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Templates by ChatPayLabs
AI chatbot call center: Taxi booking support (production-ready, part 7)
Workflow Name: 🫶 Taxi Booking Support Template was created in n8n v1.90.2 Skill Level: Mid Categories: n8n, Chatbot Stacks Schedule Trigger node Postgres node AI Agent node Google Calendar node Execute Sub-workflow If node, Switch node, Code node, Edit Fields (Set) Prerequisite Sub-workflow: Demo Call Back (or your own node) Production Features Scaling Design for n8n Queue mode in production environment Customize Expired Booking Actions example Multi-Language Design What this workflow does? This is a n8n Taxi Booking Support, the background node to process the job at scheduled. It is scheduled to check the database for outstanding booking and handle the after sales process. In this particular case, it will check for OPEN booking over 10 minutes, then update the booking status from OPEN to CANCELLED, delete the Calendar event and send a reply to the user. How it works The Schedule Trigger node is scheduled to run every 5 minutes. It will check the database for OPEN or HOLD booking. For OPEN booking update the booking status to CANCELLED delete the Calendar event send a reply to the user Optional: The AI Agent is used to create the reply message to the user in Multi-language based on the language set in the booking. Set up instructions Pull and Set up the required SQL from our Github repository. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Open Hold Booking and Set Cancel Booking. Create your Google Calendar credentials, refer to n8n integration documentation for more information. Create a Google Calendar, e.g. DEMO Select your Credentials in Delete Event, and select the above Calendar Remember to activate this workflow for schedule to run. How to adjust it to your needs There should be more status for the booking. The current action only check for OPEN and HOLD booking, you can do more based on your needs. You can replace the sub-workflow trigger Call Back to another flow as needs.
By ChatPayLabsAI chatbot call center: Taxi booking worker (production-ready, part 5)
Workflow Name: 👷♂️ Taxi Booking Worker Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Execute Sub-workflow Trigger node Chat Trigger node Redis node Postgres node Google Calendar node Execute Sub-workflow If node, Switch node, Code node, Edit Fields (Set) Prerequisite Execute Sub-workflow Trigger: Call In Center (or your own node) Sub-workflow: Demo Call Back (or your own node) Production Features Scaling Design for n8n Queue mode in production environment Customize Open Booking Action Integrate with Long Term Memory backup. Error Management What this workflow does? This is a n8n Taxi Booking Worker, the worker node to process the job. It will wait for message from the Call Center node and handle the real process here. In this particular case, it will check the input number for the selected provider, then update the booking from NEW to OPEN, then clean up the orphan data. How it works The Form Trigger node will wait for the message from any node with the input in number. First check for NEW booking under the same chat session For input 0, which is cancel Reset the user session in Redis memory For input 1 or above, which is the provider selection number Set the booking status to OPEN in database OPTIONAL Save the summary to User Memory database OPTIONAL Create a new Event in Google Calendar and sync to the database Reset the user session in Redis memory Afterward, process data clean up Delete the provider selection number queue in Redis Delete the route data in Redis OPTIONAL Delete the chat memory with current session Finally, output the response to the Call Back node Set up instructions Pull and Set up the required SQL from our Github repository. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Booking, Set Open Booking, Sync Booking Google Cal, and Save User Memory. Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Reset Session, Reset Session 2, Delete Provider Number and Delete Route Data. Create your Google Calendar credentials, refer to n8n integration documentation for more information. Create a Google Calendar, e.g. DEMO Select your Credentials in Create Event, and select the above Calendar FOR TEST ONLY. Enable the Telegram Test Output for testing from the Test Input. How to adjust it to your needs You can specific a number to trigger the specific action based on your needs. The current action only create a event in Google Calendar, you can do more based on your needs. You can replace the sub-workflow trigger Flow Trigger and Call Back to another flow as needs.
By ChatPayLabsAI chatbot call center: demo call back (production-ready, part 6)
Workflow Name: 💬 Demo Call Back Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Execute Sub-workflow Trigger node Chat Trigger node Redis node Postgres node Telegram node HTTP Request node If node, Code node, Edit Fields (Set) Prerequisite Execute Sub-workflow Trigger: your own node MiniMax Account (https://www.minimax.io/) Production Features Scaling Design for n8n Queue mode in production environment Optional Provider Data from external Database with Caching Mechanism. Optional AI Clone Voice Message response via MiniMax API with Multi-Languages support. Optional Backup Chat Log to Database, so you can use in APP/API building. Testing Flow with or without dependance on other workflow. Multi Chatbot (This is a demo for Telegram, you can add WhatsApp, Line, etc) Error Management What this workflow does? This is a n8n Telegram Output Workflow. It will receive message from other Sub-workflow then output to Telegram for Message, or Replay Message and extra Voice Message. How it works The Flow Trigger node will wait for the message from other Sub-workflow. When message is received, it will first check for the matching Provider from the PostgreSQL database. Then determine if it is a Voice message to Text message. OPTIONAL. For voice message, use the MiniMax API to generate a voice message, then send it to Telegram. Finally, send the text to Telegram. Set up instructions Pull and Set up the required SQL from our Github repository. Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Provider Cache and Save Provider Cache. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Load Member Data, Create Chat Log Input, and Create Chat Log Output. Create you Telegram credentials, refer to n8n integration documentation for more information. Select your Credentials in Telegram Voice Output, Telegram Reply Output, and Telegram Output. AI Clone Voice setup instructions (Optional) You can clone any voice with MiniMax Go to https://www.minimax.io/ and create a MiniMax account Setup the Database with the required variables found in the MiniMax TTS node That’s it How to adjust it to your needs By default, this template will use the sys_provider table provider information, you could change it for your own design. The demo use MiniMax API for AI voice cloning, you could implement any other AI your choice. The Backup Chat Log will backup all chat conversion line by line. You can use it for you own APP/API development.
By ChatPayLabsAI chatbot call center: Telegram call in (production-ready, part 1a)
Workflow Name: 🤙 Telegram Call In Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Chat Trigger node Telegram Trigger node Redis node Postgres node Execute Sub-workflow If node, Code node, Edit Fields (Set), Extract From File Prerequisite Community nodes: n8n-nodes-google-speech Sub-workflow: Demo Call Back Sub-workflow: Demo Call Center Production Features Scaling Design for n8n Queue mode in production environment Optional Member Data from external Database with Caching Mechanism. Optional Voice Message to Text Message via Google STT API with Multi-Languages support. Testing Flow with or without dependance on other workflow. Error Management What this workflow does? This is a n8n Telegram Call In Workflow. It will wait for message from Telegram bot and sent to the Call Center to process. How it works The Telegram Trigger node will wait for the message from the Telegram bot. When message is received, it will first check for the matching Member from the PostgreSQL database. Then determine if it is a Text message or Voice message. For voice message, use the Google Speech to Text API to transcript it into text. Finally, pass the text to the next flow, i.e. the Call Center. Set up instructions n8n-nodes-google-speech Pull and Set up the required SQL from our Github repository. Go User > Settings > Community nodes, install n8n-nodes-google-speech node Follow https://www.npmjs.com/package/n8n-nodes-google-speech Setup the Google STT node Create you Telegram credentials, refer to n8n integration documentation for more information. Select your Credentials in Telegram Trigger Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Member Cache and Save Member Cache. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Load Member Data. FOR TEST ONLY. Enable the Telegram Test Output for testing from the Test Input. Remember to activate this workflow for incoming message. How to adjust it to your needs By default, this template will use the sys_member table for member information, you could change it for your own design. The demo implementation does not include failed member loading situation, you should implement based on your needs, e.g. if is_active is not true, do… You can replace the sub-workflow Demo Call Back and Demo Call Center to another flow as needs.
By ChatPayLabsAI chatbot call center: Taxi service (Production-ready, part 3)
Workflow Name: 🛎️ Taxi Service Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Execute Sub-workflow Trigger node Chat Trigger node Redis node Postgres node AI Agent node If node, Switch node, Code node, Edit Fields (Set) Prerequisite Execute Sub-workflow Trigger: Taxi Service Workflow (or your own node) Sub-workflow: Taxi Service Provider (or your own node) Sub-workflow: Demo Call Back (or your own node) Production Features Scaling Design for n8n Queue mode in production environment Service Data from external Database with Caching Mechanism Optional Long Terms Memory design Find Route Distance using Google Map API Optional Multi-Language Wait Output example Error Management What this workflow does? This is a n8n Taxi Service Workflow demo. It is the core node for Taxi Service. It will receive message from the Call Center Workflow, handling the QA from the caller, and pass to each of the Taxi Service Provider Workflow to process the estimation. How it works The Flow Trigger node will wait for the message from Call Center or other Sub-workflow. When message is received, it will first check for the matching Service from the PostgreSQL database. If no service or service is inactive, output Error. Next, always reset the Session Data in Cache, with channel_no set to taxi Next, delete the previous Route Data in Cache Trigger a AI Agent to process the fare estimation question to create the Route Data Use the Google Map Route API to calculate the distance. Repeat until created the route data, then pass to all the Taxi Service Provider for an estimation. Set up instructions Pull and Set up the required SQL from our Github repository. Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Service Cache, Save Service Cache, Reset Session, Delete Route Data, Route Data, Update User Session and Create Route Data. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Load Service Data, Postgres Chat Memory, Load User Memory and Save User Memory. Modify the AI Agent prompt to fit your need Set you Google Map API key in Find Route Distance How to adjust it to your needs By default, this template will use the sys_service table provider information, you could change it for your own design. You can use any AI Model for the AI Agent node Learn we use the prompt for the Load/Save User Memory on demand. Include is our prompt for the taxi service. It is a flexible design which use the data from the Service node to customize the prompt, so you could duplicate this workflow as another service. Create difference Taxi Providers to process the and feedback the estimate.
By ChatPayLabs