Mystical Palm Reader AI: Unveiling Your Destiny with Pinata and AI
This is a submission for the The Pinata Challenge
What I Built
I developed "Palm Reader AI," an innovative (and mostly fun) webapp that combines the mystical art of palm reading with cutting-edge AI technology from HuggingFace and the Pinata decentralized storage. This application allows users to upload images of their palms, which are then analyzed by an AI model to generate personalized "readings." The palm images and the audio versions of the readings are stored securely using Pinata's IPFS solution, ensuring decentralized and persistent storage of user data.
Key features include:
- AI-powered palm analysis
- Text-to-speech conversion of readings
- Decentralized storage of images and audio files
- Interactive UI with real-time feedback
- Gallery of past readings
Demo
You can try out the Palm Reader AI live at: https://palm-reader-ai2.onrender.com/
Here are some screenshots of the application in action:
My Code
The full source code for this project is available on GitHub:
ehernandezvilla
/
palm-reader-ai
DEV Pinata challenge - Palm Reader AI
Palm Reader AI 🔮🖐️
Palm Reader AI is an innovative (but mostly fun) web application that uses artificial intelligence to analyze palm images and provide mystical readings. This project was developed as part of the Dev Pinata challenge, showcasing the integration of AI technologies with decentralized storage solutions.
🌟 Features
- Upload palm images for AI analysis
- Receive personalized palm readings
- Text-to-speech functionality for audio readings
- Gallery of past readings
- Responsive and mystical UI design
🚀 Tech Stack
- Frontend: Next.js with React
- Styling: Tailwind CSS
- UI Components: shadcn/ui
- Animations: Framer Motion
- Icons: Lucide React
- API Requests: Axios
- Text-to-Speech: Hugging Face Inference API
- Decentralized Storage: Pinata IPFS
🧠 AI Models
- Palm Analysis: facebook/detr-resnet-50 (Object Detection)
- Text Generation: meta-llama/Llama-2-7b-chat-hf
- Text-to-Speech: espnet/kan-bayashi_ljspeech_vits
🏗️ Project Structure
-
components/: React components (Hero, FileUpload, PalmReading, etc.) -
pages/: Next.js pages…
More Details
Pinata played a crucial role in the development of this application. Here's how I utilized Pinata's services:
- Image Storage: When a user uploads a palm image, it's immediately stored on IPFS through Pinata. The returned IPFS hash is then used to retrieve the image for AI analysis.
const audioFile = new File([audioBlob], 'reading.wav', { type: 'audio/wav' });
const audioUploadResult = await uploadToPinata(audioFile);
- Audio Storage: After generating the palm reading, the application uses text-to-speech to create an audio version. This audio file is also stored on IPFS via Pinata.
const audioResponse = await hf.textToSpeech({
model: "espnet/kan-bayashi_ljspeech_vits",
inputs: reading,
});
const audioBlob = new Blob([audioResponse], { type: 'audio/wav' });
const audioUploadResult = await uploadToPinata(audioFile);
- Content Retrieval: The application uses Pinata's IPFS gateway to retrieve stored images and audio files for display and playback in the user interface.
const imageUrl = `https://gateway.pinata.cloud/ipfs/${ipfsHash}`;
- Persistent Storage: By using Pinata's IPFS solution, all user data (palm images and audio readings) are stored in a decentralized manner, ensuring data persistence and availability.
The integration of Pinata's services allowed me to create a robust, decentralized storage solution for user-generated content, which is critical for the functionality and user experience of the Palm Reader AI application.
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