Automatisation de la publication RSS vers Medium avec Groq, Gemini et un système d'approbation Slack

• •Compte Google et informations d'identification Gmail API
• •Token Bot Slack ou URL Webhook
• •Informations d'identification Google Drive API
• •Peut nécessiter les informations d'identification d'authentification de l'API cible
• •Informations d'identification Google Sheets API
• •Clé API Google Gemini

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        "content": "## 📰 RSS for Content Fetching\n\nNodes involved:\n\nSchedule Trigger\nThe Verge - Tech RSS\nTechCrunch RSS\n\nThis section uses a scheduled trigger to pull in fresh content from two tech-focused RSS feeds: The Verge and TechCrunch. These feeds act as the primary sources for news articles. It ensures that every run starts with up-to-date, relevant tech content from reputable platforms.\n\n\n\n## 🧮 Sort, Merge, and Pick a Post\nNodes involved:\n\nGet row(s) in sheet : TITLE, IMAGE_URL, CREATOR, & DESCRIPTION\n\nMerge\n\nPick Random Post[Customize to your preferred Niche]\n\nNote:\nFetched articles are merged into a single list. The workflow then checks a Google Sheet to verify which articles were already posted before. One new, unique article is picked randomly from the valid entries to be used for further processing. This ensures no duplicate publishing and supports content diversity.\n\n\n🚫 Check If Already Posted\nNodes involved:\n\nCheck If Already Posted\n\nNote:\nThis node verifies if the selected article has already been used in a past run by comparing its title or link with existing records in the Google Sheet. If already posted, it either halts or skips the duplicate to maintain uniqueness in published content."
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        "content": "🧠 Agent Article & Image Generation\nNodes involved:\n\nGoogle Gemini Model (text generation)\n\nBasic LLM Chain (structured content)\n\nGroq Chat Model (content expansion)\n\nGenerate Image Prompt\n\nCreate Image with Pollinations and get the URL\n\nHTTP Request (fetch/download image)\n\nDownload Image file \n\nNote:\nThis is the AI generation stage:\n\nText: Google Gemini and Groq LLM models are used to generate a well-written article based on the RSS content.\n\nImage: Pollinations AI generates a relevant visual image from a text prompt. An HTTP node is used to fetch the image, which is then uploaded to the cloud (possibly Drive or another host).\n\nOutput is split to handle both article and image streams for better control downstream.\n\n"
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        "content": "☁️ Upload to Google Drive\nNodes involved:\n\nCreate Google Doc\n\nMerge4\n\nUpdate Doc\n\nEdit Fields\n\nNote:\nThe generated article and image are uploaded and stored in Google Drive. A Google Doc is created, updated with the AI-generated content, and linked back to the system. This provides a centralized place for human reviewers and stores the article for archiving or reuse.\n\nHere We Send the post to Slack DM or Channel for the user to Review the Article."
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        "content": "📤 Slack Notification for Approval\nNodes involved:\n\nSend a message2\n\nSend a message and wait for response\n\nCheck Approval Status\n\nNote:\nSlack is used as the manual review checkpoint. The system sends a message with the content preview and waits for a response (approval or rejection) from a designated reviewer or group. This introduces human judgment before public publishing.\n\n✅ Approved = Publish to Medium + Gmail\nNodes involved:\n\nPublish to Medium\n\nSend a message1 (Gmail)\n\nNote:\nOnce content is approved via Slack, it's automatically published to Medium through an API call. At the same time, an email is sent via Gmail, which could be used to notify stakeholders, send to a mailing list, or archive the content. This step ensures distribution across multiple channels.\n\n❌ Rejected = Notify on Slack\nNodes involved:\n\nRejection Notification\n\nNote:\nIf the reviewer rejects the article in Slack, a rejection notification is triggered and sent to the same Slack user or group. This keeps the content creation team informed and ready to revise or skip the rejected content. It closes the loop with proper rejection feedback.\n\n"
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