Integrations
HTTP Request
Webhook
Respond to Webhook
Sticky Note
Basic LLM Chain
Window Buffer Memory (easiest)
Aggregate
Limit
Chat Memory Manager
OpenAI
Google Gemini Chat Model
Who is this for?
This workflow is ideal for businesses or developers wanting to integrate voice-based chat applications with dynamic responses and conversational memory.
What problem does this solve?
It enables AI-powered voice conversations that maintain context between sessions, automatically converting speech-to-text and text-to-speech for a seamless experience.
What this workflow does:
The workflow receives audio input, transcribes it using OpenAI, processes the conversation with the Google Gemini Chat Model (or alternatively, OpenAI Chat Model), and converts responses back to speech via ElevenLabs.
Prerequisites:
You'll need API keys for:
- OpenAI (available on the OpenAI website)
- ElevenLabs (available on their website)
- Google Gemini (available from
Google AI Studio)
Setup:
- Configure your API keys in the workflow settings.
- In the Webhook node, set the
"Path"parameter to(voice_message), which will act as the parameter name for the voice message in the HTTP Post request.
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