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🧠 Document Intelligence

A private, local-first AI assistant that actually knows your files.

Java 21 LangChain4j Ollama

I built Document Intelligence because I was tired of "Command+F-ing" through dozens of PDFs and notes just to find one specific detail. This tool transforms your local folders into a searchable, interactive knowledge base using Retrieval-Augmented Generation (RAG).

Unlike most AI tools, this doesn't require you to upload your sensitive data to the cloud. Everything—from indexing to searching—happens on your own hardware.


🚀 Key Features

  • 100% Data Privacy: We use local Ollama embeddings (nomic-embed-text). Your files stay where they belong: on your machine.
  • Virtual Thread Performance: Built on Java 21, the system uses Virtual Threads (Project Loom) to process and index massive document sets in parallel.
  • Verified Citations: No more AI "hallucinations." Every answer includes the specific source filename (e.g., (Source: roadmap_2026.pdf)).
  • Streaming & Thinking: Features a professional "thinking" indicator and human-like streaming response for a smooth, Ollama-style CLI experience.
  • Persistent Memory: It remembers your conversation context, so you can ask follow-up questions without repeating yourself.

📂 Supported Formats

Category File Types
Documents .pdf, .docx
Technical .md, .markdown, .txt
Data .csv, .json

🛠️ Setup & Installation

1. Prerequisites

  • Java 21+ (The Virtual Thread magic depends on it).
  • Ollama installed and running on localhost:11434.
  • Groq API Key: Set as an environment variable: GROQ_API_KEY.

2. Pull the Models

Open your terminal and grab the embedding model:

ollama pull nomic-embed-text

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