Workflow Templates

This workflow automatically fetches reviews for one or more Google Play Store apps, summarizes the feedback using OpenAI, stores and manages review data with Pinecone, and posts the summary to a Slack channel. It is designed for product teams, community managers, or anyone who wants to keep track of app sentiment and review trends without manually reading each review. Features: Fetches daily reviews for specified Google Play Store app bundle IDs using a Google Service Account. Stores reviews in a Pinecone vector database for efficient retrieval and summarization. Uses OpenAI to generate a summary, including: Positive and negative review highlights Star rating breakdown and average rating Total number of reviews processed Posts the summary to a Slack channel of your choice. Supports both daily and weekly triggers. Automatically clears old reviews from the vector store weekly to keep data fresh. Setup Instructions: Add your Google Play app bundle IDs in the “Set the bundle ids” node. Configure your Google Service Account, Pinecone, OpenAI, and Slack credentials. Set your preferred Slack channel in the “Send to Slack channel” node. Enable the workflow and customize the schedule as needed. Use Cases: Monitor app sentiment and user feedback trends. Share review insights with your team in Slack. Automate reporting for product or support teams.

🧠 How It Works This intelligent workflow turns ancient stories and legendary characters into modern-style vlog ideas — then automatically builds cinematic prompts ready to generate short videos using Veo3. Think: “What if biblical figures had GoPros?” — funny, emotional, and visually stunning AI-made videos. 🔄 Workflow Steps ✨ 1. Concept Generator (AI Node 1) The first AI agent creates a video concept inspired by a biblical or mythological theme. It structures output as JSON with: 🎬 caption – Short, emotional or humorous line with emojis & hashtags 💭 concept – A short summary of the story or moment captured on camera 🌄 setting – Visual and mood details (lighting, style, colors) 📋 status – Stage label like “draft” or “to produce” Example Output: { "caption": "POV: Moses trying to record a vlog mid–Red Sea split 🌊📹 #faithvibes #holyshorts", "concept": "Moses looks straight into the camera, trying to act calm while walls of water rise dramatically beside him.", "setting": "Vast sea corridor glowing in blue light, reflections dancing on wet sand, robes fluttering in the wind.", "status": "to produce" } 🎬 2. Cinematic Prompt Builder (AI Node 2) This agent converts the concept and setting into a Veo3-ready cinematic prompt that guides realistic video generation. Each output includes: Scene layout & description 🌅 Character framing & expression 🎭 Camera movement (pan, orbit, dolly-in, etc.) 🎥 Lighting style & atmosphere 💡 Textural realism (dust, wind, shadows, fabrics) Example Output: > A robed man stands between two towering walls of water, facing the camera as waves shimmer in the light. The handheld camera slowly pushes forward, capturing ripples and wind-blown fabric. His tone is confident yet tense. The atmosphere feels surreal — reflections glisten and mist drifts through golden rays. ☁️ 3. Send to Veo3 API The cinematic description is sent directly to the Veo3 video generation API to create the visual clip. POST Request https://queue.fal.run/fal-ai/veo3 Header → Authorization: Key YOUR_API_KEY Body → { "prompt": "{{ $json.output }}" } The API responds with a request_id to track progress. ⏳ 4. Track Video Progress Monitor generation status and retrieve your final clip details. GET Request https://queue.fal.run/fal-ai/veo3/requests/{{ $json.request_id }} Header → Authorization: Key YOUR_API_KEY When complete, the Veo3 model delivers your AI-generated short film. ⚙️ Setup Guide 1. Connect APIs • Create a Veo3 (fal.run) account • Copy your API key → Add it under Header Auth: Authorization: Key YOUR_API_KEY 2. Customize Prompts • Change the core question in Node 1 to explore other themes — e.g., “Greek myths,” “ancient warriors,” or “historic leaders.” • Refine the camera and lighting tone in Node 2 for different cinematic vibes (gritty, vintage, surreal). 3. Run & Validate • Trigger manually to test flow • Check JSON output → must include caption, concept, setting, status • Ensure Veo3 receives your cinematic prompt correctly 4. Automate & Expand • Add a Scheduler to generate new ideas daily or weekly • Send results to Google Sheets, Notion, or Discord for creative collaboration 🚀 Ideal For • 🎬 Creators & Filmmakers → Quickly generate cinematic ideas & AI-shot scripts • 🙏 Faith-Based Artists → Reimagine ancient lessons with modern storytelling • 💡 Creative Studios → Automate short video ideation for campaigns • 🧠 Educators & Animators → Visualize history or mythology through creative AI prompts

How It Works This template is a workflow that registers Jira tickets to Pinecone. By combining it with the Automated Jira Ticket Responses with GPT-4 and Pinecone Knowledge Base template, you can continuously improve the quality of automated responses in Jira. Prerequisites A Jira account and credentials (API key and email address) A Pinecone account and credentials (API key and environment settings) OpenAI credentials (API key) Setup Instructions Jira Credentials Register your Jira credentials (API key and email address) in n8n. Vector Database Setup (Pinecone) Register your Pinecone credentials (API key and environment variables) in n8n. AI Node Configure the OpenAI node with your credentials (API key). Step by Step Scheduled Trigger The workflow runs at regular intervals according to the schedule set in the Scheduled Trigger node. Jira Trigger (Completed Tickets) Retrieves the summary, description, and comments of completed Jira tickets. Register to Pinecone Converts the retrieved ticket information into vectors and registers them in Pinecone. Notes Configure the Scheduled Trigger interval carefully to avoid exceeding API rate limits. Further Reference For a detailed walkthrough (in Japanese), see this article: 👉 Automating knowledge registration to Pinecone with n8n (Qiita) You can find the template file on GitHub here: 👉 Template File on GitHub

How it works User enters name of a city for which most current weather information will be gathered Custom Python code processes the weather data and generates a custom email about the weather AI agent further customizes the email and add a related joke about the weather Recipient gets the custom email for the city Set up instructions Enter city to get the weather data Add OpenWeather API and replace <your_API_key> with your actual API key Add your OpenAI API in OpenAI Chat Model Node Add your Gmail credentials and specify a recipient for the custom email

Company Knowledge Base Assistant Who's it for This workflow is designed for companies looking to onboard new employees and interns efficiently. It's perfect for HR teams, team leaders, and organizations that want to provide instant access to company knowledge without manual intervention. Whether you're a startup or an established company, this assistant helps your team find answers quickly from your existing documentation. What it does This AI-powered chatbot automatically learns from your company documents stored in Google Drive and provides accurate, contextual answers to employee questions. The system continuously monitors a designated Drive folder, processes new documents, and makes them instantly searchable through a conversational interface. Key features: Automatic document ingestion from Google Drive Intelligent search across all company documents Conversational interface with memory Source citation for answers Real-time updates when new documents are added How it works The workflow has two main components: Document Processing Pipeline: Monitors your Google Drive folder every minute for new files. When a document is added, it's automatically downloaded, split into searchable chunks, converted into vector embeddings, and stored in an in-memory knowledge base. Chat Interface: Users send questions via webhook, the AI agent searches the knowledge base for relevant information, maintains conversation history for context, and returns accurate answers with source citations. Requirements Google Drive account with OAuth2 credentials Google Service Account for document downloads OpenAI API key for embeddings and chat model Designated Google Drive folder for company documents Setup Instructions Configure Google Drive: Set up Google Drive OAuth2 credentials in the "Watch Company Docs Folder" node Set up Google Service Account credentials in the "Fetch New Document" node Select your company documents folder in the trigger node Configure OpenAI: Add your OpenAI API key to both embedding nodes The workflow uses GPT-4 Mini for cost-effective responses Upload Your Documents: Add company handbooks, policies, procedures, and FAQs to the designated Drive folder Documents will be automatically processed within minutes Test the Chat Interface: The webhook endpoint accepts POST requests with this format: { "data": "Your question here", "session_id": "unique-user-id" } Integrate with Your Tools: Connect the webhook to Slack, Teams, or your internal chat platform Each user gets their own conversation history via session_id How to customize Change check frequency**: Adjust polling interval in "Watch Company Docs Folder" from every minute to hourly or daily Adjust chunk size**: Modify the "Split into Searchable Chunks" node to change how documents are segmented Increase context**: Change topK parameter in "Search Company Documents" to retrieve more relevant sections Extend memory**: Adjust contextWindowLength in "Conversation History" to remember more previous messages Switch AI model**: Replace GPT-4 Mini with GPT-4 or other models based on your accuracy needs Add filters**: Modify the system prompt to focus on specific departments or document types Custom responses**: Update the system message in "Company Knowledge Assistant" to match your company's tone Tips for best results Use clear, descriptive file names for documents in Drive Organize documents by department or topic in subfolders Include FAQ documents with common questions and answers Regularly update outdated documents to maintain accuracy Monitor the assistant's responses and refine the system prompt as needed

Overview Transform your receipt management with this comprehensive n8n workflow that automatically processes receipts through Telegram, extracts transaction data using AI, and stores it across multiple platforms for seamless expense tracking. Key Features 📱 Telegram Bot Integration**: Send receipts via photo or manual text entry 🔍 OCR Processing**: Automatic text extraction from receipt images using OCR.space API 🤖 AI Data Extraction**: OpenAI GPT-4 intelligently extracts vendor, amount, date, and category 📊 Multi-Platform Storage**: Automatically saves to Google Sheets, Notion, and custom APIs 💾 Receipt Archival**: Stores original receipt images in Google Drive ✅ Smart Validation**: Validates extracted data and handles errors gracefully 📲 Real-time Feedback**: Sends confirmation messages with transaction details How It Works Input Methods: Send receipt photos or text messages to your Telegram bot Image Processing: Downloads and processes receipt images using OCR technology AI Analysis: GPT-4 extracts structured transaction data from OCR text Data Validation: Ensures data quality and handles missing information Multi-Storage: Simultaneously saves to Google Sheets, Notion database, and external APIs Confirmation: Sends formatted confirmation with all transaction details Use Cases Personal expense tracking and budgeting Small business receipt management Travel expense documentation Tax preparation and record keeping Automated bookkeeping workflows Required Credentials Telegram Bot API (for bot functionality) OCR.space API (for receipt text extraction) OpenAI API (for AI data processing) Google Sheets OAuth2 (for spreadsheet storage) Google Drive OAuth2 (for image storage) Notion API (for database integration) Setup Notes Replace placeholder values in the workflow: YOUR_GOOGLE_SHEET_ID_HERE in Google Sheets node YOUR_NOTION_DATABASE_ID_HERE in Notion node YOUR_API_KEY_HERE and API endpoint in Website API node This workflow provides a complete solution for automated receipt processing, making expense tracking effortless through simple Telegram interactions while maintaining data across multiple platforms for maximum accessibility and backup.

AI-Powered LinkedIn Viral Content Generator & Telegram Bot Disclaimer: This workflow uses community-contributed nodes which are not officially maintained by n8n. Please test thoroughly before running in production. Do not use this template in production without your own independent validation. Overview This workflow empowers you to generate highly viral LinkedIn posts, including both compelling copy and AI-generated custom images, directly from a Telegram chat interface. Leveraging AI-powered research, GPT-based content creation, and community-based integrations, it creates a seamless automation: from prompt to trend analysis, viral copywriting, image generation, and message delivery—all in one flow. Node-by-Node Workflow Explanation Telegram Trigger:** Starts the workflow from a specified Telegram chat by capturing user prompts. Expert Algo (AI Analysis):** Uses OpenAI and Tavily to research current LinkedIn trends, analyzes top-performing content, and produces a content framework plus an AI image prompt. Structured Output Parser:** Validates and formats the AI's returned JSON output. CM Junior:** Generates three LinkedIn post drafts in your own style, based on the viral framework and rules. Structured Output Parser1:** Ensures correct JSON for the drafted posts. Community Manager:** Evaluates the draft posts using additional trend analysis via Tavily, selects the one most likely to go viral. Structured Output Parser2:** Validates the community manager's single post output. Generate Image:** Calls the AI image generator on RapidAPI to create a picture for your post, using the recommended prompt. Split Out/Download Image:** Prepares and downloads the generated image file. Send Telegram Photo and Message:** Sends the chosen LinkedIn post and the generated image to your Telegram bot. Setup Instructions Telegram: Create a bot using @BotFather and get your bot token and target chat ID. OpenAI: Register at OpenAI, obtain your API key. Tavily: Register at Tavily and get your API key. RapidAPI (AI Image Generator): Create an account, subscribe to the "ai-text-to-image-generator-flux-free-api", and copy your API key. Credentials: Use the n8n Credentials Manager to configure each key securely—never hardcode API keys into nodes. Workflow Personalization: Replace all placeholders like Telegram chat ID by referencing the credentials or environment variables. Testing: Run the workflow using your bot and ensure that no personal or sensitive data remains before publishing. Additional Recommendations Update the image generator, Telegram, OpenAI, and Tavily node credentials through the n8n Credentials panel. Custom tailor prompts and output formatting as needed for your LinkedIn content strategy. For security, do not share any personal API keys or chat IDs in your public template.

n8n – Outlook AI Categorization & Labeling (Fully Automated) > Zero manual mapping. The workflow automatically discovers your Outlook folders, understands the context, assigns the correct category, and moves the email into the right folder. It uses the original Microsoft Outlook nodes plus an AI Agent. You can connect OpenAI or any other LLM provider. ✨ Features Self-Discovery:** Scans your Outlook folders automatically – no manual mapping required. AI-Powered Decisions:** Considers sender, subject, content, links, attachments, timing, and business context. Label + Move:** Assigns the right Outlook category and moves the email into the correct folder. Dual Category Logic:** Can apply both a primary and a secondary category (e.g., Action + Project). Error Handling:** Captures errors and continues without breaking the workflow. Flexible AI Backend:** Replace OpenAI with your own LLM if preferred. 🚀 Setup (5 Steps) Connect Outlook In n8n → Credentials → Microsoft Outlook, grant at least Mail.ReadWrite. Connect AI In n8n → Credentials, set up OpenAI (or another model). Works best with GPT-4.x or GPT-4o. Import the Workflow n8n → Workflows → Import from File/Clipboard and paste the provided JSON. Enable Trigger Adjust the Schedule Trigger (e.g., every 5 minutes). Run & Verify Test run and watch emails get categorized and moved automatically. 🧠 How It Works Schedule Trigger pulls new emails Loop Over Items processes them one by one Markdown / varEmail cleans the content Get Many Folders fetches Outlook categories and folders Summarize + Code prepare category IDs AI Agent applies deep categorization logic Update Category applies the Outlook category Move Folder places the email in the right folder Error Handling ensures workflow stability 🧩 System Prompt Example You are an advanced AI email categorization system. Your mission is to intelligently analyze and categorize emails with maximum accuracy and context awareness. INTELLIGENT CATEGORIZATION ENGINE: Parse all available categories: {{ $json.category }} Multi-layer analysis: Sender, Subject, Body, Links, Attachments Prioritize: Security threats, Action Required, Business Context Specialized: SaaS, Hosting, E-commerce, Finance, Support, Corporate Anti-Spam: Pattern detection, spoofing, red-flag subjects Dual Logic: Primary + Secondary categories when applicable OUTPUT FORMAT (JSON only): { "subject": "EXACT_EMAIL_SUBJECT", "category": "PRIMARY_CATEGORY_FROM_AVAILABLE_LIST", "subCategory": "SECONDARY_CATEGORY_IF_APPLICABLE", "analysis": "Reasoning", "confidence": "HIGH/MEDIUM/LOW" } Available Categories: {{ $json.category }} ⚙️ Parameters & Notes Uses only existing Outlook categories (never invents new ones). Works with any LLM that supports Chat Completions. Requires Mail.ReadWrite permissions. Safe fallback: if unsure, it uses the Action category. 🛡️ Security Processes only what is needed for classification. No external logging of email content unless you configure it. AI provider can be swapped for self-hosted LLMs for compliance. 📄 License & Sharing License:** MIT (or your choice). Tags:** n8n, Outlook, Email, AI, Automation, Categorization Import Method:** Copy/paste workflow JSON into n8n. ✅ Summary Connect → Import → Run. No manual mapping. AI-powered categorization that labels and organizes your Outlook mailbox automatically.

Overview This n8n workflow automatically fetches the latest post from a Telegram channel, translates it using OpenAI, and republishes it to another channel. It supports text, images, and videos. Features Works Without Admin Privileges** - Does not require any bot to be an admin in the source channel. Scheduled execution** - Runs daily at a configurable time AI-powered translation** - Uses OpenAI GPT-4o-mini for natural translations Multi-media support** - Handles text, images, and videos Easy configuration** - All settings in one centralized node Automatic content cleaning** - Removes original channel signatures Prerequisites Required Credentials Telegram Bot API Create a bot via @BotFather Get your bot token Add the bot as an admin to your target channel OpenAI API Sign up at OpenAI Platform Generate an API key Ensure you have sufficient credits Channel Requirements Source Telegram channel must be public Bot must have admin rights in the target channel Setup Instructions 1. Import the Workflow Copy the workflow JSON and import it into your n8n instance The workflow will be imported in inactive state 2. Configure Credentials Telegram Bot Credentials Go to Credentials → Add Credential Select Telegram Enter your bot token from BotFather Test the connection Save as "TelegramBot" OpenAI Credentials Go to Credentials → Add Credential Select OpenAI Enter your OpenAI API key Save as "OpenAI API" 3. Configure Channel Settings Open the "Set Source Channel" node and modify: sourceChannel: "channel_here", // Source channel username (without @) targetChannel: "@your_channel_here", // Target channel (@channel or chat_id) targetLanguage: "Persian", // Target language for translation channelSignature: "signature text" // The channel signature to replaced 4. Adjust Schedule (Optional) Open the "Daily Schedule" node Default: Runs daily at 9:00 AM Modify triggerAtHour and triggerAtMinute as needed 5. Test the Workflow Click "Execute Workflow" to test manually Check if content appears in your target channel Verify translation quality and formatting 6. Activate the Workflow Toggle the workflow to Active status Monitor execution logs for any errors Content Filtering Modify the "Clean Post Content" node to remove specific text patterns: let cleanPost = $input.first().json.post .replaceAll('unwanted_text', '') .replaceAll(/regex_pattern/g, '') .trim(); Multiple Source Channels To monitor multiple channels: Duplicate the workflow Change the sourceChannel in each copy Use different schedules to avoid conflicts Custom Scheduling The Schedule Trigger supports various patterns: Hourly**: { "triggerAtMinute": 0 } Weekly**: { "triggerAtWeekday": 1, "triggerAtHour": 9 } Multiple times**: Use multiple schedule nodes Troubleshooting Common Issues No content fetched Verify source channel is public Check if channel name is correct (without @) Ensure channel has recent posts Translation fails Verify OpenAI API key is valid Check API usage limits and credits Ensure content is not empty Can't send to target channel Verify bot is admin in target channel Check channel username/ID format Test bot permissions manually Compliance Respect copyright and fair use policies Add proper attribution when required Follow Telegram's Terms of Service

WhatsApp RAG Agent (Text + Voice) with Weekly Google Drive Sync One-line summary : Answers WhatsApp in under 100 words, understands voice notes, and retrieves trusted answers from your Google Drive docs (RAG) kept fresh weekly. What this template does Reply to WhatsApp messages* in a polite, human tone with *≤100 words**. Understands text and voice notes**: auto-downloads audio and transcribes to text. Retrieves answers from your knowledge base (RAG)**: Google Drive docs → chunk → embed → store in Supabase → rerank with Cohere. Keeps short-term memory** across the conversation to avoid repetition. Weekly doc sync** from a selected Google Drive folder so non-technical staff can update content without touching n8n. Why it matters Zero busywork:** Update a Google Doc; the bot learns it on the next sync. Trustworthy answers:* Responses come from *your** vetted docs, not random web text. Voice-first friendly:** Handles the WhatsApp reality of “send a voice note.” Safer by design:** Guardrails—no pricing unless in KB, no pushy sales, no medical advice. Triggers WhatsApp Trigger:** Receives incoming messages (text or audio). Google Drive Trigger (weekly):** Detects new/updated files in the chosen folder for ingestion. App credentials required WhatsApp Business Cloud** (App ID, Token, Phone Number ID) OpenAI** (Chat + Embeddings) Cohere** (Rerank) Supabase** (SUPABASE_URL, ANON_KEY) Google Drive** (OAuth2) + target Folder ID Suggested environment variables WHATSAPP_APP_ID= WHATSAPP_TOKEN= WHATSAPP_PHONE_NUMBER_ID= OPENAI_API_KEY= COHERE_API_KEY= SUPABASE_URL= SUPABASE_ANON_KEY= GDRIVE_FOLDER_ID= RAG_TABLE_NAME="documents" # table to store vectors/metadata MAX_ANSWER_WORDS=100 # guardrail for concise replies Architecture overview Answer-time lane (RAG Tool):** Receive WhatsApp message → 2) Transcribe audio if present → 3) Maintain short-term memory → 4) Retrieve from Supabase vectors (topK) → 5) Rerank with Cohere → 6) Compose ≤100-word reply with sources → 7) Send on WhatsApp. Ingest lane (Weekly Sync):** A) Detect Drive file updates → B) Download & convert (Docs → text/plain) → C) Chunk (size/overlap) → D) Embed with OpenAI → E) Upsert to Supabase with metadata & hashes. How it works (node rundown) | # | Node | Key Inputs | Key Outputs | | -- | ------------------------------------------- | ------------------------------- | --------------------------------- | | 1 | WhatsApp Trigger | Incoming message | Raw WhatsApp payload | | 2 | Switch (Attachment presence/type) | Payload | Route: Text or Audio | | 3 | HTTP Request (Audio path) | attachments[0].data_url | Audio file | | 4 | OpenAI – Translate/ASR | Audio file | Transcribed text | | 5 | Merge | Text path + Audio path | Unified text message | | 6 | Simple Memory | Recent turns | Short-term context | | 7 | OpenAI Chat Model | Prompt + message + memory | Draft answer (tool calls allowed) | | 8 | Supabase Vector Tool (retrieve-as-tool) | Query text, topK=10 | Candidate KB passages | | 9 | Cohere Reranker | Candidates | Re-ranked context | | 10 | Send WhatsApp Message | to, body | Reply sent | | 11 | Google Drive Trigger (weekly) | Folder ID, fileUpdated | Changed files | | 12 | Set (File Id) | id from trigger | File ref | | 13 | Google Drive – Download File | Id (Docs→txt) | Raw text | | 14 | Character Text Splitter | chunkSize=2000, overlap=300 | Chunks | | 15 | Default Data Loader | Binary→Document | Clean docs | | 16 | OpenAI Embeddings (ingest) | Chunks | Vectors | | 17 | Supabase Vector Store (insert) | Table: documents | Upserted KB | Notes The KB Tool is the combo of steps 8–9–7 at answer time (retrieve → rerank → answer). The Ingest lane is steps 11–17 (weekly sync of your Drive folder). Setup (7‑minute sprint) Import the workflow JSON. Connect credentials: WhatsApp, OpenAI, Cohere, Supabase, Google Drive. Google Drive Trigger: paste your Folder ID; keep fileUpdated event. Download File: ensure Google Docs convert to text/plain. Supabase Vector Store (insert): set table name to documents (or your schema). Character Text Splitter: keep chunkSize=2000, overlap=300 (balanced recall/latency). Retrieve-as-tool: set topK=10 and enable reranker. Send WhatsApp Message mapping: Recipient: {{$("WhatsApp Trigger").item.json.messages[0].from}} Body: {{$json.output}} Test: Send a text and a voice note to your WhatsApp number → confirm concise answers. Drop a Google Doc into the watched folder → verify it’s chunked/embedded on the next weekly poll (or run ingest nodes once manually). Prompt, tone & guardrails System prompt:** Be polite, human, and concise (≤ MAX_ANSWER_WORDS). Cite or reference only the KB content; if unknown, say so and offer to escalate. No prices unless present in the KB. No medical advice. Temperature:* start at *0.2** for factual replies. Memory window:** keep a short rolling buffer (e.g., last 4–6 turns). Data model (minimum viable) Table documents (example columns): id (uuid) source_url (text) title (text) chunk (text) embedding (vector/float[] depending on extension) chunk_hash (text) updated_at (timestamp) Indexes Unique index on chunk_hash to dedupe Index on updated_at for syncs Observability & ops Log question, selected chunk ids/hashes, and final response to a DB/Sheet for QA. Add a low-confidence route (score threshold) → Slack/Telegram escalation to a human. Track latency and token usage to tune topK and chunk sizes. Customization Latency vs quality:** try topK=6–8 and chunkSize=1200 for speed. Languages:** ASR node can be swapped for native multilingual output. Escalation:** add channel handoff on low confidence or no KB hits. Sync cadence:* change Drive Trigger to *daily** if content updates frequently. Safety & compliance No medical advice.** If uncertain or clinical, ask to schedule a consult or refer to the right department. PII:** Don’t log full phone numbers in plaintext analytics; hash where possible. Prices & rates:** Only answer if present in the KB; otherwise hand off to front desk. Troubleshooting No reply sent:* Ensure *Send message** node reads {{$json.output}} (Agent’s response property). Audio path failing:** Confirm attachments[0].data_url exists and HTTP node fetches a valid file. KB not updating:** Manually execute the ingest lane; check rows in Supabase. Irrelevant answers:* Lower temperature to *0.2, increase overlap to **400, and verify Drive docs are clean and structured. Categories & tags Categories:** AI, Customer Support, Healthcare Ops, RAG, WhatsApp Tags:** WhatsApp, RAG, Google Drive, Supabase, OpenAI, Cohere, Voice Notes Pricing (rough, BYO keys) n8n:** self-host free; n8n.cloud billed by plan. OpenAI, Cohere:** usage-based by tokens/calls. Supabase:** free tier + usage; vector storage billed by size. WhatsApp Cloud:** Meta pricing per conversation. Nodes used in workflow WhatsApp Trigger, Switch, HTTP Request, OpenAI (ASR + Chat + Embeddings), Merge, Simple Memory, Supabase Vector Tool (retrieve), Cohere Reranker, Google Drive Trigger, Set, Google Drive – Download, Character Text Splitter, Default Data Loader.

Telegram Voice → AI Summary & Sentiment Analysis via Gmail This n8n template demonstrates how to capture Telegram voice messages, transcribe them into text using AssemblyAI, analyze the transcript with AI for summary and sentiment insights, and finally deliver a structured email report via Gmail. Use cases Automating meeting or lecture voice note transcriptions. Gathering student feedback or training session insights from voice messages. Quickly summarizing Telegram-delivered audio inputs into structured reports. Reducing manual effort in capturing sentiment and key action items from conversations. How it works A voice message is sent to a connected Telegram Bot. The workflow fetches the file and uploads it to AssemblyAI. AssemblyAI generates a transcript from the audio. The transcript is analyzed by OpenAI to extract: Executive summary (120–180 words) Sentiment label and score Key points Action items (if any) Notable quotes Topics The formatted analysis is sent as an email report using Gmail. The workflow ends with a clean summary email containing actionable insights. How to use Import this workflow into your n8n instance. Set up and connect the required credentials: Telegram Bot API token AssemblyAI API key OpenAI API key Gmail OAuth2 account Replace placeholders (e.g., <<YOUR_EMAIL ID>> and <<YOUR_ASSEMBLYAI_API_KEY>>) with your actual values. Start the workflow. Whenever a voice message is received on the Telegram Bot, the workflow will process it end-to-end and deliver a polished email report. Requirements Telegram Bot account (API token) AssemblyAI account with API key OpenAI account with API key Gmail OAuth2 credentials configured in n8n Active n8n instance Customising this workflow You can customize the email formatting, sentiment thresholds, or extend the workflow to save transcripts into Google Drive, Airtable, or any other connected apps. Additionally, you can trigger the same workflow from multiple input sources (e.g., local audio files, Google Drive links, or Telegram).

Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents This n8n workflow creates a complete AI-powered content department. It starts when a chat request is received, then a Content Director Agent (powered by OpenAI O3) analyzes the request and delegates tasks to specialized agents (blogs, social, video, email, website, strategy). Each agent is powered by GPT-4.1-mini, keeping costs low and quality high. ✅ 📩 Section 1: Trigger & Director Setup ⚙️ Nodes 1️⃣ When Chat Message Received What it does:** Starts the workflow whenever a user sends a content request. Why it’s useful:** Allows real-time or on-demand content creation from chat inputs. 2️⃣ Content Director Agent (O3) What it does:** Analyzes user request, defines the best content mix, and delegates tasks to specialist agents. Why it’s useful:** Keeps your brand voice consistent and ensures all channels align to a unified content strategy. 💡 Beginner Benefit ✅ Single entry point → just type your content idea once ✅ AI Director coordinates everything for you ✅ No need to manage multiple tools ✅ 👥 Section 2: Specialist Content Agents Each request gets routed to one (or several) of these agents, depending on the strategy. 3️⃣ Blog Content Writer Long-form articles, editorials, and thought leadership pieces. 4️⃣ Social Media Content Creator Social posts, captions, hashtags, and community content. 5️⃣ Video Script Writer YouTube scripts, explainer videos, and video marketing content. 6️⃣ Email Newsletter Writer Campaigns, nurture sequences, and newsletter copy. 7️⃣ Website Copy Specialist Landing pages, product descriptions, and conversion-focused web copy. 8️⃣ Content Strategist & Planner Editorial calendars, campaign planning, and audience strategy. 💡 Beginner Benefit ✅ Each agent is an expert in its field ✅ Powered by GPT-4.1-mini → faster and cheaper ✅ Parallel execution → all content types can be generated at once ✅ 🧠 Section 3: Language Models & Execution Flow O3 Model → Content Director** Handles analysis, strategy, and delegation. GPT-4.1-mini → All Specialists** Powers blog, social, video, email, website, and strategy agents. Think Node** Helps the Content Director organize reasoning before delegating tasks. 💡 Beginner Benefit ✅ AI Director (O3) = smart leadership ✅ Specialists (GPT-4.1-mini) = cost-efficient execution ✅ Built-in reasoning = better, more aligned campaigns 📊 Workflow Overview | Section | What Happens | Key Benefit | | --------------------------- | --------------------------------------------------------------- | -------------------------- | | 📩 Trigger & Director Setup | Workflow starts from chat → Content Director interprets request | Centralized control | | 👥 Specialist Agents | Each AI agent produces tailored content | Multi-channel coverage | | 🧠 Models & Flow | O3 for Director, GPT-4.1-mini for specialists | Cost-efficient + strategic | 📌 How You Benefit Overall ✅ One input → full content campaign ✅ Consistent brand voice across all platforms ✅ Cost-effective (O3 only for strategy, GPT-4.1-mini for bulk work) ✅ Ready-to-publish content in minutes ✨ You’ve basically built an AI marketing department inside n8n — no extra staff required! 🚀