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Grounded retrieval sandbox

Multimodal Document RAG Platform

A multimodal RAG system for PDF parsing, vector retrieval, and document-grounded chat, built as one integrated upload-to-answer experience.

A guided preview that walks visitors through document selection, retrieval inspection, and grounded answering for multimodal RAG workflows.

ReactFastAPILangChainMilvusRAG
Multimodal Document RAG Platform

Why this local version exists

This local sandbox focuses on the strongest product signal: visible retrieval evidence. It is a better portfolio demo than exposing an unrestricted upload endpoint.

Interactive Preview

Explore the retrieval workflow

This sandbox walks through the product flow that matters most in a document RAG system: choosing a document, inspecting retrieved chunks, and watching the grounded answer stay tied to explicit evidence.

Sample document library

Grounded question

PDF + charts

Parse + chunk

Normalize mixed-layout PDF content into searchable text blocks.

Retrieve context

Expose the exact chunks that will ground the final answer.

Generate answer

Compose a cited response from retrieved evidence instead of hallucinated recall.

Retrieval inspector

Retrieved chunks

0/3
Run the preview to reveal the exact chunks used to answer the question.

Grounded answer

Response with citations

Waiting
retrieval grounded

Choose a sample document, keep the question visible, and run the preview to watch retrieval and answer generation unfold step by step.

Sandbox telemetry

Product flow checkpoints

Mixed-layout document intake
Retrieval chunk visibility
Answer grounded by cited context

Activity log

The sandbox log will show how the document moves from upload to retrieval-backed answer generation.