All-in-one Telegram/Baserow AI assistant 🤖🧠 Voice/Photo/Save notes/Long term mem

Telegram Personal Assistant with Long-Term Memory & Note-Taking This n8n workflow transforms your Telegram bot into a powerful personal assistant that handles voice, photo, and text messages. The assistant uses AI to interpret messages, save important details as long-term memories or notes in a Baserow database, and recall information for future interactions. --- 🌟 How It Works 1. Message Reception & Routing - Telegram Integration: The workflow is triggered by incoming messages on your Telegram bot. - Dynamic Routing: A switch node inspects the message to determine whether it's voice, text, or photo (with captions) and routes it for the appropriate processing. 2. Content Processing - Voice Messages: Audio files are retrieved and sent to an AI transcription node to convert spoken words into text. - Text Messages: Text is directly captured and prepared for analysis. - Photos: If an image is received, the bot fetches the file (and caption, if provided) and uses an AI-powered image analysis node to extract relevant details. 3. AI-Powered Agent & Memory Management - The core AI agent (powered by GPT-4o-mini) processes the incoming message along with any previous conversation history stored in PostgreSQL memory buffers. - Long-Term Memory: When a message contains personal or noteworthy information, the assistant uses a dedicated tool to save this data as a long-term memory in Baserow. - Note-Taking: For specific instructions or reminders, the assistant saves concise notes in a separate Baserow table. - The AI agent follows defined rules to decide which details are saved as memories and which are saved as notes. 4. Response Generation - After processing the message and updating memory/notes as needed, the AI agent crafts a contextual and personalized response. - The response is sent back to the user via Telegram, ensuring smooth and natural conversation flow. --- 🚀 Key Features - Multimodal Input: Seamlessly handles voice, photo (with captions), and text messages. - Long-Term Memory & Note-Taking: Uses a Baserow database to store personal details and notes, enhancing conversational context over time. - AI-Driven Contextual Responses: Leverages an AI agent to generate personalized, context-aware replies based on current input and past interactions. - User Security & Validation: Incorporates validation steps to verify the user's Telegram ID before processing, ensuring secure and personalized interactions. - Easy Baserow Setup: Comes with a clear setup guide and sample configurations to quickly integrate Baserow for managing memories and notes. --- 🔧 Setup Guide 1. Telegram Bot Setup: - Create your bot via BotFather and obtain the Bot Token. - Configure the Telegram webhook in n8n with your bot's token and URL. 2. Baserow Database Configuration: - Memory Table: - Create a workspace titled "Memories and Notes". - Set up a table (e.g., "Memory Table") with at least two fields: - Memory (long text) - Date Added (US date format with time) - Notes Table: - Duplicate the Memory Table and rename it to "Notes Table". - Change the first field's name from "Memory" to "Notes". 3. n8n Workflow Import & Configuration: - Import the workflow JSON into your n8n instance. - Update credentials for Telegram, Baserow, OpenAI, and PostgreSQL (for memory buffering) as needed. - Adjust node settings if you need to customize AI agent prompts or memory management rules. 4. Testing & Deployment: - Test your bot by sending various message types (text, voice, photo) to confirm that the workflow processes them correctly, updates Baserow, and returns the appropriate response. - Monitor logs to ensure that memory and note entries are correctly stored and retrieved. --- ✨ Example Interactions - Voice Message Processing: - User sends a voice note requesting a reminder. - Bot Response: "Thanks for your message! I've noted your reminder and saved it for future reference." - Photo with Caption: - User sends a photo with the caption "Save this recipe for dinner ideas."