Interactive Multimodal Playground — See & Parse Any Image
A live, gated demo: drop in an image — a receipt, chart, photo, or screenshot — and the AI parses it on the spot. Describe the scene, detect objects, read text (OCR), extract data from a chart or table, or ask your own question. Start instantly with a sample. LLM-agnostic; this instance uses Gemini.
Overview
The Multimodal Playground is a working proof-of-value for real-time visual understanding. Authenticated users pick a built-in sample image or upload their own, then run a task with one tap: a detailed scene description, object detection with tags, full text transcription (OCR), structured data extraction from charts/receipts/forms, or a free-form question about the image. Every response is grounded strictly in what is visible — the model is instructed never to invent text or details. Because samples are bundled, a visitor can interact and see a result in seconds with nothing to prepare. The architecture is deliberately LLM-agnostic: the same flow runs against a local vision model served by Ollama (for example Llava or Llama 3.2 Vision) or any cloud vision LLM. This deployment is wired to Google Gemini, but the model is a swappable component. Images are processed in-memory and expire automatically.
Problem Solved
Teams sit on huge volumes of visual content — receipts, forms, screenshots, product photos, charts — that is hard to use because it is not text. This demo shows how a vision-capable LLM turns any image into structured, queryable information (descriptions, objects, transcribed text, extracted tables) in real time, and how the model choice (local or cloud) can be swapped without changing the application.
Capabilities
- One-tap visual tasks: describe, detect objects, OCR, parse data
- Free-form visual question answering
- Built-in sample images for instant, zero-setup interaction
- Image upload (PNG, JPG, WebP, GIF) up to 8MB
- Grounded output — refuses to invent text or details
- Answers in your chosen language
- Pluggable LLM backend — Ollama / Llava (local) or cloud vision LLM
- Gated access, in-memory processing, rate limiting, size limits