HumationHuman + Automation
Back to Catalog

Conversational travel booker: Automate flight & hotel reservations with GPT-3.5

Oneclick AI SquadOneclick AI Squad
2949 views
2/3/2026
Lead GenerationJotFormAutomationSalesforceCRM
Official Page

This guide walks you through setting up an AI-driven workflow to automate flight and hotel reservation processes using a conversational travel booking system. The workflow accepts booking requests, processes them via APIs, and sends confirmations, enabling a seamless travel booking experience.

What’s the Goal?

  • Automatically accept and process booking requests for flights and hotels via HTTP POST.
  • Use AI to understand natural language requests and route them to appropriate data processors.
  • Search for flights and hotels using external APIs and process booking confirmations.
  • Send confirmation emails and return structured booking data to users.
  • Enable an automated system for efficient travel reservations.

By the end, you’ll have a self-running system that handles travel bookings effortlessly.

Why Does It Matter?

Manual booking processes are time-consuming and prone to errors. This workflow offers:

  • Zero Human Error: AI ensures accurate request parsing and booking processing.
  • Time-Saving Automation: Automates the entire booking lifecycle, boosting efficiency.
  • Seamless Confirmation: Sends automated emails and responses without manual intervention.
  • Enhanced User Experience: Provides a conversational interface for bookings. Think of it as your reliable travel booking assistant that keeps the process smooth and efficient.

How It Works

Here’s the step-by-step flow of the automation:

Step 1: Trigger the Workflow

  • Webhook Trigger: Accepts incoming booking requests via HTTP POST, initiating the workflow.

Step 2: Parse the Request

  • AI Request Parser: Uses AI to understand natural language booking requests (e.g., flight or hotel) and extracts relevant details.

Step 3: Route Booking Type

  • Booking Type Router: Determines whether the request is for a flight or hotel and routes it to the respective data processor.

Step 4: Process Flight Data

  • Flight Data Processor: Handles flight-specific data and prepares it for the search API.

Step 5: Search Flight API

  • Flight Search API: Searches for available flights based on parameters (e.g., https://api.aviationstack.com) and returns results.

Step 6: Process Hotel Data

  • Hotel Data Processor: Handles hotel-specific data and prepares it for the search API.

Step 7: Search Hotel API

  • Hotel Search API: Searches for available hotels based on parameters (e.g., https://api.booking.com) and returns results.

Step 8: Process Flight Booking

  • Flight Booking Processor: Processes flight bookings and generates confirmation details.

Step 9: Process Hotel Booking

  • Hotel Booking Processor: Processes hotel bookings and generates confirmation details.

Step 10: Generate Confirmation Message

  • Confirmation Message Generator: Creates structured confirmation messages for the user.

Step 11: Send Confirmation Email

  • Send Confirmation Email: Sends booking confirmation via email to the user.

Step 12: Send Response

  • Send Response: Returns structured booking data to the user, completing the workflow.

How to Use the Workflow?

Importing the workflow in n8n is a straightforward process. Follow these steps to import the Conversational Travel Booker workflow:

  1. Download the Workflow: Obtain the workflow file (e.g., JSON export from n8n).
  2. Open n8n: Log in to your n8n instance.
  3. Import Workflow: Navigate to the workflows section, click "Import," and upload the workflow file.
  4. Configure Nodes: Adjust settings (e.g., API keys, webhook URLs) as needed.
  5. Execute Workflow: Test and activate the workflow to start processing bookings.

Requirements

  • n8n account and instance setup.
  • Access to flight and hotel search APIs (e.g., Aviationstack, Booking.com).
  • Email service integration for sending confirmations.
  • Webhook URL for receiving booking requests.

Customizing this Workflow

  • Modify the AI Request Parser to handle additional languages or booking types.
  • Update API endpoints in Flight Search API and Hotel Search API nodes to match your preferred providers.
  • Adjust the Send Confirmation Email node to include custom email templates or additional recipients.
  • Schedule the Webhook Trigger to align with your business hours or demand peaks.

6262-conversational-travel-booker-automate-flight--hotel-reservations-with-gpt-35

This n8n workflow demonstrates a basic integration with OpenAI and email, triggered by a webhook. It's designed to receive an input via webhook, process it using an OpenAI model, and then send an email based on the AI's response. A switch node allows for conditional branching, although the specific conditions are not defined in the provided JSON.

What it does

  1. Receives Webhook Input: The workflow starts by listening for incoming data via a Webhook.
  2. Processes with OpenAI: The received data is then sent to an OpenAI model for processing (e.g., generating text, answering questions).
  3. Conditional Logic: A Switch node is present, indicating that the workflow can branch based on certain conditions derived from previous steps. However, the specific conditions are not configured in this JSON.
  4. Responds to Webhook: The workflow can send a response back to the originating webhook.
  5. Sends Email: An email is sent, likely containing the output from the OpenAI model or a summary of the interaction.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance to host the workflow.
  • OpenAI API Key: An OpenAI API key configured as a credential in n8n.
  • SMTP Credentials: SMTP server details configured as a credential in n8n for sending emails.
  • Webhook Trigger: An external system or application capable of sending HTTP requests to the n8n Webhook URL.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key credential in n8n.
    • Set up your SMTP (Email Send) credential in n8n.
  3. Configure Webhook:
    • Activate the "Webhook" trigger node. n8n will provide a unique URL.
    • Configure your external application to send data to this Webhook URL.
  4. Configure OpenAI Node:
    • Select your OpenAI credential.
    • Adjust the "Model" and "Prompt" parameters as needed for your specific use case (e.g., to generate flight/hotel reservation summaries, conversational responses).
  5. Configure Switch Node:
    • Define the conditions within the "Switch" node based on the expected output from OpenAI or the initial webhook data. This will determine which path the workflow takes.
  6. Configure Send Email Node:
    • Select your SMTP credential.
    • Specify the recipient email address, subject, and body. You can use expressions to dynamically include data from previous nodes (e.g., OpenAI's response).
  7. Activate the Workflow: Once configured, activate the workflow to make it live.

This workflow provides a foundation for building more complex conversational AI agents that can interact via webhooks and send email notifications. You would typically expand the "Switch" node to handle different types of user requests or AI responses, and potentially add more nodes for data storage, CRM integration, or other actions.

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.

Ranjan DailataBy Ranjan Dailata
161

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

Daniel NkenchoBy Daniel Nkencho
601

Automate 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.

Le NguyenBy Le Nguyen
942