Rebuild the Gemini Demo with GPT-4V, Whisper, and TTS

Rebuild the Gemini Demo with GPT-4V, Whisper, and TTS. Learn how to recreate the Gemini demo using GPT-4V, Whisper for speech-to-text, and text-to-speech models. Includes step-by-step implementation details and real-time multimodal application demo.

July 14, 2024


Unlock the power of multimodal AI with this step-by-step guide to rebuilding the Gemini demo using GPT-4V, Whisper, and Text-to-Speech. Discover how to seamlessly integrate these cutting-edge technologies to create an engaging, hands-free AI experience that understands both visual and audio inputs. Whether you're an AI enthusiast or a developer looking to push the boundaries of what's possible, this introduction will inspire you to explore the future of multimodal AI.

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The next shape in the sequence should be a hexagon.

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Rebuilding the Gemini Demo

To rebuild the Gemini demo using GPT-4V, Whisper, and text-to-speech models, we'll follow these steps:

  1. Set up a Next.js project: We'll create a new Next.js project with TypeScript and the necessary dependencies, including the Vercel AI SDK, OpenAI SDK, and various utility libraries.

  2. Implement the video and audio recording: We'll set up the video and audio recording functionality using the MediaRecorder API and the CUSilenceAwareRecorder library to detect when the user stops speaking.

  3. Generate the image grid: We'll capture screenshots from the video feed at regular intervals and stitch them together into an image grid using the merge-images library. We'll also upload the image grid to a free image hosting service like Temp.files.

  4. Transcribe the audio using Whisper: When the user stops speaking, we'll send the recorded audio to the Whisper API to get a text transcript.

  5. Integrate with GPT-4V: We'll create a route handler in the Next.js API folder to handle requests from the client. This route handler will send the image grid and the text transcript to the GPT-4V model and stream the response back to the client.

  6. Implement text-to-speech: We'll create another route handler to send the generated response from GPT-4V to the OpenAI text-to-speech model and play the audio back to the user.

  7. Enhance the user experience: We'll add UI elements to allow the user to input their OpenAI API key and select the language, as well as display the generated response and play the audio.

By following these steps, you'll be able to recreate a Gemini-like demo using the latest large language models and other AI technologies. The resulting application will allow users to interact with an AI assistant using both visual and audio inputs, and receive responses in both text and audio formats.