initial implementation works.

README.md

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+# EmbeddingBuddy
+
+A Python Dash application for interactive exploration and visualization of
+embedding vectors through dimensionality reduction techniques.
+
+## Overview
+
+EmbeddingBuddy provides an intuitive web interface for analyzing high-dimensional
+embedding vectors by applying various dimensionality reduction algorithms and
+visualizing the results in interactive 2D and 3D plots.
+
+## Features
+
+- **Dimensionality Reduction**: Support for PCA, t-SNE, and UMAP algorithms
+- **Interactive Visualizations**: 2D and 3D plots using Plotly
+- **Web Interface**: Built with Python Dash for easy accessibility
+- **Vector Analysis**: Tools for exploring embedding vector relationships and
+  patterns
+
+## Data Format
+
+EmbeddingBuddy accepts newline-delimited JSON (NDJSON) files where each line contains an embedding document with the following structure:
+
+```json
+{"id": "doc_001", "embedding": [0.1, -0.3, 0.7, ...], "text": "Sample text content", "category": "news", "subcategory": "politics", "tags": ["election", "politics"]}
+{"id": "doc_002", "embedding": [0.2, -0.1, 0.9, ...], "text": "Another example", "category": "review", "subcategory": "product", "tags": ["tech", "gadget"]}
+```
+
+**Required Fields:**
+
+- `embedding`: Array of floating-point numbers representing the vector
+- `text`: String content associated with the embedding
+
+**Optional Fields:**
+
+- `id`: Unique identifier (auto-generated if missing)
+- `category`: Primary classification
+- `subcategory`: Secondary classification
+- `tags`: Array of string tags for flexible labeling
+
+## Features (Initial Version)
+
+- **Drag-and-drop file upload** for NDJSON embedding datasets
+- **PCA dimensionality reduction** (automatically applied)
+- **Interactive 2D/3D visualizations** with toggle between views
+- **Color coding options** by category, subcategory, or tags
+- **Point inspection** - click points to view full document content
+- **Real-time visualization** optimized for small to medium datasets
+
+## Installation & Usage
+
+This project uses [uv](https://docs.astral.sh/uv/) for dependency management.
+
+1. **Install dependencies:**
+   ```bash
+   uv sync
+   ```
+
+2. **Run the application:**
+   ```bash
+   uv run python app.py
+   ```
+
+3. **Open your browser** to http://127.0.0.1:8050
+
+4. **Test with sample data** by dragging and dropping the included `sample_data.ndjson` file
+
+## Tech Stack
+
+- **Python Dash**: Web application framework
+- **Plotly**: Interactive plotting and visualization
+- **scikit-learn**: PCA implementation
+- **NumPy/Pandas**: Data manipulation and analysis
+- **uv**: Modern Python package and project manager