Cold Case Detective

A Next.js application that uses AI to analyze cold case evidence.

Features

• Next.js Framework: Built with Next.js for server-side rendering and static site generation.
• AI Integration: Utilizes Google's Gemini AI (@google/generative-ai) for advanced text analysis and generation.
• Vector Search: Implements local vector search using LanceDB (@lancedb/lancedb) and Transformers (@xenova/transformers) for efficient evidence retrieval.
• Styling: Styled with Tailwind CSS for a modern and responsive UI.
• Animation: Uses Framer Motion for smooth animations.

Tech Stack

• Frontend: React, Next.js, Tailwind CSS, Framer Motion, Lucide React
• Backend/AI: Google Generative AI, LanceDB, Xenova Transformers
• Language: TypeScript

Getting Started

Prerequisites

• Node.js (v18 or higher recommended)
• npm or yarn

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/coldcase-detective.git
   cd coldcase-detective

2. Install dependencies:

   npm install
   # or
   yarn install

3. Set up environment variables: Create a .env file in the root directory and add your necessary API keys (e.g., Google AI API key).

Running the Application

1. Start the development server:

   npm run dev
   # or
   yarn dev

2. Open http://localhost:3000 with your browser to see the result.

Project Structure

• src/app: Application source code and pages.
• src/index.ts: Main entry point (if applicable).
• src/ingestion.ts: Scripts for ingesting evidence data.
• src/vectorStore.ts: Configuration and logic for the vector database.
• evidence/: Directory containing raw evidence files (text logs, reports).
• db/: Directory for the LanceDB database files.

Scripts

• npm run dev: Runs the app in development mode.
• npm run build: Builds the app for production.
• npm start: Starts the production server.
• npm run lint: Lints the code.

License

This project is licensed under the ISC License.