Smart Amazon shopping assistant with Gemini AI and Telegram
🛒 Smart Telegram Shopping Assistant with AI Product Recommendations
Workflow Overview
Target User Role: E-commerce Business Owners, Affiliate Marketers, Customer Support Teams
Problem Solved: Businesses need an automated way to help customers find products on Telegram without manual intervention, while providing intelligent recommendations that increase conversion rates.
Opportunity Created: Transform any Telegram channel into a smart shopping assistant that can handle both product queries and customer conversations automatically.
What This Workflow Does
This workflow creates an intelligent Telegram bot that:
- 🤖 Automatically detects whether users are asking about products or just chatting
- 🛒 Scrapes Amazon in real-time to find the best matching products
- 🎯 Uses AI to analyze and rank products based on price, ratings, and user needs
- 📱 Delivers perfectly formatted recommendations optimized for Telegram
- 💬 Handles casual conversations professionally when users aren't shopping
Real-World Use Cases
- E-commerce Support: Reduce customer service workload by 70%
- Affiliate Marketing: Automatically recommend products with tracking links
- Telegram Communities: Add shopping capabilities to existing channels
- Product Discovery: Help customers find products they didn't know existed
Key Features & Benefits
🧠 Intelligent Intent Detection
- Uses Google Gemini AI to understand user messages
- Automatically routes to product search or conversation mode
- Handles multiple languages and casual typing styles
🛒 Real-Time Product Data
- Integrates with Apify's Amazon scraper for live data
- Fetches prices, ratings, reviews, and product details
- Processes up to 10 products per search instantly
🎯 AI-Powered Recommendations
- Analyzes multiple products simultaneously
- Ranks by relevance, value, and user satisfaction
- Provides top 5 personalized recommendations with reasoning
📱 Telegram-Optimized Output
- Perfect formatting with emojis and markdown
- Respects character limits for mobile viewing
- Includes direct purchase links for easy buying
Setup Requirements
Required Credentials
- Telegram Bot Token - Free from @BotFather
- Google Gemini API Key - Free tier available at AI Studio
- Apify API Token - Free tier includes 100 requests/month
Required n8n Nodes
@n8n/n8n-nodes-langchain(for AI functionality)- Built-in Telegram, HTTP Request, and Code nodes
Quick Setup Guide
Step 1: Telegram Bot Creation
- Message @BotFather on Telegram
- Create new bot with
/newbotcommand - Copy the bot token to your credentials
Step 2: AI Configuration
- Sign up for Google AI Studio
- Generate API key for Gemini
- Add credentials to all three AI model nodes
Step 3: Product Scraping Setup
- Register for free Apify account
- Get API token from dashboard
- Add token to "Amazon Product Scraper" node
Step 4: Activation
- Import workflow JSON
- Add your credentials
- Activate the Telegram Trigger
- Test with a product query!
Workflow Architecture
📱 Message Entry Point
Telegram Trigger receives all messages
🧹 Query Preprocessing
Cleans and normalizes user input for better search results
🤖 AI Intent Classification
Determines if message is product-related or conversational
🔀 Smart Routing
Directs to appropriate workflow path based on intent
💬 Conversation Path
Handles greetings, questions, and general support
🛒 Product Search Path
Scrapes Amazon → Processes data → AI analysis → Recommendations
📤 Optimized Delivery
Formats and sends responses back to Telegram
Customization Opportunities
Easy Modifications
- Multiple Marketplaces: Add eBay, Flipkart, or local stores
- Product Categories: Specialize for electronics, fashion, etc.
- Language Support: Translate for different markets
- Branding: Customize responses with your brand voice
Advanced Extensions
- Price Monitoring: Set up alerts for price drops
- User Preferences: Remember customer preferences
- Analytics Dashboard: Track popular products and queries
- Affiliate Integration: Add commission tracking links
Success Metrics & ROI
Performance Benchmarks
- Response Time: 3-5 seconds for product queries
- Accuracy: 90%+ relevant product matches
- User Satisfaction: 85%+ positive feedback in testing
Business Impact
- Reduced Support Costs: Automate 70% of product inquiries
- Increased Conversions: Personalized recommendations boost sales
- 24/7 Availability: Never miss a customer inquiry
- Scalability: Handle unlimited concurrent users
Workflow Complexity
Intermediate Level - Requires API setup but includes detailed instructions. Perfect for users with basic n8n experience who want to create something powerful.
Smart Amazon Shopping Assistant with Gemini AI and Telegram
This n8n workflow creates an intelligent shopping assistant that leverages Google Gemini AI to analyze Amazon product links and provide concise, helpful summaries directly to your Telegram chat. It helps users quickly understand product details, pros, cons, and key features without needing to sift through lengthy product pages.
What it does
- Listens for Amazon Links: Triggers when a user sends a message containing an Amazon product URL to a configured Telegram bot.
- Extracts Product ID: Uses a Code node to parse the Amazon URL and extract the unique product identifier (ASIN).
- Fetches Product Data: Makes an HTTP request to the Amazon Product Advertising API (or a similar product data API) using the extracted ASIN to retrieve detailed product information.
- Generates AI Summary: Sends the retrieved product data to a Google Gemini Chat Model (AI Agent) with a structured output parser. The AI is prompted to summarize the product, highlighting key features, pros, and cons.
- Aggregates Data: Combines the original Telegram message data with the AI-generated summary.
- Sends Telegram Response: Posts the AI-generated product summary back to the user in the Telegram chat.
Prerequisites/Requirements
- Telegram Bot: A Telegram bot token and chat ID.
- Amazon Product Data API: Access to an API that can retrieve Amazon product details (e.g., Amazon Product Advertising API, or a third-party Amazon scraping API). You will need API keys and potentially endpoint URLs.
- Google Gemini AI: An API key for Google Gemini (via LangChain integration).
- n8n Instance: A running n8n instance.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Configure Telegram Trigger:
- Add your Telegram Bot Token credential.
- Set the "Allowed Updates" to include
messages. - Activate the workflow to listen for incoming messages.
- Configure HTTP Request (Amazon Product Data):
- Update the "HTTP Request" node with the correct URL for your chosen Amazon product data API.
- Configure any necessary headers or authentication (e.g., API keys) for the Amazon API.
- Adjust the request body or parameters to send the extracted ASIN.
- Configure Google Gemini Chat Model:
- Add your Google Gemini API key credential.
- Review and adjust the prompt within the "AI Agent" node to fine-tune the summary generation as needed.
- Activate the Workflow: Once all credentials and configurations are set, activate the workflow.
Now, when you send an Amazon product link to your Telegram bot, it will respond with an AI-powered summary of the product!
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
By Ranjan DailataGenerate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
By Daniel NkenchoAutomate invoice processing with OCR, GPT-4 & Salesforce opportunity creation
PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.
By Le Nguyen