Metadata-Version: 2.4
Name: ezmemory
Version: 0.1.5
Summary: AI Agent Memory System with embeddings and vector storage
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: fastmcp>=2.14.4
Requires-Dist: pydantic>=2.12.5
Requires-Dist: pydantic-settings>=2.10.1
Requires-Dist: python-dotenv>=1.2.1
Requires-Dist: qdrant-client>=1.16.2
Requires-Dist: voyageai>=0.3.7
Requires-Dist: openai>=2.16.0
Requires-Dist: rich>=14.3.1
Requires-Dist: questionary>=2.1.1
Requires-Dist: click>=8.3.1
Requires-Dist: python-dateutil>=2.9.0
Requires-Dist: httpx>=0.28.1
Requires-Dist: fastapi>=0.128.0
Requires-Dist: pymilvus>=2.6.8
Requires-Dist: pinecone>=8.0.0
Requires-Dist: google-genai>=1.62.0

# EzMemory

AI Agent Memory System with embeddings and vector storage

## Installation

```bash
pip install ezmemory
```

## Quick Start

After installation, launch the CLI:

```bash
ezmemory
```

The setup wizard will guide you through:
- Selecting a vector database (Qdrant, Pinecone, or Zilliz)
- Configuring your embedding provider (OpenAI, VoyageAI, OpenRouter, NVIDIA, or Gemini)
- Setting up your first collection

## Features

- Multiple embedding provider support
- Multiple vector database support
- Interactive CLI for easy configuration
- FastMCP server for agent integration
- HTTP API server
- Memory lifecycle management

## Documentation

For detailed configuration and usage, visit the [GitHub repository](https://github.com/EsshUwU/EzMemory).

