Automatisation de la création de blogs dans le style de la marque avec l'IA

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Ceci est unAI, Marketingworkflow d'automatisation du domainecontenant 27 nœuds.Utilise principalement des nœuds comme Set, Html, Limit, Merge, Markdown, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Utiliser l'IA pour automatiser la création de blog dans le style de la marque

Prérequis
  • Peut nécessiter les informations d'identification d'authentification de l'API cible
  • Clé API OpenAI
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
  "nodes": [
    {
      "id": "d3159589-dbb7-4cca-91f5-09e8b2e4cba8",
      "name": "Lors du clic sur 'Tester le workflow'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        240,
        500
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "b4b42b3f-ef30-4fc8-829d-59f8974c4168",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2180,
        700
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "032c3012-ed8d-44eb-94f0-35790f4b616f",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2980,
        460
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "bf922785-7e8f-4f93-bfff-813c16d93278",
      "name": "OpenAI Chat Model2",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2020,
        520
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "d8d4b26f-270f-4b39-a4cd-a6e4361da591",
      "name": "Extraire les caractéristiques vocales",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        2160,
        540
      ],
      "parameters": {
        "text": "=### Analyse the given content\n\n{{ $json.data.map(item => item.replace(/\\n/g, '')).join('\\n---\\n') }}",
        "options": {
          "systemPromptTemplate": "You help identify and define a company or individual's \"brand voice\". Using the given content belonging to the company or individual, extract all voice characteristics from it along with description and examples demonstrating it."
        },
        "schemaType": "manual",
        "inputSchema": "{\n\t\"type\": \"array\",\n    \"items\": {\n      \"type\": \"object\",\n    \t\"properties\": {\n          \"characteristic\": { \"type\": \"string\" },\n          \"description\": { \"type\": \"string\" },\n          \"examples\": { \"type\": \"array\", \"items\": { \"type\": \"string\" } }\n        }\n\t}\n}"
      },
      "typeVersion": 1
    },
    {
      "id": "8cca272c-b912-40f1-ba08-aa7c5ff7599c",
      "name": "Obtenir le blog",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        480,
        500
      ],
      "parameters": {
        "url": "https://blog.n8n.io",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "aa1e2a02-2e2b-4e8d-aef8-f5f7a54d9562",
      "name": "Obtenir l'article",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1120,
        500
      ],
      "parameters": {
        "url": "=https://blog.n8n.io{{ $json.article }}",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "78ae3dfc-5afd-452f-a2b6-bdb9dbd728bd",
      "name": "Extraire les URL d'articles",
      "type": "n8n-nodes-base.html",
      "position": [
        640,
        500
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "article",
              "attribute": "href",
              "cssSelector": ".item.post a.global-link",
              "returnArray": true,
              "returnValue": "attribute"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "3b2b6fea-ed2f-43ba-b6d1-e0666b88c65b",
      "name": "Séparer les URL",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        800,
        500
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "article"
      },
      "typeVersion": 1
    },
    {
      "id": "68bb20b1-2177-4c0f-9ada-d1de69bdc2a0",
      "name": "Articles récents",
      "type": "n8n-nodes-base.limit",
      "position": [
        960,
        500
      ],
      "parameters": {
        "maxItems": 5
      },
      "typeVersion": 1
    },
    {
      "id": "f20d7393-24c9-4a51-872e-0dce391f661c",
      "name": "Extraire le contenu de l'article",
      "type": "n8n-nodes-base.html",
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        1280,
        500
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
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    },
    {
      "id": "299a04be-fe9b-47d9-b2c6-e2e4628f77e0",
      "name": "Combiner les articles",
      "type": "n8n-nodes-base.aggregate",
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      ],
      "parameters": {
        "options": {
          "mergeLists": true
        },
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "data"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "8480ece7-0dc1-4682-ba9e-ded2c138d8b8",
      "name": "Style d'article & Voix de marque",
      "type": "n8n-nodes-base.merge",
      "position": [
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      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3
    },
    {
      "id": "024efee2-5a2f-455c-a150-4b9bdce650b2",
      "name": "Enregistrer comme brouillon",
      "type": "n8n-nodes-base.wordpress",
      "position": [
        3460,
        320
      ],
      "parameters": {
        "title": "={{ $json.output.title }}",
        "additionalFields": {
          "slug": "={{ $json.output.title.toSnakeCase() }}",
          "format": "standard",
          "status": "draft",
          "content": "={{ $json.output.body }}"
        }
      },
      "credentials": {
        "wordpressApi": {
          "id": "YMW8mGrekjfxKJUe",
          "name": "Wordpress account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "71f4ab1e-ef61-48f3-92e8-70691f7d0750",
      "name": "Note adhésive",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        480,
        180
      ],
      "parameters": {
        "color": 7,
        "width": 606,
        "height": 264,
        "content": "## 1. Import Existing Content\n[Read more about the HTML node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.html/)\n\nFirst, we'll need to gather existing content for the brand voice we want to replicate. This content can be blogs, social media posts or internal documents - the idea is to use this content to \"train\" our AI to produce content from the provided examples. One call out is that the quality and consistency of the content is important to get the desired results.\n\nIn this demonstration, we'll grab the latest blog posts off a corporate blog to use as an example. Since, the blog articles are likely consistent because of the source and narrower focus of the medium, it'll serve well to showcase this workflow."
      },
      "typeVersion": 1
    },
    {
      "id": "3d3a55a5-4b4a-4ea2-a39c-82b366fb81e6",
      "name": "Note adhésive1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1440,
        240
      ],
      "parameters": {
        "color": 7,
        "width": 434,
        "height": 230,
        "content": "## 2. Convert HTML to Markdown\n[Learn more about the Markdown node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.markdown)\n\nMarkdown is a great way to optimise the article data we're sending to the LLM because it reduces the amount of tokens required but keeps all relevant writing structure information.\n\nAlso useful to get Markdown output as a response because typically it's the format authors will write in."
      },
      "typeVersion": 1
    },
    {
      "id": "08c0b683-ec06-47ce-871c-66265195ca29",
      "name": "Note adhésive2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1980,
        80
      ],
      "parameters": {
        "color": 7,
        "width": 446,
        "height": 233,
        "content": "## 3. Using AI to Analyse Article Structure and Writing Styles\n[Read more about the Basic LLM Chain node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm)\n\nOur approach is to first perform a high-level analysis of all available articles in order to replicate their content layout and writing styles. This will act as a guideline to help the AI to structure our future articles."
      },
      "typeVersion": 1
    },
    {
      "id": "515fe69f-061e-4dfc-94ed-4cf2fbe10b7b",
      "name": "Capturer la structure d'article existante",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        2020,
        380
      ],
      "parameters": {
        "text": "={{ $json.data.join('\\n---\\n') }}",
        "messages": {
          "messageValues": [
            {
              "message": "=Given the following one or more articles (which are separated by ---), describe how best one could replicate the common structure, layout, language and writing styles of all as aggregate."
            }
          ]
        },
        "promptType": "define"
      },
      "typeVersion": 1.4
    },
    {
      "id": "ba4e68fb-eccc-4efa-84be-c42a695dccdb",
      "name": "Markdown",
      "type": "n8n-nodes-base.markdown",
      "position": [
        1600,
        540
      ],
      "parameters": {
        "html": "={{ $json.data }}",
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "d459ff5b-0375-4458-a49f-59700bb57e12",
      "name": "Note adhésive3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2340,
        740
      ],
      "parameters": {
        "color": 7,
        "width": 446,
        "height": 253,
        "content": "## 4. Using AI to Extract Voice Characteristics and Traits\n[Read more about the Information Extractor node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor/)\n\nSecond, we'll use AI to analysis the brand voice characteristics of the previous articles. This picks out the tone, style and choice of language used and identifies them into categories. These categories will be used as guidelines for the AI to keep the future article consistent in tone and voice. "
      },
      "typeVersion": 1
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    {
      "id": "71fe32a9-1b8a-446c-a4ff-fb98c6a68e1b",
      "name": "Note adhésive4",
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      "position": [
        2720,
        0
      ],
      "parameters": {
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        "width": 626,
        "height": 633,
        "content": "## 5. Automate On-Brand Articles Using AI\n[Read more about the Information Extractor node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor)\n\nFinally with this approach, we can feed both content and voice guidelines into our final LLM - our content generation agent - to produce any number of on-brand articles, social media posts etc.\n\nWhen it comes to assessing the output, note the AI does a pretty good job at simulating format and reusing common phrases and wording for the target article. However, this could become repetitive very quickly! Whilst AI can help speed up the process, a human touch may still be required to add a some variety."
      },
      "typeVersion": 1
    },
    {
      "id": "4e6fbe4e-869e-4bef-99ba-7b18740caecf",
      "name": "Agent de génération de contenu",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        3000,
        320
      ],
      "parameters": {
        "text": "={{ $json.instruction }}",
        "options": {
          "systemPromptTemplate": "=You are a blog content writer who writes using the following article guidelines. Write a content piece as requested by the user. Output the body as Markdown. Do not include the date of the article because the publishing date is not determined yet.\n\n## Brand Article Style\n{{ $('Article Style & Brand Voice').item.json.text }}\n\n##n Brand Voice Characteristics\n\nHere are the brand voice characteristic and examples you must adopt in your piece. Pick only the characteristic which make sense for the user's request. Try to keep it as similar as possible but don't copy word for word.\n\n|characteristic|description|examples|\n|-|-|-|\n{{\n$('Article Style & Brand Voice').item.json.output.map(item => (\n`|${item.characteristic}|${item.description}|${item.examples.map(ex => `\"${ex}\"`).join(', ')}|`\n)).join('\\n')\n}}"
        },
        "attributes": {
          "attributes": [
            {
              "name": "title",
              "required": true,
              "description": "title of article"
            },
            {
              "name": "summary",
              "required": true,
              "description": "summary of article"
            },
            {
              "name": "body",
              "required": true,
              "description": "body of article"
            },
            {
              "name": "characteristics",
              "required": true,
              "description": "comma delimited string of characteristics chosen"
            }
          ]
        }
      },
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    },
    {
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      "name": "Note adhésive6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
        "color": 7,
        "width": 406,
        "height": 173,
        "content": "## 6. Save Draft to Wordpress\n[Learn more about the Wordpress node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.wordpress/)\n\nTo close out the template, we'll simple save our generated article as a draft which could allow human team members to review and validate the article before publishing."
      },
      "typeVersion": 1
    },
    {
      "id": "fe54c40e-6ddd-45d6-a938-f467e4af3f57",
      "name": "Note adhésive5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
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        "width": 440,
        "height": 120,
        "content": "### Q. Do I need to analyse Brand Voice for every article?\nA. No! I would recommend storing the results of the AI's analysis and re-use for a list of planned articles rather than generate anew every time."
      },
      "typeVersion": 1
    },
    {
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      "name": "Note adhésive7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1000,
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      ],
      "parameters": {
        "color": 5,
        "width": 380,
        "height": 120,
        "content": "### Q. Can I use other media than blog articles?\nA. Yes! This approach can use other source materials such as PDFs, as long as they can be produces in a text format to give to the LLM."
      },
      "typeVersion": 1
    },
    {
      "id": "8e8706a3-122d-436b-9206-de7a6b2f3c39",
      "name": "Note adhésive8",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
        "width": 400,
        "height": 800,
        "content": "## Try It Out!\n### This n8n template demonstrates how to use AI to generate new on-brand written content by analysing previously published content.\n\nWith such an approach, it's possible to generate a steady stream of blog article drafts quickly with high consistency with your brand and existing content.\n\n### How it works\n* In this demonstration, the n8n.io blog is used as the source of existing published content and 5 of the latest articles are imported via the HTTP node.\n* The HTML node is extract the article  bodies which are then converted to markdown for our LLMs.\n* We use LLM nodes to (1) understand the article structure and writing style and (2) identify the brand voice characteristics used in the posts.\n* These are then used as guidelines in our final LLM node when generating new articles.\n* Finally, a draft is saved to Wordpress for human editors to review or use as starting point for their own articles.\n\n### How to use\n* Update Step 1 to fetch data from your desired blog or change to fetch existing content in a different way.\n* Update Step 5 to provide your new article instruction. For optimal output, theme topics relevant to your brand.\n\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
      },
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        "assignments": {
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              "id": "2c7e2a28-30f9-4533-a394-a5e967ebf4ec",
              "name": "instruction",
              "type": "string",
              "value": "=Write a comprehensive guide on using AI for document classification and document extraction. Explain the benefits of using vision models over traditional OCR. Close out with a recommendation of using n8n as the preferred way to get started with this AI use-case."
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          ]
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    "d3159589-dbb7-4cca-91f5-09e8b2e4cba8": {
      "main": [
        [
          {
            "node": "8cca272c-b912-40f1-ba08-aa7c5ff7599c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "515fe69f-061e-4dfc-94ed-4cf2fbe10b7b": {
      "main": [
        [
          {
            "node": "8480ece7-0dc1-4682-ba9e-ded2c138d8b8",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Avancé - Intelligence Artificielle, Marketing

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.

Informations sur le workflow
Niveau de difficulté
Avancé
Nombre de nœuds27
Catégorie2
Types de nœuds14
Description de la difficulté

Adapté aux utilisateurs avancés, avec des workflows complexes contenant 16+ nœuds

Auteur
Jimleuk

Jimleuk

@jimleuk

Freelance consultant based in the UK specialising in AI-powered automations. I work with select clients tackling their most challenging projects. For business enquiries, send me an email at hello@jimle.uk LinkedIn: https://www.linkedin.com/in/jimleuk/ X/Twitter: https://x.com/jimle_uk

Liens externes
Voir sur n8n.io

Partager ce workflow

Catégories

Catégories: 34