Transformation" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "Code" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "Code", "typeVersion": 2, "nodeCategories": [ { "id": 5, "name": "Development" }, { "id": 9, "name": "Core Nodes" } ] }, { "id": 838, "icon": "fa:mouse-pointer", "name": "n8n-nodes-base.manualTrigger", "codex": { "data": { "resources": { "generic": [], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0" } }, "group": "[\"trigger\"]", "defaults": { "name": "When clicking ‘Execute workflow’", "color": "#909298" }, "iconData": { "icon": "mouse-pointer", "type": "icon" }, "displayName": "Manual Trigger", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 1123, "icon": "fa:link", "name": "@n8n/n8n-nodes-langchain.chainLlm", "codex": { "data": { "alias": [ "LangChain" ], "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/" } ] }, "categories": [ "AI", "Langchain" ], "subcategories": { "AI": [ "Chains", "Root Nodes" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "Basic LLM Chain", "color": "#909298" }, "iconData": { "icon": "link", "type": "icon" }, "displayName": "Basic LLM Chain", "typeVersion": 2, "nodeCategories": [ { "id": 25, "name": "AI" }, { "id": 26, "name": "Langchain" } ] }, { "id": 1153, "icon": "file:openAiLight.svg", "name": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "codex": { "data": { "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/" } ] }, "categories": [ "AI", "Langchain" ], "subcategories": { "AI": [ "Language Models", "Root Nodes" ], "Language Models": [ "Chat Models (Recommended)" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "OpenAI Chat Model" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iNDAiIGhlaWdodD0iNDAiIHZpZXdCb3g9IjAgMCA0MCA0MCIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTM2Ljg2NzEgMTYuMzcxOEMzNy43NzQ2IDEzLjY0OCAzNy40NjIxIDEwLjY2NDIgMzYuMDEwOCA4LjE4NjYxQzMzLjgyODIgNC4zODY1MyAyOS40NDA3IDIuNDMxNDkgMjUuMTU1NiAzLjM1MTUxQzIzLjI0OTMgMS4yMDM5NiAyMC41MTA1IC0wLjAxNzMxNDggMTcuNjM5MiAwLjAwMDE4NTUzM0MxMy4yNTkxIC0wLjAwOTgxNDY4IDkuMzcyNzMgMi44MTAyNSA4LjAyNTIgNi45Nzc4M0M1LjIxMTM5IDcuNTU0MSAyLjc4MjU4IDkuMzE1MzggMS4zNjEzIDExLjgxMTdDLTAuODM3NDkzIDE1LjYwMTggLTAuMzM2MjMyIDIwLjM3OTQgMi42MDEzMyAyMy42Mjk0QzEuNjkzODEgMjYuMzUzMiAyLjAwNjMyIDI5LjMzNzEgMy40NTc2IDMxLjgxNDZDNS42NDAxNSAzNS42MTQ3IDEwLjAyNzcgMzcuNTY5NyAxNC4zMTI4IDM2LjY0OTdDMTYuMjE3OSAzOC43OTczIDE4Ljk1NzkgNDAuMDE4NSAyMS44MjkyIDM5Ljk5OThDMjYuMjExOCA0MC4wMTEgMzAuMDk5NCAzNy4xODg1IDMxLjQ0NjkgMzMuMDE3MUMzNC4yNjA4IDMyLjQ0MDkgMzYuNjg5NiAzMC42Nzk2IDM4LjExMDggMjguMTgzM0M0MC4zMDcxIDI0LjM5MzIgMzkuODA0NiAxOS42MTk0IDM2Ljg2ODMgMTYuMzY5M0wzNi44NjcxIDE2LjM3MThaTTIxLjgzMTcgMzcuMzg2QzIwLjA3OCAzNy4zODg1IDE4LjM3OTIgMzYuNzc0NyAxNy4wMzI5IDM1LjY1MDlDMTcuMDk0MSAzNS42MTg0IDE3LjIwMDQgMzUuNTU5NyAxNy4yNjkxIDM1LjUxNzJMMjUuMjM0MyAzMC45MTcxQzI1LjY0MTggMzAuNjg1OCAyNS44OTE4IDMwLjI1MjEgMjUuODg5MyAyOS43ODMzVjE4LjU1NDNMMjkuMjU1NyAyMC40OTgxQzI5LjI5MTkgMjAuNTE1NiAyOS4zMTU3IDIwLjU1MDYgMjkuMzIwNyAyMC41OTA2VjI5Ljg4OTZDMjkuMzE1NyAzNC4wMjQ3IDI1Ljk2NjggMzcuMzc3MiAyMS44MzE3IDM3LjM4NlpNNS43MjY0IDMwLjUwNzFDNC44NDc2MyAyOC45ODk2IDQuNTMxMzcgMjcuMjEwOCA0LjgzMjYzIDI1LjQ4NDVDNC44OTEzOCAyNS41MTk1IDQuOTk1MTMgMjUuNTgzMiA1LjA2ODg4IDI1LjYyNTdMMTMuMDM0MSAzMC4yMjU4QzEzLjQzNzggMzAuNDYyMSAxMy45Mzc4IDMwLjQ2MjEgMTQuMzQyOCAzMC4yMjU4TDI0LjA2NjggMjQuNjEwN1YyOC40OTgzQzI0LjA2OTMgMjguNTM4MyAyNC4wNTA1IDI4LjU3NyAyNC4wMTkzIDI4LjYwMkwxNS45Njc5IDMzLjI1MDlDMTIuMzgxNSAzNS4zMTU5IDcuODAxNDQgMzQuMDg4NCA1LjcyNzY1IDMwLjUwNzFINS43MjY0Wk0zLjYzMDEgMTMuMTIwNUM0LjUwNTEyIDExLjYwMDQgNS44ODY0IDEwLjQzNzkgNy41MzE0NCA5LjgzNDE1QzcuNTMxNDQgOS45MDI5IDcuNTI3NjkgMTAuMDI0MiA3LjUyNzY5IDEwLjEwOTJWMTkuMzEwNkM3LjUyNTE5IDE5Ljc3ODEgNy43NzUxOSAyMC4yMTE5IDguMTgxNDUgMjAuNDQzMUwxNy45MDU0IDI2LjA1N0wxNC41MzkxIDI4LjAwMDhDMTQuNTA1MyAyOC4wMjMzIDE0LjQ2MjggMjguMDI3IDE0LjQyNTMgMjguMDEwOEw2LjM3MjY2IDIzLjM1ODJDMi43OTM4MyAyMS4yODU2IDEuNTY2MzEgMTYuNzA2OCAzLjYyODg1IDEzLjEyMTdMMy42MzAxIDEzLjEyMDVaTTMxLjI4ODIgMTkuNTU2OUwyMS41NjQyIDEzLjk0MTdMMjQuOTMwNiAxMS45OTkyQzI0Ljk2NDMgMTEuOTc2NyAyNS4wMDY4IDExLjk3MjkgMjUuMDQ0MyAxMS45ODkyTDMzLjA5NyAxNi42MzhDMzYuNjgyMSAxOC43MDkzIDM3LjkxMDggMjMuMjk1NyAzNS44Mzk1IDI2Ljg4MDhDMzQuOTYzMyAyOC4zOTgzIDMzLjU4MzIgMjkuNTYwOCAzMS45Mzk1IDMwLjE2NThWMjAuNjg5NEMzMS45NDMyIDIwLjIyMTkgMzEuNjk0NSAxOS43ODk0IDMxLjI4OTQgMTkuNTU2OUgzMS4yODgyWk0zNC42MzgzIDE0LjUxNDJDMzQuNTc5NSAxNC40NzggMzQuNDc1OCAxNC40MTU1IDM0LjQwMiAxNC4zNzNMMjYuNDM2OCA5Ljc3Mjg5QzI2LjAzMzEgOS41MzY2NCAyNS41MzMxIDkuNTM2NjQgMjUuMTI4MSA5Ljc3Mjg5TDE1LjQwNDEgMTUuMzg4VjExLjUwMDRDMTUuNDAxNiAxMS40NjA0IDE1LjQyMDQgMTEuNDIxNyAxNS40NTE2IDExLjM5NjdMMjMuNTAzIDYuNzUxNThDMjcuMDg5NCA0LjY4Mjc5IDMxLjY3NDUgNS45MTQwNiAzMy43NDIgOS41MDE2NEMzNC42MTU4IDExLjAxNjcgMzQuOTMyIDEyLjc5MDUgMzQuNjM1OCAxNC41MTQySDM0LjYzODNaTTEzLjU3NDEgMjEuNDQzMUwxMC4yMDY1IDE5LjQ5OTRDMTAuMTcwMiAxOS40ODE5IDEwLjE0NjUgMTkuNDQ2OCAxMC4xNDE1IDE5LjQwNjhWMTAuMTA3OUMxMC4xNDQgNS45Njc4MSAxMy41MDI4IDIuNjEyNzQgMTcuNjQyOSAyLjYxNTI0QzE5LjM5NDIgMi42MTUyNCAyMS4wODkyIDMuMjMwMjUgMjIuNDM1NSA0LjM1MDI4QzIyLjM3NDMgNC4zODI3OCAyMi4yNjkzIDQuNDQxNTMgMjIuMTk5MiA0LjQ4NDAzTDE0LjIzNDEgOS4wODQxM0MxMy44MjY2IDkuMzE1MzggMTMuNTc2NiA5Ljc0Nzg5IDEzLjU3OTEgMTAuMjE2N0wxMy41NzQxIDIxLjQ0MDZWMjEuNDQzMVpNMTUuNDAyOSAxNy41MDA2TDE5LjczNDIgMTQuOTk5M0wyNC4wNjU1IDE3LjQ5OTNWMjIuNTAwN0wxOS43MzQyIDI1LjAwMDdMMTUuNDAyOSAyMi41MDA3VjE3LjUwMDZaIiBmaWxsPSIjN0Q3RDg3Ii8+Cjwvc3ZnPgo=" }, "displayName": "OpenAI Chat Model", "typeVersion": 1, "nodeCategories": [ { "id": 25, "name": "AI" }, { "id": 26, "name": "Langchain" } ] }, { "id": 1234, "icon": "file:convertToFile.svg", "name": "n8n-nodes-base.convertToFile", "codex": { "data": { "alias": [ "CSV", "Spreadsheet", "Excel", "xls", "xlsx", "ods", "tabular", "encode", "encoding", "Move Binary Data", "Binary", "File", "JSON", "HTML", "ICS", "iCal", "RTF", "64", "Base64" ], "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.converttofile/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Files", "Data Transformation" ] } } }, "group": "[\"input\"]", "defaults": { "name": "Convert to File" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "Convert to File", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 1236, "icon": "file:aggregate.svg", "name": "n8n-nodes-base.aggregate", "codex": { "data": { "alias": [ "Aggregate", "Combine", "Flatten", "Transform", "Array", "List", "Item" ], "details": "", "resources": { "generic": [], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.aggregate/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Data Transformation" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "Aggregate" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "Aggregate", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 1239, "icon": "file:splitOut.svg", "name": "n8n-nodes-base.splitOut", "codex": { "data": { "alias": [ "Split", "Nested", "Transform", "Array", "List", "Item" ], "details": "", "resources": { "generic": [], "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.splitout/" } ] }, "categories": [ "Core Nodes" ], "nodeVersion": "1.0", "codexVersion": "1.0", "subcategories": { "Core Nodes": [ "Data Transformation" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "Split Out" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSI1MTIiIGhlaWdodD0iNTEyIiBmaWxsPSJub25lIj48ZyBmaWxsPSIjOUI2REQ1IiBjbGlwLXBhdGg9InVybCgjYSkiPjxwYXRoIGZpbGwtcnVsZT0iZXZlbm9kZCIgZD0iTTQ4MCAxNDhjMC02LjYyNy01LjM3My0xMi0xMi0xMkgzMjJjLTYuNjI3IDAtMTIgNS4zNzMtMTIgMTJ2MjRjMCA2LjYyNyA1LjM3MyAxMiAxMiAxMmgxNDZjNi42MjcgMCAxMi01LjM3MyAxMi0xMnptMCA5NmMwLTYuNjI3LTUuMzczLTEyLTEyLTEySDMyMmMtNi42MjcgMC0xMiA1LjM3My0xMiAxMnYyNGMwIDYuNjI3IDUuMzczIDEyIDEyIDEyaDE0NmM2LjYyNyAwIDEyLTUuMzczIDEyLTEyem0wIDk2YzAtNi42MjctNS4zNzMtMTItMTItMTJIMzIyYy02LjYyNyAwLTEyIDUuMzczLTEyIDEydjI0YzAgNi42MjcgNS4zNzMgMTIgMTIgMTJoMTQ2YzYuNjI3IDAgMTItNS4zNzMgMTItMTJ6IiBjbGlwLXJ1bGU9ImV2ZW5vZGQiLz48cGF0aCBkPSJNNDM4IDc2YzAgNi42MjctNS4zNzMgMTItMTIgMTJIMzA5Ljc4M2MtMTcuNjczIDAtMzIgMTQuMzI3LTMyIDMydjU2YzAgMjYuOTc4LTEwLjI3MiA1MS41NTctMjcuMTE5IDcwLjAzOS01LjA1NSA1LjU0NS01LjA1NSAxNC4zNzcgMCAxOS45MjIgMTYuODQ3IDE4LjQ4MiAyNy4xMTkgNDMuMDYxIDI3LjExOSA3MC4wMzl2NTZjMCAxNy42NzMgMTQuMzI3IDMyIDMyIDMySDQyNmM2LjYyNyAwIDEyIDUuMzczIDEyIDEydjI0YzAgNi42MjctNS4zNzMgMTItMTIgMTJIMzA5Ljc4M2MtNDQuMTgzIDAtODAtMzUuODE3LTgwLTgwdi01NmMwLTMwLjkyOC0yNS4wNzItNTYtNTYtNTZhNS43ODMgNS43ODMgMCAwIDEtNS43ODMtNS43ODN2LTM2LjQzNGE1Ljc4MyA1Ljc4MyAwIDAgMSA1Ljc4My01Ljc4M2MzMC45MjggMCA1Ni0yNS4wNzIgNTYtNTZ2LTU2YzAtNDQuMTgzIDM1LjgxNy04MCA4MC04MEg0MjZjNi42MjcgMCAxMiA1LjM3MyAxMiAxMnoiLz48cGF0aCBmaWxsLXJ1bGU9ImV2ZW5vZGQiIGQ9Ik0xMzYgMjQ0YzAtNi42MjctNS4zNzMtMTItMTItMTJIMTJjLTYuNjI3IDAtMTIgNS4zNzMtMTIgMTJ2MjRjMCA2LjYyNyA1LjM3MyAxMiAxMiAxMmgxMTJjNi42MjcgMCAxMi01LjM3MyAxMi0xMnoiIGNsaXAtcnVsZT0iZXZlbm9kZCIvPjwvZz48ZGVmcz48Y2xpcFBhdGggaWQ9ImEiPjxwYXRoIGZpbGw9IiNmZmYiIGQ9Ik01MTIgMEgwdjUxMmg1MTJ6Ii8+PC9jbGlwUGF0aD48L2RlZnM+PC9zdmc+" }, "displayName": "Split Out", "typeVersion": 1, "nodeCategories": [ { "id": 9, "name": "Core Nodes" } ] }, { "id": 1250, "icon": "file:openAi.svg", "name": "@n8n/n8n-nodes-langchain.openAi", "codex": { "data": { "alias": [ "LangChain", "ChatGPT", "Sora", "DallE", "whisper", "audio", "transcribe", "tts", "assistant" ], "resources": { "primaryDocumentation": [ { "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai/" } ] }, "categories": [ "AI", "Langchain" ], "subcategories": { "AI": [ "Agents", "Miscellaneous", "Root Nodes" ] } } }, "group": "[\"transform\"]", "defaults": { "name": "OpenAI" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,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" }, "displayName": "OpenAI", "typeVersion": 2, "nodeCategories": [ { "id": 25, "name": "AI" }, { "id": 26, "name": "Langchain" } ] } ], "categories": [ { "id": 31, "name": "Content Creation" }, { "id": 51, "name": "Multimodal AI" } ], "image": [] } }