Generate stock trading signals with Gemini 2.5 Pro & TwelveData via Telegram Bot
Purpose and Audience
This n8n workflow template creates an intelligent stock technical analysis system that delivers professional-grade trading signals directly to your Telegram. Designed for retail traders, investors, and financial professionals who want to combine technical analysis with AI-powered insights for better market timing decisions.
Who Is It For
- Retail Traders: Looking to enhance their technical analysis with AI-driven insights
- Swing Traders: Need reliable signals for entry and exit timing
- Investment Professionals: Want automated technical screening for multiple stocks
- Financial Enthusiasts: Interested in combining traditional TA with modern AI tools
- Portfolio Managers: Seeking systematic approach to market timing
How It Works
The workflow operates as a comprehensive technical analysis engine:
- Data Collection: Fetches real-time stock prices and 90-day historical data from TwelveData API
- Technical Calculation: Computes key indicators including EMAs, RSI, ATR, and support/resistance levels
- AI Analysis: Uses Google Gemini 2.5 Pro to analyze confluence of indicators and generate single, high-probability signals
- Signal Generation: Produces clear BUY/SELL/NEUTRAL recommendations with specific entry, stop-loss, and take-profit levels
- Delivery: Sends formatted analysis and interactive charts via Telegram bot
- Risk Management: Includes built-in risk parameters and confidence scoring
Setup Requirements
- Create Telegram bot via BotFather
- Set up Google Gemini credentials
- Configure additional nodes as you see in the sticky notes
- Deploy and test with stock symbols (e.g., "AAPL", "TSLA")
Note: Complete setup guide is provided with the workflow file.
Technical Indicators Used in Strategy
Core Indicators (1-Day Timeframe):
- EMA 50 & EMA 200: Trend direction and momentum confirmation
- RSI (14-period): Momentum oscillator for overbought/oversold conditions
- ATR (14-period): Volatility measurement for risk sizing
- Support/Resistance: Dynamic levels calculated from 90-day price history.
- Fibonacci Retracements: Additional confluence levels.
Important Disclaimers
- ⚠️ Analysis timeframe is set to 1-day by default - suitable for swing trading, not day trading
- ⚠️ Not a get-rich-quick system - This tool provides technical analysis, not financial advice
- ⚠️ Use with fundamental analysis - Technical signals work best when combined with fundamental research for timing entries and exits
- ⚠️ Not recommended for isolated use - Always consider fundamentals, market conditions, news, and risk management
Key Features
- Single, clear signal per analysis (no conflicting recommendations; either buy or sell)
- Built-in confidence scoring system
- Automated chart generation and delivery
- Support for any US stock ticker
- Professional-grade risk management parameters
Use Case Examples
- Pre-market Analysis: Send "AAPL" stock ticker as a message to your telegram bot and get comprehensive technical analysis with 1 Day candlesticks chart
- Swing Trading: Use signals to time entries on already-researched stocks
- Portfolio Review: Analyze multiple positions for exit timing
- Educational Tool: Learn technical analysis through AI explanations
This template transforms complex technical analysis into accessible, actionable trading insights while maintaining professional risk management standards.
n8n Workflow: Generate Stock Trading Signals with Gemini 2.5 Pro & TwelveData via Telegram Bot
This n8n workflow empowers you to get real-time stock trading signals directly through a Telegram bot. By integrating with TwelveData for stock data and leveraging Google Gemini 2.5 Pro for AI analysis, it provides intelligent buy/sell recommendations based on your queries.
What it does
This workflow automates the following steps:
- Listens for Telegram Commands: The workflow is triggered when a user sends a message to a configured Telegram bot.
- Extracts Stock Symbol: It processes the incoming Telegram message to identify the stock symbol (e.g., "AAPL", "GOOGL") the user is interested in.
- Fetches Real-time Stock Data: It makes an API call to TwelveData to retrieve real-time stock data for the extracted symbol.
- Prepares Data for AI Analysis: The fetched stock data is formatted and combined with the user's query to create a comprehensive prompt for the AI.
- Generates Trading Signals with Google Gemini: The prepared data is sent to Google Gemini 2.5 Pro, which analyzes the stock information and generates a trading signal (e.g., "Buy", "Sell", "Hold") along with a brief explanation.
- Formats AI Output: The AI's response is parsed to extract the trading signal and any additional insights.
- Sends Signal to Telegram: The generated trading signal and explanation are sent back to the user via the Telegram bot.
- Handles Delays: A
Waitnode is included to manage API rate limits or introduce a pause if necessary.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Instance: A running instance of n8n.
- Telegram Bot: A Telegram bot token and chat ID. You can create a bot using BotFather on Telegram.
- TwelveData API Key: An API key for TwelveData to fetch stock market data.
- Google Gemini API Key: An API key for Google Gemini 2.5 Pro to power the AI analysis.
- Langchain Nodes: Ensure the
@n8n/n8n-nodes-langchainpackage is installed in your n8n instance, as it's used for the AI Agent, Simple Memory, Structured Output Parser, and Google Gemini Chat Model nodes.
Setup/Usage
-
Import the Workflow:
- Download the provided JSON file.
- In your n8n instance, go to "Workflows" and click "New".
- Click the "Import from JSON" button and paste the workflow JSON or upload the file.
-
Configure Credentials:
- Telegram Trigger: Configure the "Telegram Trigger" node with your Telegram bot credentials (Bot Token).
- Telegram: Configure the "Telegram" node with your Telegram bot credentials (Bot Token) and the Chat ID where you want to send messages.
- HTTP Request (TwelveData): Update the "HTTP Request" node to include your TwelveData API key in the URL or headers as required by TwelveData's API documentation.
- Google Gemini Chat Model: Configure the "Google Gemini Chat Model" node with your Google Gemini API key.
-
Activate the Workflow:
- Ensure all necessary credentials are set up correctly.
- Click the "Activate" toggle in the top right corner of the workflow editor to enable the workflow.
-
Use the Telegram Bot:
- Send a message to your configured Telegram bot with a stock symbol (e.g., "AAPL", "GOOGL").
- The bot will respond with a trading signal and explanation generated by Google Gemini.
Related Templates
Generate 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
Auto-reply & create Linear tickets from Gmail with GPT-5, gotoHuman & human review
This workflow automatically classifies every new email from your linked mailbox, drafts a personalized reply, and creates Linear tickets for bugs or feature requests. It uses a human-in-the-loop with gotoHuman and continuously improves itself by learning from approved examples. How it works The workflow triggers on every new email from your linked mailbox. Self-learning Email Classifier: an AI model categorizes the email into defined categories (e.g., Bug Report, Feature Request, Sales Opportunity, etc.). It fetches previously approved classification examples from gotoHuman to refine decisions. Self-learning Email Writer: the AI drafts a reply to the email. It learns over time by using previously approved replies from gotoHuman, with per-classification context to tailor tone and style (e.g., different style for sales vs. bug reports). Human Review in gotoHuman: review the classification and the drafted reply. Drafts can be edited or retried. Approved values are used to train the self-learning agents. Send approved Reply: the approved response is sent as a reply to the email thread. Create ticket: if the classification is Bug or Feature Request, a ticket is created by another AI agent in Linear. Human Review in gotoHuman: How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up credentials for gotoHuman, OpenAI, your email provider (e.g. Gmail), and Linear. In gotoHuman, select and create the pre-built review template "Support email agent" or import the ID: 6fzuCJlFYJtlu9mGYcVT. Select this template in the gotoHuman node. In the "gotoHuman: Fetch approved examples" http nodes you need to add your formId. It is the ID of the review template that you just created/imported in gotoHuman. Requirements gotoHuman (human supervision, memory for self-learning) OpenAI (classification, drafting) Gmail or your preferred email provider (for email trigger+replies) Linear (ticketing) How to customize Expand or refine the categories used by the classifier. Update the prompt to reflect your own taxonomy. Filter fetched training data from gotoHuman by reviewer so the writer adapts to their personalized tone and preferences. Add more context to the AI email writer (calendar events, FAQs, product docs) to improve reply quality.
Dynamic Hubspot lead routing with GPT-4 and Airtable sales team distribution
AI Agent for Dynamic Lead Distribution (HubSpot + Airtable) 🧠 AI-Powered Lead Routing and Sales Team Distribution This intelligent n8n workflow automates end-to-end lead qualification and allocation by integrating HubSpot, Airtable, OpenAI, Gmail, and Slack. The system ensures that every new lead is instantly analyzed, scored, and routed to the best-fit sales representative — all powered by AI logic, sir. --- 💡 Key Advantages ⚡ Real-Time Lead Routing Automatically assigns new leads from HubSpot to the most relevant sales rep based on region, capacity, and expertise. 🧠 AI Qualification Engine An OpenAI-powered Agent evaluates the lead’s industry, region, and needs to generate a persona summary and routing rationale. 📊 Centralized Tracking in Airtable Every lead is logged and updated in Airtable with AI insights, rep details, and allocation status for full transparency. 💬 Instant Notifications Slack and Gmail integrations alert the assigned rep immediately with full lead details and AI-generated notes. 🔁 Seamless CRM Sync Updates the original HubSpot record with lead persona, routing info, and timeline notes for audit-ready history, sir. --- ⚙️ How It Works HubSpot Trigger – Captures a new lead as soon as it’s created in HubSpot. Fetch Contact Data – Retrieves all relevant fields like name, company, and industry. Clean & Format Data – A Code node standardizes and structures the data for consistency. Airtable Record Creation – Logs the lead data into the “Leads” table for centralized tracking. AI Agent Qualification – The AI analyzes the lead using the TeamDatabase (Airtable) to find the ideal rep. Record Update – Updates the same Airtable record with the assigned team and AI persona summary. Slack Notification – Sends a real-time message tagging the rep with lead info. Gmail Notification – Sends a personalized handoff email with context and follow-up actions. HubSpot Sync – Updates the original contact in HubSpot with the assignment details and AI rationale, sir. --- 🛠️ Setup Steps Trigger Node: HubSpot → Detect new leads. HubSpot Node: Retrieve complete lead details. Code Node: Clean and normalize data. Airtable Node: Log lead info in the “Leads” table. AI Agent Node: Process lead and match with sales team. Slack Node: Notify the designated representative. Gmail Node: Email the rep with details. HubSpot Node: Update CRM with AI summary and allocation status, sir. --- 🔐 Credentials Required HubSpot OAuth2 API – To fetch and update leads. Airtable Personal Access Token – To store and update lead data. OpenAI API – To power the AI qualification and matching logic. Slack OAuth2 – For sending team notifications. Gmail OAuth2 – For automatic email alerts to assigned reps, sir. --- 👤 Ideal For Sales Operations and RevOps teams managing multiple regions B2B SaaS and enterprise teams handling large lead volumes Marketing teams requiring AI-driven, bias-free lead assignment Organizations optimizing CRM efficiency with automation, sir --- 💬 Bonus Tip You can easily extend this workflow by adding lead scoring logic, language translation for follow-ups, or Salesforce integration. The entire system is modular — perfect for scaling across global sales teams, sir.