Google Docs and Telegram integration

Empower Your AI Chatbot with Long-Term Memory and Dynamic Tool Routing This n8n workflow equips your AI agent with long-term memory and a dynamic tools router, enabling it to provide intelligent, context-aware responses while managing tasks across multiple tools. By combining persistent memory and modular task routing, this workflow makes your AI smarter, more efficient, and highly adaptable. 👥 Who Is This For? AI Developers & Automation Enthusiasts: Integrate advanced AI features like long-term memory and task routing without coding expertise. Businesses & Teams: Automate tasks while maintaining personalized, context-aware interactions. Customer Support Teams: Improve user experience with chatbots that remember past interactions. Marketers & Content Creators: Streamline communication across platforms like Gmail and Telegram. AI Researchers: Experiment with persistent memory and multi-tool integration. 🚀 What Problem Does This Solve? This workflow simplifies the creation of intelligent AI systems that retain memory, manage tasks dynamically, and automate notifications across tools like Gmail and Telegram—saving time and improving efficiency. 🛠️ What This Workflow Does Save & Retrieve Memories**: Uses Google Docs for long-term storage to recall past interactions or user preferences. Dynamic Task Routing**: Routes tasks to the right tools (e.g., saving/retrieving memories or sending notifications). AI-Powered Context Understanding**: Combines OpenAI GPT-based short-term memory with long-term memory for smarter responses. Multi-Channel Notifications**: Sends updates via Gmail or Telegram. 🔧 Setup API Credentials: Connect to OpenAI (AI processing), Google Docs (memory storage), Gmail/Telegram (notifications). Customize Parameters: Adjust the AI agent's system message for your use case. Define task-routing rules in the tools router node. Test & Deploy: Verify memory saving/retrieval, task routing, and notification delivery. 💡 How to Customize Modify the system message in the OpenAI node to tailor your agent’s behavior. Add or adjust routing rules for additional tools. Update notification settings to match your communication preferences.

This n8n workflow template is designed to integrate a DeepSeek AI agent with Telegram, incorporating long-term memory capabilities for personalized and context-aware responses. Here's a detailed breakdown: Core Features Telegram Integration Uses a webhook to receive messages from Telegram users. Validates user identity and message content before processing. AI-Powered Responses Employs DeepSeek's AI models for conversational interactions. Includes memory capabilities to personalize responses based on past interactions. Error Handling Sends an error message if the input cannot be processed. Model Options 🧠 DeepSeek-V3 Chat**: Handles general conversational tasks. DeepSeek-R1 Reasoning**: Provides advanced reasoning capabilities for complex queries. Memory Buffer Window**: Maintains session context for ongoing conversations. Quick Setup 🛠️ Telegram Webhook Configuration Set up a webhook using the Telegram Bot API: https://api.telegram.org/bot{my_bot_token}/setWebhook?url={url_to_send_updates_to} Replace {my_bot_token} with your bot's token and {url_to_send_updates_to} with your n8n webhook URL. Verify the webhook setup using: https://api.telegram.org/bot{my_bot_token}/getWebhookInfo DeepSeek API Configuration Base URL: https://api.deepseek.com Obtain your API key from the DeepSeek platform. Implementation Details 🔧 User Validation The workflow validates the user's first name, last name, and ID using data from incoming Telegram messages. Only authorized users proceed to the next steps. Message Routing Routes messages based on their type (text, audio, or image) using a switch node. Ensures appropriate handling for each message format. AI Agent Interaction Processes text input using DeepSeek-V3 or DeepSeek-R1 models. Customizable system prompts define the AI's behavior and rules, ensuring user-centric and context-aware responses. Memory Management Retrieves long-term memories stored in Google Docs to enhance personalization. Saves new memories based on user interactions, ensuring continuity across sessions.

This template monitors Google Drive folder for new files, extracts text from PDFs, images, text files, CSVs, and Google Docs., reads images with meta/llama-3.2-11b-vision-instruct, structures the result with nvidia/llama-3.3-nemotron-super-49b-v1.5, logs everything to Google Sheets, and sends a Telegram notification when processing finishes. ✨ What This Template Does Watches a specific Google Drive folder for new files with Google Drive Trigger. 📂 Downloads each new file with Google Drive before processing. ⬇️ Routes PDFs, images, text files, CSVs, and Google Docs through the correct extraction branch. 🔀 Extracts image text with meta/llama-3.2-11b-vision-instruct 🖼️ Structures extracted content into JSON fields with nvidia/llama-3.3-nemotron-super-49b-v1.5 through NVIDIA NIM. 🤖 Appends the final result to Google Sheets in Extract_Log. 📊 Sends a Telegram notification when processing is complete. 📬 Key Benefits Turns a Drive folder into a reusable intake point for mixed file types. ⏱️ Creates a searchable audit trail in Google Sheets for every processed file. 📚 Sends a lightweight Telegram notification without requiring Telegram as the input channel. ✅ Keeps the extraction and structuring logic reusable for internal ops or client delivery workflows. 🔁 Makes it easier to test multimodal document processing with free-tier NVIDIA NIM models. 💡 Features Google Drive Trigger configured for new files in a specific folder. 📥 Google Drive download step for binary file access before extraction. ⚙️ File-type routing with Switch and normalization with Code nodes. 🧠 Native n8n Extract from File nodes for PDF, TXT, and CSV parsing. 📄 NVIDIA NIM HTTP Request nodes for image OCR and structured JSON generation. 🤖 Google Sheets append logging with a fixed Extract_Log tab schema. 📈 Plain-text Telegram completion notifications with a fixed destination chat ID. 📨 Requirements n8n instance with access to Google Drive Trigger, Google Drive, Google Docs, Google Sheets, HTTP Request, Telegram, and Extract from File nodes. 🧰 Google Drive OAuth2 credential with access to the watched folder. 🔐 Google Docs OAuth2 credential with access to any Google Docs files you want to process. 📘 Google Sheets OAuth2 credential and a sheet with an Extract_Log tab. 📊 Telegram bot credential plus a valid destination chat ID for notifications. 🤝 NVIDIA NIM API key stored as an HTTP Header Auth credential. 🔑 A folder ID and Google Sheet ID added to the provided placeholders before activation. 🛠️ Target Audience Operations teams monitoring a shared Drive folder for inbound files. 🗂️ Founders and solo operators who want document extraction. 👤 Agencies building reusable back-office workflows for receipts, notes, and uploaded files. 🏢 Analysts who want structured text output logged into Google Sheets automatically. 📋 Automation builders testing file-driven multimodal extraction with Drive as the source. 🧪 Step-by-Step Setup Instructions Import the workflow and read every sticky note on the canvas before editing any nodes. 📝 Connect your Google Drive, Google Docs, Google Sheets, Telegram, and NVIDIA NIM credentials. 🔐 Replace REPLACE_WITH_GOOGLE_DRIVE_FOLDER_ID, REPLACE_WITH_GOOGLE_SHEET_ID, and REPLACE_WITH_TELEGRAM_CHAT_ID in the marked nodes. 📌 Create the Extract_Log tab with the required headers shown in the sticky notes. 📑 Test one file at a time in this order: PDF, TXT, CSV, image, then Google Docs file. 🧪 Confirm that each test adds one clean row to Google Sheets and sends one Telegram notification. ✅ Activate the workflow only after every supported path works end to end. 🚀 Built by Cordexa Technologies https://cordexa.tech | [email protected]

The Ultimate Beginner's Guide to an AI-Powered Telegram Assistant (PDF, Brave search & Google Suite) This comprehensive workflow bundle is designed as a powerful starter kit, enabling you to build a multi-functional AI assistant on Telegram. It seamlessly integrates AI-powered voice interactions, an intelligent PDF document search using a Retrieval-Augmented Generation (RAG) system, and automates various Google Suite tasks like calendar management and document generation. Perfect for beginners looking to explore advanced AI and automation capabilities. Disclaimer This template is designed for self-hosted n8n instances. 🚀 Key Features Telegram Bot Interface:** Interact with your AI assistant using both text and voice commands through Telegram. AI Voice Bot:** Transcribes user voice messages using OpenAI Whisper. Processes requests with an AI agent powered by Google Gemini. Responds with AI-synthesized voice using Replicate API. PDF RAG System:** Index PDF documents from Google Drive via Telegram commands. Utilizes Mistral AI for Optical Character Recognition (OCR) on PDFs. Stores document content and embeddings in a Qdrant vector database. Answers questions about your documents using Google Gemini, based on retrieved context. Google Suite Automation:** Manage Google Calendar: Create events, find upcoming holidays, and list birthdays. Google Drive: Search for PDF files and manage document templates. Google Docs: Automatically generate invoices from templates. Intelligent Web Search:** Employs Brave Search for fetching real-time information from the web. Versatile AI Agent:** Leverages Google Gemini with a suite of tools including a calculator, date & time utilities, and custom integrations (e.g., example Airbnb tools). Command-Driven Functionality:** Easily trigger specific actions using Telegram commands like /help, /pdf, /rag, /invoice, /chat, /brave, and /birthday. ⚙️ How It Works The workflow is initiated by messages or commands sent to your Telegram bot. A central Switch node directs the flow based on the input received. Telegram Interaction & Command Routing A Telegram Trigger node listens for new messages (text or voice). A "typing..." indicator is sent to Telegram for better user experience. The Switch node parses the message content and routes it to the appropriate sub-workflow based on predefined commands (e.g., /pdf, /rag, /voice) or general chat. AI Voice Bot Functionality For voice messages (or if the voice path is triggered): The voice file is downloaded from Telegram. OpenAI Whisper transcribes the audio into text. The transcribed text is fed to an AI Agent (powered by Google Gemini and equipped with various tools and memory). The AI Agent's text response is then sent to the Replicate API to generate a natural-sounding voice. The generated audio response is sent back to the user on Telegram. PDF RAG System with Mistral OCR & Qdrant Indexing PDFs (via /qdrant <Google_Drive_File_ID> command):** The specified PDF is downloaded from Google Drive. The PDF is uploaded to Mistral AI for OCR processing. The extracted text (in markdown format) is retrieved. The text is split into manageable chunks. OpenAI Embeddings are generated for each chunk. These chunks and their embeddings are stored in a Qdrant vector collection. A confirmation message is sent to Telegram. Querying PDFs (via /rag <your_question> command):** The user's question is processed by a RetrievalQA Chain. This chain uses Google Gemini as the Language Model and retrieves relevant document chunks from Qdrant based on semantic similarity (embeddings). Google Gemini then generates a concise answer based on the user's question and the retrieved contextual information from the documents. The answer is sent back to the user on Telegram. Searching PDFs in Drive (via /pdf <search_term> command):** Searches your Google Drive for PDF files matching the provided search term. Sends a list of found PDF files (name and ID) to the user on Telegram, allowing them to easily identify files for indexing with /qdrant. AI Chat & Task Automation (General Chat & /chat command) Handles general text messages or transcribed voice inputs that are not specific commands. An AI Agent (Google Gemini) processes these inputs. The agent is equipped with tools such as: Google Calendar Tools: To create events, find the next public holiday, or list upcoming birthdays. Brave Search Tool: To search the internet for information. Calculator Tool: For mathematical computations. Date & Time Utility: For handling and formatting dates. Example Airbnb Tools: Demonstrates extensibility for custom tool integrations. The agent utilizes a "Think Node" process for reasoning and Window Buffer Memory to maintain conversational context. Responses are formulated and sent back to the user on Telegram. Google Automations Invoice Generation (via /invoice command):** Copies a predefined Google Docs invoice template from your Google Drive. Populates the new document with details (client name, items, etc. – currently uses placeholder data from an 'Edit Fields' node, which can be customized to parse input from the command). Converts the populated Google Doc into a PDF file. Sends the generated PDF invoice to the user via Telegram. Calendar Management (via AI Agent or specific commands like /birthday):** The /birthday command fetches upcoming birthdays from a specified Google Calendar. The AI Agent can also interact with Google Calendar to create events or retrieve information based on natural language requests. Web Search (via /brave <query> command or AI Agent) Performs a web search using the Brave Search API. Returns a list of search results, including titles and URLs, to the user on Telegram. Help Command (/help) Provides the user with a formatted list of all available Telegram commands and their basic usage instructions. 🛠️ Setup Steps & Credentials To get this workflow bundle up and running, you'll need to configure several credentials: Telegram: Create a new bot via @BotFather on Telegram to obtain a Bot Token. Add this token to the Telegram Trigger node and all Telegram (sender) nodes in the workflow. OpenAI: Obtain an API Key from platform.openai.com. Create an OpenAI credential. Use this credential in the Convert audio to text (OpenAI node for Whisper transcription) and all Embeddings OpenAI nodes (for RAG system). Replicate API (Text-to-Speech): Sign up at replicate.com and get your API token. Create an HTTP Bearer Auth credential using this token. Assign this credential to the Call Replicate API (HTTP Request) node. Google Gemini (PaLM API): Get an API key from Google AI Studio or Google Cloud Console. Create a Google Gemini(PaLM) Api credential. Assign it to all Google Gemini Chat Model nodes. Qdrant (Vector Database): Set up a Qdrant instance (either cloud-hosted or self-managed). Note your Qdrant instance URL and API Key (if security is enabled). Create a QdrantApi credential with these details. Assign it to the Qdrant Vector Store nodes. For the Refresh collection node (an HTTP Request node used to clear the collection for /pdf command demo), create an HTTP Header Auth credential with your Qdrant API key if required by your instance. Mistral AI (PDF OCR): Obtain an API key from console.mistral.ai. Create a Mistral Cloud API credential. Assign this to the Mistral Upload, Mistral Signed URL, and Mistral DOC OCR (HTTP Request) nodes. Google Drive & Google Docs: Ensure the Google Drive API and Google Docs API are enabled in your Google Cloud Console project. Set up OAuth 2.0 credentials (Client ID and Client Secret). Create Google Drive OAuth2 Api and Google Docs OAuth2 Api credentials. Assign these to the respective Google Drive and Google Docs nodes throughout the workflow. Important: Configure relevant Folder IDs (for PDF search, invoice template source, invoice output) and the invoice template Document ID in the Google Drive and Google Docs nodes. Google Calendar: Enable the Google Calendar API in your Google Cloud Console project. Set up OAuth 2.0 credentials. Create a Google Calendar OAuth2 Api credential. Assign it to the Google CalendarTool and Google Calendar nodes. Specify the correct calendar names or IDs in the nodes (e.g., for birthdays, holidays, new event creation). Brave Search: Get a Brave Search API key from their developer portal. Create a Brave Search API credential. Assign it to the Brave Search nodes and tools. (Optional) Airbnb MCP Client: The workflow includes example nodes for Airbnb MCP tools. If you intend to use or expand these, set up the corresponding MCP Client API credentials. 💡 Customization & Learning This "Beginner Bundle" is not just a ready-to-use solution but also a fantastic learning resource: Explore AI Agent Prompts:** Dive into the AI Agent nodes to see how prompts are structured to guide the LLM's behavior, including the "Think Node" process and character guidance for robust messaging. Modify Toolsets:** Easily add or remove tools for the AI agent to expand its capabilities. Invoice Customization:** Adapt the Edit Fields node and the Google Docs template to match your invoicing needs. You can extend it to parse invoice details directly from the Telegram command. RAG Parameters:** Experiment with chunk sizes, overlap, and different embedding models in the RAG pipeline. Extend Commands:** Add new commands and corresponding functionalities by expanding the main Switch node and building out new automation paths. By setting up and dissecting this workflow, beginners can gain a practical understanding of building complex, AI-driven applications, integrating various services, and managing different data flows.

Your AI secretary that self-learning every day and remembers everything you said (text, audio, image). Imagine having a personal AI secretary accessible right from your Telegram, ready to assist you with information and remember everything you discuss. This n8n workflow transforms Telegram into your intelligent assistant, capable of understanding text, audio, and images, and continuously learning from your interactions. It integrates RAG's offline data ingestion and online querying functionalities, letting you save inspiration and key information permanently in real-time, and giving you an AI assistant that remembers all your dialogues and information. It builds and queries a powerful vector database in real-time, ensuring relevant and accurate responses. Video guidance on how to set up Telegram integration is also included. Who is this for? This template is ideal for: Individuals seeking a personal AI assistant for quick information retrieval and note-taking. Professionals who need to keep track of important conversations and insights. Anyone interested in leveraging the power of Retrieval-Augmented Generation (RAG) and vector databases for personal knowledge management. Users who want a self-learning AI that improves over time based on their interactions. What problem is this workflow solving? This workflow integrates RAG's offline data ingestion and online querying functionalities, letting you save inspiration and key information permanently in real-time, and giving you an AI assistant that remembers all your dialogues and information. This workflow addresses the challenge of information overload and the need for an easily accessible, personalized knowledge base. It eliminates the need to manually organize notes and search through past conversations. By automatically storing and retrieving information from a vector database, this workflow makes it effortless to access the knowledge you need, when you need it. It also provides a way to retain information from various media types like voice notes and images. What this workflow does: This workflow automates the following steps: Instant Information Capture:** Receives text messages, audio notes (transcribed), and images (with content analysis) directly from your Telegram. Intelligent Question Answering:** When you ask a question, the AI searches its knowledge base (Pinecone vector store) for relevant information and provides a comprehensive answer. It even considers your recent conversations for context. Automatic Knowledge Storage:** When you make a statement or provide information, the AI extracts key details and saves them in a Google Docs "memory palace." Daily Self-Learning:** Every day, the workflow automatically takes all the information stored in the Google Docs, converts it into a vector representation, and adds it to its knowledge base (Pinecone vector store). This ensures the AI continuously learns and remembers everything you've shared. Image Understanding:** Extracts text and information from images you send. Audio Transcription:** Automatically transcribes your voice notes into text for processing and storage. Short-Term Memory:** Remembers recent interactions within a session for more context-aware conversations. Setup: To get started, you'll need to connect the following services to your n8n instance: Telegram: Connect your Telegram bot API credentials. A video guidance is included for telegram integration setup. OpenAI: Provide your OpenAI API key for audio transcription and image analysis. Pinecone: Set up a Pinecone account and provide your API key and environment. Create a namespace in Pinecone. Google Docs: Connect your Google account with access to Google Docs. You'll need to create a Google Doc that will serve as the daily "memory palace" and provide its ID in the workflow. How to customize this workflow: Adjust the AI Agent's Personality:** Modify the system prompt in the "AI Agent" node to tailor the AI's tone and behavior. Expand Knowledge Sources:** Integrate other data sources into the daily learning process, such as emails or other documents, by adding more nodes to the scheduled trigger workflow. Add More Tools for the AI Agent:** Integrate additional tools into the AI Agent, such as web search or other APIs, to further enhance its capabilities. Modify the Daily Schedule:** Adjust the schedule trigger to run at a different time or interval.

Summarize YouTube Videos & Chat About Content with GPT-4o-mini via Telegram Description This n8n workflow automates the process of summarizing YouTube video transcripts and enables users to interact with the content through AI-powered question answering via Telegram. It leverages the GPT-4o-mini model to generate summaries and provide insights based on the video’s transcript. How It Works Input: The workflow starts by receiving a YouTube video URL. This can be submitted through: A Telegram chat message. A webhook (e.g., triggered by a shortcut on Apple devices). Transcript Extraction: The URL is processed to extract the video transcript using the custom youtubeTranscripter community node (available here). The transcript is concatenated into a single text and stored in a Google Docs document. Summarization: The GPT-4o-mini AI model analyzes the transcript and generates a structured summary, including: A general overview. Key moments. Instructions (if applicable). The summary is then sent back to the user via Telegram. Interactive Q&A: Users can ask questions about the video content via Telegram. The AI retrieves the stored transcript from Google Docs and provides accurate, context-based answers, which are sent back through Telegram. Setup Instructions To configure this workflow, follow these steps: Import the Workflow: Download the provided JSON template and import it into your n8n instance. Install the Community Node: Install the youtubeTranscripter community node via npm: npm install n8n-nodes-youtube-transcription-kasha Important: This node requires a self-hosted n8n instance due to its external dependencies. Configure Nodes: Webhook: Set up the webhook to receive YouTube URLs. Alternatively, configure the Telegram node if using Telegram as the input method. Google Docs: Provide valid credentials to enable writing the transcript to a Google Docs document. AI Model: Set up the GPT-4o-mini model for summarization and Q&A functionality. Test the Workflow: Send a YouTube URL via your chosen input method (Telegram or webhook) and confirm that the summary is generated and delivered correctly. Customization Language**: Adjust the AI prompts to generate summaries and answers in any desired language. Output Format**: Modify the summary structure by editing the prompt in the summarization node. Input Methods**: Replace the Telegram node with another messaging or input node to adapt the workflow to different platforms. Who Can Benefit? This template is perfect for: Content Creators**: Quickly summarize video content for repurposing or review. Students and Researchers**: Extract key insights from educational or informational videos efficiently. General Users**: Interact with video content via AI without needing to watch the full video. Problem Solved This workflow simplifies video content consumption by: Automating the extraction and summarization of key points. Enabling interactive Q&A to address specific questions without rewatching the video. Additional Notes Disclaimer**: The youtubeTranscripter community node is required and only works on self-hosted n8n instances due to its reliance on external services. Apple Users**: Enhance your experience with a custom shortcut to share YouTube videos directly to the workflow. Download the shortcut here.

Who is this for? Job seekers who want to automate their entire job search pipeline — from discovering new listings to generating tailored resumes and cover letters — without manually browsing LinkedIn every day. What does this workflow do? This workflow runs on a schedule, scrapes LinkedIn jobs via Apify, filters out spam recruiters and wrong locations, then uses a 2-stage AI evaluation to find the best matches for your profile. Matching jobs are logged to Google Sheets and you get a Telegram notification. When you're ready to apply, a second trigger generates a tailored resume + cover letter using AI and fills in your Google Docs templates automatically. How it works Stage 1 — Scrape & Filter (runs on schedule) Schedule Trigger fires hourly (customizable cron) Apify LinkedIn Scraper pulls fresh job listings based on your keywords and location Filter nodes remove unwanted recruiter companies and jobs outside your target country HTML → Markdown converts job descriptions for better AI processing GateKeeper AI (fast, cheap model) does a quick yes/no — rejects 90% of irrelevant jobs Results are saved to a "Gatekeeper Results" Google Sheet Stage 2 — Score & Notify (for GateKeeper matches) Job Match Scorer AI (smarter model) evaluates matches in detail with a 0–100 score Jobs above your threshold are added to a "Roles to Apply" Google Sheet Telegram notification alerts you about new matches Stage 3 — Generate Resume & Apply (triggered from Google Sheets) When you update a row in your sheet, the workflow triggers AI Resume Writer generates a tailored resume + cover letter in JSON format Language detection routes to EN or DE templates (extensible to more languages) Google Drive copies your template documents and fills in all variables Links and status are updated back in Google Sheets — ready to submit Setup Guide Prerequisites n8n instance (self-hosted or cloud) Apify account (free tier works) — for LinkedIn scraping OpenRouter account — for AI models (GateKeeper + Job Match Scorer) OpenAI API key — for resume generation Google Workspace — Sheets, Docs, Drive (OAuth2) Telegram Bot — for notifications Step 1: Credentials Add the following credentials in n8n (do not hardcode API keys): HTTP Query Auth → Apify API token OpenRouter API → your OpenRouter key OpenAI API → your OpenAI key Google Sheets OAuth2 → connect your Google account Google Docs OAuth2 → same Google account Google Drive OAuth2 → same Google account Telegram API → your bot token Step 2: Google Sheets Create two Google Sheets: Sheet 1 — Gatekeeper Results Columns: title, company, location, url, score, reason, match Sheet 2 — Roles to Apply Columns: title, company, url, job_description, status, resume_link Paste each sheet's ID into the corresponding Google Sheets nodes. Step 3: Google Docs Templates Create resume and cover letter templates in Google Docs with placeholder variables like {{summary}}, {{experience_1_title}}, {{experience_1_company}}, etc. The AI output JSON keys map directly to these variables. Step 4: Customize the Workflow Set Profile node — Replace the placeholder with your full career profile (the more detailed, the better the AI results) LinkedIn URLs — Update the Apify scraper with your own search URLs (keywords, geoId, filters) GateKeeper prompt — Customize rejection criteria, "sweet spot" description, and location preferences Job Match Scorer prompt — Adjust scoring criteria to your skills Filter nodes — Update country filter and recruiter blocklist Telegram Chat ID — Set your personal chat ID for notifications Google Sheet/Doc/Drive IDs — Link all nodes to your own documents Step 5: Activate Turn on the Schedule Trigger and the Google Sheets Trigger. You're live! Nodes used in this workflow Schedule Trigger HTTP Request (Apify) Filter, Switch, Merge Markdown (HTML to Markdown) LangChain LLM Chain (OpenRouter — Haiku for GateKeeper, Sonnet for Scorer) OpenAI (GPT for resume generation) Code (JSON parsing) Google Sheets, Google Docs, Google Drive Telegram Questions or need help? If you have any questions about this workflow or want the ready-made Google Docs/Sheets templates to get started faster, feel free to reach out: 👉 Connect with me on LinkedIn

Automated Social Media Content Publishing Factory + System Prompt Composition This workflow is a powerful automation for creating and publishing social media content. It uses AI to generate content and images based on external prompts and schemas, and routes the final posts to various social media platforms. How it Works This workflow operates as a "Content Publishing Factory". It generates platform-optimized content for platforms like LinkedIn, Instagram, Facebook, X (Twitter), Threads, and YouTube Shorts. A key feature is its dynamic system prompt and output schema composition, which pulls content from external Google Docs to ensure consistency. The workflow can also create images to match the content and send the final draft for approval via email before publishing. Use Cases Centralized Content Management**: Store and manage all system prompts and schemas in Google Docs for easy team collaboration and version control. Brand Consistency**: Ensure a consistent brand voice across all social media platforms by centralizing brand guidelines and content rules. Automated Publishing**: Automate content creation, image generation, and publishing, reducing manual effort and design bottlenecks. Fact-checking and Contextual Relevance**: Incorporate real-time research and fact-checking into content to ensure accuracy and relevance. Setup Instructions Google Docs: Create two Google Docs: one for the social media schema and one for the system prompt, and update the respective node IDs in the workflow. API Credentials: Provide credentials for the following services: OpenAI: For the AI agents and content creation. SerpAPI: For the web search tool to perform research. Gmail: For sending content for approval and notifications. Google Drive: For archiving images and final posts. Social Media Platforms: You'll need credentials for the platforms you wish to publish to (X, Instagram, Facebook, LinkedIn, etc.). Image Hosting: The workflow uses imgbb.com to host generated images, requiring an API key. Workflow Logic Routing Agent: The Social Media Router Agent receives a user prompt and uses a toolWorkflow node to route the request to the appropriate content generation workflow. Prompt & Schema Composition: The workflow fetches the system prompt and platform-specific schemas from Google Docs, parses them, and composes a dynamic prompt for the AI agent. Content Creation: The Social Media Content Creator agent uses the composed prompt and a web search tool to generate platform-optimized content and an image suggestion. Image Generation & Archiving: The workflow generates an image from the AI suggestion using an external service and archives both the image and the final post content in Google Drive. Approval Process: The draft content is sent to a Gmail address for approval. Publishing: If the content is approved, the Social Media Publishing Router node directs the content to the correct publishing node for the specified platform (e.g., X Post, Instagram Image, Facebook Post, etc.). Node Descriptions | Node Name | Description | |-----------|-------------| | When chat message received | A trigger node that initiates the workflow based on a chat message. | | Social Media System Prompt | A Google Docs node that retrieves the main system prompt for the AI agent. | | Social Media Schema | A Google Docs node that retrieves the JSON schema for each social media platform's output. | | Social Media Content Creator | An AI agent that generates content based on user prompts, system prompts, and schemas, using a web search tool for research. | | pollinations.ai1 | An HTTP Request node that generates an image from a text prompt using an external service. | | Gmail User for Approval | Sends a draft of the social media post for approval and pauses the workflow until a decision is made. | | Social Media Publishing Router | A Switch node that routes the workflow to the correct publishing node based on the user's selected platform. | | X Post, Instagram Post, Facebook Post, LinkedIn Post | These nodes publish the final, approved content to their respective social media platforms. | Customization Tips You can replace the pollinations.ai image generation service with any other online service that produces an image file. Replace the gpt-4o and gpt-4o-mini models with other LLMs and web search tools to suit your needs. Adjust the content and parameters for each social media platform to better fit your brand and audience. Suggested Sticky Notes for Workflow Start Here**: "Update all Social Media Platform Credentials as required. Adjust parameters and content for each platform to suit your needs". External System Prompt and Schema**: "Create Google Doc for the Social Media Schema and copy the provided schema. Update the Google Doc ID in the Social Media Schema node.". Create Post Image**: "Replace pollinations.ai with any online image generation service that produces an image file you can download". Social Media Content Creator**: "Replace Chat model with other LLMs and test out the results. Add more tools or try other web search tools to suit your use case." Testing Tips Start the workflow with a manual trigger and verify that the social media content and a related image are generated and sent for approval via Gmail. Approve the content in the Gmail email to test the publishing side of the workflow. Check the specified social media accounts to confirm that the post was published correctly. Suggested Tags & Categories SocialMedia Automation AI ContentCreation Publishing GoogleDocs OpenAI

Arabic OCR Telegram Bot How it Works Receive PDF Files - Users send PDF documents via Telegram to the bot OCR Processing - Mistral AI's OCR service extracts Arabic text from document pages Text Organization - Processes and formats extracted content with page numbers Create Google Doc - Generates a formatted document with all extracted text Deliver Results - Sends users a clickable link to their processed document Set up Steps Setup Time: ~20 minutes Create Telegram Bot - Get bot token from @BotFather on Telegram Configure APIs - Set up Mistral AI OCR and Google Docs API credentials Set Folder Permissions - Create Google Drive folder for storing results Test Bot - Send a sample Arabic PDF to verify OCR accuracy Deploy Webhook - Activate the Telegram webhook for real-time processing Detailed API configuration and Arabic text handling notes are included as sticky notes within the workflow. What You'll Need: Telegram Bot Token (free from @BotFather) Mistral AI API key (OCR service) Google Docs/Drive API credentials Google Drive folder for document storage Sample Arabic PDF files for testing Key Features: Real-time progress updates (5-step process notifications) Automatic page numbering in Arabic Direct Google Docs integration Error handling for non-PDF files

Transform your email workflow with this intelligent automation that drafts professional emails through Telegram commands using AI and contact retrieval. Key Features 📱 Telegram Integration: Send email requests directly from Telegram 🤖 AI-Powered Email Generation: Uses OpenAI GPT-4 to create formal, professional emails 📧 Smart Contact Retrieval: Leverages Pinecone vector database with RAG to automatically find recipient email addresses ✉️ Gmail Draft Creation: Automatically creates email drafts in your Gmail account 📋 Google Docs Integration: Sync contact data from Google Docs to vector database 🎯 Structured Email Formatting: Ensures consistent professional email format with proper recipients and formal tone How It Works Send Message: Send a message via Telegram with your email request AI Processing: AI agent processes your request and queries the contact database to find recipient emails Email Generation: OpenAI generates a professionally formatted email based on your input Draft Creation: Gmail draft is automatically created with the formatted content Confirmation: Receive confirmation via Telegram with a completion sticker Perfect For Business professionals managing multiple contacts Academic professionals (professors, researchers) who frequently send formal emails Anyone wanting to streamline their email creation process with AI assistance Required Credentials Telegram Bot API OpenAI API google OAuth2 for(gmail&docs) Pinecone Vector Database Setup Instructions Load Contact Data: Add your contact information to the Google Docs document Configure Pinecone: Set up your Pinecone index with namespace "contacts" Connect Services: Add all required API credentials to their respective nodes Customize AI: Modify the AI system message and sender name in the AI Agent node Test Workflow: Run the manual trigger to populate your vector database first ** Ex. of the google docs data

This n8n template demonstrates how to automatically analyze all your accumulated notes from the past week and generate actionable insights, task lists, and priorities using AI. Use cases are many: Try automating weekly planning sessions, extracting action items from meeting notes, identifying recurring themes in your thoughts, or creating data-driven weekly reports for personal productivity tracking! Good to know ChatGPT analysis costs approximately $0.01-0.05 per week depending on the volume of notes The workflow uses advanced date filtering to process exactly 7 days of content Email sending requires SMTP configuration (Gmail, Outlook, etc.) Perfect companion:* Works seamlessly with the "Audio Notes to Google Docs*" workflow - it reads and analyzes all notes created by that system! How it works A schedule trigger runs every Sunday at your preferred time (default: 11 PM) The workflow reads your complete Google Doc containing all accumulated notes A smart filter function extracts only entries from the past 7 days using date stamp recognition The filtered content gets sent to ChatGPT which analyzes patterns and extracts: Actionable tasks for next week Important deadlines and appointments Key insights and learnings Top 3 priorities Category distribution (Work, Private, Health, etc.) A second AI call creates a personalized email summary with context and recommendations The structured analysis gets appended to your Google Doc as a weekly summary You receive a Telegram notification when the review is complete A detailed email report lands in your inbox with the full analysis and action items How to use The workflow runs automatically every Sunday - no manual intervention needed Adjust the schedule trigger to your preferred day/time for weekly planning Review the email summary and use the extracted tasks for your upcoming week planning The Google Doc serves as your permanent archive of weekly insights Requirements Google Docs API access to read your notes document OpenAI API account for ChatGPT analysis (GPT-4 recommended for best results) SMTP email configuration for sending summary reports Telegram Bot Token for notifications Prerequisite:* The "Audio Notes to Google Docs*" workflow or similar system that creates timestamped entries Customising this workflow Modify the AI analysis prompt to focus on specific areas (business metrics, health tracking, learning goals) Add multiple analysis modes (daily, bi-weekly, monthly reviews) Include additional outputs like calendar event creation, task manager integration, or team sharing Connect to project management tools like Notion, Asana, or Monday.com for automatic task creation

This n8n template demonstrates how to automatically convert voice messages from Telegram into structured, searchable notes in Google Docs using AI transcription and intelligent tagging. Use cases are many: Try capturing ideas on-the-go while walking, recording meeting insights hands-free, creating voice journals, or building a personal knowledge base from spoken thoughts! Good to know OpenAI Whisper transcription costs approximately $0.006 per minute of audio ChatGPT tagging adds roughly $0.001-0.003 per message depending on length The workflow supports both German and English voice recognition Text messages are also supported - they bypass transcription and go directly to AI tagging Perfect companion: Combine with the "Weekly AI Review**" workflow for automated weekly summaries of all your notes! How it works Telegram receives your voice message or text and triggers the workflow An IF node intelligently detects whether you sent audio or text content For voice messages: Telegram downloads the audio file and OpenAI Whisper transcribes it to text For text messages: Content is passed directly to the next step ChatGPT analyzes the content and generates up to 3 relevant keywords (Work, Ideas, Private, Health, etc.) A function node formats everything with Swiss timestamps, message type indicators, and clean structure The formatted entry gets automatically inserted into your Google Doc with date, keywords, and full content Telegram sends you a confirmation with the transcribed/original text so you can verify accuracy How to use Simply send a voice message or text to your Telegram bot - the workflow handles everything automatically The manual execution can be used for testing, but in production this runs on every message Voice messages work best with clear speech in quiet environments for optimal transcription Requirements Telegram Bot Token and configured webhook OpenAI API account for Whisper transcription and ChatGPT tagging Google Docs API access for document writing A dedicated Google Doc where all notes will be collected Customising this workflow Adjust the AI prompt to use different tagging categories relevant to your workflow (e.g., project names, priorities, emotions) Add multiple Google Docs for different contexts (work vs. private notes) Include additional processing like sentiment analysis or automatic task extraction Connect to other apps like Notion, Obsidian, or your preferred note-taking system And don't forget to also implement the complimentary workflow Weekly AI Review!

Automated App Analysis & ASO Report Generator This workflow automates the process of analyzing a mobile app from the Google Play Store and generating a professional ASO (App Store Optimization) Report. Simply submit a Play Store URL, and the workflow will fetch app intelligence data, parse it, run an AI-based analysis, and deliver a formatted report in Google Docs. A Telegram notification with the document link ensures you never miss a new report. ✨ Key Features Form Input Trigger** – Start the workflow by submitting a Play Store URL. Automated Data Retrieval** – Uses HTTP request to fetch app intelligence (via SensorTower or similar APIs). Smart Data Parsing** – Extracts essential app details, competitor insights, reviews, downloads, and revenue data. AI-Powered ASO Report** – Generates a professional analysis using LLM (Gemini via OpenRouter) with structured sections: 📱 App Overview ⭐ User Ratings & Reviews 📊 Competitor Analysis 📈 Market Insights 💡 Actionable Recommendations Google Docs Integration** – Creates and updates a Google Doc with the generated report. Instant Notification** – Sends a Telegram message with the app report link for quick access. 🔐 Required Credentials To run this workflow, you’ll need: SensorTower API (or alternative App Intelligence API)** – for app details, reviews, competitors, and market data. OpenRouter API** – to access LLM model. Google Docs OAuth2** – to create and update the ASO report in Google Docs. Telegram API** – for instant notifications with the report link. 🎁 Benefits Save Time** – Automates the manual process of app research and reporting. Consistent Reporting** – Ensures every report follows a professional structure with clear sections. Actionable Insights** – Get AI-generated recommendations to improve app performance and competitiveness. Collaboration-Ready** – Reports are stored in Google Docs for easy sharing and editing. Real-Time Alerts** – Stay updated via Telegram whenever a new report is generated.

Who’s it for This workflow is ideal for marketers, content creators, agencies, and small businesses that want to streamline the process of creating and publishing platform-optimized posts across multiple social media channels. How it works / What it does From a single user prompt, the workflow uses a custom system prompt and schema to generate tailored social media content for LinkedIn, Instagram, Facebook, Twitter (X), Threads, and YouTube Shorts. It creates platform-specific captions, hashtags, calls to action, and even AI-generated image suggestions, then routes the content to the correct publishing channel. How to set up Connect your social media platform credentials in n8n. Add your Google Docs links for the system prompt and content schema. Configure the IMGBB_API_KEY and any other required API credentials. Optionally connect Gmail and Telegram for approval workflows and notifications. Requirements n8n instance (self-hosted or cloud) API credentials for desired platforms Google Docs and Google Drive accounts How to customize the workflow Edit the system prompt and schema in Google Docs to adjust tone, style, and content format for each platform. Modify routing logic or add new platform integrations as needed.

N8N Hybrid RAG Chatbot with Multiple AI Agents One of the most powerful system in the market, this template creates a sophisticated, multi-agent hybrid RAG (Retrieval-Augmented Generation) chatbot that can handle diverse user queries by routing them to a “Supervisor AI agent”. The Supervisor agent will then send the request to “Expert AI agents”, agents specializing in specific domains. In addition, this system automates data ingestion from various sources (including websites and Google Drive), processes and stores the information in a vector database, and interacts with users through Telegram in multiple languages. For more powerful n8n templates, visit our website at aiautomationpro.org. Who’s it for? This template is ideal for: Developers and Businesses** looking to build a powerful, knowledge-based chatbot for customer support, internal knowledge management, or lead generation. AI Enthusiasts** who want to explore advanced concepts like multi-agent systems, RAG, and automated data pipelines. n8n Users** who want to build a scalable and customizable AI solution that integrates multiple services. Key Features Multi-Agent Architecture:** Utilizes a supervisor agent to route queries to specialized agents for different domains (e.g., Products, News, Academy). Automated Data Ingestion:** Automatically scrapes data from websites and syncs new or updated files from Google Drive. Retrieval-Augmented Generation (RAG):** Enriches the chatbot's knowledge by retrieving relevant information from a Supabase vector store and a Postgres database. Telegram Integration:** Provides a seamless, multi-language chat interface for users to interact with the bot. Dynamic Data Handling:** Automatically processes and embeds data from various sources like Google Docs, PDFs, and Word documents. Data Management:** Keeps the knowledge base up-to-date by automatically handling document creation, updates, and deletions. How it works The workflow is divided into three main parts: data ingestion, data management, and the chat interface. Data Ingestion & Processing: Web Scraping: The workflow fetches URLs from a Google Sheet, scrapes the content using Crawl4ai, cleans it with an AI agent, and saves it to a Google Doc. Google Drive Sync: It monitors specific Google Drive folders for new or updated files (Google Docs, PDFs, Word documents). Embedding & Storage: The content from these sources is then chunked, converted into vector embeddings using OpenAI, and stored in a Supabase vector database for efficient retrieval. Data Deletion: A scheduled trigger periodically checks a Google Sheet for records marked as "deleted." It then removes the corresponding data from the Supabase vector store and deletes the file from Google Drive to ensure the chatbot's knowledge remains current. Chat Interface & Logic (Telegram): User Input: The chatbot receives user messages via a Telegram trigger. Language Detection: It first detects the language of the query and translates it to English if necessary. Supervisor Agent: A central "Supervisor" AI agent analyzes the user's query. Agent Routing: Based on the query, the Supervisor delegates the task to the most appropriate specialized agent: News AI Agent: Handles questions about current events. Product AI Agent: Answers queries about product details from a Postgres database. Academy AI Agent: Responds to questions about courses and educational content. Response Generation: The selected agent processes the query, retrieves the necessary information using RAG, generates a response, and translates it back to the user's original language before sending it via Telegram. Requirements To use this template, you will need accounts and credentials for the following services: n8n OpenAI Supabase (for vector storage) Google Workspace (Google Drive, Google Sheets, Google Docs) Telegram Bot Postgres Database Crawl4AI Step-by-step Setup Configure Credentials: Add your API keys and credentials for all the required services (OpenAI, Supabase, Google, Telegram, Postgres) in the n8n Credentials section. Set up Google Drive: Create two folders in your Google Drive: one for documents scraped from websites and another for manual document uploads. Note the folder IDs. Set up Google Sheets: Clone the Google Sheet template, or create a Google Sheet with two tabs: Website Links and Manual Documents. In the Website Links tab, add columns for Link, Category Code, Is Scraped, and Is Deleted. In the Manual Documents tab, add columns for Document ID, Title, Category Code, and Is Deleted. Set up Supabase: Create a new project in Supabase. Run the provided SQL script to create the documents table for vector storage. Set up Postgres: Set up a Postgres database (in Supabase). Run the provided SQL script to create the products table to store product details. Configure the Main Workflow: Open the AIAutomationPro Ultimate RAG Chatbot main workflow. Update the Google Drive, Google Sheets, Supabase, and Postgres nodes with your specific Folder IDs, Sheet Names, and table names. Link the three sub-workflows (News AI Agent, Product AI Agent, Academy AI Agent) in the corresponding Workflow Tool nodes. Activate Workflows: Activate the main workflow and all three sub-flow workflows. Start Chatting: Send a message to your Telegram bot to start interacting with your new RAG chatbot. How to Customize the Workflow Add More Agents:** You can create new sub-workflows with specialized agents for different topics (e.g., a "Finance AI Agent"). Simply add a new Workflow Tool node in the main flow and update the Supervisor Agent's system prompt to include the new agent's capabilities. Change Data Sources:** Modify the data ingestion part of the workflow to pull data from other sources like Notion, HubSpot, or a CRM by adding the relevant n8n nodes. Adjust the AI Model:** You can switch to a different LLM by replacing the OpenAI Chat Model nodes. Modify Prompts:** Fine-tune the system prompts in the Agent nodes to alter the personality, instructions, or output format of the chatbot and its specialized agents.