{ "edges": [ { "to": "c19ca9b7-3d0a-4f8a-be54-bff3b188c12a", "from": "b99f1752-f6cd-4149-88c7-ba02975aeaf4", "toPort": "0", "fromPort": "0" }, { "to": "377af262-7c5f-45ad-81a3-ea8af25f3862", "from": "b1c72cac-7e02-4a24-8dc0-99ea96a00c44", "toPort": "0", "fromPort": "0" }, { "to": "d9397243-bad3-4699-9056-a22e41009a4d", "from": "53ff6b5d-cda9-4bf5-b28a-a8983e8b8d5e", "toPort": "0", "fromPort": "0" }, { "to": "d1d0195c-ec4e-4990-bce9-0b103ceef218", "from": "377af262-7c5f-45ad-81a3-ea8af25f3862", "toPort": "0", "fromPort": "0" }, { "to": "3eb75e0a-0c99-4cf1-b6a5-105a5fb705d4", "from": "b00dc7bd-c999-4617-b752-1c78a93fabd7", "toPort": "0", "fromPort": "0" }, { "to": "88ce4578-58f3-4cbc-8ae4-fed95b73a75d", "from": "5afb4709-1651-4ba5-9cb7-e9da7437afe4", "toPort": "0", "fromPort": "0" }, { "to": "b900240c-9695-4c2a-8766-a0703c530721", "from": "d1d0195c-ec4e-4990-bce9-0b103ceef218", "toPort": "0", "fromPort": "0" }, { "to": "b00dc7bd-c999-4617-b752-1c78a93fabd7", "from": "ae31ca41-9c74-48ef-bb43-9ff5627c1c0f", "toPort": "0", "fromPort": "0" }, { "to": "5afb4709-1651-4ba5-9cb7-e9da7437afe4", "from": "ae31ca41-9c74-48ef-bb43-9ff5627c1c0f", "toPort": "0", "fromPort": "0" }, { "to": "b99f1752-f6cd-4149-88c7-ba02975aeaf4", "from": "88ce4578-58f3-4cbc-8ae4-fed95b73a75d", "toPort": "0", "fromPort": "0" }, { "to": "3eb75e0a-0c99-4cf1-b6a5-105a5fb705d4", "from": "7d068914-c1cc-4553-945d-0327ea5e66df", "toPort": "0", "fromPort": "ai_languageModel" }, { "to": "ae31ca41-9c74-48ef-bb43-9ff5627c1c0f", "from": "d9397243-bad3-4699-9056-a22e41009a4d", "toPort": "0", "fromPort": "0" }, { "to": "b99f1752-f6cd-4149-88c7-ba02975aeaf4", "from": "b900240c-9695-4c2a-8766-a0703c530721", "toPort": "1", "fromPort": "0" }, { "to": "b1c72cac-7e02-4a24-8dc0-99ea96a00c44", "from": "3eb75e0a-0c99-4cf1-b6a5-105a5fb705d4", "toPort": "0", "fromPort": "0" }, { "to": "3eb75e0a-0c99-4cf1-b6a5-105a5fb705d4", "from": "426f6797-088e-42f2-9f5d-ebcf2b853974", "toPort": "0", "fromPort": "ai_outputParser" } ], "nodes": [ { "id": "53ff6b5d-cda9-4bf5-b28a-a8983e8b8d5e", "name": "Github Trigger1", "type": "integration", "params": { "owner": { "__rl": true, "mode": "name", "value": "your-github-username" }, "events": [ "push" ], "options": {}, "service": "githubtrigger", "operation": "run", "repository": { "__rl": true, "mode": "name", "value": "your-source-repo-name" }, "__originalType": "n8n-nodes-base.githubTrigger" }, "position": [ -1808, 352 ] }, { "id": "ae31ca41-9c74-48ef-bb43-9ff5627c1c0f", "name": "GitHub File Download", "type": "integration", "params": { "owner": { "__rl": true, "mode": "name", "value": "your-github-username" }, "service": "github", "filePath": "={{ $json.filePath }}", "resource": "file", "operation": "get", "repository": { "__rl": true, "mode": "name", "value": "your-source-repo-name" }, "additionalParameters": {} }, "position": [ -1392, 352 ] }, { "id": "c19ca9b7-3d0a-4f8a-be54-bff3b188c12a", "name": "Post to LinkedIn", "type": "integration", "params": { "text": "={{ $('LinkedIn Content Creator').item.json.output.post_title }}\n\n{{ $('LinkedIn Content Creator').item.json.output.post_content }}\n{{ $('LinkedIn Content Creator').item.json.output.hashtags }}\n\nLink to Github: {{ $json.content._links.html }}\n", "person": "your-linkedin-urn", "service": "linkedin", "operation": "read", "additionalFields": { "visibility": "PUBLIC" }, "shareMediaCategory": "IMAGE" }, "position": [ -304, 416 ] }, { "id": "3eb75e0a-0c99-4cf1-b6a5-105a5fb705d4", "name": "LinkedIn Content Creator", "type": "llm", "params": { "text": "=Data\n{{ $json.data }}", "prompt": "=Data\n{{ $json.data }}", "options": { "systemMessage": "You are a LinkedIn content strategist and copywriter specialising in professional, engaging technical content focused on infrastructure as code with bicep for azure workloads.\n\nAnalyze the provided code file and create:\n1. A LinkedIn post with compelling narrative (without including the actual code)\n2. Extract the most important/interesting code snippet (10-20 lines max) that showcases the key concept\n\nFor the LinkedIn post:\n- Open with a compelling hook that grabs attention\n- Explain what the code does and why it's valuable\n- Use professional yet conversational tone\n- Include a clear call-to-action\n- Stay within 400 characters\n- DO NOT include the actual code in the post content\n\nFor the code snippet:\n- Select the most interesting or important part\n- Keep it concise (10-20 lines)\n- Ensure it's self-contained and understandable\n- Include any necessary context as comments\n\nIMPORTANT: Return hashtags as a single string with space-separated hashtags, NOT as an array.\n\nFormat your response as JSON with the following structure:\n{\n \"post_title\": \"string\",\n \"post_content\": \"string (narrative without code and without hashtags)\",\n \"code_snippet\": \"string (the actual code to display)\",\n \"code_language\": \"string (javascript, typescript, python, etc.)\",\n \"hashtags\": \"string\",\n \"character_count\": integer\n}" }, "provider": "openai", "promptType": "define", "approximated": true, "systemMessage": "You are a LinkedIn content strategist and copywriter specialising in professional, engaging technical content focused on infrastructure as code with bicep for azure workloads.\n\nAnalyze the provided code file and create:\n1. A LinkedIn post with compelling narrative (without including the actual code)\n2. Extract the most important/interesting code snippet (10-20 lines max) that showcases the key concept\n\nFor the LinkedIn post:\n- Open with a compelling hook that grabs attention\n- Explain what the code does and why it's valuable\n- Use professional yet conversational tone\n- Include a clear call-to-action\n- Stay within 400 characters\n- DO NOT include the actual code in the post content\n\nFor the code snippet:\n- Select the most interesting or important part\n- Keep it concise (10-20 lines)\n- Ensure it's self-contained and understandable\n- Include any necessary context as comments\n\nIMPORTANT: Return hashtags as a single string with space-separated hashtags, NOT as an array.\n\nFormat your response as JSON with the following structure:\n{\n \"post_title\": \"string\",\n \"post_content\": \"string (narrative without code and without hashtags)\",\n \"code_snippet\": \"string (the actual code to display)\",\n \"code_language\": \"string (javascript, typescript, python, etc.)\",\n \"hashtags\": \"string\",\n \"character_count\": integer\n}", "hasOutputParser": true }, "position": [ -1616, 784 ] }, { "id": "377af262-7c5f-45ad-81a3-ea8af25f3862", "name": "Create Code HTML", "type": "code", "params": { "jsCode": "// Get the code snippet and language from previous node\nconst codeSnippet = $json.code_snippet || '';\nconst language = $json.code_language || 'javascript';\n\n// Calculate dimensions based on content\nconst lines = codeSnippet.split('\\n');\nconst lineCount = lines.length;\nconst maxLineLength = Math.max(...lines.map(line => line.length));\n\n// Adjust sizing calculations\nconst charWidth = 8.4; // approximate width per character in monospace\nconst lineHeight = 24; // pixels per line\nconst containerPadding = 20; // padding inside code container\nconst bodyPadding = 10; // minimal body padding\nconst headerHeight = 40; // header with dots\n\n// Calculate dimensions and FORCE INTEGERS (Math.ceil) to prevent API errors\nconst calculatedWidth = Math.max(400, maxLineLength * charWidth + (containerPadding * 2));\nconst contentWidth = Math.ceil(Math.min(calculatedWidth, 1200)); \nconst contentHeight = Math.ceil((lineCount * lineHeight) + headerHeight + (containerPadding * 2));\n\n// Create HTML with minimal padding, sized to content\nconst html = `\n\n\n\n \n \n \n \n \n \n\n\n

\n \n

${codeSnippet.replace(//g, '>')}

\n \n \n\n\n`;\n\nreturn [{\n json: {\n ...items[0].json,\n html: html,\n estimatedWidth: contentWidth + (bodyPadding * 2),\n estimatedHeight: contentHeight + (bodyPadding * 2)\n }\n}];" }, "position": [ -1152, 752 ] }, { "id": "d1d0195c-ec4e-4990-bce9-0b103ceef218", "name": "Generate Code Image", "type": "http", "params": { "url": "https://hcti.io/v1/image", "method": "POST", "options": { "timeout": 30000, "response": { "response": { "responseFormat": "json" } } }, "sendBody": true, "sendHeaders": true, "authentication": "genericCredentialType", "bodyParameters": { "parameters": [ { "name": "html", "value": "={{ $json.html }}" }, { "name": "google_fonts", "value": "Fira Code" }, { "name": "viewport_width", "value": "={{ Math.min($json.estimatedWidth || 800, 1920) }}" }, { "name": "viewport_height", "value": "={{ Math.min($json.estimatedHeight || 400, 1080) }}" }, { "name": "device_scale", "value": "={{ 2 }}" } ] }, "genericAuthType": "httpBasicAuth", "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] } }, "position": [ -960, 752 ] }, { "id": "b900240c-9695-4c2a-8766-a0703c530721", "name": "GET the genarted Image", "type": "http", "params": { "url": "={{ $json.url }}", "options": { "response": { "response": { "responseFormat": "file" } } } }, "position": [ -752, 752 ] }, { "id": "88ce4578-58f3-4cbc-8ae4-fed95b73a75d", "name": "Upload to Image Repo", "type": "integration", "params": { "owner": { "__rl": true, "mode": "name", "value": "your-github-username" }, "service": "github", "filePath": "={{ $('GitHub File Download').item.json.filePath }}", "resource": "file", "operation": "read", "repository": { "__rl": true, "mode": "name", "value": "your-image-storage-repo" }, "fileContent": "={{ $json.data }}", "commitMessage": "=Upload generated image for {{ $('GitHub File Download').item.json.filePath }}" }, "position": [ -864, 192 ] }, { "id": "b99f1752-f6cd-4149-88c7-ba02975aeaf4", "name": "Merge", "type": "merge", "params": { "mode": "combine", "options": {}, "combineBy": "combineAll" }, "position": [ -496, 416 ] }, { "id": "d9397243-bad3-4699-9056-a22e41009a4d", "name": "Extract Modified Files", "type": "code", "params": { "jsCode": "// Get the head_commit object from the webhook body\nconst headCommit = $json.body.head_commit;\n\n// Get the arrays of added and modified files. Default to empty arrays if they don't exist.\nconst addedFiles = headCommit.added || [];\nconst modifiedFiles = headCommit.modified || [];\n\n// Combine both arrays into a single list of file paths\nconst allChangedFiles = [...addedFiles, ...modifiedFiles];\n\n// If there are no changed files, return an empty result to stop the workflow gracefully.\nif (allChangedFiles.length === 0) {\n return [];\n}\n\n// Create a new list of n8n items. Each item will contain one file path.\nconst items = allChangedFiles.map(filePath => {\n return {\n json: {\n // We store the path in a new field called 'filePath'\n filePath: filePath\n }\n };\n});\n\n// Return the new list of items\nreturn items;" }, "position": [ -1584, 352 ] }, { "id": "b00dc7bd-c999-4617-b752-1c78a93fabd7", "name": "Extract from File", "type": "passthrough", "params": { "mode": "noOp", "options": {}, "operation": "text" }, "position": [ -1120, 352 ] }, { "id": "426f6797-088e-42f2-9f5d-ebcf2b853974", "name": "Structured Output Parser", "type": "passthrough", "params": { "mode": "noOp", "schemaType": "manual", "inputSchema": "{\n\t\"type\": \"object\",\n\t\"properties\": {\n\t\t\"post_title\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"post_content\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"code_snippet\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"code_language\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"hashtags\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"character_count\": {\n\t\t\t\"type\": \"integer\"\n\t\t}\n\t}\n}" }, "position": [ -1472, 1008 ] }, { "id": "b1c72cac-7e02-4a24-8dc0-99ea96a00c44", "name": "Edit Fields", "type": "set", "params": { "options": {}, "assignments": { "assignments": [ { "id": "13b0cb01-c54d-43bb-90df-a48f12d76fb3", "name": "post_title", "type": "string", "value": "={{ $json.output.post_title }}" }, { "id": "f3b23908-6876-46b7-be5f-d8a41c209202", "name": "post_content", "type": "string", "value": "={{ $json.output.post_content }}" }, { "id": "a915c874-e76a-408e-ad92-d8863397a5e0", "name": "code_snippet", "type": "string", "value": "={{ $json.output.code_snippet }}" }, { "id": "571704c3-425c-4aa2-a44a-1147ac56ad1c", "name": "code_language", "type": "string", "value": "={{ $json.output.code_language }}" }, { "id": "6599c4be-cbaf-4155-b7b9-4930b1386e48", "name": "hashtags", "type": "string", "value": "={{ $json.output.hashtags }}" }, { "id": "0e9bde61-489f-4c20-b68a-0193cd8a388e", "name": "character_count", "type": "number", "value": "={{ $json.output.character_count }}" } ] } }, "position": [ -1328, 752 ] }, { "id": "7d068914-c1cc-4553-945d-0327ea5e66df", "name": "OpenRouter Chat Model", "type": "llm", "params": { "model": "google/gemini-2.5-flash", "options": { "responseFormat": "json_object" }, "provider": "openai" }, "position": [ -1616, 1008 ] }, { "id": "5afb4709-1651-4ba5-9cb7-e9da7437afe4", "name": "Extract from File1", "type": "passthrough", "params": { "mode": "noOp", "options": {}, "operation": "binaryToPropery" }, "position": [ -1120, 192 ] } ] }

Convert GitHub code commits to LinkedIn posts with Gemini AI and code image generation