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PROJECT 05 / DOCUMENT INTELLIGENCE

MyChatPDF.

Engineering case study by Priyansh Dobariya · React · FastAPI · PostgreSQL · Vector search

Ask a document. Check the source.

A document workspace for uploading PDFs, processing searchable content, and asking questions with source-aware chat and previews.

AI-generated open document with a search beam linking a selected passage to an answer card.
AI-GENERATED · CONCEPT VISUAL
INTERACTIVE PROJECT WORKSPACE

Explore MyChatPDF.

Explore a representative workflow with sample data. Everything runs in your browser.

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PROJECT OVERVIEW

Behind the build.

  • Document processing pipeline

  • Retrieval-backed chat

  • Document organization and usage controls

Tools & technologies

  • React
  • FastAPI
  • PostgreSQL
  • Vector search
THE PROBLEM

What this solves

Long PDFs are difficult to search when a user needs a precise answer and the surrounding evidence. This product combines document organization, previews, and chat in one workflow.

ARCHITECTURE

How it works

A React frontend calls a FastAPI backend for document, folder, chat, and account operations. Processing and extraction services turn uploaded files into searchable content; the vector service handles retrieval, while the chat service builds responses. SQLAlchemy models hold users, documents, folders, conversations, processing state, and billing records.

ONE WORKFLOW

From input to outcome

After upload, the processing service extracts document content and prepares it for retrieval. A question reaches the chat route, which resolves the user and document context, retrieves relevant passages, and returns an answer to the conversation. Preview and folder routes let the user inspect and organize the original files.

ENGINEERING

Decisions visible in the code

  • Separate processing state from document records gives the UI a way to represent ingestion progress and failures.
  • Document-scoped retrieval and authenticated route dependencies provide a basis for keeping answers attached to the files a user selected.
BENEFIT & EVIDENCE

What the workflow enables

Users can search and discuss their document collection while retaining a path back to the original PDF. Automated frontend document-chat coverage exists in the repository.

No public accuracy or time-saved measurement was found; test files alone do not prove a production pass.

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