PDF-Dokumentenassistent 2.0
Dies ist ein AI Summarization, Multimodal AI-Bereich Automatisierungsworkflow mit 18 Nodes. Hauptsächlich werden Code, Gmail, Webhook, GoogleSheets, Agent und andere Nodes verwendet. Verwenden Sie GPT und o4-mini, um Rechtsdokumente zu analysieren, und integrieren Sie Gmail und Google Sheets
- •Google-Konto + Gmail API-Anmeldedaten
- •HTTP Webhook-Endpunkt (wird von n8n automatisch generiert)
- •Google Sheets API-Anmeldedaten
- •OpenAI API Key
Verwendete Nodes (18)
Kategorie
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"name": "PDF Document Assistant 2.0",
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"text": "=You are an advanced AI document review assistant embedded in an automated workflow. A user has submitted a PDF for structured review. Your role is to help the user fully understand the document by performing a detailed, insightful analysis and delivering a polished, professional response via email.\n\nYour output should reflect **expert-level comprehension**, not surface-level summaries. Aim for **depth, precision, and clarity** throughout. Treat each section of the document as if preparing a report for a legal, compliance, or business-critical audience.\n\nYou are provided with:\n- Name: {{ $json.name }}\n- Email: {{ $json.email }}\n- Extracted PDF Text: {{ $json.full_summary }}\n- Name of File in Subject Title:\n\nYour response must be:\n- Addressed directly to the user (by name)\n- Professionally written and ready for email delivery\n- Fully structured, richly formatted, and highly detailed\n\n---\n\n## 🔍 Your Tasks:\n\n### 1. Identify and Classify the Document Type\n\nBegin with a short section titled **“Document Type”**.\n\n- Analyze the content, language, and structure to determine the specific type of document, such as: \n **contract**, **employment agreement**, **project proposal**, **policy document**, **business plan**, **financial report**, **technical manual**, etc.\n \n- Do **not** simply say \"Legal\" or \"Non-legal.\" Instead, **state the actual document category** and its apparent purpose.\n\n- If it is a legal document, explicitly state: \n > “This appears to be a legal document: [type]” \n and proceed to the legal clause analysis.\n\n- If it is not a legal document, still identify and state the exact type and purpose clearly. Example: \n > “This appears to be a business strategy document focused on product launch planning.”\n\nBe confident but not speculative — only classify based on what’s clearly supported by the content.\n\n\n---\n\n### 2. Chapter-by-Chapter Summary and Deep Analysis\n\nReview the document **in structured order**, chapter by chapter, section by section (or by major headings if chapters are not explicitly labeled).\n\nFor each chapter or major section:\n\n- Begin with a bold heading in this format: \n > **Chapter 1: [Section Title]**\n\n- Provide a **thorough multi-paragraph analysis** covering:\n - The **main ideas or arguments** expressed\n - Any **supporting evidence, examples, or rationale**\n - The **intent or strategic purpose** behind the section\n - How the section contributes to or supports the overall goals of the document\n\n- Expand on:\n - Any **assumptions**, **biases**, or **limitations** in the content\n - Key **stakeholders** referenced or implied\n - What the section **means for the reader** or decision-maker\n\n- Highlight any:\n - 🟨 Inconsistencies or contradictions\n - ⚠️ Risks or red flags (if applicable)\n - 💡 Strategic or operational insights\n\nApproach each section as if you are writing a standalone **mini-report** — not a surface-level summary. Provide context, clarity, and insight. Be analytical, not just descriptive.\n\n---\n\n### 3. If Legal, Perform Legal-Specific Review\n\nIf the document is legal in nature, begin this section with:\n\n> _“This appears to be a legal document.”_\n\nThen conduct a structured legal analysis with the following breakdown:\n\n---\n\n- 🧾 **Key Clauses** \n Identify and briefly explain the most important clauses, grouped by category where applicable:\n - **Parties & Scope**\n - **Rights and Responsibilities**\n - **Payment Terms**\n - **Termination & Exit Clauses**\n - **Liability & Indemnity**\n - **Confidentiality / IP Ownership**\n - Any other key legal mechanisms\n\n---\n\n- 🚩 **Red Flags or Areas of Concern** \n List any elements that could introduce risk, confusion, or legal exposure, such as:\n - Ambiguous or undefined terms\n - One-sided obligations or power imbalance\n - Vague or missing exit terms\n - Loopholes or conflicting provisions\n - Unusual penalty structures\n\n---\n\n- 🧠 **Inferred Conclusions** \n Based on the document’s tone, structure, and content:\n - What is the **true strategic purpose** or intent behind the document?\n - What risks, responsibilities, or long-term obligations are implied — even if not explicitly stated?\n - What **assumptions** does the document appear to make?\n - Is the document **balanced**, or does it favor one party? \n - If imbalanced, explain **how** and **in whose favor** (e.g., language favoring employer, vendor, landlord, etc.)\n - Does the document reflect a **standard template**, or something tailored and possibly aggressive?\n\nConclude this section with a brief opinion: \n> “Overall, this document appears [balanced/imbalanced], leaning in favor of [Party A/Party B], with [low/moderate/high] legal risk exposure based on the language and structure.”\n\n---\n\n### 4. If Not Legal, Provide Business/Contextual Insights\n\nIf the document is not legal in nature, continue with a detailed, chapter-by-chapter analysis.\n\nAlso extract and summarize the following:\n\n- 📌 **Actionable Insights** \n Identify any suggestions, decisions, or next steps the reader or organization should consider.\n\n- 📊 **Themes, Trends, or Conclusions** \n Highlight key messages, repeated patterns, overall direction, or stated conclusions.\n\n- 🔍 **Strategic Implications** \n What does the document imply about the organization’s goals, priorities, risks, or competitive position?\n\n- 🧱 **Operational Notes** \n Extract any timelines, deliverables, roles/responsibilities, or execution plans.\n\n- 💡 **Assumptions or Unspoken Context** \n Point out any implicit assumptions, missing data, or background context the reader should be aware of.\n\n- ❓ **Questions or Ambiguities** \n Identify unclear sections, vague terms, or places where clarification may be needed.\n\nThe goal is to help the user **understand not just what the document says, but what it means and why it matters.**\n\n---\n\n### 5. **Finish with a Professional Closing Message**\n- Thank the user by name\n- Inform them this analysis is automatically generated\n- Encourage follow-up review if the document is critical or sensitive\n\n---\n\n## 🧾 Tone & Format Guidelines:\n- Professional, helpful, and articulate\n- Use section headers, bullet points, and bold formatting to structure your output\n- Avoid legal speculation outside the text’s content\n- Write as though this is being sent to a C-suite executive, legal advisor, or stakeholder\n\n---\n\n## 📬 Final Output Format:\nOutput **only the email-style response** to the user. Do not include prompts, commentary, or instruction headers. Begin directly with content. Your structure should include the following:\n\n- **Document Type**\n- **Chapter-by-Chapter Summary**\n- **Key Clauses** (if legal)\n- **Red Flags / Observations**\n- **Inferred Conclusions**\n- **Recommendations / Next Steps**\n- **Professional Closing**\n- **Disclaimer**\n\n---\n\n### ⚠️ Include this disclaimer at the bottom of the email:\n\n> _Disclaimer: This review has been automatically generated by an AI document assistant. It is intended to provide insight and aid understanding, but does not constitute legal or professional advice. For high-stakes or binding decisions, we strongly recommend consulting with a qualified professional._\n\n\nNow begin your response.\n\n \n\n“You are responding via an HTML email using the Gmail node in n8n. Format all output in clean, professional HTML using:\n\n<strong> for bold.</strong>\"\n\n##this is an exact sample to use below##:\n\n<p>Dear {{ $json.name }},</p>\n\n<p>Thank you for submitting your document for analysis. Below is a detailed, AI-generated review based on the contents provided.</p>\n\n<p><strong>📘 Document Type:\n[Clearly state only what kind of document, e.g., contract, policy, NDA, report, etc.]\n</p>\n\n<p><strong>🧾 Chapter-by-Chapter Summary:</strong></p>\n<ul>\n <li><strong>Chapter 1: [Title]</strong><br>\n [Detailed explanation of this chapter’s contents, its intent, key ideas, implications, and how it fits the overall document.]</li>\n <li><strong>Chapter 2: [Title]</strong><br>\n [Continue same structure with depth, clarity, and professional interpretation.]</li>\n <!-- Add more chapters as needed -->\n</ul>\n\n<p><strong>📑 Key Clauses Identified:</strong></p>\n<ul>\n <li><strong>Confidentiality:</strong> [Summarize how confidential information is defined and protected]</li>\n <li><strong>Termination:</strong> [Conditions under which the agreement can be ended]</li>\n <li><strong>Liability:</strong> [Limits of responsibility and potential exposures]</li>\n <!-- Add more if relevant -->\n</ul>\n\n<p><strong>🚩 Red Flags or Areas of Concern:</strong></p>\n<ul>\n <li>[Example: Unilateral termination clauses that may favor one party disproportionately]</li>\n <li>[Example: Vague definitions that could create legal loopholes]</li>\n</ul>\n\n<p><strong>🧠 Inferred Conclusions:</strong></p>\n<ul>\n <li>This document is structured to legally formalize [insert purpose, e.g., a service relationship, IP transfer, etc.]</li>\n <li>Language suggests [potential drafting bias / strategic intent]</li>\n <li>The agreement may pose [insert type of risk: financial, legal, operational] due to [insert reasoning]</li>\n</ul>\n\n<p><strong>✅ Recommendations:</strong></p>\n<ul>\n <li>Consider having a legal expert review clauses marked as high-risk</li>\n <li>Seek clarification on any undefined or ambiguous terms before signing</li>\n <li>Ensure all business-critical terms (IP, termination, liability) align with your goals</li>\n</ul>\n\n<p>Best regards,<br>\n<strong>Swot AI - Your Smart PDF Assistant</strong></p>\n<p></p>\n<p style=\"margin-top: 1.5rem;\">\n <a href=\"mailto:swot.ai25@gmail.com\" style=\"background: #cb1b2c; color: white; padding: 0.6rem 1rem; text-decoration: none; border-radius: 6px; font-weight: bold;\">\n 💬 Want to leave a quick comment?\n </a>\n</p>\n\n<p></p>\n<p></p>\n\n<p style=\"font-size: 0.8rem; color: #555; line-height: 1.4; margin-top: 2rem;\">\n<em><strong>Disclaimer:</strong> This review was automatically generated by an AI document assistant. It is intended to provide insights and aid understanding but does not constitute legal or professional advice. For critical decisions or binding interpretations, we strongly recommend consulting with a qualified legal or subject matter expert.</em></p>\n",
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"parameters": {
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"__rl": true,
"mode": "list",
"value": "o4-mini-2025-04-16",
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"options": {}
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"id": "6eb4a414-e654-43ae-8193-e4935db5e5ba",
"name": "Gmail1",
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"webhookId": "9c995f46-1437-46a3-a156-9d08665a3010",
"parameters": {
"sendTo": "={{ $('Code1').item.json.email }}",
"message": "={{ $json.output }}",
"options": {
"senderName": "Swot AI",
"appendAttribution": false
},
"subject": "=Summary of your attached Document- {{ $('Code1').item.json.title }}"
},
"credentials": {
"gmailOAuth2": {
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"name": "Gmail account 3"
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"jsCode": "const chunkSize = 4000; // characters per chunk\n\nconst text = $input.first().json.text ?? \"\";\nconst name = $(\"Webhook\").first().json.body.name;\nconst email = $(\"Webhook\").first().json.body.email;\nconst title = $input.first().json.info.Title;\n\nconst chunks = [];\n\nfor (let i = 0; i < text.length; i += chunkSize) {\n chunks.push({\n chunk: text.slice(i, i + chunkSize),\n chunkIndex: i / chunkSize + 1,\n name,\n email,\n title,\n });\n}\n\nreturn chunks.map((c) => ({ json: c }));\n"
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"name": "Basic LLM Kette",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
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"parameters": {
"text": "=Summarize the following section of a document. Retain legal terms, obligations, or business meaning.\n\n{{ $json.chunk }}\n",
"batching": {},
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{
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"name": "Code1",
"type": "n8n-nodes-base.code",
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"parameters": {
"jsCode": "const summaries = items.map(item => item.json.text || item.json.output || item.json.chunk || \"\");\n\nreturn [{\n json: {\n full_summary: summaries.join(\"\\n\\n\"),\n name: $('Code').first().json.name,\n email: $('Code').first().json.email,\n title: $('Code').first().json.title\n }\n}];\n"
},
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{
"id": "1c4a2473-afaa-4e9b-844e-847eaa4f89ae",
"name": "Respond to Webhook-Trigger",
"type": "n8n-nodes-base.respondToWebhook",
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"parameters": {
"options": {
"responseCode": 302,
"responseHeaders": {
"entries": [
{
"name": "Content-Type",
"value": "text/html"
}
]
}
},
"redirectURL": "https://swot-ai25.github.io/pdf-document-assistant/success.html",
"respondWith": "redirect"
},
"typeVersion": 1.3
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{
"id": "a970c4d6-36f2-4387-93d3-1d52de3dcd2d",
"name": "Google Tabellen",
"type": "n8n-nodes-base.googleSheets",
"position": [
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],
"parameters": {
"columns": {
"value": {
"Date": "={{ $now.toFormat('dd-LL-yyyy') }}",
"Time": "={{ $now.toFormat('HH:mm') }}",
"Name ": "={{ $('Code1').item.json.name }}",
"Email ": "={{ $('Code1').item.json.email }}",
"Status": "={{ $json.labelIds[0] }}",
"Filename": "={{ $('Code1').item.json.title }}"
},
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{
"id": "Date",
"type": "string",
"display": true,
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{
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{
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"displayName": "Number of Pages",
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"id"
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"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/16eDhxjB3ZEpb9-zWaBxAX0z4xhsb-aQfTWqeGvQaNI0/edit#gid=0",
"cachedResultName": "Sheet1"
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"mode": "list",
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"cachedResultUrl": "https://docs.google.com/spreadsheets/d/16eDhxjB3ZEpb9-zWaBxAX0z4xhsb-aQfTWqeGvQaNI0/edit?usp=drivesdk",
"cachedResultName": "SwotAI_Users"
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"name": "Haftnotiz1",
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"parameters": {
"height": 380,
"content": "## Entry point — \n**receives uploaded PDF via POST request.** "
},
"typeVersion": 1
},
{
"id": "e3b6121a-45bb-44ae-9169-0dd4126ad675",
"name": "Haftnotiz2",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"width": 320,
"height": 320,
"content": "## 🟨 Code (pre-processing)\n**Clean/format the extracted text (remove line breaks, non-text content, etc.)**"
},
"typeVersion": 1
},
{
"id": "3f9a3e21-7d9a-48d3-b66a-c0f83159c0bb",
"name": "Haftnotiz",
"type": "n8n-nodes-base.stickyNote",
"position": [
600,
60
],
"parameters": {
"height": 560,
"content": "## 🟨 AI Agent\n****📌 Central intelligence. Handles prompts, memory, and reasoning.\n\n📌 Uses OpenAI Chat Model for deeper analysis.\n\n📌 Configurable to extract clauses, answer questions, or generate insights.** to edit me."
},
"typeVersion": 1
},
{
"id": "424540ff-40d1-4c75-9b84-35d5c5366e3e",
"name": "Haftnotiz3",
"type": "n8n-nodes-base.stickyNote",
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180,
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],
"parameters": {
"width": 300,
"height": 640,
"content": "## 🟨 Basic LLM Chain \n* First AI pass: summarization / restructuring of document content.*\n\n Connected to OpenAI Chat Model1 for text understanding.**"
},
"typeVersion": 1
},
{
"id": "2d1e46b9-f72a-40f7-87f5-1a3aaacd3db0",
"name": "Haftnotiz4",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"width": 380,
"height": 700,
"content": "##🟨 AI Agent\n\n**📌 Central intelligence. Handles prompts, memory, and reasoning.\n📌 Uses OpenAI Chat Model for deeper analysis.\n📌 Configurable to extract clauses, answer questions, or generate insights.** to edit me.\n"
},
"typeVersion": 1
},
{
"id": "62d5aae6-e7d0-41a6-98a1-0eb95aa89ac9",
"name": "Haftnotiz5",
"type": "n8n-nodes-base.stickyNote",
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-400,
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],
"parameters": {
"width": 400,
"height": 340,
"content": "## 🟨 Respond to Webhook\n\n**📌 Sends immediate acknowledgment back to the client after upload.** to edit me."
},
"typeVersion": 1
},
{
"id": "8643df4f-0146-4aac-9177-be2a69b370ed",
"name": "Haftnotiz6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1360,
120
],
"parameters": {
"width": 360,
"height": 460,
"content": "## 🟨 Gmail\n\n**📌 Sends formatted results to the user (summary, clauses, flagged risks, etc.).\n"
},
"typeVersion": 1
}
],
"active": true,
"pinData": {},
"settings": {
"callerPolicy": "workflowsFromSameOwner",
"executionOrder": "v1"
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"6eb4a414-e654-43ae-8193-e4935db5e5ba": {
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{
"node": "Google Sheets",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
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{
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"type": "main",
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"type": "main",
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},
"AI Agent": {
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"Basic LLM Chain": {
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{
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"cacbb1dc-cb5b-4d1f-b9ea-ce113a6e73f4": {
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[
{
"node": "d0541618-d148-4f89-9dd1-9576fe6102d0",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
}
}
}Wie verwende ich diesen Workflow?
Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.
Für welche Szenarien ist dieser Workflow geeignet?
Experte - KI-Zusammenfassung, Multimodales KI
Ist es kostenpflichtig?
Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.
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Swot.AI
@swotaiAutomation consultant with over 5 years experience helping Individuals and teams to streamline their processes. Use my link to book an initial consultation for custom n8n work.
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