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AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants

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AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

The "Voice RAG Chatbot with ElevenLabs and OpenAI" workflow in n8n is designed to create an interactive voice based chatbot system that leverages both text and voice inputs for providing informatio...

Best for

  • Support Chatbot automation workflows
  • AI RAG automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.toolvectorstore, @n8n/n8n-nodes-langchain.vectorstoreqdrant, @n8n/n8n-nodes-langchain.embeddingsopenai, n8n-nodes-base.stickynote, n8n-nodes-base.manualtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.googledrive

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Davide.

Original n8n.io source

1.1 Workflow description

Title
AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants
Workflow name
AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants

The "Voice RAG Chatbot with ElevenLabs and OpenAI" workflow in n8n is designed to create an interactive voice-based chatbot system that leverages both text and voice inputs for providing information. Ideal for shops, commercial activities and restaurants

How it works:

Here's how it operates:

  1. Webhook Activation: The process begins when a user interacts with the voice agent set up on ElevenLabs, triggering a webhook in n8n. This webhook sends a question from the user to the AI Agent node.
  2. AI Agent Processing: Upon receiving the query, the AI Agent node processes the input using predefined prompts and tools. It extracts relevant information from the knowledge base stored within the Qdrant vector database.
  3. Knowledge Base Retrieval: The Vector Store Tool node interfaces with the Qdrant Vector Store to retrieve pertinent documents or data segments matching the user’s query.
  4. Text Generation: Using the retrieved information, the OpenAI Chat Model generates a coherent response tailored to the user’s question.
  5. Response Delivery: The generated response is sent back through another webhook to ElevenLabs, where it is converted into speech and delivered audibly to the user.
  6. Continuous Interaction: For ongoing conversations, the Window Buffer Memory ensures context retention by maintaining a history of interactions, enhancing the conversational flow.

Set up steps:

To configure this workflow effectively, follow these detailed setup instructions:

  1. ElevenLabs Agent Creation:

    • Create a FREE account on ElevenLabs
    • Begin by creating an agent on ElevenLabs (e.g., named 'test_n8n').
    • Customize the first message and define the system prompt specific to your use case, such as portraying a character like a waiter at "Pizzeria da Michele".
    • Add a Webhook tool labeled 'test_chatbot_elevenlabs' configured to receive questions via POST requests.
  2. Qdrant Collection Initialization:

    • Utilize the HTTP Request nodes ('Create collection' and 'Refresh collection') to initialize and clear existing collections in Qdrant. Ensure you update placeholders QDRANTURL and COLLECTION accordingly.
  3. Document Vectorization:

    • Use Google Drive integration to fetch documents from a designated folder. These documents are then downloaded and processed for embedding.
    • Employ the Embeddings OpenAI node to generate embeddings for the downloaded files before storing them into Qdrant via the Qdrant Vector Store node.
  4. AI Agent Configuration:

    • Define the system prompt for the AI Agent node which guides its behavior and responses based on the nature of queries expected (e.g., product details, troubleshooting tips).
    • Link necessary models and tools including OpenAI language models and memory buffers to enhance interaction quality.
  5. Testing Workflow:

    • Execute test runs of the entire workflow by clicking 'Test workflow' in n8n alongside initiating tests on the ElevenLabs side to confirm all components interact seamlessly.
    • Monitor logs and outputs closely during testing phases to ensure accurate data flow between systems.
  6. Integration with Website:

    • Finally, integrate the chatbot widget onto your business website replacing placeholder AGENT_ID with the actual identifier created earlier on ElevenLabs.

By adhering to these comprehensive guidelines, users can successfully deploy a sophisticated voice-driven chatbot capable of delivering precise answers utilizing advanced retrieval-augmented generation techniques powered by OpenAI and ElevenLabs technologies.


Need help customizing?

Contact me for consulting and support or add me on Linkedin.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.7

Block 2 - Vector Store Tool

Type / Role
@n8n/n8n-nodes-langchain.toolVectorStore - toolVectorStore
Config choices
Version 1

Block 3 - Qdrant Vector Store

Type / Role
@n8n/n8n-nodes-langchain.vectorStoreQdrant - vectorStoreQdrant
Config choices
Version 1

Block 4 - Embeddings OpenAI

Type / Role
@n8n/n8n-nodes-langchain.embeddingsOpenAi - embeddingsOpenAi
Config choices
Version 1.1

Block 5 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 6 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 7 - When clicking ‘Test workflow’

Type / Role
n8n-nodes-base.manualTrigger - manualTrigger
Config choices
Version 1

Block 8 - Create collection

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 9 - Refresh collection

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 10 - Get folder

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 11 - Download Files

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 12 - Default Data Loader

Type / Role
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices
Version 1

Block 13 - Token Splitter

Type / Role
@n8n/n8n-nodes-langchain.textSplitterTokenSplitter - textSplitterTokenSplitter
Config choices
Version 1

Block 14 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 15 - Qdrant Vector Store1

Type / Role
@n8n/n8n-nodes-langchain.vectorStoreQdrant - vectorStoreQdrant
Config choices
Version 1

Block 16 - Embeddings OpenAI1

Type / Role
@n8n/n8n-nodes-langchain.embeddingsOpenAi - embeddingsOpenAi
Config choices
Version 1.1

Block 17 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 18 - Respond to ElevenLabs

Type / Role
n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices
Version 1.1

Block 19 - OpenAI

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1

Block 20 - Listen

Type / Role
n8n-nodes-base.webhook - webhook
Config choices
Version 2

Block 21 - Window Buffer Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 22 - OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1

Block 23 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

3. Summary Table

Workflow AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants
Complexity advanced
Nodes 23
Categories Support Chatbot, AI RAG
Author Davide
Published 04 Feb 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/2846/2846.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does AI voice chatbot with ElevenLabs & OpenAI for customer service and restaurants do?

The "Voice RAG Chatbot with ElevenLabs and OpenAI" workflow in n8n is designed to create an interactive voice based chatbot system that leverages both text and voice inputs for providing informatio...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI RAG use case.