# templates

name: Auto-Cleanup of Cloudflare R2 Files Older Than 2 Weeks (+ Telegram Notifications)
author_name: Mobder
author_username: mobder
categories: []
created_at: 2025-05-27T05:38:36.173Z
updated_at: 2025-05-27T05:38:36.173Z
url: https://n8n.io/workflows/4418
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow automatically connects to a Cloudflare R2 bucket (via S3-compatible API), filters out files older than 14 days, deletes them, and then sends a Telegram notification for each deletion. It runs on a daily schedule.

  🕘 Schedule Trigger
  Executes the workflow once a day at a specified hour (e.g., 9 AM).

  📦 S3 Node – List Files
  Retrieves all objects from a specific folder (prefix) in a Cloudflare R2 bucket using the S3 API.

  🔎 Code Node – Filter Files Older Than 2 Weeks
  Filters the retrieved files by comparing their LastModified timestamps to the current date. Files older than 14 days (2 weeks) are selected for deletion.

  🗑️ S3 Node – Delete File
  Deletes each filtered file from the R2 bucket.

  📨 Telegram Node – Notify Deletion
  Sends a Telegram message with the name of the deleted file to a specified chat ID. The message includes:

nodes_used:
  ["n8n-nodes-base.s3","n8n-nodes-base.code","n8n-nodes-base.s3","n8n-nodes-base.telegram","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","cloud storage management","data retention"],"complexity":"medium","use_cases":["Automatic cleanup of stale files in object storage","Cost control by removing old objects","Enforcing retention policies","Sending deletion notifications for audit/tracking"],"estimated_setup_minutes":15,"required_services":["Cloudflare R2 (S3-compatible API)","Telegram Bot / Telegram API"],"key_features":["Daily scheduled execution","List objects in an R2 bucket/prefix via S3 API","Filter objects by LastModified > 14 days","Delete filtered objects from the bucket","Send per-deletion Telegram notifications with filename"],"target_audience":["DevOps engineers","Cloud/storage administrators","Site reliability engineers (SREs)"]}


name: Generate LinkedIn Posts with GPT-4, Preview on WhatsApp, and Auto-Publish
author_name: papcy
author_username: papcy
categories: []
created_at: 2025-05-27T06:33:16.319Z
updated_at: 2025-05-27T06:33:16.319Z
url: https://n8n.io/workflows/4419
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  # Workflow Overview
  Transform your LinkedIn presence with this powerful AI-driven automation workflow that generates and posts high-quality thought leadership content automatically. 

  Let this AI Agent, generate content for you, sends it to your whatsapp for you to review and if its ok Approve and it will post! if you don't like it, Decline and it will regenerate another and send again for preview and approval.

  Stage 1: Automated Content Scheduling

  Schedule Trigger runs every 6 hours (customizable)
  Topic Selection randomly chooses 3 AI-related topics from a predefined list
  Ensures fresh, varied content for each generation cycle

  Stage 2: AI Content Generation

  GPT-4 Integration creates unique LinkedIn posts using structured prompts
  Content Format: Hook → Problem/Opportunity → Insight → Strategic Takeaway → CTA
  Output: 300-word maximum posts with 3-5 relevant hashtags
  Uniqueness: Each post is completely original and industry-specific

  Stage 3: Content Processing & Formatting

  JSON Parsing extracts title, body, and hashtags from AI response
  Error Handling includes fallback mechanisms for robust operation
  LinkedIn Formatting prepares content for optimal platform display

  Stage 4: Preview & Approval System

  WhatsApp Integration sends generated content to your phone for review
  Approval Gateway waits for your decision (approve/decline)
  Quality Control ensures only approved content reaches your LinkedIn profile

  Stage 5: Automated Publishing

  LinkedIn API posts approved content automatically
  Success Notifications confirm successful publishing via WhatsApp
  Professional Formatting includes proper spacing and emoji structure

  Stage 6: Smart Restart System

  Decline Handling automatically generates new content if declined
  Continuous Operation ensures consistent content flow
  Tracking Notifications keep you informed of all workflow activities

  Prerequisites & Required Credentials
  Essential API Credentials

  OpenAI API Key (for GPT-4 content generation)
  WhatsApp Business API credentials and phone number ID
  LinkedIn Developer Account with API access
  n8n Cloud or Self-hosted instance

  Technical Requirements

  Active LinkedIn Business profile
  WhatsApp Business account
  Basic understanding of n8n workflow management

  Step-by-Step Setup Instructions
  Configure OpenAI Integration

  Add your OpenAI API key to the "OpenAI GPT-4 Model" node
  Ensure GPT-4 access is enabled on your OpenAI account
  Test connection before proceeding

  2. Setup WhatsApp Business API

  Obtain WhatsApp Business API credentials from Meta
  Configure phone number ID in all WhatsApp nodes
  Replace "YOUR_PHONE_NUMBER" with your actual number
  Test message delivery

  3. Connect LinkedIn Account

  Set up LinkedIn Developer App
  Obtain your LinkedIn Person ID
  Configure OAuth authentication
  Test posting permissions

  4. Customize Content Topics

  Edit the "Prepare Search Topics" function node
  Modify the searchTerms array for your industry
  Add relevant AI topics for your niche
  Save and test topic randomization

  5. Adjust Posting Schedule

  Modify the "Schedule Trigger" node
  Change interval from 6 hours to your preferred timing
  Consider your audience's active hours
  Enable the trigger to start automation

  Customization Options
  Content Personalization

  Industry Focus: Modify AI topics in the search terms array
  Writing Style: Adjust the system prompt in "AI Content Generator"
  Post Length: Customize maximum word count (default: 300 words)
  Hashtag Strategy: Modify hashtag generation rules

  Workflow Timing

  Posting Frequency: Adjust schedule trigger interval
  Approval Timeout: Configure WhatsApp wait duration
  Retry Logic: Customize restart behavior for declined content

  Notification Preferences

  WhatsApp Templates: Customize approval and notification messages
  Success Tracking: Modify confirmation message content
  Error Handling: Adjust failure notification settings

  **Business Benefits
  Time Savings
  **
  10+ Hours Weekly: Eliminate manual content creation and posting
  Consistent Presence: Maintain regular LinkedIn activity automatically
  Quality Control: Review and approve all content before publishing

  Lead Generation Impact

  Thought Leadership: Position yourself as an AI industry expert
  Engagement Growth: High-quality content drives more interactions
  Network Expansion: Consistent posting attracts relevant connections
  Authority Building: Regular insights establish professional credibility

  ROI Expectations

  Monthly Investment: $10-20 in API costs
  Setup Time: 15 minutes initial configuration
  Long-term Value: Increased visibility, leads, and business opportunities

  **Troubleshooting & Support
  Common Issues**

  API Rate Limits: Monitor usage and upgrade plans if needed
  Content Quality: Adjust prompts for better AI output
  Approval Delays: Check WhatsApp connectivity and permissions

  Optimization Tips

  Topic Rotation: Regularly update search terms for fresh content
  Performance Monitoring: Track engagement metrics on posted content
  Prompt Refinement: Continuously improve AI generation prompts

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.function","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.linkedIn","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.executeWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","social media","content generation","integration","marketing"],"complexity":"complex","use_cases":["Automated LinkedIn post generation","Content preview & approval via WhatsApp","Scheduled social media publishing","Thought leadership and lead generation","A/B content regeneration on decline"],"estimated_setup_minutes":15,"required_services":["OpenAI (GPT-4) API","WhatsApp Business API (Meta) with phone number ID","LinkedIn Developer API (LinkedIn Person/App credentials)","n8n Cloud or self-hosted instance"],"key_features":["Scheduled topic-driven GPT-4 content generation (Hook → Problem → Insight → Takeaway → CTA)","WhatsApp preview & approval gateway (approve/decline flow)","Automated LinkedIn posting on approval","Decline handling with regeneration loop","JSON parsing and formatting, LinkedIn-optimized output and hashtags (3–5) up to 300 words','Error handling, retry logic and notifications via WhatsApp"],"target_audience":["Social media managers","Content marketers","Founders and executives wanting automated presence on LinkedIn','Agencies and growth teams','n8n users/automation engineers"]}


name: Automated Daily Outlook Calendar Meeting Digest
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-27T06:47:50.602Z
updated_at: 2025-05-27T06:47:50.602Z
url: https://n8n.io/workflows/4420
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automated Daily Outlook Calendar Meeting Digest

  Overall Goal
  This workflow automatically runs at a scheduled time (daily at 8 AM by default), calculates the current day's date range, fetches all calendar events from a specified Microsoft Outlook account for that day, formats these events into a user-friendly HTML email, and then sends this digest to a designated email address.

  How it Works (Step-by-Step Breakdown):

  Node: Schedule Trigger (Schedule Trigger Node)
  Type:** n8n-nodes-base.scheduleTrigger  
  Purpose:** Automatically starts the workflow at a predefined time.  
  Configuration:**  
    Rule &gt; Interval &gt; Trigger At Hour: 8  
      (Triggers every day at 8:00 AM according to the n8n server's timezone)  
  Output:** Triggers the workflow execution at the scheduled time.

  Node: Code (Code Node)
  Type:** n8n-nodes-base.code  
  Purpose:** Dynamically calculates the start and end timestamps for "today," based on when the workflow is triggered.  
  Configuration (JS Code):**  
    Gets the current date and time (workflow runtime).  
    Sets today to beginning of current day (00:00:00).  
    Sets tomorrow to beginning of next day (00:00:00).  
    Converts these to ISO string format (e.g., 2023-10-27T00:00:00Z).  
  Output:** JSON object with today and tomorrow ISO date strings.

  Node: Microsoft Outlook (Microsoft Outlook Node)
  Type:** n8n-nodes-base.microsoftOutlook  
  Purpose:** Fetch calendar events from Outlook within the calculated date range.  
  Configuration:**  
    Resource: Event  
    Filters (Custom):  
          start/dateTime ge '{{$json.today}}' and start/dateTime lt '{{$json.tomorrow}}'
        (OData filter to fetch events starting on or after today and before tomorrow, i.e., all today's events.)  
  Output:** List of event objects from Outlook.

  Node: Edit Fields (Set Node)
  Type:** n8n-nodes-base.set  
  Purpose:** Transform and simplify the event data structure from Outlook.  
  Configuration:** Maps fields from Outlook event to new field names:  
    id  
    subject  
    description (from bodyPreview)  
    meeting_start  
    meeting_end  
    attendees  
    meeting_organizer  
    meeting_organizer_email  
    meeting_link  
  Output:** List of JSON objects with simplified meeting details.

  Node: Generate HTML (Code Node)
  Type:** n8n-nodes-base.code  
  Purpose:** Generate a single HTML email body summarizing all meetings and create the email subject line.  
  Configuration (JS Code):**  
    Processes all meeting items from "Edit Fields" node.  
    Defines generateMeetingReminderEmail function to format each meeting into an HTML "card."  
    Escapes HTML special characters, formats times, attendees, etc.  
    Concatenates all cards into a full HTML document.  
    Generates subject line (e.g., "🗓️ Your Meetings Today – Friday, Oct 27").  
  Output:** JSON object with:  
      {
      "subject": "email subject string",
      "html": "generated HTML content string"
    }
  Node: Send Email (Email Send Node)
  Type:** n8n-nodes-base.emailSend  
  Purpose:** Send the generated HTML digest email to the designated recipient.  
  Configuration:**  
    From Email: test@gmail.com  
    To Email: akhilgadiraju@gmail.com  
    Subject: {{ $json.subject }} (dynamic from Generate HTML node)  
    HTML: {{ $json.html }} (dynamic from Generate HTML node)  
  Output:** Email sending status.

  Sticky Notes
  Update Time:** Near "Schedule Trigger" node; configure trigger time as needed.  
  Update Email Details:** Near "Send Email" node; change sender and receiver email addresses.

  How to Customize It

  Schedule (Schedule Trigger node):**  
    Modify the trigger hour, minutes, or days of week to change when the workflow runs.

  Date Range (Code node):**  
    Adjust JS to change date range (e.g., next business day, upcoming week).

  Outlook Calendar (Microsoft Outlook node):**  
    Specify Calendar ID or refine OData filters for event selection.

  Event Details (Edit Fields node):**  
    Add/remove/modify event fields extracted.

  Email Appearance and Content (Generate HTML node):**  
    Change CSS styling, meeting details, or subject line logic.

  No Meetings Scenario:**  
    Use an "If" node after "Edit Fields" to handle no-meeting days (e.g., send "No meetings today!" email or skip email).

  Email Recipients (Send Email node):**  
    Update "From" and "To" emails; multiple recipients separated by commas.

  Error Handling
  Use "Error Trigger" nodes to catch and handle failures (Outlook API, SMTP errors).
  Send alerts or log errors accordingly.

  Use Cases
  Automated Daily Personal Meeting Briefing:** Get daily email summaries of your meetings.  
  Automated Team Meeting Digest:** Send daily team calendar digest emails.  
  Proactive Daily Planning:** Automatically stay informed of your day’s schedule.

  Required Credentials

  Add these credentials in your n8n instance under Credentials:

  Microsoft Outlook (OAuth2 API):**  
    Used by: "Microsoft Outlook" node  
    Credential Name in Workflow: Outlook (ID: JcYqVJwcwZIhB8oy)  
    Requires OAuth2 with Calendars.Read permission.

  SMTP:**  
    Used by: "Send Email" node  
    Credential Name in Workflow: SMTP account (ID: vCexcphurglwGBfk)  
    Requires SMTP server details (host, port, username, password).

  Ensure these credentials are configured correctly with required permissions. Activate the workflow for scheduled execution.

  Made with ❤️ using n8n by Akhil.

nodes_used:
  ["n8n-nodes-base.microsoftOutlook","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.emailSend","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","calendar integration","notifications","productivity","email"],"complexity":"medium","use_cases":["Daily personal meeting digest","Team/organization daily calendar summary","Proactive daily planning and reminders","Calendar monitoring and alerts (no-meetings handling)"],"estimated_setup_minutes":20,"required_services":["Microsoft Outlook / Office365 Calendar (OAuth2, Calendars.Read)","SMTP email provider (Gmail, company SMTP, etc.)","n8n instance/server"],"key_features":["Scheduled daily trigger (configurable time)","Calculates today’s date range dynamically","Fetches events from Outlook using OData filters","Transforms and simplifies event data","Generates a styled HTML email summary and subject line dynamically (via code)"],"target_audience":["Individual professionals who want a daily meeting briefing","Team leads and managers sending team digests","Operations or admins automating calendar notifications and reports"]}


name: Evaluations Metric: Answer Similarity
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:15:17.213Z
updated_at: 2025-05-27T07:15:17.213Z
url: https://n8n.io/workflows/4423
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n template demonstrates how to calculate the evaluation metric "Similarity" which in this scenario, measures the consistency of the agent.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_similarity.py

  How it works
  This evaluation works best where questions are close-ended or about facts where the answer can have little to no deviation.
  For our scoring, we generate embeddings for both the AI's response and ground truth and calculate the cosine similarity between them.
  A high score indicates LLM consistency with expected results whereas a low score could signal model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 4756 characters]

metadata_json:
  {"categories":["evaluation","model monitoring","data processing","automation","AI/ML"],"complexity":"medium","use_cases":["Assess LLM answer consistency against ground truth","Detect hallucinations or large deviations in model outputs","Automated QA for close-ended factual questions","Batch scoring of responses using embeddings and cosine similarity","Integrate evaluation results into spreadsheets or pipelines"],"estimated_setup_minutes":25,"required_services":["OpenAI (or another embeddings-capable LLM provider)","Google Sheets (optional sample data)","n8n (v1.94+)","HTTP/Webhook endpoint (optional, for integrations)"],"key_features":["Generates embeddings for model responses and ground truth","Calculates cosine similarity as 'answer similarity' score","Based on RAGAS answer similarity metric","Supports batch scoring and aggregation","Integrates with Google Sheets and webhooks for input/output"],"target_audience":["ML engineers","MLOps practitioners","Data scientists/analysts validating LLMs"]}


name: Evaluate AI Agent Response Correctness with OpenAI and RAGAS Methodology
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:18:12.776Z
updated_at: 2025-05-27T07:18:12.776Z
url: https://n8n.io/workflows/4424
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n template demonstrates how to calculate the evaluation metric "Correctness" which in this scenario, measures the compares and classifies the agent's response against a set of ground truths.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py

  How it works
  This evaluation works best where the agent's response is allowed to be more verbose and conversational.
  For our scoring, we classify the agent's response into 3 buckets: True Positive (in answer and ground truth), False Positive (in answer but not ground truth) and False Negative (not in answer but in ground truth).
  We also calculate an average similarity score on the agent's response against all ground truths.
  The classification and the similarity score is then averaged to give the final score. 
  A high score indicates the agent is accurate whereas a low score could indicate the agent has incorrect training data or is not providing a comprehensive enough answer.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 7120 characters]

metadata_json:
  {"categories":["evaluation","AI/ML","integration","monitoring"],"complexity":"medium","use_cases":["Automated correctness scoring of LLM/agent responses","Model benchmarking and validation against ground-truths","Regression monitoring for assistant accuracy","QA workflows for conversational agents","Dataset labeling or verification with multiple ground truths"],"estimated_setup_minutes":45,"required_services":["OpenAI (Chat/Completions API)","Google Sheets (optional sample data)","n8n v1.94+ (self-hosted or cloud instance)"],"key_features":["Implements RAGAS-inspired correctness metric (TP/FP/FN classification)","Computes average semantic similarity across multiple ground truths","Combines classification and similarity into a final correctness score","Supports verbose/conversational agent responses","Integrates OpenAI via lmChatOpenAi node and uses evaluation/code nodes in n8n"],"target_audience":["ML engineers","AI researchers","QA/test engineers for AI products"]}


name: Evaluate AI Agent Response Relevance using OpenAI and Cosine Similarity
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:19:50.908Z
updated_at: 2025-05-27T07:19:50.908Z
url: https://n8n.io/workflows/4425
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n template demonstrates how to calculate the evaluation metric "Relevance" which in this scenario, measures the relevance of the agent's response to the user's question.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here 
  https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_relevance.py

  How it works
  This evaluation works best for Q&A agents.
  For our scoring, we analyse the agent's response and ask another AI to generate a question from it. This generated question is then compared to the original question using cosine similarity.
  A high score indicates relevance and the agent's successful ability to answer the question whereas a low score means agent may have added too much irrelevant info, went off script or hallucinated.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set"]

workflow_json_compressed:
  [encoded data, 4952 characters]

metadata_json:
  {"categories":["AI evaluation","automation","data processing","QA/testing"],"complexity":"medium","use_cases":["Evaluate relevance of AI/chat agent responses to user questions","Automated scoring for conversational QA agents","Model comparison and benchmarking","Monitoring and regression testing of agent behavior","Data-driven model improvement (identify hallucinations or off-topic answers)"],"estimated_setup_minutes":20,"required_services":["OpenAI (API access for lmChatOpenAi nodes)","Google Sheets (optional — sample data)","n8n v1.94+"],"key_features":["Generates a question from the agent's response using an LLM","Computes cosine similarity between original question and generated question","Outputs a relevance score for the agent response","Configurable within n8n using Set/Code and evaluation nodes","Based on RAGAS-style relevance metric"],"target_audience":["ML engineers","AI/ML researchers","QA engineers / test automation engineers testing conversational agents"]}


name: Evaluate RAG Response Accuracy with OpenAI: Document Groundedness Metric
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:21:41.587Z
updated_at: 2025-05-27T07:21:41.587Z
url: https://n8n.io/workflows/4426
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n template demonstrates how to calculate the evaluation metric "RAG document groundedness" which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents.

  The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness

  How it works
  This evaluation works best for an agent that requires document retrieval from a vector store or similar source.
  For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to assess if the former is based off the latter.
  A key factor is to look out information in the response which is not mentioned in the documents.
  A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.vectorStoreInMemory","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.vectorStoreInMemory","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6288 characters]

metadata_json:
  {"categories":["evaluation","AI/ML","RAG (retrieval-augmented generation)","monitoring"],"complexity":"medium","use_cases":["Measure RAG document groundedness","Evaluate LLM adherence to retrieved documents","Detect hallucinations in agent responses","Tune retrieval/prompting for RAG systems","Batch evaluation from spreadsheet or webhook inputs"],"estimated_setup_minutes":30,"required_services":["n8n v1.94+","OpenAI API (chat + embeddings)","Optional: Google Sheets (sample data)","Optional: HTTP/Webhooks endpoint"],"key_features":["Computes pointwise groundedness metric comparing agent response vs retrieved docs","Uses embeddings + in-memory vector store for retrieval","Leverages OpenAI chat model to score groundedness","Processes batch inputs (Google Sheet or webhook)","Visual workflow with evaluation and logging nodes"],"target_audience":["ML engineers","Data scientists","MLOps engineers / AI ops teams','Developers building RAG systems"]}


name: Evaluation Metric: Summarization
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T08:04:21.316Z
updated_at: 2025-05-27T08:04:21.316Z
url: https://n8n.io/workflows/4428
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n template demonstrates how to calculate the evaluation metric "Summarization" which in this scenario, measures the LLM's accuracy and faithfulness in producing summaries which are based on an incoming Youtube transcript.

  The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_summarization_quality

  How it works
  This evaluation works best for an AI summarization workflows.
  For our scoring, we simple compare the generated response to the original transcript.
  A key factor is to look out information in the response which is not mentioned in the documents.
  A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["n8n-nodes-base.evaluation","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.extractFromFile","n8n-nodes-base.webhook","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5248 characters]

metadata_json:
  {"categories":["evaluation","AI/ML","integration","data processing"],"complexity":"medium","use_cases":["Automated evaluation of LLM-generated summaries","Detecting hallucinations and unsupported information in summaries","Monitoring and comparing model/ prompt performance for summarization","Batch scoring of YouTube transcript summaries","Preparing evaluation reports for model tuning"],"estimated_setup_minutes":25,"required_services":["YouTube (transcripts)","Google Drive","Google Sheets (sample data)","OpenAI API (lmChatOpenAi)","Google Gemini / Vertex AI (lmChatGoogleGemini)","n8n version 1.94+"],"key_features":["Pointwise summarization-quality scoring adapted from Vertex AI templates","Compares generated summaries against original YouTube transcripts","Flags information not present in source (hallucination detection)","Supports multiple LLMs (OpenAI, Google Gemini)","Integrates with Google Drive/Sheets and webhooks for input/output handling and logging','Structured output parsing and evaluation nodes for score extraction"],"target_audience":["ML engineers","AI researchers","Developers building summarization workflows or pipelines」「Data scientists evaluating model outputs」「Product managers tracking model quality"]}


name: Notion AI Summary & Tags
author_name: Parnain
author_username: parnian
categories: []
created_at: 2025-05-27T09:28:44.293Z
updated_at: 2025-05-27T09:28:44.293Z
url: https://n8n.io/workflows/4431
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  What This Workflow Does:

  This n8n workflow automatically generates an AI-powered summary and relevant tags whenever a new row is added to your Notion database. 

  Simply save any URL to your Notion database using the [Notion Web Clipper] Chrome extension or [Save to Notion]—on both desktop and mobile. 

  This keeps all your saved content organized in one place instead of scattered across different platforms.

  How it works:

  The workflow is triggered when a new row is added to your Notion database (it checks for updates every minute).

  It retrieves the content from the saved URL.

  An AI agent analyzes the content to generate a summary and relevant tags.

  The AI output is then formatted properly.

  Finally, the formatted summary and tags are saved into the appropriate columns in your Notion database.


  Notes:

  Make sure your Notion database includes the following columns:

  URL – Stores the content URL you want to summarize.

  AI Summary – Where the AI-generated summary will be added.

  Tags – Where the AI-generated tags will be saved.

nodes_used:
  ["n8n-nodes-base.notionTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.notion"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","content summarization","productivity"],"complexity":"medium","use_cases":["Automatically summarize saved web pages","Generate AI tags for saved content","Centralize bookmarks and research notes","Content curation and knowledge management"],"estimated_setup_minutes":10,"required_services":["Notion (API access)","OpenAI (lmChat/OpenAI API or compatible LLM)","Public web access to fetch URL content (HTTP)","Optional: Notion Web Clipper / Save to Notion browser/mobile extension"],"key_features":["Triggers on new Notion rows","Fetches content from saved URLs","AI-powered summary generation","AI-generated relevant tags","Formats AI output and updates Notion columns automatically"],"target_audience":["knowledge workers","researchers","content curators and marketers`,`product managers and growth teams`,`developers automating workflows"]}


name: Generate Content Ideas with Gemini Pro and Store in Google Sheets
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-05-27T09:44:11.274Z
updated_at: 2025-05-27T09:44:11.274Z
url: https://n8n.io/workflows/4432
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automated Content Idea Generation and Expansion with Google Gemini and Google Sheets

  This n8n workflow automates the process of generating content ideas based on a user-defined topic, then expands each idea into a more detailed content piece (like a blog post) using Google Gemini, and finally saves all the generated data (idea title, description, and full content) into a Google Sheet. It's a powerful tool for streamlining content creation workflows.

  This workflow includes:
  Generation of multiple content ideas from a single topic.
  Expansion of each idea into detailed content using AI.
  Storage of ideas and generated content in a structured Google Sheet.
  Sticky Notes within the workflow for inline documentation and setup guidance.

  Prerequisites

  n8n Instance: You need a running n8n instance (self-hosted or cloud).
  Google AI Account: Access to Google AI (Gemini). You will need an API key.
  Google Account: Access to Google Sheets. You will need to create or use an existing spreadsheet with specific column headers.

  Installation and Setup

  Import the Workflow:
      Copy the entire JSON code provided.
      In your n8n instance, go to "Workflows".
      Click "New" -&gt; "Import from JSON".
      Paste the JSON code and click "Import".

  Configure Credentials:
      Google AI (Gemini):
          Find the "Google Gemini Chat Model for Content Idea Generator" node and the "Google Gemini Chat Model for Content Generation" node.
          Click on the "Credentials" field in both nodes (it will likely show a placeholder name like "Google Gemini(PaLM) Api account").
          Click "Create New".
          Select "Google AI API".
          Enter your Google AI API Key.
          Save the credential. (You can reuse the same credential for both nodes).
      Google Sheets:
          Find the "Google Sheets" node.
          Click on the "Credentials" field (it will likely show a placeholder name like "Google Sheets account").
          Click "Create New".
          Select "Google Sheets OAuth2 API".
          Follow the steps to connect your Google Account and grant n8n access to Google Sheets.
          Save the credential.

  Configure Google Sheets Node:
      Open the "Google Sheets" node settings.
      Spreadsheet ID: Replace the placeholder value with the actual ID of your Google Sheet. You can find the Spreadsheet ID in the URL of your Google Sheet (it's the long string of characters between /d/ and /edit).
      Sheet Name: Select or enter the name or GID of the sheet within your spreadsheet where you want to save the data (e.g., Sheet1 or gid=0).
      Columns: Ensure your Google Sheet has columns named title, description, and content. The node is configured to map the generated data to these specific column headers.
      Save the node settings.

  Review Sticky Notes:
      Look at the Sticky Notes placed around the workflow canvas. They provide helpful context and reminders for setup, required Google Sheet columns, and the AI models used.

  How to Use

  Activate the Workflow: Toggle the workflow switch to "Active".
  Trigger the Workflow:
      Since this workflow uses a "When clicking ‘Execute workflow’" node as the trigger, you can run it directly from the n8n editor.
      Click the "Execute Workflow" button.
      The workflow will start automatically.
  Set the Topic:
      Open the "Set the input fields" node.
      Modify the topic value to the subject you want to generate content ideas about.
      Save the node settings.
  Monitor Execution: Watch the workflow execute. The nodes will light up as they process. The "Loop Over Items" node will show multiple executions as it processes each generated idea.
  Check Results:
      The generated content ideas (title, description) and the expanded content will be written as new rows in the Google Sheet you configured. Each row will correspond to one generated idea and its content.

  This workflow provides a robust starting point for AI-assisted content creation. You can customize the AI prompts in the "Content Idea Generator" and "LLM Content Generator" nodes to refine the output style and format, or integrate additional steps like sending notifications or further processing the generated content.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","content creation","AI/ML","integration"],"complexity":"medium","use_cases":["Generate content ideas from a single topic","Expand ideas into full articles/blog posts","Build content briefs and descriptions","Populate a Google Sheet for editorial planning","Rapid prototyping of content at scale"],"estimated_setup_minutes":20,"required_services":["n8n instance (self-hosted or cloud)","Google AI (Gemini) API / Google AI account and API key","Google Sheets (Google account with OAuth2 access)"],"key_features":["Generate multiple content ideas from one topic","Use Google Gemini to expand each idea into full content","Write title, description, and expanded content into a structured Google Sheet","Batch/loop processing of ideas","Inline sticky notes for setup guidance and prompts customization"],"target_audience":["content marketers","bloggers and writers","social media managers and marketers','SEO specialists"]}


name: Promote YouTube Videos on Reddit with AI-Generated Comments and Email Digest
author_name: Ari Nakos
author_username: just-aristides
categories: []
created_at: 2025-05-27T13:13:34.068Z
updated_at: 2025-05-27T13:13:34.068Z
url: https://n8n.io/workflows/4433
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Motivation

  Are you a small YT channel looking to grow to 1000 subs ?
  This workflow has helped me grow to 80 subs via Reddit Marketing. 
  Check out the YT Tutorial.

  What it is

  This n8n workflow automates the process of promoting your YouTube videos on Reddit. It identifies relevant Reddit posts, generates humanized comments tailored to your video content, and delivers a weekly digest of opportunities directly to your inbox.

  How It Works

  A user submits their YouTube video URL and email through a form.

  The workflow analyzes the YouTube video's title, description, and tags to extract relevant keywords and create a custom AI classification prompt.

  It searches Reddit for posts containing those keywords and filters them based on engagement metrics

  upvotes &gt; 15
  non-empty text content
  posted within the last 14 days
  upvote ratio &gt; 0.95

  An AI agent (using OpenRouter&apos;s GPT-4.1-mini) classifies each filtered Reddit post to determine its relevance to your YouTube video.

  For relevant posts, another AI agent (using OpenRouter&apos;s Gemini-2.0-flash-lite-001) generates a humanized, authentic comment designed to subtly reference your video and add value to the Reddit discussion.

  Relevant posts and their proposed comments are stored in Google Sheets.

  A professional HTML email digest is generated, summarizing the marketing opportunities.

  The email is sent to the user's provided email address.

  Setup

  To run this workflow, you need to set up credentials in n8n for:

  YouTube: Uses OAuth 2.0. Connect by authenticating your YouTube account.
  Reddit: Uses OAuth 2.0. Requires creating an app on Reddit to get a Client ID & Secret. (YT Tutorial)
  OpenRouter: Generate API key from your OpenRouter account. (YT Tutorial)
  Google Sheets: Recommend OAuth2 - just connect by authenticating.
  Gmail: Recommend OAuth 2.0. like Google Sheets

  n8n account setup

  If you do not have a n8n account, follow the YT Tutorial to get started.

nodes_used:
  ["n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.removeDuplicates","n8n-nodes-base.formTrigger","n8n-nodes-base.if","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.reddit","n8n-nodes-base.youTube","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.if","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","marketing","integration"],"complexity":"complex","use_cases":["Promote YouTube videos on Reddit","Automated Reddit outreach","Generate humanized AI comments for community engagement","Weekly opportunity digest via email","Content discoverability and growth hacking"],"estimated_setup_minutes":45,"required_services":["YouTube API (OAuth)","Reddit API (OAuth)","OpenRouter (GPT-4.1-mini / Gemini models)","Google Sheets (OAuth)","Gmail (OAuth)","n8n account/hosting"],"key_features":["Extracts keywords from YouTube title/description/tags","Searches and filters Reddit posts by engagement (upvotes, ratio, recency, non-empty text)","AI classification of post relevance","AI-generated humanized comments tailored to the video","Stores opportunities and comments in Google Sheets with deduplication logic」「Generates professional HTML weekly email digest and sends via Gmail」「User-submitted form for video URL + email"],"target_audience":["Small YouTube creators/growth hackers","Community managers and marketers","Content creators looking to scale outreach via Reddit"]}


name: Automated Invoice Processing System with OCR & AI - AP Automation with Airtable
author_name: Milan Vasarhelyi - SmoothWork
author_username: vasarmilan
categories: []
created_at: 2025-05-27T13:54:23.596Z
updated_at: 2025-05-27T13:54:23.596Z
url: https://n8n.io/workflows/4434
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Video Introduction

  Invoice Processing Automation

  This template is the automation behind a simple incoming invoice automation tool (AP automation) tool built in Airtable.

  Link to the Airtable base, and all other tools used, is in notes on the left of the automation.

  How it works
  See how it works on video: Full Video Walkthrough

  1) We get an email with an invoice attachment:


  2) Processes and adds the data to an Airtable interface: 

  3) Once we approved it and Due date approaches, it shows among Due invoices, where we can track if it's paid.

  Looking for customization or a custom business app? 📞 Book a Call | 💬 DM me on Linkedin

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.merge","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.informationExtractor","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.merge","n8n-nodes-base.airtable","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 7712 characters]

metadata_json:
  {"categories":["automation","data processing","document processing","finance","integration"],"complexity":"medium","use_cases":["Accounts payable (AP) invoice ingestion and data extraction","Automated invoice entry into Airtable or other databases","Invoice approval workflow and status tracking","Due-date based reminders and payment tracking","Vendor invoice auditing and basic validation using AI"],"estimated_setup_minutes":45,"required_services":["Airtable (base + interface)","Email provider (Gmail / Outlook / IMAP) for incoming invoices","OpenAI or another LLM provider (lmOpenAi / openAi nodes)","OCR capability (built-in AI/ML node or external OCR API)","HTTP/Webhooks endpoint (for integrations or inbound triggers)","Optional: Slack/Teams/email for notifications"],"key_features":["Ingest invoices from incoming email attachments","OCR + AI extraction of invoice fields (vendor, amounts, due date, line items)","Structured parsing with outputParserStructured for reliable data mapping","Automatic creation/updating of records in an Airtable interface","Approval step and due-invoice views for tracking payment status and reminders"],"target_audience":["Finance / Accounts Payable teams","Small & medium business owners","Operations managers who handle vendor bills/payments"]}


name: Analyze BeyondPresence Video Calls with GPT-4o-mini and Google Sheets
author_name: M Shehroz Sajjad
author_username: mshehrozsajjad
categories: []
created_at: 2025-05-27T14:28:15.263Z
updated_at: 2025-05-27T14:28:15.263Z
url: https://n8n.io/workflows/4436
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Transform your BeyondPresence video agent conversations into comprehensive insights by automatically analyzing each call with AI and organizing 35+ data points in Google Sheets. This template helps customer success, support, and training teams save 30+ minutes per call on documentation while ensuring no critical action items or insights are missed.

  How it works
  Webhook receives** completed call data from BeyondPresence including full transcript
  Data validation** ensures quality and adds enriched metadata (duration, time calculations)  
  AI analysis** (GPT-4) extracts action items, sentiment, decisions, and recommendations
  Parse response** handles the AI output and structures it for sheets
  Auto-append** to Google Sheets with 35+ insights per call organized beautifully

  Set up steps
  Copy our Google Sheets template - One click! Get pre-formatted sheet: BeyondPresence Call Analytics Template
  Connect accounts - Add OpenAI API key and Google Sheets OAuth2
  Configure webhook - Copy URL from n8n to BeyondPresence Settings → Webhooks
  Customize AI prompt (optional) - Adjust analysis focus for your use case
  Test with a call - Make a test call and watch insights appear!

  Setup time: 5-10 minutes
  Requirements: BeyondPresence account, OpenAI API key, Google account

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-beyondpresence.beyondPresence","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 7712 characters]

metadata_json:
  {"categories":["automation","integration","data_processing","ai"],"complexity":"medium","use_cases":["Automated call documentation","Action-item extraction and tracking","Sentiment and decision logging","Customer success and support reporting","Training and coaching insight generation"],"estimated_setup_minutes":10,"required_services":["BeyondPresence account (webhook support)","OpenAI API key (GPT-4o-mini/GPT-4)","Google account with Google Sheets (OAuth)","n8n instance to host the workflow"],"key_features":["Receives completed call data via webhook","Validates and enriches call metadata (duration, timestamps)","AI analysis extracts 35+ structured data points (action items, sentiment, decisions, recommendations)","Parses AI output into structured fields","Auto-appends results to a pre-formatted Google Sheet template"],"target_audience":["Customer success teams","Support and operations teams","Training and coaching teams at SaaS companies or contact centers"]}


name: Goodreads Quote Extraction with Bright Data and Gemini
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-05-27T16:36:14.875Z
updated_at: 2025-05-27T16:36:14.875Z
url: https://n8n.io/workflows/4438
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Goodreads Quote Extraction with Bright Data and Gemini

  This workflow demonstrates how to fetch data specifically from Goodreads web pages using Bright Data and then extract specific information (quotes) from that data using a Google Gemini AI model.

  How it works

  The workflow is triggered manually.
  It sends a request to a Bright Data collector to scrape data from a predefined list of Goodreads URLs.
  The collected text data from Goodreads is then passed to a Google Gemini AI node.
  The AI node processes the text and extracts quotes based on a specified JSON schema output format.

  Set up steps

  Setting up this workflow should take only a few minutes.

  You will need a Bright Data API key to configure the 'Header Auth' credential.
  You will need a Google Gemini API key to configure the 'Google Gemini(PaLM) Api account' credential.
  Ensure the correct Bright Data collector ID is set in the 'Perform Bright Data Web Request' node URL.
  Make sure the full list of target Goodreads URLs is correctly added to the 'Perform Bright Data Web Request' node's body.
  Link your created credentials to the respective nodes ('Perform Bright Data Web Request' and 'Quotes Extractor').
  Keep detailed descriptions for specific node configurations in sticky notes inside your workflow canvas.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","web scraping","data extraction","AI/NLP","integration"],"complexity":"medium","use_cases":["Extract quotes from Goodreads pages into structured JSON","Build a quotes database or content feed","Content curation and aggregation","Preprocessing data for analysis or downstream ML","Automated data collection from multiple URLs"],"estimated_setup_minutes":10,"required_services":["Bright Data (collector / API key)","Google Gemini (PaLM) API key","Goodreads (target web pages / URLs)"],"key_features":["Uses Bright Data collector to scrape predefined Goodreads URLs","Passes scraped text to Google Gemini for structured extraction","Outputs quotes in a specified JSON schema","Manual trigger with simple node chain (manual, set, HTTP, Gemini, extractor)","Credential-based auth for Bright Data and Google Gemini"],"target_audience":["developers","data engineers","content curators / editors"]}


name: Automated Brand Mentions Tracker With GPT-4o, Google Sheets, and Email
author_name: Daniel Shashko
author_username: tomax
categories: []
created_at: 2025-05-27T21:43:46.459Z
updated_at: 2025-05-27T21:43:46.459Z
url: https://n8n.io/workflows/4443
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow enables you to automate the daily monitoring of how an AI model (like ChatGPT) responds to specific queries relevant to your market. It identifies mentions of your brand and predefined competitors, logs detailed interactions in Google Sheets, and delivers a comprehensive email report.

  Main Use Cases

  Monitor how your brand is mentioned by AI in response to relevant user queries.
  Track mentions of key competitors to understand AI's comparative positioning.
  Gain insights into AI's current knowledge and portrayal of your brand and market landscape.
  Automate daily intelligence gathering on AI-driven brand perception.

  How it works

  The workflow operates as a scheduled process, organized into these stages:

  Configuration & Scheduling
      Triggers daily (or can be run manually).
      Key variables are defined within the workflow: your brand name (e.g., "YourBrandName"), a list of queries to ask the AI, and a list of competitor names to track in responses.
  AI Querying
      For each predefined query, the workflow sends a request to the OpenAI ChatGPT API (via an HTTP Request node).
  Response Analysis
      Each AI response is processed by a Code node to:
          Check if your brand name is mentioned (case-insensitive).
          Identify if any of the listed competitors are mentioned (case-insensitive).
          Extract the core AI response content (limited to 500 characters for brevity in logs/reports).
  Data Logging to Google Sheets
      Detailed results for each query—including timestamp, date, the query itself, query index, your brand name, the AI's response, whether your brand was mentioned, and any errors—are appended to a specified Google Sheet.
  Email Report Generation
      A comprehensive HTML email report is compiled. This report summarizes:
          Total queries processed, number of times your brand was mentioned, total competitor mentions, and any errors encountered.
          A summary of competitor mentions, listing each competitor and how many times they were mentioned.
          A detailed table listing each query, whether your brand was mentioned, and which competitors (if any) were mentioned in the AI's response.
  Automated Reporting
      The generated HTML email report is sent to specified recipients, providing a daily snapshot of AI interactions.

  Summary Flow:

  Schedule/Workflow Trigger → Initialize Brand, Queries, Competitors (in Code node) → For each Query: Query ChatGPT API → Process AI Response (Check for Brand & Competitor Mentions) → Log Results to Google Sheets → Generate Consolidated HTML Email Report → Send Email Notification

  Benefits:

  Fully automated daily monitoring of AI responses concerning your brand and competitors.
  Provides objective insights into how AI models are representing your brand in user interactions.
  Delivers actionable competitive intelligence by tracking competitor mentions.
  Centralized logging in Google Sheets for historical analysis and trend spotting.
  Easily customizable with your specific brand, queries, competitor list, and reporting recipients.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 7312 characters]

metadata_json:
  {"categories":["automation","brand monitoring","AI monitoring","integration","reporting','competitive intelligence"],"complexity":"medium","use_cases":["Daily monitoring of how AI models mention your brand","Tracking competitor mentions and comparative positioning in AI responses","Automated collection of AI response samples for trend analysis","Generating daily email reports summarizing brand/competitor mentions","Maintaining historical logs in Google Sheets for analysis"],"estimated_setup_minutes":30,"required_services":["OpenAI / ChatGPT API (HTTP)","Google Sheets","Email provider (SMTP/Gmail/SendGrid or n8n Communication)","Running n8n instance/account"],"key_features":["Scheduled daily execution (or manual run)","Parameterized brand name, query list, and competitor list","Sends queries to ChatGPT via HTTP Request node","Parses responses to detect brand and competitor mentions (case-insensitive)","Truncates/extracts response content for logs (500 chars) and logs details to Google Sheets (timestamp, query, flags, errors)`,`Generates consolidated HTML email report with summaries and detailed table`,`Sends email notifications to configured recipients"],"target_audience":["Marketing teams","Brand / PR managers","Competitive intelligence analysts`,`Product managers / founders"]}


name: Build Production-Ready User Authentication with Airtable and JWT
author_name: NanaB
author_username: nanabrown
categories: []
created_at: 2025-05-28T03:58:04.708Z
updated_at: 2025-05-28T03:58:04.708Z
url: https://n8n.io/workflows/4444
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n workflow provides a comprehensive solution for user authentication and management, leveraging Airtable as the backend database. It includes flows for user sign-up and login, aswell as the sample crud operations retrieving user details, and updating user information.

  Youtube Video of me explaining the flow: https://www.youtube.com/watch?v=gKcGfyq3dPM

  How it Works

  User Sign-Up Flow
  Receives POST request: A webhook listens for POST requests containing new user details (email, first name, last name, password).
  Checks for existing email: The workflow queries Airtable to see if the submitted email already exists.
  Handles email in use: If the email is found, it responds with {"response": "email in use"}.
  Creates new user: If the email is unique, the password is SHA256 hashed (Base64 encoded), and the user's information (including the hashed password) is stored in Airtable. A successful response of {"response": "success"} is then sent.

  User Login Flow
  Receives POST request: A webhook listens for POST requests with user email and password for login.
  Verifies user existence: It checks Airtable for a user with the provided email. If no user is found, it responds with a failure message ("wrong email").
  Compares passwords: If a user is found, the submitted password is hashed (SHA256, Base64 encoded) and compared with the stored hashed password in Airtable.
  Responds with JWT or error: If passwords match, a JWT token containing the user's ID and email is issued. If they don't match, a "wrong password" response is sent.

  Flows for a Logged-In User

  These flows require a JWT-authenticated request.

  Get User Details:**
      Webhook (GET): Receives a JWT-authenticated request.
      Airtable (Read): Fetches the current user’s record using the jwtPayload.id.
      Set Node ("Specify Current Details"): Maps fields like "First Name," "Last Name," "Email," and "Date" from Airtable to a standard output format.

  Update User Details:**
      Webhook (POST): Receives updated user data (email, name, password).
      Airtable (Upsert): Updates the record matching jwtPayload.id using the submitted fields.
      Set Node ("Specify New Details"): Outputs the updated data in a standard format.

  Set Up Steps (Approx. 5 Minutes)

  Step 1: Set up your Airtable Base and Table

  You'll need an Airtable Base and a table to store your user data. Ensure your table has at least the following columns:

  Email** (Single Line Text)
  First Name** (Single Line Text)
  Last Name** (Single Line Text)
  Password** (Single Line Text - this will store the hashed password)
  Date** (Date - optional, for user sign-up date)

  Step 2: Obtain an Airtable Personal Access Token

  Go to the Airtable website and log in to your account.
  Navigate to your personal access token page (usually found under your developer settings or by searching for "personal access tokens").
  Click "Create new token."
  Give your token a name (e.g., "n8n User Management").
  Grant necessary permissions:
      Scope: data.records:read, data.records:write for the specific base you will be using.
      Base: Select the Airtable base where your user management table resides.
  Generate the token and copy it immediately. You won't be able to see it again. Store it securely.

  Step 3: Create a JWT Auth Credential in n8n

  In your n8n instance, go to "Credentials" (usually found in the left-hand sidebar).
  Click "New Credential" and search for "JWT Auth".
  Give the credential a name (e.g., "UserAuthJWT").
  For the "Signing Secret," enter a strong, random string of characters. This secret will be used to sign and verify your JWT tokens. Keep this secret highly confidential.
  Save the credential.

  Customization Options

  This workflow is designed to be highly adaptable:

  Database Integration**: Easily switch from Airtable to other databases like PostgreSQL, MySQL, MongoDB, or even Google Sheets by replacing the Airtable nodes with the appropriate database nodes in n8n.
  Authentication Methods**: Extend the authentication to include multi-factor authentication (MFA), social logins (Google, Facebook), or integrate with existing identity providers (IdP) by adding additional nodes.
  User Profile Fields**: Add or remove user profile fields (e.g., phone number, address, user roles) by adjusting the Airtable table columns and the Set nodes in the workflow.
  Notification System**: Integrate notification systems (e.g., email, SMS) for events like new user sign-ups, password resets, or account changes.
  Admin Panel**: Build an admin panel using n8n to manage users directly, including functionalities for adding, deleting, or updating user records, and resetting passwords.

  This workflow provides a solid foundation for building robust user management systems, adaptable to a wide range of applications and security requirements.

  Need Assistance or Customization?

  Do you have specific integrations in mind, or are you looking to add more user management features to this workflow?

  If you need help setting this up, or want to adapt it for a unique use case, don't hesitate to reach out! You can contact me directly at nanabrownsnr@gmail.com. I'd be glad to assist you.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.crypto","n8n-nodes-base.airtable","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.respondToWebhook","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.crypto","n8n-nodes-base.if","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["authentication","integration","user management","automation"],"complexity":"medium","use_cases":["Lightweight user authentication backend for web/mobile apps","Prototyping or bootstrapping user management for MVPs","Replacing/augmenting identity for small SaaS products","Admin panel or user CRUD operations integrated with Airtable","Learning example for JWT-based auth with n8n"],"estimated_setup_minutes":5,"required_services":["Airtable (Base & table)","n8n instance with public webhook access (self-hosted or n8n.cloud)"],"key_features":["User sign-up with email-uniqueness check","Password hashing using SHA256 (Base64)","User login issuing JWT containing user id and email","JWT-protected endpoints to get and update user details","Airtable read/write/upsert operations for user records"],"target_audience":["Developers building small apps or prototypes","No-code/low-code builders using n8n","Product teams wanting quick user auth without a full IdP integration"]}


name: Generate AI Stock Images with Flux1-schnell, Metadata Tagging & Google Integration
author_name: victor Adriano
author_username: bwire
categories: []
created_at: 2025-05-28T05:38:15.887Z
updated_at: 2025-05-28T05:38:15.887Z
url: https://n8n.io/workflows/4445
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  📣 This template generates up to 2,000 AI-based stock images per day for under $3. It includes prompt generation, image creation, metadata enrichment, upload to Google Drive, and error logging — fully automated with minimal setup.

  📌 Who is this for?

  This workflow is designed for:

  Stock image creators** and contributors
  Agencies** managing visual content at scale
  Solo creators** or marketers automating asset production
  Anyone aiming to populate image libraries (e.g., Adobe Stock, Shutterstock)

  ❓ What problem is this workflow solving?

  Manually generating, naming, tagging, and uploading thousands of stock images is time-consuming and expensive. This automation solves that by:

  Generating photorealistic images via AI
  Auto-tagging with rich metadata
  Uploading them to structured Google Drive folders
  Logging progress and capturing errors automatically

  ⚙️ What this workflow does

  ✅ Generates text prompts from idea topics using GPT
  🎨 Converts prompts into 4 images each via the Flux Schnell model
  📐 Resizes and compresses images for preview and final use
  🧠 Uses GPT-4o-mini to generate metadata: filename, title, category, and 25 keywords
  ☁️ Uploads to Google Drive, logs metadata to Google Sheets
  🟢 Marks each prompt as completed
  📲 Sends Telegram alerts for success and errors

  🛠 Setup

  Google Sheets

     Sheet 1: Ideas — New prompt topics
     Sheet 2: Generated Pmts — Tracks generated prompts and status
     Sheet 3: Error Logs — Execution error records

  Google Drive

     A folder for image uploads
     A folder for copied daily spreadsheets

  API Access

     OpenAI GPT (gpt-4o-mini)
     PIAPI (Flux Schnell image model)

  Telegram Bot (optional but recommended)

     Real-time status notifications

  🧩 How to customize this workflow to your needs

  🔁 Change frequency of generation via trigger settings
  🧠 Swap models if using a different image API
  🧾 Adjust metadata fields or format rules
  📤 Redirect outputs to Airtable, Notion, Dropbox, etc.

  🧠 Node Naming & Notes

  ✅ All nodes are clearly renamed to reflect their purpose (e.g., Generate Image, Upload to Drive)
  🗒️ Sticky notes are used to document setup and logic
  🔗 External links to Notion setup docs or Loom videos are recommended

  🗂️ Categories

  AI**
  Marketing**
  Product**
  Building Blocks**

  🎁 Bonus Feature

  This template includes a bonus stock image renamer workflow — ideal for renaming:

  📸 Taken photos
  🗃️ Existing stock libraries
  🖼️ Downloaded image batches

  It applies SEO-friendly, consistent naming compatible with major platforms like Adobe Stock and Shutterstock.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.editImage","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.splitOut","n8n-nodes-base.editImage","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.googleDrive","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.telegram","n8n-nodes-base.errorTrigger"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","AI image generation","content creation","integration","digital asset management"],"complexity":"complex","use_cases":["High-volume AI stock image generation","Automated metadata tagging and SEO-friendly naming","Uploading and organizing assets in Google Drive","Logging and auditing outputs in Google Sheets","Batch renaming existing image libraries"],"estimated_setup_minutes":30,"required_services":["OpenAI (gpt-4o-mini)","PIAPI / Flux Schnell image model","Google Drive","Google Sheets","Telegram Bot (optional for alerts)","n8n hosting (to run the workflow)"],"key_features":["Generates text prompts from idea topics using GPT","Creates 4 images per prompt via Flux Schnell (up to ~2,000 images/day cost-optimized)","Resizes and compresses preview and final assets","Generates filename/title/category and 25 keywords via GPT-4o-mini","Uploads images to structured Google Drive folders and copies daily spreadsheets','Logs metadata and status to Google Sheets and marks prompts completed','Error logging and Telegram notifications for successes/errors','Bonus batch image renamer for SEO-friendly naming','Clear node naming and onboard notes for easy customization"],"target_audience":["Stock image creators and contributors","Agencies managing visual content at scale","Solo creators and marketers automating asset production"]}


name: Schedule Appointments via Telegram with GPT-4o & Google Calendar
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-05-28T06:43:45.375Z
updated_at: 2025-05-28T06:43:45.375Z
url: https://n8n.io/workflows/4446
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔧 How It Works
  Telegram Trigger – Listens for incoming messages from users via your Telegram bot.

  Watch Full Step-by-step Guide Video here:
  https://www.youtube.com/watch?v=GzWO7_1lyI8

  AI Agent – Processes the message to determine the user's intent (booking or canceling) and extracts necessary details like date, time, and participant names.

  Google Calendar Node – Depending on the intent:

  Booking: Creates a new event in Google Calendar with the extracted details.

  Canceling: Searches for the specified event and deletes it from the calendar.

  Telegram Node – Sends a confirmation message back to the user, informing them of the successful booking or cancellation.

  🧠 Why This is Useful
  Managing appointments can be time-consuming. This workflow automates the process, allowing users to schedule or cancel meetings effortlessly through a simple chat interface. It's ideal for:

  Solopreneurs managing their own schedules.

  Small businesses coordinating meetings with clients.

  Anyone looking to streamline their appointment management process.

  🪜 Setup Instructions
  Set Up Telegram Bot:

  Create a new bot using BotFather on Telegram.
  Obtain the API token and set up the Telegram Trigger node in n8n with this token.

  OpenAI Platform API required for OpenAI Chat Model

  Connect to Google Calendar

  For the full video tutorial, watch here:
  https://youtu.be/GzWO7_1lyI8

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","communication","scheduling","ai"],"complexity":"medium","use_cases":["Schedule appointments via Telegram chat","Cancel/delete events from Google Calendar via chat","Automate appointment management for clients or teams","Extract booking details (date/time/participants) using AI agent"],"estimated_setup_minutes":20,"required_services":["Telegram Bot API","OpenAI (GPT-4o / OpenAI Chat API)","Google Calendar API","n8n instance"],"key_features":["Telegram-triggered conversational booking and canceling","AI agent for intent recognition and detail extraction","Create and delete events in Google Calendar","Confirmation messages delivered back to the user via Telegram","Memory buffer for multi-turn context handling"],"target_audience":["Solopreneurs","Small businesses","Customer-facing teams (support/sales) looking to automate bookings`,`Developers and automation engineers setting up chat-driven scheduling"]}


name: Categorize Support Tickets with Gemini AI, Typeform, and Google Sheets Reporting
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T07:18:42.975Z
updated_at: 2025-05-28T07:18:42.975Z
url: https://n8n.io/workflows/4447
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Transform chaotic support requests into organized, actionable insights automatically.

  This intelligent workflow captures support tickets from forms, uses AI to categorize and analyze sentiment, stores everything in organized databases, and delivers comprehensive analytics reports to your team - eliminating manual sorting while providing valuable business intelligence.

  🚀 What It Does

  Intelligent Ticket Processing: Automatically categorizes incoming support requests into Billing, Bug Reports, Feature Requests, How-To questions, and Complaints using advanced AI analysis.

  Sentiment Analysis: Analyzes customer emotion (Positive, Neutral, Negative) to prioritize responses and identify satisfaction trends.

  Real-Time Analytics: Generates instant reports showing ticket distribution, sentiment patterns, and team workload insights.

  Automated Data Storage: Organizes all ticket information in searchable Google Sheets with timestamps and customer details.

  Smart Reporting: Sends regular email summaries to stakeholders with actionable insights and trend analysis.

  🎯 Key Benefits

  ✅ Save 10+ Hours Weekly: Eliminate manual ticket sorting and categorization  
  ✅ Improve Response Times: Prioritize tickets based on category and sentiment  
  ✅ Boost Customer Satisfaction: Never miss urgent issues or complaints  
  ✅ Track Performance: Monitor support trends and team effectiveness  
  ✅ Scale Operations: Handle increasing ticket volume without additional staff  
  ✅ Data-Driven Decisions: Make informed improvements based on real patterns  

  🏢 Perfect For

  Customer Support Teams
  SaaS companies managing user inquiries and bug reports
  E-commerce stores handling order and product questions  
  Service businesses organizing client communications
  Startups scaling support operations efficiently

  Business Applications
  Help Desk Management**: Organize and prioritize incoming support requests
  Customer Success**: Monitor satisfaction levels and identify improvement areas
  Product Development**: Track feature requests and bug report patterns
  Team Management**: Distribute workload based on ticket categories and urgency

  ⚙️ What's Included

  Complete Workflow Setup: Ready-to-use n8n workflow with all nodes configured
  AI Integration: Google Gemini-powered classification and sentiment analysis
  Form Integration: Works with Typeform (easily adaptable to other platforms)
  Data Management: Automated Google Sheets organization and storage
  Email Reporting: Professional summary reports sent to your team
  Documentation: Step-by-step setup and customization guide

  🔧 Technical Requirements

  n8n Platform**: Cloud or self-hosted instance
  Google Gemini API**: For AI classification (free tier available)
  Typeform Account**: For support form creation (alternatives supported)
  Google Workspace**: For Sheets data storage and Gmail reporting
  SMTP Email**: For automated report delivery

  📊 Sample Output

  Daily Support Summary Email:
  📧 Support Ticket Summary - March 15, 2024

  📊 TICKET BREAKDOWN:
  • Billing: 12 tickets (30%)
  • Bug Report: 8 tickets (20%)  
  • Feature Request: 6 tickets (15%)
  • How-To: 10 tickets (25%)
  • Complaint: 4 tickets (10%)

  😊 SENTIMENT ANALYSIS:
  • Positive: 8 tickets (20%)
  • Neutral: 22 tickets (55%)
  • Negative: 10 tickets (25%)

  ⚡ PRIORITY ACTIONS:
  • 4 complaints requiring immediate attention
  • 3 billing issues escalated to finance team
  • 6 feature requests for product backlog review

  🎨 Customization Options

  Categories: Easily modify ticket categories for your specific business needs
  Form Platforms: Adapt to Google Forms, JotForm, Wufoo, or custom webhooks
  Reporting Frequency: Set daily, weekly, or real-time report delivery
  Team Notifications: Configure alerts for urgent tickets or negative sentiment
  Data Visualization: Create custom dashboards and charts in Google Sheets
  Integration Extensions: Connect to CRM, project management, or chat platforms

  🔄 How It Works

  Customer submits support request via your form
  AI analyzes message content and assigns category + sentiment
  Data is automatically stored in organized Google Sheets
  System generates real-time analytics on all historical tickets
  Professional report is emailed to your support team
  Team can prioritize responses based on urgency and sentiment

  💡 Use Case Examples

  SaaS Company: Automatically route billing questions to finance, bugs to development, and feature requests to product team

  E-commerce Store: Prioritize shipping complaints, categorize product questions, and track customer satisfaction trends

  Consulting Firm: Organize client requests by service type, monitor project-related issues, and ensure timely responses

  Healthcare Practice: Sort appointment requests, billing inquiries, and medical questions while maintaining HIPAA compliance

  📈 Expected Results

  80% reduction** in manual ticket sorting time
  50% faster** initial response times through better prioritization  
  25% improvement** in customer satisfaction scores
  100% visibility** into support trends and team performance
  Unlimited scalability** as your business grows

  📞 Get Help & Learn More

  🎥 Free Video Tutorials  
  YouTube Channel: https://www.youtube.com/@YaronBeen/videos


  💼 Professional Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/
  Connect for implementation consulting
  Share your automation success stories
  Access exclusive templates and updates

  📧 Direct Support  
  Email: Yaron@nofluff.online
  Technical setup assistance
  Custom workflow modifications
  Integration with existing systems
  Response within 24 hours

  🏆 Why Choose This Workflow

  Proven Results: Successfully deployed across 100+ businesses worldwide
  Expert Created: Built by automation specialist with 10+ years experience
  Continuously Updated: Regular improvements and new features added
  Money-Back Guarantee: Full refund if not satisfied within 30 days
  Lifetime Support: Ongoing help and updates included with purchase

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.typeformTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","data processing","customer support","analytics"],"complexity":"medium","use_cases":["Automated ticket categorization and routing","Sentiment analysis for prioritization","Storing and organizing tickets in Google Sheets","Automated email reporting and summaries","Monitoring support trends and team workload"],"estimated_setup_minutes":45,"required_services":["n8n (cloud or self-hosted)","Google Gemini API","Typeform (or alternative form/webhook provider)","Google Workspace (Google Sheets)","SMTP email or Gmail"],"key_features":["AI-powered ticket classification (Billing, Bug, Feature, How-To, Complaint)","Sentiment analysis (Positive/Neutral/Negative)","Automated storage and timestamping in Google Sheets","Scheduled or real-time summary email reports","Configurable categories, reporting frequency, and alerts"],"target_audience":["Customer support teams","SaaS companies","E-commerce stores and ops teams"]}


name: AI Client Onboarding Agent: Auto Welcome Email Generator
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T07:22:15.806Z
updated_at: 2025-05-28T07:22:15.806Z
url: https://n8n.io/workflows/4448
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  AI Client Onboarding Agent: Auto Welcome Email Generator

  Subtitle: From Form Response to Personalized Welcome Email

  🌍 Overview

  This workflow automates the client onboarding process.
  When a new client fills in the Google Form, their data flows into Google Sheets → gets structured → an AI model (Gemini) generates a personalized onboarding email → and finally, Gmail sends it directly to the client.

  Think of it as your automated client success assistant.

  🟢 Section 1: Trigger – Capture New Client

  🔗 Node: Google Sheets Trigger

  Watches for new rows added to the “Onboarding” Google Sheet.
  Starts the workflow whenever a new client submits the onboarding form.

  💡 Why useful?
  You never have to check the sheet manually — the workflow kicks off the moment a client signs up.

  📩 Example Input (from form):

  Name: Sarah Ali
  Email: sarah@startup.com
  Company: GreenTech Solutions
  Services Needed: Branding + Website

  🟦 Section 2: Structure Client Data

  🔗 Nodes:

  Client Data → Formats the raw form submission into a clean text summary (Name, Email, Company, Service, Extra Info).
  Client Checklist → Prepares a standard onboarding checklist with items like:

    Account setup
    Welcome call scheduled
    Document collection
    Service configuration
    Onboarding session
    First milestone review

  💡 Why useful?
  It makes sure the AI has all key details + a clear structure before writing the email.

  🟣 Section 3: AI-Generated Email

  🔗 Nodes:

  Basic LLM Chain → Prompted to write a professional onboarding email body.
  Google Gemini Chat Model → Supports the LLM chain with Gemini 2.0 Flash for fast generation.

  🧠 Prompt Logic:

  Starts with:
    Hi [Client Name],
  Includes personalized fields (Name, Company, Services Needed).
  Inserts onboarding checklist steps.
  Ends with:
    Best regards, Your [Company Name] Team

  💡 Why useful?
  Instead of a generic welcome, each client gets a personalized email that feels human-written.

  📩 Example Output Email:

  &gt; Hi Sarah Ali,
  &gt;
  &gt; Welcome to GreenTech Solutions! 🎉
  &gt;
  &gt; Here’s your onboarding plan:
  &gt;
  &gt; 1. Account setup
  &gt; 2. Welcome call scheduled
  &gt; 3. Document collection
  &gt; 4. Service configuration
  &gt; 5. Onboarding session
  &gt; 6. First milestone review
  &gt;
  &gt; We’re excited to start working with you on Branding + Website.
  &gt;
  &gt; Best regards,
  &gt; Your GreenTech Solutions Team

  🟡 Section 4: Send Email

  🔗 Node: Gmail

  Sends the AI-generated email to the client’s email address.
  Subject line:
    Welcome to Our Service, [Client Name]

  💡 Why useful?
  No delays → the client gets a personalized welcome instantly after filling the form.

  🔴 Section 5: Error Handling

  🔗 Nodes:

  Error Handler → Listens for any errors during execution.
  Execution Failure → Logs failed runs.
  Execution Completed → Confirms successful runs.

  💡 Why useful?
  Ensures nothing gets stuck silently — you’ll always know if something fails.

  📊 Workflow Summary

  | Section           | Node(s)                       | Purpose                                    | Benefit                        |
  | ----------------- | ----------------------------- | ------------------------------------------ | ------------------------------ |
  | 🟢 Trigger        | Google Sheets Trigger         | Detect new client submissions              | Fully automated start          |
  | 🟦 Structure      | Client Data, Client Checklist | Prepare structured client info + checklist | Clean, reliable input for AI   |
  | 🟣 AI Generation  | Basic LLM Chain, Gemini       | Generate personalized onboarding email     | Professional + tailored emails |
  | 🟡 Send Email     | Gmail                         | Deliver onboarding email                   | Instant communication          |
  | 🔴 Error Handling | Error Handler, NoOp nodes     | Handle success/failure states              | Reliable + transparent process |

  🚀 Benefits

  Zero manual effort** → Clients get emails automatically.
  Consistency** → Every client follows the same onboarding structure.
  Personalization** → Emails include name, company, and services.
  Reliability** → Built-in error handling ensures smooth execution.
  Scalability** → Works whether you onboard 10 or 1,000 clients.

nodes_used:
  ["n8n-nodes-base.errorTrigger","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5012 characters]

metadata_json:
  {"categories":["automation","integration","client onboarding","communication"],"complexity":"medium","use_cases":["Automated client onboarding","Personalized welcome email generation","Form-to-email workflows","Standardizing onboarding checklists"],"estimated_setup_minutes":20,"required_services":["Google Sheets","Google Forms (optional, source of responses)","Gmail (Google Workspace)","Google Gemini / Vertex AI (Gemini chat model)","n8n account with connected credentials"],"key_features":["Trigger on new Google Sheets row (form submission)","Format and structure raw client data","Generate onboarding checklist","AI-generated personalized onboarding email using Gemini","Send email via Gmail with dynamic subject/body fields"],"target_audience":["small businesses","agencies","client success teams / account managers / onboarding specialists"]}


name: AI Testimonial Extractor Agent: Feedback to Marketing Gold
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T07:27:22.201Z
updated_at: 2025-05-28T07:27:22.201Z
url: https://n8n.io/workflows/4449
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  AI Testimonial Extractor Agent: Feedback to Marketing Gold

  Subtitle: Feedback to Marketing Gold

  🌍 Overview

  This workflow transforms raw customer feedback from Google Forms into short, emotionally engaging testimonials using Google Gemini.
  It then saves the testimonial back into Google Sheets and notifies the marketing team via email.

  Think of it as your automatic testimonial assistant.

  🟢 Section 1: Trigger – Capture New Feedback

  🔗 Node: New Form Response Trigger (Google Sheets Trigger)

  Watches for new rows added to a Google Sheet (linked to your form).
  Starts the workflow whenever a customer submits feedback.

  💡 Why useful?
  No manual copy-pasting — the process kicks off instantly.

  📩 Example:
  Someone fills in:

  &gt; “The product made my workflow so much easier — I finished tasks in half the time!”

  🟦 Section 2: AI Extraction with Gemini

  🔗 Nodes:

  Extract Testimonial with Gemini → Uses Google Gemini Flash to rephrase the raw feedback into a concise testimonial.
  Google Gemini Chat Model → Supports the LLM chain.

  🧠 Prompt Logic:

  Keep only the emotional & engaging part.
  Remove neutral/irrelevant text.
  Return only the testimonial quote.

  💡 Why useful?
  Raw feedback is often long or messy → Gemini cleans it up into a marketing-ready quote.

  📩 Example output:

  &gt; “This tool cut my work time in half and boosted my productivity instantly!”

  🟣 Section 3: Save to Database

  🔗 Node: Save Extracted Testimonial (Google Sheets)

  Saves the following data into the sheet:

    Timestamp
    Name
    Email
    Original Feedback
    Extracted Testimony

  💡 Why useful?
  Keeps an organized log of all testimonials in one place.

  🟡 Section 4: Notify the Marketing Team

  🔗 Node: Notify Marketing Team (Gmail)

  Sends an email alert with the new testimonial.
  Subject: New Testimonial Extracted
  Body: Contains the extracted quote.

  💡 Why useful?
  Your team gets notified in real time → no need to keep checking the sheet.

  📊 Workflow Summary

  | Section          | Node(s)               | Purpose                          | Benefit                    |
  | ---------------- | --------------------- | -------------------------------- | -------------------------- |
  | 🟢 Trigger       | Google Sheets Trigger | Detects new form submissions     | Fully automated start      |
  | 🟦 AI Extraction | Gemini LLM Chain      | Turns raw feedback → testimonial | Marketing-ready content    |
  | 🟣 Save          | Google Sheets         | Logs testimonial + user info     | Organized central database |
  | 🟡 Notify        | Gmail                 | Emails marketing team            | Real-time updates          |

  🚀 Benefits

  Automation** → No manual editing or sorting needed.
  Consistency** → Every testimonial is short, emotional, and engaging.
  Centralized storage** → Everything logged in Google Sheets.
  Team alignment** → Marketing notified instantly.

  ⚡ Bonus: You already added Sticky Notes inside the workflow → makes it beginner-friendly for anyone opening it in n8n.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleSheetsTrigger","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4368 characters]

metadata_json:
  {"categories":["automation","marketing","AI","integration","data processing"],"complexity":"simple","use_cases":["Automatically convert raw customer feedback into marketing-ready testimonials","Centralize and log testimonials in Google Sheets","Notify marketing or growth teams of new high-quality quotes via email","Clean and condense long or messy form responses into short emotional quotes"],"estimated_setup_minutes":15,"required_services":["Google Sheets (and Google Forms if using a linked form)","Google Gemini (Gemini/Google Cloud AI or Gemini API access)","Gmail"],"key_features":["Trigger on new form responses (Google Sheets row trigger)","LLM-powered extraction/rephrasing to produce concise, emotional testimonials","Save testimonial + metadata (timestamp, name, email, original feedback) to Google Sheets","Email notification to marketing team with the extracted quote","Beginner-friendly with sticky notes and clear node structure"],"target_audience":["Marketing teams","Growth/CRM teams","Product managers / customer success teams collecting feedback from users or customers"]}


name: Automate Face Swapping for GIFs with Fal.run AI and Google Services
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-05-28T07:57:38.531Z
updated_at: 2025-05-28T07:57:38.531Z
url: https://n8n.io/workflows/4450
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow allows you to automatically swap faces in animated GIFs using AI, without writing a single line of code.

  By simply inserting the URL of a face image and a GIF into a Google Sheet, the automation takes care of everything: it sends the data to AI platform, monitors the processing status, retrieves the final face-swapped GIF, uploads it to Google Drive, and updates the Google Sheet with the result.

  This solution is perfect for content creators, marketers, or developers looking to integrate AI-powered GIF editing into their workflows in a fast and scalable way.

  Whether used manually or on a scheduled basis, the workflow turns a tedious creative task into a fully automated pipeline.

  This workflow automates GIF face-swapping by integrating Google Sheets for input/output and Fal.run for AI processing, ensuring seamless execution via scheduled or manual triggers.

  Example

  Face image:

  Gif Image:

  Result:

  How It Works  
  Trigger:  
     The workflow can be triggered manually ("When clicking ‘Test workflow’") or automatically via a scheduled trigger ("Schedule Trigger") set to run at intervals (e.g., every 5 minutes).  

  Data Retrieval:  
     The "Google Sheets" node fetches data from a predefined Google Sheet, which includes two columns:  
       FACE IMAGE: URL of the face image to swap.  
       GIF IMAGE: URL of the target GIF.  

  API Request:  
     The "Set data" node formats the retrieved URLs into variables (face_image and gif_image).  
     The "Create Image" node sends a POST request to the Fal.run API (easel-gifswap endpoint) with these URLs to initiate the face-swapping process. The API returns a request_id.  

  Status Check:  
     The "Wait 60 sec." node pauses execution for 60 seconds to allow processing time.  
     The "Get status" node queries the Fal.run API using the request_id to check if the task is COMPLETED.  
     If completed, the "Get Url image" node retrieves the final GIF URL.  

  Output Handling:  
     The "Upload Image" node saves the resulting GIF to Google Drive.  
     The "Update result" node writes the output GIF URL back to the Google Sheet under the RESULT column.  

  Set Up Steps  
  Prepare Google Sheet:  
     Create a Google Sheet with columns: FACE IMAGE, GIF IMAGE, and RESULT.  
     Populate the first two columns with image URLs. Leave RESULT empty for the workflow to fill.  

  Configure API Key:  
     Sign up to obtain an API key.  
     In the "Create Image" node, set HTTP header authentication:  
       Name: Authorization  
       Value: Key YOURAPIKEY  

  Schedule Execution:  
     Link the "Schedule Trigger" node to run periodically (e.g., every 5 minutes) or trigger manually for testing.  

  Test and Deploy:  
     Run the workflow to verify face-swapping functionality.  
     Monitor the Google Sheet for the RESULT column updates with the processed GIF URL.  

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.wait","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","AI/ML","media processing"],"complexity":"medium","use_cases":["Automated face-swapping for GIFs","Batch media processing for social content","Integrating AI image-editing into business workflows","Generating personalized marketing/advertising assets"],"estimated_setup_minutes":20,"required_services":["Fal.run (easel-gifswap API)","Google Sheets (Google account / API access)","Google Drive (Google account / API access)","n8n instance or n8n cloud"],"key_features":["No-code automation of GIF face swaps","Google Sheets-driven input/output (FACE IMAGE, GIF IMAGE, RESULT)","Asynchronous job handling with status polling and wait node","Uploads final GIFs to Google Drive","Supports scheduled or manual triggers for recurring or ad-hoc runs"],"target_audience":["Content creators","Social media marketers","Growth/marketing teams\",\"Developers building media workflows"]}


name: AI-Powered PDF Invoice Parser with Google Drive, Google Sheets & OpenAI
author_name: Billy Christi
author_username: billy
categories: []
created_at: 2025-05-28T08:35:56.008Z
updated_at: 2025-05-28T08:35:56.008Z
url: https://n8n.io/workflows/4451
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?

  This workflow is perfect for:

  Companies that manage invoices through Google Drive
  Business owners who want to minimize manual data entry and maximize accuracy
  Accounting teams and finance departments seeking to automate invoice processing

  What problem is this workflow solving?

  Processing invoices manually is time-consuming, error-prone, and inconsistent. This workflow solves those issues by:

  Automating invoice processing** from detection to data extraction to storage
  Improving accuracy** by using AI to extract key invoice data fields reliably
  Reducing human workload** while maintaining compliance and consistency

  What this workflow does

  This workflow creates a fully automated invoice processing system by:

  Monitoring a Google Drive folder for new PDF invoices in real time
  Downloading the PDF files and extracting their content using OCR technology
  Using AI (OpenAI) to parse and extract key invoice fields such as invoice number, date, total amount, vendor name, itemized details, tax, and category
  Validating the extracted data to ensure compliance with a structured JSON schema
  Storing structured data in Google Sheets for easy access, review, and reporting

  Key Features:

  AI-powered extraction handles both text-based and scanned PDF invoices
  Provides a structured, searchable invoice database in Google Sheets
  Configured to run as frequently as the user needs, ensuring timely processing.

  Setup
  Copy the Google Sheet template here:
  👉 PDF Invoice Parser – Google Sheet Template

  Connect your Google Drive account to the Drive Trigger and File Download nodes

  Add your OpenAI API key in the AI Parser node

  Link the Google Sheet in the final storage node

  Drop a test invoice PDF into the monitored Drive folder

  Required Credentials:

  OpenAI API Key**
  Google Drive Credentials**
  Google Sheets Credentials**

  How to customize this workflow to your needs
  Modify the polling interval** (default: every minute) for higher/lower frequency.
  Integrate with your accounting software** by adding nodes (e.g., QuickBooks, Xero).
  Use alternative LLM** such as Gemini, Claude.

  Contact me for consulting and support:   
  📧 billychartanto@gmail.com

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4332 characters]

metadata_json:
  {"categories":["automation","integration","data processing","document processing"],"complexity":"medium","use_cases":["Automate end-to-end invoice ingestion and extraction from Google Drive","Reduce manual data entry and improve accounting accuracy","Create a structured, searchable invoice database in Google Sheets","Validate and standardize invoice data to a JSON schema for downstream systems","Integrate extracted invoice data with accounting software or reporting workflows"],"estimated_setup_minutes":20,"required_services":["OpenAI (API key)","Google Drive (credentials)","Google Sheets (credentials)","OCR capability (built-in extractFromFile node or external OCR)","Optional integrations: QuickBooks, Xero, or other accounting APIs"],"key_features":["Real-time Drive folder monitoring for new PDF invoices","OCR extraction of text from scanned and text-based PDFs","AI-powered parsing to extract invoice fields (number, date, total, vendor, line items, tax, category)","Structured JSON validation against a schema","Stores parsed, validated records in Google Sheets for review and reporting','Configurable polling interval and extensible to other LLMs"],"target_audience":["Companies managing invoices via Google Drive","Business owners looking to minimize manual bookkeeping","Accounting teams and finance departments seeking automation support','Developers/IT or automation specialists implementing invoice workflows"]}


name: Automated PDF Invoice Processing & Approval Flow using OpenAI and Google Sheets
author_name: Billy Christi
author_username: billy
categories: []
created_at: 2025-05-28T08:38:25.269Z
updated_at: 2025-05-28T08:38:25.269Z
url: https://n8n.io/workflows/4452
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-30 08:33:37
description:
  Who is this for?

  This workflow is ideal for:

  Finance teams** that need to process incoming invoices faster with minimal errors
  Small to mid-sized businesses** that want to automate invoice intake, review, and storage
  Operations managers** who require approval workflows and centralized record-keeping

  What problem is this workflow solving?

  Manually processing invoices is time-consuming, error-prone, and often lacks structure. This workflow solves those challenges by:

  Automating the intake of invoices** from multiple sources (email, Google Drive, web form)
  Extracting invoice data using AI**, eliminating manual data entry
  Implementing an email-based approval system** to add human oversight
  Automatically storing approved invoice data** in Google Sheets for easy access and reporting
  Notifying stakeholders** when invoices are approved or rejected

  What this workflow does

  This end-to-end invoice processing workflow includes:

  Three invoice input methods: Google Drive folder monitor, Gmail attachments, and web form uploads
  PDF to text extraction for each input method using native PDF parsing
  AI-powered invoice analysis with GPT-4 to extract structured fields such as vendor, total, and due date
  Dynamic categorization of invoice type (e.g., Travel, Software, Utilities) via AI
  Email-based approval workflow with embedded forms to collect decisions and notes
  Automated Google Sheets logging of all invoice data, approval status, and reviewer feedback
  Rejection notifications sent automatically to your finance team for transparency and follow-up

  Setup

  Copy the Google Sheet template here:  
  👉 PDF Invoice Parser with Approval Workflow – Google Sheet Template
  Connect your Google Drive account and specify the invoice folder ID  
  Set up Gmail to monitor incoming invoices with PDF attachments  
  Enable your form trigger to accept direct uploads from your internal or external users  
  Enter your OpenAI API key in the AI processing node for data extraction  
  Configure Google Sheets with a target spreadsheet to store invoice data  
  Set recipient email addresses for invoice approvals and rejection notifications  
  Test with a sample invoice to ensure end-to-end flow is working  

  How to customize this workflow to your needs

  Change input sources**: Replace Gmail with Outlook or use Slack uploads instead
  Add validation steps**: Include regex or keyword checks before AI analysis
  Customize the AI schema**: Modify the expected JSON structure based on your internal finance system
  Integrate with accounting tools**: Add Xero, QuickBooks, or custom API nodes to push data
  Route based on category**: Add conditional logic to handle invoices differently based on vendor or category
  Multi-level approvals**: Add additional email steps if higher-level signoff is needed
  Audit logging**: Use database or Google Sheets to maintain a historical log of approvals and rejections

  Contact me for consulting and support:   
  📧 billychartanto@gmail.com

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.gmailTrigger","n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.if","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6820 characters]

metadata_json:
  {"categories":["automation","document processing","data extraction","integration","finance"],"complexity":"medium","use_cases":["Automated invoice intake and OCR/data extraction","Invoice review and approval workflows","Centralized invoice record-keeping in Google Sheets","Reducing manual entry and human errors in AP","Routing invoices and sending notifications to approvers"],"estimated_setup_minutes":60,"required_services":["OpenAI (AI/ML for parsing / output parsing)","Google Sheets","Google Drive","Email or team chat service (e.g., Gmail, Slack) for notifications/communication","Form service (if using an intake form)"],"key_features":["Automated extraction of invoice data from uploaded files","AI-assisted parsing and structured output validation","Conditional approval routing and if-logic for decisions","Notifications/communication to approvers","Persistent storage of invoice records in Google Sheets and Drive linkage to files/files metadata tracking"],"target_audience":["Finance teams","Small to mid-sized business owners / operators","Operations managers / AP staff"]}


name: BeyondPresence Sales Intelligence → Real-Time Lead Scoring
author_name: M Shehroz Sajjad
author_username: mshehrozsajjad
categories: []
created_at: 2025-05-28T11:35:23.910Z
updated_at: 2025-05-28T11:35:23.910Z
url: https://n8n.io/workflows/4454
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Monitor BeyondPresence video agent conversations in real-time to automatically score leads (0-100+) based on buying signals and send instant Slack alerts when hot opportunities or competitors are mentioned. This template helps sales teams prioritize leads immediately, never miss competitor mentions, and respond to high-intent prospects while they're still engaged.

  How it works
  Real-time webhook** processes each user message as it happens during calls
  Scoring engine** analyzes for buying signals (+points) and objections (-points)
  Competitor detection** instantly identifies when alternatives are mentioned
  Smart routing** sends alerts to different Slack channels based on urgency
  Hot leads** (70+ score) trigger immediate notifications with recommendations
  Call summary (Optional)** provides final qualification score when conversation ends

  Set up steps
  Connect Slack OAuth2 - Use n8n's built-in Slack integration (no webhooks needed!)
  Create Slack channels - Set up #sales-hot-leads, #sales-competitors, #sales-qualified
  Add webhook to BeyondPresence - Copy URL from n8n to BeyondPresence Settings → Webhooks
  Customize competitors - Edit the scoring node to add your specific competitor names
  Adjust scoring weights (optional) - Tune point values for your sales process

  Setup time: 10-15 minutes
  Requirements: BeyondPresence account, Slack workspace admin access

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.switch","n8n-nodes-base.code","n8n-nodes-base.switch","n8n-nodes-base.slack","n8n-nodes-base.slack","n8n-nodes-base.slack","n8n-nodes-base.code","n8n-nodes-base.slack","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 9664 characters]

metadata_json:
  {"categories":["automation","sales & revenue","real-time monitoring","integration"],"complexity":"medium","use_cases":["Real-time lead scoring during video calls","Instant Slack alerts for high-intent prospects","Automatic competitor mention detection","Prioritizing outbound/inbound follow-ups","Routing alerts to different teams based on urgency"],"estimated_setup_minutes":12,"required_services":["BeyondPresence account (webhooks enabled)","Slack workspace with OAuth2/admin access","n8n instance (hosted or self-hosted)"],"key_features":["Real-time webhook processing of user messages","Configurable scoring engine (positive and negative signals)","Competitor detection and instant alerts","Smart routing to different Slack channels by urgency","Hot-lead threshold triggers with recommendations (70+)  and optional call summary on call end"],"target_audience":["Sales teams (SDRs, AEs)","Revenue operations / Sales ops","Sales managers and team leads"]}


name: Shopify Multi-Module Automation with GPT-4o, Langchain Agents & Integrations
author_name: Sam Yassine
author_username: samyassine
categories: []
created_at: 2025-05-28T12:02:18.101Z
updated_at: 2025-05-28T12:02:18.101Z
url: https://n8n.io/workflows/4455
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n workflow orchestrates a powerful suite of AI Agents and automations to manage and optimize various aspects of an e-commerce operation, particularly for platforms like Shopify. It leverages Langchain AI Agents powered by OpenAI, along with a variety of integrated services, to handle customer support, product recommendations, abandoned cart recovery, inventory management, post-purchase engagement, review monitoring, marketing campaigns, and operational alerts.

  Tools & Services Used
  n8n:** Core automation and orchestration platform.
  Langchain AI Agents:** For intelligent decision-making, task execution, and natural language processing across multiple modules.
  OpenAI (e.g., GPT-4o Mini):** Powers the AI Agents and direct LLM calls for tasks like sentiment analysis and content generation.
  Shopify (Conceptual - requires specific API/Webhook setup):** For triggers (abandoned cart, order delivered) and actions (fetching products/inventory, creating discounts).
  Google Sheets:** Used as a data store for FAQs, logging low stock, review databases, and campaign outcomes.
  Slack:** For internal team notifications (escalations, low stock, negative reviews).
  Twilio (or similar SMS service):** For sending SMS alerts (cart recovery, restock notifications).
  Email (Generic SMTP/API):** For sending various emails (AI responses, recovery emails, review requests, campaign emails).
  Notion:** For logging customer interactions.
  HTTP Request Nodes:** For generic API interactions (fetching customer info, product search, CRM, campaign tracking).
  Webhook Nodes:** For receiving external triggers (incoming messages, product inquiries, review submissions, restock signals).
  Cron Nodes:** For scheduled tasks (hourly inventory checks, daily campaigns).

  Workflow Overview
  This workflow is a collection of interconnected sub-workflows, each designed to automate a specific e-commerce process:

  1. Customer Support & Escalation
  Handles incoming customer messages, attempts to answer with FAQs or order status using an AI Agent, and escalates to a human agent via Slack if necessary. Logs interactions to Notion.

  2. Product Inquiry & Recommendation
  Processes product inquiries, searches a product catalog, filters/sorts results, uses an AI Agent for selection refinement, and can build a product carousel for user response.

  3. Abandoned Cart Recovery
  Detects abandoned carts, fetches customer data, uses an AI Agent to strategize recovery (e.g., offer discounts), and sends follow-up communications via email/SMS.

  4. Inventory Management (Low Stock Alert)
  Periodically checks inventory levels, identifies low-stock items, uses an AI Agent to format reports, and notifies relevant teams via Slack/email, logging to Google Sheets.

  5. Post-Purchase Review Request
  After a set period post-delivery, an AI Agent drafts and initiates sending a personalized product review request email to the customer.

  6. Review Monitoring & Flagging
  Listens for new product reviews, uses an AI model for sentiment analysis, alerts a support team for negative reviews via Slack, and logs all reviews.

  7. Scheduled Marketing Campaigns
  Fetches target audiences, segments them, uses AI Agents to generate tailored email content, sends campaigns, tracks basic metrics, and employs another AI Agent to suggest campaign adjustments.

  8. Manual Restock Alert & Logging
  Allows triggering a restock notification via webhook, sends an SMS alert, and uses an LLM to log the event.

  Prerequisites
  Ensure you have active accounts and necessary API keys/credentials for:

  OpenAI
  Shopify (or your e-commerce platform API)
  Google Cloud (for Google Sheets API)
  Slack (Bot Token)
  Twilio (Account SID, Auth Token, From Number)
  Your Email Sending Service (SMTP details or API key)
  Notion (Integration Token)
  Any other external APIs used (e.g., CRM, Product Search, Customer Info, Campaign Tracking)

  How to Use This Template

  Step 1: Import the Template
  Open your n8n instance.
  Go to “Workflows” &gt; “Create Workflow”.
  Click the three dots (…) &gt; “Import from File”.
  Upload the downloaded JSON file of this workflow.

  Step 2: Configure Critical Nodes & Credentials
  This is the most crucial step. Systematically go through each of the 8 sections outlined in the Sticky Notes within the workflow and configure the relevant nodes:

  SECTION 1 (Customer Support):**
      Get FAQs Data (Google Sheets): Set sheetId to YOUR_SHEET_ID_HERE and configure Google API credentials.
      Lookup Order API (HTTP Request): Set url to YOUR_ORDER_LOOKUP_API_ENDPOINT_HERE.
      Notify Human Agent (Slack): Configure Slack API credentials and channel.
      Send AI Response to Customer (HTTP Request): Set url to YOUR_CUSTOMER_RESPONSE_API_ENDPOINT_HERE.
      Store to Notion (Notion): Set pageId (Database ID) to YOUR_NOTION_DATABASE_URL_OR_ID_HERE and Notion API credentials.
  SECTION 2 (Product Inquiry):**
      Search Products API (HTTP Request): Set url to YOUR_PRODUCT_SEARCH_API_ENDPOINT_HERE.
      Build Product Carousel (Function): Update YOUR_DEFAULT_PRODUCT_IMAGE_URL_HERE and YOUR_FALLBACK_PRODUCT_URL_HERE.
      Respond to User with Carousel (HTTP Request): Set url for sending carousel data.
  SECTION 3 (Abandoned Cart):**
      Detect Abandoned Cart (Shopify Trigger): Configure Shopify credentials and ensure the correct trigger event.
      Fetch Customer Info (HTTP Request): Set url to YOUR_CUSTOMER_INFO_API_ENDPOINT_HERE.
      Create Discount (if applicable) (Shopify): Configure Shopify credentials and review discount creation parameters.
      Send Recovery Email (HTTP Request/Email Send): Set email API endpoint or SMTP credentials.
      Send SMS Reminder (Twilio): Configure Twilio credentials and from number (YOUR_TWILIO_PHONE_NUMBER_HERE).
  SECTION 4 (Low Stock Alerts):**
      Fetch Inventory (Shopify): Configure Shopify credentials.
      Notify Slack (Low Stock) (Slack): Configure Slack API credentials and channel.
      Generate Email Report (Low Stock) (Email Send): Configure SMTP/email credentials and to address.
      Export to Sheets (Low Stock Log) (Google Sheets): Set sheetId to YOUR_INVENTORY_LOG_SHEET_ID_HERE and Google API credentials.
  SECTION 5 (Review Request):**
      Order Delivered Trigger (Shopify Trigger): Configure Shopify credentials.
      Fetch Customer Data (for Review) (HTTP Request): Set url to YOUR_CUSTOMER_INFO_API_ENDPOINT_HERE.
      DraftReviewRequestEmail (Tool): Update YOUR_PRODUCT_PAGE_URL_BASE_HERE and YOUR_WEBSITE_URL_HERE.
      Send Review Request Email (Email Send): Configure SMTP/email credentials.
  SECTION 6 (Review Monitoring):**
      OpenAI node (currently Assistant Create): IMPORTANT: For sentiment analysis, change this node type to @n8n/n8n-nodes-langchain.lmChatOpenAi. Then configure its prompt for sentiment analysis (e.g., System: "Analyze sentiment. Respond with positive, negative, or neutral." User: "Review: {{ $('Listen for Review Webhook').first().json.body.review_text }}"). Set OpenAI credentials.
      Notify Support Team (Negative Review) (Slack): Configure Slack API credentials and channel.
      Add Review to Database (Google Sheets): Set sheetId to YOUR_REVIEWS_DATABASE_SHEET_ID_HERE and Google API credentials.
  SECTION 7 (Marketing Campaigns):**
      Fetch Target Audience API (HTTP Request): Set url to YOUR_CRM_API_FOR_AUDIENCE_HERE.
      GenerateCampaignEmailVariant (Tool): Update YOUR_CAMPAIGN_LANDING_PAGE_HERE.
      Send Campaign Email (Email Send): Configure SMTP/email credentials.
      Track Campaign Metrics API (HTTP Request): Set url for YOUR_CAMPAIGN_TRACKING_API_ENDPOINT_HERE.
      Log Campaign Outcome & Adjustments (Google Sheets): Set sheetId to YOUR_CAMPAIGN_LOG_SHEET_ID_HERE and Google API credentials.
  SECTION 8 (Manual Restock):**
      Send SMS Alert (Restock) (Twilio): Configure Twilio credentials, from number (YOUR_TWILIO_PHONE_NUMBER_HERE), and to (WAREHOUSE_MANAGER_PHONE_NUMBER_HERE).
      OpenAI Chat Model (for Basic LLM Chain): Configure OpenAI credentials.
      Send restock Request Email1 (Email Send): Configure SMTP/email credentials and to address.

  Step 3: Implement Tool Logic
  Go into each @n8n/n8n-nodes-langchain.toolCode node (e.g., SearchFAQs, RefineProductSelection, DetermineDiscount, etc.).
  The current JavaScript is placeholder. You MUST replace this with actual JavaScript logic that performs the intended action for each tool, often by making API calls or processing data based on the agent's input.

  Step 4: Review AI Agent Prompts & Tool Connections
  Carefully review the systemMessage for each AI Agent node to ensure it accurately reflects its role and how it should use its tools.
  CRITICAL:** Verify the index for tools connected to each AI Agent. Each tool connected to a single agent must have a unique, sequential index (0, 1, 2, ...).
      AI Agent (*ID cd71629d-...* in your JSON): SearchFAQs tool should be index: 0, LookupOrderStatus tool should be index: 1. (Please double-check and correct the connection indices in your actual workflow file if they are still both pointing to index 0).
      AI Agent6 (*ID 4c24879b-...* in your JSON): AnalyzeCampaignPerformance tool should be index: 0, SuggestCampaignAdjustments tool should be index: 1. (Please double-check and correct the connection indices in your actual workflow file if they are still both pointing to index 0).

  Initial Test Run
  Disable most of the workflow sections initially.
  Focus on one section at a time (e.g., Section 1: Customer Support).
  Manually trigger the first node (e.g., simulate an incoming webhook).
  Execute node by node, checking the output and debugging configurations and tool logic.
  For time-based triggers (Cron, Wait nodes), temporarily shorten the durations for faster testing.
  Once a section is working, move to the next.

  Use Cases
  E-commerce Businesses (Shopify, etc.):** To automate customer service, marketing, sales recovery, and operations.
  Digital Marketing Agencies:** To offer advanced automation services to e-commerce clients.
  Freelancers & Consultants:** To build and deploy sophisticated AI-driven e-commerce solutions.
  n8n Developers:** As a comprehensive template and learning resource for building complex multi-agent systems.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.if","n8n-nodes-base.slack","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.notion","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.webhook","n8n-nodes-base.function","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.function","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.function","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.shopifyTrigger","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.function","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.shopify","n8n-nodes-base.httpRequest","n8n-nodes-base.twilio","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.cron","n8n-nodes-base.shopify","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.slack","n8n-nodes-base.emailSend","n8n-nodes-base.googleSheets","n8n-nodes-base.webhook","n8n-nodes-base.twilio","n8n-nodes-base.shopifyTrigger","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.emailSend","n8n-nodes-base.webhook","n8n-nodes-base.if","n8n-nodes-base.slack","n8n-nodes-base.googleSheets","n8n-nodes-base.cron","n8n-nodes-base.httpRequest","n8n-nodes-base.function","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.function","n8n-nodes-base.emailSend","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.function","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.emailSend","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6988 characters]

metadata_json:
  {"categories":["automation","integration","e-commerce","AI"],"complexity":"complex","use_cases":["AI-driven customer support and escalation","Product inquiry handling & personalized recommendations","Abandoned cart recovery via email/SMS","Inventory monitoring and low-stock alerts","Post-purchase review requests and review sentiment monitoring/flagging\",\"Scheduled, segmented marketing campaigns with AI-generated content"],"estimated_setup_minutes":120,"required_services":["n8n (self-hosted or cloud)","LangChain (n8n Langchain nodes / agents)","OpenAI (GPT-4o or GPT-4o Mini)","Shopify (or another e-commerce platform API/webhooks)","Google Sheets (Google Cloud API)","Slack (bot token)","Twilio (SMS) or equivalent SMS provider","Email provider (SMTP or API)","Notion (integration token)","Any CRM / Product Search / Campaign Tracking APIs (HTTP endpoints)"],"key_features":["Multi-module orchestration (support, inventory, marketing, reviews, cart recovery)","LangChain-powered AI Agents and tool integrations","Automated triggers via webhooks and cron schedules","Personalized emails and SMS sends (campaigns, recovery, reviews, alerts)","Sentiment analysis and negative-review escalation to Slack/human agents','Google Sheets logging and reporting for FAQs, inventory, reviews, campaigns'"],"target_audience":["E‑commerce businesses (Shopify merchants)","Digital marketing agencies and consultants","Freelancers building e-commerce automations for clients\",\"n8n developers learning multi-agent integrations"]}


name: WhatsApp AI Customer Service Bot with GPT-4o-mini and Gmail Alerts
author_name: Ghufran Ridhawi
author_username: ghufran-ridhawi
categories: []
created_at: 2025-05-28T13:33:23.084Z
updated_at: 2025-05-28T13:33:23.084Z
url: https://n8n.io/workflows/4456
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?
  This workflow is intended for WhatsApp admins, customer service, individual users or teams in businesses who want to automate their small business or medium to large businesses on WhatsApp practically by automatically replying about your business products or services using Open AI capabilities on AI Agent. Based on an automated system there is a task to answer many customers or clients on WhatsApp, in reality answering one by one is very time consuming and tiring, especially if we have to compose sentences first or click on the template and send them. This is also a form of devotion to the community at n8n and the n8n company, as well as devotion to small businesses so that the reality is no longer tiring and able to answer the problems of reality that exist.

  How does it work?
  Easy explanation:

  Whatsapp trigger here the "Input submissions" node is responsible for inputting chats from customers in the form of data. Then, it is sent to the next node, namely the if node, here there are two if nodes, namely "Signpost" and "Is text message?" responsible for forwarding customer chat input data and selecting if correct then it will be forwarded to the AI ​​Agent and if wrong then there is a "Fallback Text" node. Once correct, the AI ​​Agent will analyze with the OpenAI model capability and store it in Simple Memory. The AI ​​Agent here has been given directions and commands on what it should be like, in the parameters section, the prompt contains a special task, the knowledge base of your business, and several points and rules that must be there. After that, it will be sent via the WhatsApp reply node which is addressed to the customer. After that, the Gmail Set will process it again to be addressed to the Send Gmail Notifications Node, which contains email address parameters and also the contents of the email as a notification of success or failure. Then, there are no operations after that after the Gmail node. And enjoy this workflow that works for you.

  Setup instructions
  Complete what is in the node as stated in the notes column.
  You need a "Credential Account" on each WhatsApp node, then the OpenAI node and the Gmail Node. If you already have an account, just connect it, and if not, create it first, you can register it by following the guide from n8n, it makes it very easy.
  Because here it has been set up neatly and cleanly like in the if node. Next, you need to add your business to the AI ​​Agent node, there are parameters and a prompt section, I have made a sample here to make it easier for you. You can immediately adjust it to your business or service or product, later what communication or sentence you want to convey to customers on WhatsApp. After that, don't forget to add an email address to the Gmail node for notification of success or failure of each customer from the running of this system.
  Save and run, test the workflow and activate the workflow. This workflow is ready to use.

  Requirements
  As a reminder:

  Must be set in nodes such as your business description, also according to the conditions of your business, services, products, so that the AI ​​Agent matches your business knowledge base
  Must have (if not, make sure you have registered) in each "Credential Account" by following the guide on how to create it n8n the guide is very complete
  Don't forget to save, and make sure the workflow is active.

  How to customize this workflow to your needs

  You can immediately set up your business knowledge base in the nodes, so that the accuracy is also high when carrying out tasks and answering them.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.whatsApp","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","customer support","AI/machine learning","messaging"],"complexity":"medium","use_cases":["Automated WhatsApp customer replies using OpenAI","Routing and fallback for non-text inputs","Email notifications for conversation success/failure","Embedding business knowledge into AI agent for consistent answers","Small-to-medium business customer support automation"],"estimated_setup_minutes":25,"required_services":["n8n account","WhatsApp Business API or supported WhatsApp provider (node credential)","OpenAI (GPT-4o-mini / Agent credentials)","Gmail account (API/SMTP credential)"],"key_features":["AI Agent (OpenAI) driven automated responses","Conditional routing (If nodes) to handle text vs non-text and signposts","Simple memory buffer to maintain short conversation context","Fallback text handling for unsupported inputs","WhatsApp reply node to send responses to customers automatically and Gmail notifications for success/failure events"],"target_audience":["WhatsApp admins","Customer support teams","Small and medium business owners/operators automating messaging workflows」「Developers or integrators implementing n8n automations"]}


name: AI Telegram Bot Agent: Smart Assistant & Content Summarizer
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:19:55.730Z
updated_at: 2025-05-28T14:19:55.730Z
url: https://n8n.io/workflows/4457
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Create your own intelligent Telegram bot that summarizes articles and processes commands automatically.

  This powerful workflow turns Telegram into your personal AI assistant, handling /help, /summary &lt;URL&gt;, and /img &lt;prompt&gt; commands with intelligent responses - perfect for teams, content creators, and anyone wanting smart automation in their messaging.

  🚀 What It Does

  Smart Command Processing: Automatically recognizes and routes /help, /summary, and /img commands to appropriate AI-powered responses.

  Article Summarization: Fetches any URL, extracts content, and generates professional 10-12 bullet point summaries using OpenAI.

  Image Generation: Processes image prompts and integrates with AI image generation services.

  Help System: Provides users with clear command instructions and usage examples.

  🎯 Key Benefits

  ✅ Personal AI Assistant: Get instant article summaries in Telegram  
  ✅ Team Productivity: Share quick content summaries with colleagues  
  ✅ Content Research: Rapidly digest articles and web content  
  ✅ 24/7 Availability: Bot works around the clock without maintenance  
  ✅ Easy Commands: Simple /summary &lt;link&gt; format anyone can use  
  ✅ Scalable: Handles multiple users and requests simultaneously  

  🏢 Perfect For

  Content Teams & Researchers
  Journalists quickly summarizing news articles
  Marketing teams researching competitor content
  Students processing academic papers and articles
  Analysts digesting industry reports

  Business Applications
  Team Communication**: Share article insights in group chats
  Research Assistance**: Quick content analysis for decision making
  Content Curation**: Summarize articles for newsletters or reports
  Knowledge Sharing**: Help teams stay informed efficiently

  ⚙️ What's Included

  Complete Bot Workflow: Ready-to-deploy Telegram bot with all commands
  AI Integration: OpenAI-powered content summarization and processing
  Smart Routing: Intelligent command recognition and response system
  Error Handling: Robust system handles invalid commands gracefully
  Extensible Design: Easy to add new commands and features

  🔧 Quick Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  Telegram Bot Token**: Create via @BotFather (free, 5 minutes)
  OpenAI API**: For content summarization (pay-per-use)
  Basic Configuration**: Follow 15-minute setup guide

  📱 User Experience

  Simple Commands:
  /help - Show available commands
  /summary https://example.com - Get article summary
  /img sunset over mountains - Generate image (with supported APIs)

  Sample Summary Output:
  📄 Article Summary:

  • Company reports 40% revenue growth in Q3 2024
  • New AI features driving customer acquisition
  • Expansion into European markets planned for 2025
  • Investment in R&D increased by 25% this quarter
  • Customer satisfaction scores improved to 94%
  • Three new product launches scheduled for next year
  • Remote work policy made permanent post-pandemic
  • Sustainability goals on track to meet 2025 targets
  • Partnership with major tech firm announced
  • Stock price up 15% following earnings report

  🎨 Customization Options

  Command Extensions: Add custom commands for specific workflows
  Response Formatting: Customize summary style and length
  Multi-Language: Support different languages for international teams
  Integration APIs: Connect additional AI services and tools
  User Permissions: Control who can use specific commands
  Analytics: Track usage patterns and popular content

  🏷️ Tags & Categories

  #telegram-bot #ai-automation #content-summarization #article-processing #team-productivity #openai-integration #smart-assistant #workflow-automation #messaging-bot #content-research #ai-agent #n8n-workflow #business-automation #telegram-integration #ai-powered-bot

  💡 Use Case Examples

  News Team: Quickly summarize breaking news articles for editorial meetings
  Marketing Agency: Research competitor content and industry trends efficiently  
  Sales Team: Digest industry reports and share insights with prospects
  Remote Team: Keep everyone informed with summarized company updates

  📈 Expected Results

  80% faster** content research and analysis
  50% more articles** processed per day vs manual reading
  100% team accessibility** through familiar Telegram interface
  24/7 availability** for global teams across time zones

  🛠️ Setup & Support

  Quick Start: Deploy your bot in 15 minutes with included guide
  Video Tutorial: Complete walkthrough available
  Template Commands: Pre-built responses and formatting
  Expert Support: Direct help from workflow creator

  📞 Get Help & Resources

  YouTube: https://www.youtube.com/@YaronBeen/videos

  💼 Professional Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  📧 Direct Help  
  Email: Yaron@nofluff.online - Response within 24 hours

  Ready to build your intelligent Telegram assistant?

  Get this AI Telegram Bot Agent and transform your messaging app into a powerful content processing tool. Perfect for teams, researchers, and anyone who wants AI-powered assistance directly in Telegram.

  Stop manually reading long articles. Start getting instant, intelligent summaries with simple commands.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.html","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.telegram","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4192 characters]

metadata_json:
  {"categories":["automation","integration","ai-assistant","content-summarization","messaging-bot"],"complexity":"medium","use_cases":["Article summarization from URLs","Team knowledge sharing and notifications","Content research and competitor analysis","On-demand image generation via chat commands","Automating help and command responses in Telegram"],"estimated_setup_minutes":15,"required_services":["n8n (cloud or self-hosted)","Telegram Bot (BotFather token)","OpenAI API (or compatible LLM API)","AI image generation service (optional, e.g., DALL·E or similar)","Publicly reachable webhook/HTTP endpoint for Telegram (if self-hosted)"],"key_features":["Smart command routing for /help, /summary, /img","URL fetching and article content extraction","10–12 bullet point AI-generated summaries","Image prompt processing and integration with image APIs","Robust error handling and invalid command responses / extensibility"],"target_audience":["Content teams","Journalists and editors","Marketing teams and researchers (competitive analysis/content curation)"]}


name: Score Contact Form Leads with GPT-4 and Send Slack Notifications
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:21:41.116Z
updated_at: 2025-05-28T14:21:41.116Z
url: https://n8n.io/workflows/4458
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔥 AI Lead Scoring Agent: Smart Contact Form Triager

  Automatically score every contact form lead as Hot/Warm/Cold and alert your sales team instantly.

  This intelligent workflow captures contact form submissions, uses GPT-4 to analyze message content and score lead quality, then sends formatted alerts to Slack - ensuring your sales team always focuses on the hottest prospects first.

  🚀 What It Does

  Instant Lead Capture: Automatically receives contact form submissions via webhook endpoint

  AI-Powered Scoring: GPT-4 analyzes message content and classifies leads as Hot 🔥, Warm 🌤, or Cold ❄️

  Smart Data Extraction: Cleanly extracts name, email, and message from form submissions

  Real-Time Slack Alerts: Sends formatted notifications to your sales team with lead details and AI scoring

  🎯 Key Benefits

  ✅ Never Miss Hot Prospects: AI identifies urgent leads automatically  
  ✅ Save Sales Time: Focus effort on highest-probability leads first  
  ✅ Instant Team Alerts: Real-time notifications in Slack channels  
  ✅ Smart Prioritization: AI scoring eliminates guesswork in lead quality  
  ✅ Zero Manual Work: Complete automation from form to sales alert  
  ✅ Universal Integration: Works with any contact form or landing page  

  🏢 Perfect For

  Sales & Marketing Teams
  SaaS companies managing inbound leads
  Service businesses qualifying prospects  
  E-commerce stores identifying serious buyers
  Agencies prioritizing client inquiries

  Business Applications
  Lead Qualification**: Identify purchase-ready prospects instantly
  Sales Efficiency**: Focus team effort on highest-value opportunities  
  Response Prioritization**: Handle urgent inquiries first
  Team Coordination**: Keep entire sales team informed of new leads

  ⚙️ What's Included

  Complete Workflow: Ready-to-deploy lead scoring automation
  Webhook Endpoint: Receives submissions from any contact form
  AI Classification: GPT-4 powered lead interest analysis
  Slack Integration: Professional team notifications with emojis and formatting
  Data Processing: Clean extraction and formatting of lead information

  🔧 Quick Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  OpenAI API**: GPT-4 access for lead scoring
  Slack Workspace**: Team channel for lead notifications
  Contact Form**: Any form that can POST to webhook endpoint

  📱 Sample Slack Alert

  🔥 New Lead: Sarah Johnson (sarah@techstartup.com)

  Message: "We're looking for a project management solution for our 50-person team. Need to implement ASAP as we're scaling fast. Can we schedule a demo this week?"

  Triage: 🔥 Hot

  ❄️ New Lead: John Smith (john@email.com)

  Message: "Just browsing your website. Might be interested in learning more someday."

  Triage: ❄️ Cold

  🎨 Customization Options

  Scoring Criteria: Adjust AI prompts for industry-specific lead qualification
  Team Channels: Route different lead types to specific Slack channels  
  Additional Fields: Capture company size, budget, timeline data
  CRM Integration: Connect to Salesforce, HubSpot, or Pipedrive
  Follow-up Automation: Trigger email sequences based on lead temperature
  Analytics Tracking: Monitor lead quality trends and conversion rates

  🏷️ Tags & Categories

  #lead-scoring #sales-automation #contact-form-processing #ai-qualification #slack-integration #prospect-management #inbound-marketing #sales-productivity #lead-generation #openai-integration #webhook-automation #crm-automation #sales-alerts #lead-triage #ai-agent

  💡 Use Case Examples

  SaaS Company: Score demo requests based on company size and urgency mentions
  Consulting Firm: Identify clients ready to start projects vs those still researching  
  E-commerce Store: Spot bulk buyers and wholesale inquiries vs casual browsers
  Marketing Agency: Prioritize clients with specific budgets and timelines mentioned

  📈 Expected Results

  70% faster** lead response times through smart prioritization
  3x higher** conversion rates focusing on Hot leads first
  50% time savings** on manual lead qualification  
  100% lead coverage** - never miss or ignore a prospect again

  🛠️ Setup & Support

  5-Minute Setup: Simple webhook configuration with any contact form
  Universal Integration: Works with WordPress, Webflow, custom forms, landing pages
  Team Training: Clear Slack notification format anyone can understand
  Scalable: Handles unlimited form submissions automatically

  📞 Get Help & Resources

   
  YouTube: https://www.youtube.com/@YaronBeen/videos

  💼 Sales Automation Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  📧 Direct Help  
  Email: Yaron@nofluff.online - Response within 24 hours

  Ready to never miss another hot lead?

  Get this AI Lead Scoring Agent and transform your contact forms into intelligent lead qualification systems. Your sales team will always know which prospects to call first, and you'll never waste time on cold leads again.

  Stop treating all leads equally. Start prioritizing the ones ready to buy.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.slack"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","sales automation","lead scoring","AI integration","notifications"],"complexity":"medium","use_cases":["Automatic lead qualification and scoring","Prioritizing inbound sales leads (Hot/Warm/Cold)","Real-time team alerts via Slack","Extracting contact details from form submissions","Routing or triggering follow-up automation based on score"],"estimated_setup_minutes":5,"required_services":["n8n (cloud or self-hosted)","OpenAI API (GPT-4)","Slack workspace/channel","Contact form or any service that can POST to a webhook"],"key_features":["Webhook endpoint to receive form submissions","GPT-4 powered message analysis and Hot/Warm/Cold scoring","Automatic extraction of name, email, and message","Formatted Slack notifications with triage result","Configurable routing and customization (channels, prompts, fields)"],"target_audience":["Sales teams","Marketing teams","SaaS companies handling inbound leads」「E‑commerce stores」「Agencies handling client inquiries"]}


name: AI YouTube Analytics Agent: Comment Analyzer & Insights Reporter
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:26:13.676Z
updated_at: 2025-05-28T14:26:13.676Z
url: https://n8n.io/workflows/4459
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Transform YouTube comments into actionable insights with automated AI analysis and professional email reports.

  This intelligent workflow monitors your Google Sheets for YouTube video IDs, fetches comments using YouTube API, performs comprehensive AI sentiment analysis, and delivers formatted email reports with viewer insights - helping content creators understand their audience and improve engagement.

  🚀 What It Does

  Smart Video Monitoring: Watches Google Sheets for new YouTube video IDs marked as "Pending" and triggers automated analysis

  Complete Comment Collection: Fetches up to 100 top comments per video using YouTube API with relevance-based ordering

  AI-Powered Analysis: Uses GPT-4 to analyze comments for sentiment, themes, questions, feedback, and actionable insights

  Professional Email Reports: Generates detailed HTML reports with statistics, sentiment breakdown, and improvement recommendations

  Automated Status Tracking: Updates spreadsheet status to prevent duplicate processing and maintain organized workflow

  🎯 Key Benefits

  ✅ Deep Audience Insights: Understand what viewers really think about your content  
  ✅ Save Hours of Manual Work: Automated comment analysis vs reading hundreds of comments  
  ✅ Improve Content Strategy: Get actionable feedback for better video performance  
  ✅ Track Sentiment Trends: Monitor positive/negative feedback patterns  
  ✅ Professional Reporting: Receive formatted analysis reports via email  
  ✅ Scalable Analysis: Process multiple videos automatically  

  🏢 Perfect For

  Content Creators & YouTubers
  Individual creators tracking audience engagement
  Educational channels analyzing learning feedback
  Entertainment creators understanding viewer preferences
  Business channels monitoring brand sentiment

  Marketing & Business Applications
  Brand Monitoring**: Track sentiment on branded content and partnerships
  Audience Research**: Understand viewer demographics and preferences  
  Content Optimization**: Identify what resonates with your audience
  Competitor Analysis**: Analyze comments on competitor videos (where allowed)

  ⚙️ What's Included

  Complete Analytics Workflow: Ready-to-deploy YouTube comment analysis system
  Google Sheets Integration: Simple spreadsheet-based video management
  YouTube API Integration: Automated comment fetching with proper authentication
  AI Analysis Engine: GPT-4 powered sentiment and insight generation
  Email Reporting System: Professional HTML-formatted reports
  Status Management: Automatic processing tracking and duplicate prevention

  🔧 Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  YouTube API Credentials**: Google Cloud Console API access
  OpenAI API**: GPT-4 access for comment analysis
  Google Sheets**: Video ID management and status tracking
  Gmail Account**: For receiving analysis reports

  📊 Required Google Sheets Structure

  | ID | Video Title | YouTube Video ID | Status |
  |----|-------------|------------------|---------|
  | 1  | My Tutorial | dQw4w9WgXcQ     | Pending |
  | 2  | Product Demo| abc123def456    | Mail Sent |
  | 3  | Weekly Vlog | xyz789uvw012    | Draft |

  Status Options: Draft → Pending → Mail Sent

  📧 Sample Analysis Report

  📺 YouTube Comments Analysis Report
  Video: "How to Build Your First Website"

  📊 Quick Statistics:
  • Total Comments Analyzed: 87
  • Average Likes per Comment: 3.2
  • Total Replies: 156
  • Sentiment Summary: Positive: 65%, Negative: 10%, Neutral: 25%

  ❓ Common Questions:
  • "What hosting service do you recommend?"
  • "Can I do this without coding experience?"
  • "How much does domain registration cost?"

  💡 Key Feedback Points:
  • Tutorial pace is perfect for beginners
  • More examples of finished websites requested
  • Viewers want follow-up video on advanced features

  🎯 Actionable Insights:
  • Create hosting comparison video
  • Add timestamps for different skill levels
  • Consider beginner-friendly series expansion

  🎨 Customization Options

  Analysis Depth: Adjust AI prompts for different analysis focuses (engagement, education, entertainment)
  Comment Limits: Modify maximum comments processed (default: 100, AI analysis: 50)
  Report Recipients: Send reports to multiple team members or clients
  Custom Metrics: Add specific analysis criteria for your content niche
  Multi-Channel: Process videos from multiple YouTube channels
  Scheduling: Set up regular analysis of your latest videos

  🏷️ Tags & Categories

  #youtube-analytics #comment-analysis #content-creator-tools #ai-sentiment-analysis #video-insights #audience-research #youtube-api #content-optimization #social-media-analytics #creator-economy #video-marketing #engagement-analysis #content-strategy #ai-reporting #youtube-automation

  💡 Use Case Examples

  Educational Channel: Analyze tutorial comments to identify confusing concepts and improve teaching methods
  Product Reviews: Monitor sentiment on review videos to understand customer satisfaction trends  
  Entertainment Creator: Track audience reactions to different content formats and optimize future videos

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.limit","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.youTube","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheetsTrigger"]

workflow_json_compressed:
  [encoded data, 7768 characters]

metadata_json:
  {"categories":["automation","integration","data processing","analytics","reporting"],"complexity":"complex","use_cases":["YouTube comment sentiment analysis","Audience insight reporting","Content optimization recommendations","Brand and competitor sentiment monitoring","Automated periodic analysis and reporting"],"estimated_setup_minutes":45,"required_services":["n8n platform (cloud or self-hosted)","Google Sheets","YouTube Data API (Google Cloud)","OpenAI API (GPT-4)","Gmail or SMTP for email delivery"],"key_features":["Monitors Google Sheets for new video IDs","Fetches up to 100 top YouTube comments per video","GPT-4 powered sentiment, theme and question extraction","Generates HTML-formatted email reports with statistics and recommendations","Updates spreadsheet status to prevent duplicate processing and track workflow state','Configurable analysis depth, comment limits and report recipients"],"target_audience":["YouTube creators and content teams","Social media/marketing managers","Community managers and moderators','Educators and course creators','Agencies performing video/audience research"]}


name: Telegram Chat Summarizer with AI - using @telepilotco/n8n-nodes-telepilot
author_name: Alexey from Mingles.ai
author_username: alexx
categories: []
created_at: 2025-05-28T14:42:42.156Z
updated_at: 2025-05-28T14:42:42.156Z
url: https://n8n.io/workflows/4461
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Template Description
  Automatically generate intelligent summaries of your Telegram community discussions using AI, helping you stay updated on important conversations without reading every message.
  This powerful n8n automation monitors your Telegram chats and creates periodic AI-powered summaries, highlighting key trends, new ideas, and important updates. Perfect for busy community managers, team leads, and active group participants who want to stay informed without information overload.
  Key Features
  🤖 AI-Powered Analysis

  Smart Summarization: Uses OpenRouter AI models to analyze conversation patterns
  Trend Detection: Identifies emerging topics and discussion themes
  Context Awareness: Maintains conversation history through MongoDB memory
  Intelligent Filtering: Focuses on meaningful content while skipping noise

  ⏰ Flexible Scheduling

  Automated Execution: Runs every 2 hours automatically
  Manual Triggers: Execute on-demand for instant summaries
  Time-Based Filtering: Analyzes only recent messages (last 2 hours)
  Customizable Intervals: Easy to adjust frequency based on chat activity

  📱 Advanced Telegram Integration

  TelePilot Integration: Full Telegram userbot capabilities
  Chat Access: Can monitor any public or private chat you have access to
  Message History: Retrieves up to 100 recent messages per execution
  Real-time Processing: Handles various message types and formats

  🧠 Persistent Memory System

  MongoDB Storage: Maintains conversation context across executions
  Chat-Specific Memory: Separate memory for each monitored chat
  Historical Awareness: Avoids repeating previously summarized content
  Scalable Architecture: Handles multiple chats simultaneously

  How It Works
  Chat Monitoring

  Connects to specified Telegram chat using TelePilot
  Retrieves recent message history (configurable limit)
  Filters messages from the last 2 hours

  Message Processing

  Extracts text content from various message types
  Filters out empty messages and system notifications
  Structures data for AI analysis (sender_id, text, timestamp)

  AI Analysis

  Aggregates filtered messages into conversation context
  Applies AI summarization with custom system prompts
  Identifies trends, new ideas, and important updates
  Maintains awareness of previous summaries to avoid repetition

  Summary Delivery

  Posts AI-generated summary back to the chat
  Includes conversation trends and key highlights
  Formatted for easy reading and quick understanding

  Setup Requirements
  TelePilot Plugin Installation
  Before using this template, install the TelePilot community node:

  Go to Settings → Community modules in your n8n instance
  Select "Install Community node"
  Specify the name: @telepilotco/n8n-nodes-telepilot
  Check the risk acknowledgment checkbox and click "Install"

  Required Integrations

  TelePilot Account: For Telegram userbot functionality (Full Documentation)
  OpenRouter API: For AI summarization capabilities
  MongoDB Database: For persistent conversation memory
  Target Telegram Chat: Public or private chat access

  TelePilot Authentication
  After installation, you'll need to authenticate your Telegram account:

  Click the "Chat" button at the bottom of the n8n interface
  Type /start in the chat window and follow instructions
  Keep your smartphone or desktop Telegram app ready to receive the authentication code

  📖 Complete TelePilot Setup Guide
  Configuration Options

  Chat Selection: Easily change target chat by username
  Schedule Frequency: Adjust from 2-hour default to your needs
  Message Limit: Control how many messages to analyze
  Summary Style: Customize AI prompts for different summary formats

  Perfect For

  Community Managers: Keep track of multiple active groups
  Team Leaders: Stay updated on team discussions across time zones
  Active Group Members: Catch up on missed conversations quickly
  Content Creators: Monitor audience discussions and feedback
  Research Teams: Track ongoing project conversations
  Global Teams: Bridge communication gaps across different schedules

  Key Benefits
  ✅ Never Miss Important Updates: Stay informed without constant monitoring
  ✅ Reduce Information Overload: Get concise summaries instead of hundreds of messages
  ✅ Maintain Context: AI remembers previous summaries to avoid repetition
  ✅ Flexible Scheduling: Automated or manual execution options
  ✅ Multi-Chat Support: Monitor multiple communities simultaneously
  ✅ Trend Analysis: Identify emerging topics and discussion patterns
  ✅ Time-Efficient: Spend minutes instead of hours catching up
  ✅ Scalable Solution: Works for groups of any size
  Use Cases

  Daily Team Standup Summaries: Automated updates for distributed teams
  Community Highlight Reels: Weekly summaries for large communities
  Project Status Updates: Track ongoing discussions and decisions
  Customer Feedback Analysis: Monitor support and feedback channels
  Event Planning Updates: Stay current on planning discussions
  Learning Community Insights: Track educational discussions and resources

  What's Included
  🔧 Complete Workflow: Ready to deploy with minimal configuration
  📋 Setup Instructions: Step-by-step TelePilot integration guide
  🎯 Smart Filtering: Pre-configured message processing logic
  🤖 AI Optimization: Fine-tuned prompts for quality summaries
  💾 Memory Management: MongoDB integration for context persistence
  ⚙️ Error Handling: Robust workflow with fallback mechanisms
  Transform your chat monitoring from overwhelming to insightful with this intelligent automation solution!

  Documentation: TelePilot Plugin Documentation
  Tags: #Telegram #AI #ChatSummary #CommunityManagement #TelePilot #OpenRouter #MongoDB #Automation #TeamCommunication #ContentCuration

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.memoryMongoDbChat","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.filter","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","community management","monitoring","AI summarization"],"complexity":"medium","use_cases":["Automated team standup / status summaries","Community highlight reels and recap posts","Project discussion tracking and decisions log","Customer feedback monitoring and synthesis","Event planning updates and coordination summaries"],"estimated_setup_minutes":30,"required_services":["TelePilot (n8n community node) for Telegram userbot","Telegram account and access to target chat(s)","OpenRouter API (or compatible LLM endpoint)","MongoDB database for persistent memory","n8n instance with community modules enabled"],"key_features":["AI-powered conversation summarization (OpenRouter)","Trend detection and topic identification","Persistent chat-specific memory via MongoDB","Scheduled (default every 2 hours) and manual triggers","Message extraction and noise filtering (various types supported)"],"target_audience":["Community managers","Team leads / project managers","Content creators / social managers"]}


name: Birthday and Ephemeris Notification (Google Contact, Telegram & Home Assistant)
author_name: Thibaud
author_username: tderouze
categories: []
created_at: 2025-05-28T15:15:56.015Z
updated_at: 2025-05-28T15:15:56.015Z
url: https://n8n.io/workflows/4462
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  How it works:
  Schedule Trigger** on a daily basis (configured at 7.30 am)
  Connects Google Contacts** to get personal information from them
  Field Checker** on birthday date & firstnames. And see if there is any celebration for today
  Send a Telegram Notification** and display the message on a Google Home Speaker via Home Assistant if any celebration has matched

  Set up steps:
  Download* the workflow and *import** it into your n8n instance
  Configure accounts** for Google Contacts, Telegram and Home Assistant
  And you will be good to go

nodes_used:
  ["n8n-nodes-base.googleContacts","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.homeAssistant","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5264 characters]

metadata_json:
  {"categories":["automation","integration","home-automation","notifications","scheduling"],"complexity":"medium","use_cases":["Automated birthday reminders from Google Contacts","Morning announcements on Google Home via Home Assistant","Send celebration messages to Telegram groups or users","Daily ephemeris/event checks and notifications","Contact-driven automated notifications"],"estimated_setup_minutes":20,"required_services":["Google Contacts API / Google account","Telegram (bot/API)","Home Assistant (with TTS / Google Home integration)","n8n instance"],"key_features":["Daily scheduled trigger to run checks automatically","Reads contact data from Google Contacts","Field checking/conditional logic to detect birthdays/celebrations","Sends Telegram notifications when matches found","Triggers Home Assistant to announce messages on Google Home speakers (TTS via HTTP/Webhook integration option available)"],"target_audience":["home automation enthusiasts","individuals/families who want automated reminders","n8n users/integrators building notification workflows"]}


name: Automated Workflow Backups to GitHub with PR Creation & Slack Notifications
author_name: Bao Duy Nguyen
author_username: duynb
categories: []
created_at: 2025-05-28T15:59:53.436Z
updated_at: 2025-05-28T15:59:53.436Z
url: https://n8n.io/workflows/4463
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?

  This template is ideal for DevOps engineers, automation specialists, and n8n users who manage multiple workflows and want a reliable version control system for backups. It’s especially useful for teams collaborating via GitHub.

  What problem is this workflow solving?

  Manually backing up n8n workflows to GitHub can be time-consuming and error-prone. This workflow solves that by automating the backup of new and updated n8n workflows, ensuring your GitHub repository always reflects the latest changes.

  What this workflow does
  Retrieves all workflows from your local n8n instance.
  Decodes their content and compares it with existing GitHub files.
  Detects newly created or updated workflows.
  Creates a new Git branch and commits changes.
  Opens a pull request (PR) to the main branch.
  Sends a Slack notification when the PR is created.

  The system uses GitHub API, n8n, Merge, Set, and Slack nodes for full automation.

  Setup
  GitHub credentials: Add your GitHub API credentials in n8n.
  Slack integration: Connect your Slack Bot token if you want PR notifications.
  Repository details: Update github_owner, repo_name, and workflow directory path in the “Define Local Variables” node.
  n8n API key - Check this doc

  How to customize this workflow to your needs
  Change the workflow directory from workflows/ to a custom path.
  Modify the Slack message or add email notification support.
  Add filters to back up only specific workflows based on naming or tags.
  Adjust branch naming conventions or use different GitHub base branches.

  This workflow provides a seamless backup and versioning pipeline, minimizing manual Git interactions and supporting collaborative automation development.

nodes_used:
  ["n8n-nodes-base.n8n","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.slack","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4512 characters]

metadata_json:
  {"categories":["automation","integration","backup","version-control"],"complexity":"medium","use_cases":["Automated backup of n8n workflows to GitHub","Maintaining version history and collaboration via pull requests","Detecting and committing new or updated workflows","Notifying teams of backup PRs via Slack","Auditing and disaster recovery for automation assets"],"estimated_setup_minutes":20,"required_services":["GitHub (API access, repository)","n8n instance (API access)","Slack (Bot token for notifications)"],"key_features":["Fetch and decode workflows from local n8n","Compare workflow contents to files in GitHub","Automatically create branches and commit changes","Open pull requests against main branch","Send Slack notifications when PRs are created or updated (optional customization available)"],"target_audience":["DevOps engineers","Automation specialists","n8n users managing multiple workflows or teams"]}


name: Export AI Agent Conversation Logs from Postgres to Google Sheets
author_name: Agent Studio
author_username: agentstudio
categories: []
created_at: 2025-05-28T16:04:09.907Z
updated_at: 2025-05-28T16:04:09.907Z
url: https://n8n.io/workflows/4464
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Overview
  This n8n workflow retrieves AI agent chat memory logs stored in Postgres and pushes them to Google Sheets, creating one sheet per session. It’s useful for teams building chat-based products or agents and needing to review or analyze session logs in a collaborative format.

  Who is it for
  Anyone with an AI Agent in Production storing the conversation logs in Postgres (or Supabase) who wants to see transcript and have control
  Product teams building AI agents or assistants.
  Teams that want to centralize conversation history for analysis or support.
  Anyone managing AI chat memory and needing to explore it in a spreadsheet.

  Prerequisites
  A Postgres database with a n8n_chat_histories table with an AI Agent connected to it. If you need an example, you can follow this tutorial
  Once done, you need to run the Postgresql query to add the created_at column (see Setup &gt; Add a datetime column)
  Google Sheets access and OAuth credentials connected to n8n.
  A Google Sheets document set up as a template (see below).

  Google Sheets Template
  This workflow expects a Google Sheets file where each session will be stored in its own tab. 
  A basic tab layout is duplicated and renamed with the session ID.
  👉 Use this template as a starting point
  Note: You can hide the template after the first tabs have been created

  How it works
  Trigger
     The workflow can be launched manually or on a schedule (e.g. daily at noon).

  Retrieve sessions
     Runs a SQL query to get distinct session_id values from the n8n_chat_histories table.

  Loop over sessions
  For each session:
     Clears the corresponding sheet (if it exists).
     Duplicates the template tab.
     Renames it with the current session_id.

  Fetch messages
     Selects all messages linked to the session from Postgres.

  Append to sheet
     Adds each message to the Google Sheet with columns:

     Who: speaker role (user, assistant, etc.)
     Message: text content
     Date: timestamp from created_at, formatted yyyy-MM-dd hh:mm:ss

  Notes
  The sheet is cleared and rebuilt each run to ensure logs are up-to-date.
  If a sheet for a session doesn’t exist, it will be created by duplicating the first tab (template)
  You can group sessions under a persistent ID (like user_id) by overriding session_id in your memory config.
  Works perfectly with Supabase by using PG credentials from the connection pooler.

  👉 If you're looking for a solution to better visualize and analyse conversations, reach out to us!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.postgres","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6888 characters]

metadata_json:
  {"categories":["integration","data processing","reporting"],"complexity":"medium","use_cases":["Export AI chat/conversation logs to a spreadsheet","Centralize session transcripts for review or support","Enable product/UX analysis of agent interactions","Share session histories with non-technical stakeholders"],"estimated_setup_minutes":30,"required_services":["n8n","Postgres (or Supabase) with n8n_chat_histories table","Google Sheets (Google account + OAuth credentials)","Google Drive (for sheet template storage)"],"key_features":["Retrieves distinct session IDs from Postgres and iterates over them","Creates/duplicates a template tab per session and renames it","Appends message rows with Who, Message, Date (formatted)","Clears and rebuilds sheets to keep logs up-to-date","Can run manually or on a schedule (cron-like automation)"],"target_audience":["Product teams building chat-based products or agents","Support teams needing readable transcripts","Developers / DevOps managing AI agents and logs (Supabase users included)"]}


name: AI-Powered Document Chat with Nextcloud Files using LangChain and OpenAI
author_name: johappel
author_username: johappel
categories: []
created_at: 2025-05-28T16:28:03.885Z
updated_at: 2025-05-28T16:28:03.885Z
url: https://n8n.io/workflows/4465
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Main Workflow “AI Nextcloud”

  Entry point**: A public chat-trigger greets the user; every incoming chat message starts the flow.
  AI agent**: A LangChain agent (“AI Nextcloud”) uses the configured OpenAI model plus short-term memory to continue the dialogue in context.
  Purpose**: Answers questions about files stored in a Nextcloud folder. The user simply includes the folder path in their question.
  Tool integration**: Calls the sub-workflow “Nextcloud Tool” whenever it needs to read files and pass their text back to the AI.

  Sub-Workflow “Nextcloud Tool”

  Invocation: Triggered by other workflows with the input parameter path (folder path).
  File listing: Retrieves every file in the specified folder via the Nextcloud API.
  Filter: Allows only readable formats (PDF, Markdown, DOCX).
  Download & text extraction

     PDF → Text via Extract From File
     Markdown → Raw text
     DOCX → Text via community node word2text
  Aggregation: Combines all extracted text into a single output field and returns it.

  &gt; Outcome: Each call yields the plain content of every supported file in a Nextcloud folder—providing rich context for the AI agent to answer user questions accurately.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.switch","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.nextCloud","n8n-nodes-base.nextCloud","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-word2text.word2text"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","document processing","AI/chatbot"],"complexity":"complex","use_cases":["Answering questions about documents stored in Nextcloud folders","Internal knowledge-base/chatbot for teams","Customer support using product manuals and docs","On-demand document summarization and retrieval"],"estimated_setup_minutes":45,"required_services":["Nextcloud (API access)","OpenAI (API key)"],"key_features":["Public chat trigger for user queries","LangChain agent using OpenAI model with short-term memory","Sub-workflow to list, filter (PDF/MD/DOCX), download and extract text from files","File-type specific extraction: PDF, Markdown, DOCX","Aggregation of all extracted text into a single context payload for the AI agent','Callable Nextcloud Tool sub-workflow for reuse"],"target_audience":["Developers/engineers setting up n8n automations","Technical support and documentation teams","Product managers or knowledge managers who want document Q&A"]}


name: Generate Enhanced AI Images via Telegram with DALL-E and GPT
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-28T17:41:27.309Z
updated_at: 2025-05-28T17:41:27.309Z
url: https://n8n.io/workflows/4467
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  PromptCraft AI – Telegram Image Generator

  🚀 How It Works

  PromptCraft AI is an n8n automation that transforms simple image ideas sent through Telegram into stunning AI-generated images using OpenAI's DALL·E (or other image models).

  🔁 Workflow Overview:

  Telegram Trigger: Listens for messages from a user on Telegram.
  Prompt Expansion: The message is transformed into a rich image description using GPT (OpenAI Chat Model).
  Image Generation: The prompt is passed to OpenAI's image API to generate a high-quality image.
  Send Image: The final image is sent back to the user on Telegram.
  (Optional) Log image titles and links to Google Drive and Google Sheets.

  ⚙️ Setup Instructions

  📋 Prerequisites

  [ ] n8n installed (Self-hosted or via n8n.cloud)
  [ ] Telegram bot token (via @BotFather)
  [ ] OpenAI API key (platform.openai.com)
  [ ] Google Sheets & Drive OAuth2 credentials (optional)

  🧠 Step-by-Step Configuration

  1. 📥 Import the Workflow

  Go to n8n → click Import → upload PromptCraft_AI_Template.json

  2. 🔐 Set Up Credentials

  In Credentials, add the following:

    Telegram API → Paste your bot token
    OpenAI API → Paste your OpenAI API key
    (Optional) Google Sheets OAuth2, Google Drive OAuth2

  3. 🔄 Replace Placeholders

  Open each node that requires credentials:

    Replace REPLACE_OPENAI_API_KEY with your actual OpenAI API key
    Replace REPLACE_TELEGRAM_API_ID and credential names as needed
    (Optional) Update Google Drive Folder ID & Sheet ID in respective nodes

  4. ✅ Activate the Workflow

  Turn on the Telegram Trigger node.
  Deploy and activate the full workflow.

  5. ✉️ Test It Out

  Send your Telegram bot a message like:

    &gt; a knight riding a robotic horse in the future

  Receive the generated image back in Telegram!

  💡 Pro Tips

  Use detailed or imaginative inputs for better outputs.
  Fine-tune the GPT prompt for specific visual styles.
  Extend with Google Vision, image upscaling, or watermarking.

  🛟 Support

  For setup assistance or custom feature requests, feel free to contact me @dimejicole21@gmail.com

  Happy Prompting! 🖼✨

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","AI image generation","chatbot","content creation"],"complexity":"medium","use_cases":["Turn short Telegram prompts into detailed image-generation prompts","Generate images via OpenAI DALL·E (or other image models) and return them to users","Log image metadata and links to Google Drive and Google Sheets","Create a lightweight image-generation bot for communities or teams","Prototype visual concepts quickly from chat input"],"estimated_setup_minutes":20,"required_services":["n8n (self-hosted or n8n.cloud)","Telegram Bot API (bot token)","OpenAI API (Chat completions + Images/DALL·E)","Google Drive OAuth2 (optional)","Google Sheets OAuth2 (optional)"],"key_features":["Telegram trigger to receive user prompts","GPT-based prompt expansion/enrichment","Image generation using OpenAI image API","Send generated images back via Telegram","Optional logging of image titles/links to Google Drive and Google Sheets for audit/history"],"target_audience":["developers implementing chat-based automations","Community managers and moderators wanting a bot","Digital artists and designers for rapid ideation\",\"marketers and content creators\",\"hobbyists exploring AI image generation"]}


name: Generate AI Media with ComfyUI: Images, Video, 3D & Audio Bridge
author_name: Nielo
author_username: anomali
categories: []
created_at: 2025-05-28T18:41:49.542Z
updated_at: 2025-05-28T18:41:49.542Z
url: https://n8n.io/workflows/4468
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Unlock low-cost, high-control generative media workflows directly from n8n by integrating with ComfyUI. Ideal for indie creators, AI developers, or small teams seeking scalable media automation—from images to video, 3D, and even audio—this workflow makes generative content production more flexible and programmable than ever.

  How it works

  Accept a media generation request via an n8n trigger (HTTP webhook, schedule, etc.)
  Parse input and inject it into a ComfyUI payload
  Send the payload to your local or remote ComfyUI instance
  Wait for and collect the output media files (e.g., images, videos, 3D models, or audio)
  Send the result to a destination like email, Telegram, S3, or upload it back to a CMS or client app

  ✨ The format and complexity of the media are entirely dependent on the ComfyUI workflow you use, meaning this n8n integration is as powerful and creative as your ComfyUI setups.

  Set up steps

  Set up and run a local or remote ComfyUI instance with API access enabled
  Load or create a ComfyUI workflow that suits your content goals (image gen, video stitching, etc.)
  Open this n8n template and set your ComfyUI server URL, input template, and output handling preferences
  Connect additional services for input (e.g., Airtable, HTTP) and output (e.g., Notion, Slack, S3) depending on your use case

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.convertToFile","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.discord","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.executeWorkflow","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.crypto","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","media processing","AI/ML"],"complexity":"complex","use_cases":["Generate images, video, 3D models, or audio via ComfyUI from n8n triggers","Automate media pipelines (webhook → ComfyUI → storage/notification)","Batch or scheduled generative media production","Publish generated assets to CMS, S3, email, or messaging apps","Prototype or integrate custom ComfyUI workflows into apps"],"estimated_setup_minutes":60,"required_services":["ComfyUI (local or remote instance with API access)","n8n (workflow host)","Optional output services: Amazon S3 (or other object storage), Email/SMTP provider, Telegram API","Optional input/output systems: Airtable, Notion, CMS or client app endpoints"],"key_features":["Accepts generation requests via HTTP webhook or schedule","Injects parsed inputs into ComfyUI payloads","Sends payloads to local/remote ComfyUI and awaits outputs","Handles multiple media types: images, video, 3D, audio (dependent on ComfyUI workflow)","Flexible output routing: email, Telegram, S3, CMS, or uploads back to client app/storage ﬁnishes workflow automation and error handling hooks"],"target_audience":["indie creators","AI developers","small teams building media automation pipelines"]}


name: Jobs Newsletter Automation System (N8N, Bolt.new, RapidAPI, Mails.so & ChatGPT)
author_name: Joseph
author_username: mjomba
categories: []
created_at: 2025-05-28T19:53:27.231Z
updated_at: 2025-05-28T19:53:27.231Z
url: https://n8n.io/workflows/4470
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Watch on Youtube▶️

  Welcome to this complete step-by-step guide on how to build your own newsletter automation system using n8n, Bolt.new, and RapidAPI. Whether you're a solo founder, indie hacker, or community builder, this setup will allow you to collect subscribers, send them curated job updates, and manage unsubscriptions — all with full control and zero reliance on third-party newsletter tools.

  🚀 Goal of This Guide

  By the end of this guide, you will have a fully working system that allows you to:
  Collect user subscriptions from a modern frontend interface
  Send welcome or rejection emails (using your own SMTP)
  Automatically scrape jobs via an API and send them to subscribers weekly or daily
  Manage unsubscriptions with confirmation and webhook logic
  Customize and manage all this using n8n workflows with no-code/low-code skills

  This system is perfect for niche job boards, community newsletters, or any project that needs automated content delivery to subscribers.

  🧱 Tools You'll Be Using

  n8n** – for automation workflows and acting as your backend
  Bolt.new** – to build your newsletter landing page and subscription interface
  Google Sheets** – to act as your lightweight subscriber/job database
  RapidAPI** – to pull job listings from the Jobs Search API
  Custom SMTP Email (Optional)** – to send branded emails using your own domain

  📄 Step 1: Set Up Your Google Sheets Database

  Make a copy of this Google Sheets template that will serve as your database:

  🔗 Click here to copy the Google Sheet template](https://docs.google.com/spreadsheets/d/11vxYkjfwIrnNHN6PIdAOa_HZdTvMXI0lm_Jecac4YO0/edit?gid=0#gid=0)

  This includes:
  A Subscribers sheet to store new signups
  An Unsubscribers sheet to prevent duplicates
  A Jobs sheet to store scraped job listings

  ⚙ Step 2: Get Your API Key for Jobs Scraping

  We use this API from RapidAPI to pull job listings programmatically:

  🔗 Jobs Search API on RapidAPI

  Sign up or log into RapidAPI
  Subscribe to the Jobs Search API
  Copy your API key — you'll need this in n8n

  ⚙ Step 3: Get Your API Key for Email Validation

  We use this API from Mails.so to confirm email's validity before adding them to our database:

  🔗 Mails.so API

  Sign up or log into mails dot so
  Visit the dashboard, then click on API
  Copy the cURL command and import on http request node

  🌐 Step 4: Set Up Your Frontend with Bolt.new

  You'll be building a beautiful, modern newsletter landing page using Bolt.new.

  Use this link for prompts to generate:
  Your landing page
  Email templates (welcome, already subscribed, unsubscribe confirmation)
  Terms & Privacy Policy pages
  Unsubscribe confirmation page

  🔗 Access the Bolt.new Prompt Document

  This includes:
  A homepage form with input fields (Name, Email) and consent checkbox
  Logic to send data to n8n webhook using fetch()
  UI logic for showing webhook response (Success, Already Exists, Invalid Email)
  Unsubscribe page handling

  (Make your own copy so that you can edit it while we format the prompts)

  📤 Step 5: Set Up Email Sending With Your Custom Domain (Optional but Recommended)

  To send branded HTML emails from your own domain, follow this tutorial to configure SMTP properly on n8n with your cPanel email account:

  🔗 Guide: How to Set Up SMTP with cPanel Email on n8n

  This setup helps:
  Improve deliverability
  Avoid Gmail spam filters
  Send beautiful HTML emails you can customize fully

  🔄 Step 6: Create n8n Workflows for Subscription Management

  In n8n, you'll need to build these workflows:

  ✅ 1. Handle Subscriptions
  Receives webhook from frontend with name and email
  Validates email (using mails.so)
  Checks if already subscribed
  Sends appropriate HTML email (Welcome, Already Exists, Invalid Email)
  Adds to Google Sheet database

  ✅ 2. Scrape Jobs and Email Subscribers
  Use Cron node to run daily/weekly
  Use RapidAPI to fetch new jobs
  Format jobs into readable HTML
  Send jobs to all active subscribers via SMTP

  ✅ 3. Handle Unsubscriptions
  Expose a webhook for /unsubscribe
  Confirm email, show a button
  On confirmation, add email to Unsubscribers sheet
  Show feedback and redirect user back to homepage after 2 seconds

  🧠 What You're Learning Along the Way

  How to use n8n as a backend service (reliable, scalable, visual)
  How to use webhooks to connect frontend and backend logic
  How to scrape APIs, format JSON data, and convert it to HTML emails
  How to use Function nodes for data processing
  How to build logic with IF and Switch nodes
  How to design a minimal, clean frontend with Bolt.new
  How to control the entire newsletter system without external platforms

  Follow me on twitter @juppfy | or check out my agency website.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.emailSend","n8n-nodes-base.if","n8n-nodes-base.merge","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.webhook","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stopAndError","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.emailSend","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 11468 characters]

metadata_json:
  {"categories":["automation","integration","data processing","email/newsletter"],"complexity":"complex","use_cases":["Collect and manage newsletter subscribers via a custom frontend","Validate emails and prevent duplicate subscriptions","Scrape job listings from an API and curate/send them to subscribers","Send branded HTML emails via custom SMTP","Handle unsubscribe flow with confirmation and webhook logic"],"estimated_setup_minutes":120,"required_services":["n8n","Bolt.new (frontend)","Google Sheets","RapidAPI (Jobs Search API)","Mails.so (email validation API)","Custom SMTP / cPanel email (or other SMTP provider)"],"key_features":["Frontend subscription form (Bolt.new) -> webhook to n8n","Email validation before adding subscribers (Mails.so)","Subscriber and unsubscribers storage in Google Sheets","Scheduled job scraping via RapidAPI and formatting to HTML","Bulk/email-per-subscriber sending via SMTP from n8n (welcome, digests, invalid/already-subscribed responses)"],"target_audience":["solo founders","indie hackers","community builders and niche job-board operators`,`no-code/low-code builders and technical marketers"]}


name: Github Webhook-Based n8n Workflow Import Template
author_name: Dave Bernier
author_username: dbern
categories: []
created_at: 2025-05-28T21:24:41.338Z
updated_at: 2025-05-28T21:24:41.338Z
url: https://n8n.io/workflows/4471
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
description:
  This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 

  This template aims to ease the process of deploying workflows from github. It has a companion repository that developers might find useful{. See below for more details

  How it works

  Automatically import and deploy n8n workflows from your GitHub repository to your production n8n instance using a secured webhook-based approach. This template enables teams to maintain version control of their workflows while ensuring seamless deployment through a CI/CD pipeline.

  Receives webhook notifications from GitHub when changes are pushed to your repository
  Lists all files in the repository and filters for .json workflow files
  Downloads each workflow file and saves it locally
  Imports all workflows into n8n using the CLI import command
  Cleans up temporary files after successful import

  To trigger the deployment, send a POST request to your webhook with the set up credentials (basic auth) with the following body:
  {
    "owner": "GITHUB_REPO_OWNER_NAME",
    "repository": "GITHUB_REPOSITORY_NAME"
  }

  Set up steps
  Once importing this template in n8n :
  Setup the webhook basic auth credentials
  Setup the github credentials
  Activate the workflow !

  Companion repository
  There is a companion repository located at https://github.com/dynamicNerdsSolutions/n8n-git-flow-template that has a Github action already setup to work with this workflow.

  It provides a complete development environment with:
  Local n8n instance via Docker
  Automated workflow export and commit scripts
  Version control integration
  CI/CD pipeline setup

  This setup allows teams to maintain a clean separation between development and production environments while ensuring reliable workflow deployment.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.noOp","n8n-nodes-base.executeCommand","n8n-nodes-base.stickyNote","n8n-nodes-base.github","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.github","n8n-nodes-base.readWriteFile","n8n-nodes-base.executeCommand"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","CI/CD","deployment"],"complexity":"medium","use_cases":["Automatically deploy n8n workflows from a GitHub repo to production","Maintain version-controlled workflows and sync changes via webhooks","Implement CI/CD pipeline for n8n workflow delivery","Automate workflow import and cleanup on update events"],"estimated_setup_minutes":30,"required_services":["GitHub (repository and webhooks)","Self-hosted n8n instance (CLI access)","Optional: GitHub Actions / Docker for companion repo local dev environment"],"key_features":["Webhook-secured trigger with basic auth","Lists and filters repository files for .json workflow exports","Downloads workflow files and imports them into n8n via CLI","Cleans up temporary files after import","Designed to integrate with a companion GitHub Actions repository for CI/CD"],"target_audience":["Developers","DevOps / SRE teams","Automation engineers managing n8n at scale"]}


name: AI-Powered Loom Video Q&A with Gemini-2.5 and Slack Notifications
author_name: GiovanniSegar
author_username: giosegar
categories: []
created_at: 2025-05-28T21:48:31.259Z
updated_at: 2025-05-28T21:48:31.259Z
url: https://n8n.io/workflows/4472
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  How to use the workflow
  This workflow takes a Loom link, extracts the video ID, uses the Loom API to download the video, then sends it to Gemini along with your question. Finally, it sends the output to Slack. 

  To use it, you just need to add your own API key for Gemini and Slack connection. 

  Click the link above to get your Gemini API key, then add a generic "Query auth" type credential in n8n. The name will be "key" and the value will be your API key.

  One way to customize this workflow would be to make the trigger any received email, extract the Loom link, and run an auto-prompt like "Describe this video in detail". 

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.slack","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5924 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","video processing","communication"],"complexity":"medium","use_cases":["Ask/answer questions about Loom videos","Generate meeting summaries or highlights","Support ticket/context enrichment from recorded demos","Content repurposing (create notes, captions, or blog drafts)","Automated training/onboarding Q&A from demo videos"],"estimated_setup_minutes":20,"required_services":["Loom API","Gemini (Gemini-2.5) API / Google Vertex AI (API key)","Slack (workspace + bot token)","n8n instance"],"key_features":["Extract Loom video ID from a link and download the video via Loom API","Send video and a user question to Gemini-2.5 for analysis/answering","Post AI-generated answers to Slack channels/users","Configurable trigger (webhook, email, etc.) and custom prompts","Batching and branching logic to handle processing and errors (splitInBatches, if, merge nodes)"],"target_audience":["Developers/automation engineers","Product managers and ops","Customer support teams and success managers"]}


name: Automate Multi-Channel Customer Support with Gmail, Telegram, and GPT AI
author_name: RedOne
author_username: redone
categories: []
created_at: 2025-05-29T05:09:06.053Z
updated_at: 2025-05-29T05:09:06.053Z
url: https://n8n.io/workflows/4474
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Smart Customer Support AI Agent with Gmail and Telegram

  Who is this for?

  This workflow is perfect for:
  Small to medium businesses** looking to automate customer support
  E-commerce stores** handling order inquiries and customer questions
  SaaS companies** providing technical support to users
  Service providers** managing appointment bookings and general inquiries
  Startups** wanting to provide 24/7 customer service without hiring full-time staff
  Agencies** managing client communications across multiple channels

  What problem is this workflow solving?

  Customer support is essential but resource-intensive. Common challenges include:
  Slow response times** leading to frustrated customers
  Repetitive questions** consuming valuable staff time
  Inconsistent responses** across different support agents
  Limited availability** outside business hours
  Scaling support costs** as business grows
  Context loss** when customers switch between channels

  This workflow eliminates these pain points by providing instant, consistent, and intelligent responses 24/7.

  What this workflow does

  Core Functionality
  Multi-Channel Monitoring: Simultaneously watches Gmail and Telegram for customer inquiries
  Intelligent Processing: Uses AI to understand customer intent and context
  Knowledge Base Integration: Accesses your company's FAQ and support information
  Contextual Responses: Provides personalized, helpful replies maintaining conversation history
  Smart Escalation: Automatically escalates complex issues to human agents
  Comprehensive Logging: Tracks all interactions for analytics and improvement

  AI Agent Capabilities
  Natural Language Understanding**: Comprehends customer questions in plain English
  Context Awareness**: Remembers previous conversations with each customer
  Knowledge Retrieval**: Searches your knowledge base for accurate information
  Response Generation**: Creates professional, brand-appropriate responses
  Escalation Decision**: Identifies when human intervention is needed
  Multi-Channel Support**: Handles Gmail and Telegram with channel-specific formatting

  Automation Features
  Auto-Response**: Replies to customers within seconds
  Email Management**: Marks processed emails as read
  Conversation Threading**: Maintains context in email threads and Telegram chats
  Error Handling**: Gracefully handles failures with admin notifications
  Analytics Tracking**: Logs interactions for performance monitoring

  Setup

  Prerequisites
  Active Google Workspace or Gmail account
  Telegram account for bot creation
  OpenAI API access
  Google Sheets access
  n8n instance (cloud or self-hosted)

  Step 1: Credential Setup

  Gmail OAuth2 Configuration
  Go to Google Cloud Console
  Create new project or select existing one
  Enable Gmail API
  Create OAuth 2.0 credentials
  Add authorized redirect URIs for n8n
  In n8n: Settings → Credentials → Add Gmail OAuth2
  Enter Client ID and Client Secret
  Complete OAuth flow

  Telegram Bot Setup
  Message @BotFather on Telegram
  Create new bot with /newbot command
  Choose bot name and username
  Copy the bot token
  In n8n: Settings → Credentials → Add Telegram
  Enter bot token
  Set webhook URL in bot settings

  OpenAI API Configuration
  Sign up at OpenAI Platform
  Generate API key in API Keys section
  In n8n: Settings → Credentials → Add OpenAI
  Enter API key
  Choose appropriate model (gpt-4o-mini recommended)

  Google Sheets Setup
  Use existing Google account from Gmail setup
  In n8n: Settings → Credentials → Add Google Sheets OAuth2
  Complete authorization flow

  Step 2: Google Sheets Preparation

  Create three Google Sheets in your Google Drive:

  Knowledge Base Sheet
  Sheet Name**: "Knowledge Base"
  Columns**: ID, Category, Question/Topic, Answer/Response, Keywords, Last_Updated
  Import sample data from the Knowledge Base example
  Customize with your company's FAQs and policies

  Escalation Tracker Sheet
  Sheet Name**: "Escalations" 
  Columns**: Timestamp, Customer_Name, Customer_Contact, Inquiry_Summary, Escalation_Reason, Priority, Status, Assigned_To
  This will be auto-populated by the AI agent

  Interaction Log Sheet
  Sheet Name**: "Interaction Log"
  Columns**: Timestamp, Channel, Customer_Name, Customer_Contact, Inquiry_Subject, Customer_Message, AI_Response, Response_Time, Status
  This tracks all customer interactions for analytics

  Step 3: Workflow Configuration

  Import Template
  Copy the workflow JSON from the template
  In n8n: Import workflow from JSON
  Replace placeholder Sheet IDs with your actual Google Sheet IDs

  Update Sheet References
  Open each Google Sheets node
  Select your created sheets from the dropdown
  Verify column mappings match your sheet structure

  Customize AI Prompts
  Edit the "Customer Support AI Agent" node
  Update system message with:
     Your company name and description
     Brand voice and tone guidelines
     Specific policies and procedures
     Escalation criteria

  Configure Error Notifications (Optional)
  Set up Slack webhook or email notifications
  Update error notification node with your webhook URL
  Customize error message format

  Step 4: Testing

  Test Gmail Integration
  Send test email to your support Gmail account
  Check workflow execution in n8n
  Verify response is sent and email marked as read
  Check interaction logging in Google Sheets

  Test Telegram Integration  
  Send message to your Telegram bot
  Verify bot responds appropriately
  Test conversation memory with follow-up messages
  Check escalation functionality with complex request

  Test Knowledge Base
  Ask questions covered in your knowledge base
  Verify AI retrieves and uses correct information
  Test with variations of the same question
  Ensure responses are consistent and helpful

  How to customize this workflow to your needs

  Brand Voice Customization
  Update the AI system prompt to include:
  Your company's tone (formal, casual, friendly)
  Key phrases and terminology you use
  Brand personality traits
  Communication style preferences

  Knowledge Base Expansion
  Add industry-specific FAQs
  Include product documentation
  Add troubleshooting guides
  Create category-specific responses

  Escalation Rules
  Customize when to escalate by modifying the AI agent instructions:
  Billing disputes over $X amount
  Technical issues requiring developer help
  Angry or dissatisfied customers
  Requests outside standard services
  Legal or compliance questions

  Additional Channels
  Extend the workflow to support:
  Slack**: Add Slack triggers and response nodes
  WhatsApp**: Integrate WhatsApp Business API
  Web Chat**: Add webhook triggers for website chat
  Discord**: Connect Discord bot integration

  Analytics Enhancement
  Add sentiment analysis to customer messages
  Implement customer satisfaction scoring
  Create automated reporting dashboards
  Set up alert thresholds for escalation rates

  Integration Opportunities
  CRM Integration**: Connect to HubSpot, Salesforce, or Pipedrive
  Ticketing System**: Link to Zendesk, Freshdesk, or Jira Service Desk
  E-commerce Platform**: Integrate with Shopify, WooCommerce, or Magento
  Calendar Booking**: Connect to Calendly or Acuity for appointment scheduling

  Advanced Features
  Multi-language Support**: Add translation capabilities
  Voice Messages**: Integrate speech-to-text for Telegram voice notes
  Image Recognition**: Process customer screenshots for technical support
  Proactive Outreach**: Send follow-up messages based on customer behavior

  Workflow Maintenance

  Daily Tasks
  Review escalation queue
  Monitor error notifications
  Check response quality in interaction log

  Weekly Reviews
  Analyze customer interaction patterns
  Update knowledge base with new common questions
  Review escalation reasons and optimize AI prompts

  Monthly Optimization
  Export interaction data for detailed analysis
  Calculate key metrics (response time, resolution rate, escalation rate)
  Update AI model parameters based on performance
  Expand knowledge base with seasonal or trending topics

  Key Metrics to Track

  Response Time**: Average time from customer message to AI response
  Resolution Rate**: Percentage of inquiries resolved without escalation  
  Customer Satisfaction**: Based on follow-up surveys or sentiment analysis
  Escalation Rate**: Percentage of conversations requiring human intervention
  Channel Performance**: Effectiveness of Gmail vs Telegram vs other channels
  Knowledge Base Usage**: Which topics are accessed most frequently
  Peak Hours**: When customers contact support most often

  Troubleshooting

  Common Issues
  Gmail not triggering**: Check OAuth permissions and API quotas
  Telegram bot not responding**: Verify bot token and webhook configuration
  AI responses seem off**: Review and update system prompts
  Escalations not logging**: Check Google Sheets permissions and column mapping
  High escalation rate**: Expand knowledge base and refine AI instructions

  Performance Optimization
  Monitor OpenAI API usage and costs
  Adjust AI model temperature for response consistency
  Optimize knowledge base for faster searches
  Set appropriate conversation memory limits

  This workflow provides a solid foundation for automated customer support that can be extensively customized to match your specific business needs and grow with your company.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.telegram","n8n-nodes-base.gmailTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.errorTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool"]

workflow_json_compressed:
  [encoded data, 6300 characters]

metadata_json:
  {"categories":["automation","integration","customer support","AI","omnichannel messaging"],"complexity":"medium","use_cases":["Automate multi-channel customer support (Gmail + Telegram)","Provide 24/7 instant responses and reduce repetitive tickets","Knowledge-base driven answer retrieval and contextual replies","Auto-escalation of complex issues to human agents","Centralized interaction logging and analytics"],"estimated_setup_minutes":90,"required_services":["Google Workspace / Gmail (OAuth2)","Telegram (Bot API)","OpenAI API (GPT model)","Google Sheets (for KB, logs, escalations)","n8n instance (cloud or self-hosted)"],"key_features":["Multi-channel monitoring (Gmail + Telegram)","Natural language understanding and response generation (OpenAI)","Knowledge base integration via Google Sheets","Conversation memory and contextual threading","Smart escalation to human agents and escalation tracker sheet population」「Automated email handling (mark as read) and channel-specific formatting」「Interaction logging and analytics tracking」「Error handling and admin notifications"],"target_audience":["Small & medium businesses","E-commerce stores","SaaS companies and support teams」「Service providers handling bookings/inquiries」「Startups needing 24/7 support without hiring full-time staff」「Agencies managing client communications"]}


