AI Agents
AI voice chat using Webhook, OpenAI, and Google Gemini
15 nodes
217
157
Webhook
Workflow Description
An automation workflow that receives voice chat requests via Webhook and processes them using multiple AI models (OpenAI and Google Gemini), maintaining conversation context and memory for advanced, persistent dialogues.
How it works
- 1.Receive voice request through Webhook and identify the target AI model
- 2.Store conversation context and previous messages in dialog memory
- 3.Process the request through LLM chain with the selected model
- 4.Return the generated response via Webhook
- 5.Enforce rate limits to protect server from excessive requests
- 6.Update conversation memory with the new interaction
Use cases
- Build an intelligent multilingual voice assistant leveraging different models flexibly
- Integrate advanced conversations in customer applications while preserving interaction history
- Create a customer support chatbot that remembers previous user interactions
Requirements
- Valid API keys for both OpenAI and Google Gemini
- Available server capable of receiving and responding to Webhook calls
- Sufficient memory configuration for storing multiple conversation contexts
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Memory
Gemini
LLM Chain
OpenAI
Details
Trigger
Webhook
Nodes
15
Apps
4
Views
217
Downloads
157
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (15)
/
Get Chat
Memory Manager
Insert Chat
Memory Manager
Sticky Note5
Sticky Note
Sticky Note
Sticky Note
Aggregate
Aggregate
Window Buffer Memory
Memory Buffer Window
Google Gemini Chat Model
Gemini Model
Respond to Webhook
Webhook
ElevenLabs - Generate Audio
HTTP Request
Sticky Note2
Sticky Note
Sticky Note1
Sticky Note
Limit
Limit
Basic LLM Chain
LLM Chain
Webhook
Webhook
OpenAI - Speech to Text
OpenAI