Skip to main content

High performance, lightweight agent framework.

Project description

AmritaCore

Logo

PyPI Version Python Version License AmritaCore Discord QQ Group

AmritaCore is the intelligent agent core module of Proj.Amrita, serving as the primary logical or control component of the project. It provides a flexible and extensible framework for implementing AI agents with advanced capabilities.

🚀 What is AmritaCore?

AmritaCore is a next-generation agent framework designed to simplify the creation and deployment of intelligent agents. Built with modern Python technologies, it provides a comprehensive solution for implementing AI-powered applications with features like event-driven architecture, tool integration, and multi-modal support.

🎯 Mission and Value Proposition

The mission of AmritaCore is to democratize the development of intelligent agents by providing a powerful yet accessible framework. Our core value propositions include:

  • Stream-based Design: All message outputs are designed as asynchronous streams for real-time responses
  • Security: Built-in cookie security detection to ensure session safety
  • Vendor Agnostic: Data types and conversation management are independent of specific providers, offering high portability
  • Extensibility: Integrated MCP client in extension mechanisms for enhanced system scalability

🔑 Key Features

  1. Every is a Stream: All message outputs are asynchronous stream-based designs supporting real-time responses
  2. Cookie Security Detection: Built-in cookie security detection functionality to protect session security
  3. Provider Independent Mechanism: Data types and conversation management are independent of specific vendors, with high portability
  4. MCP Client Support: Extension mechanisms integrate MCP clients, enhancing system expansion capabilities
  5. Event-Driven Architecture: Comprehensive event system for flexible and reactive agent behavior
  6. Tool Integration Framework: Robust system for integrating external tools and services
  7. Advanced Memory Management: Sophisticated context handling with automatic summarization and token optimization
  8. High-Performance: Lightweight and efficient, with high performance.

📖 Documentation

Please view Docs for more information.

🛠️ Quick Start

To quickly start using AmritaCore, check out the examples in the demo directory. The basic example demonstrates how to initialize the core, configure settings, and run a simple chat session with the AI assistant.

🤝 Contributing

We welcome contributions! Please see our contribution guidelines for more information.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Significants

All versions of AmritaCore are released under the MIT License (Although the past versions are released under the AGPLv3 License, when this readme is created, we will release all versions under the MIT License).

Other files

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

amrita_core-0.7.2.tar.gz (87.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

amrita_core-0.7.2-py3-none-any.whl (66.0 kB view details)

Uploaded Python 3

File details

Details for the file amrita_core-0.7.2.tar.gz.

File metadata

  • Download URL: amrita_core-0.7.2.tar.gz
  • Upload date:
  • Size: 87.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.3 {"installer":{"name":"uv","version":"0.11.3","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for amrita_core-0.7.2.tar.gz
Algorithm Hash digest
SHA256 ace7b37b995d3d08590809144ec293d27803ee92f0bc0981191a74ba6b183246
MD5 764112e1a03fc0492365abc50234b9de
BLAKE2b-256 70fc0df327928090eb7f0f89331580f6815fc55c0e943b206d98dbb61eef4153

See more details on using hashes here.

File details

Details for the file amrita_core-0.7.2-py3-none-any.whl.

File metadata

  • Download URL: amrita_core-0.7.2-py3-none-any.whl
  • Upload date:
  • Size: 66.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.3 {"installer":{"name":"uv","version":"0.11.3","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for amrita_core-0.7.2-py3-none-any.whl
Algorithm Hash digest
SHA256 bf6d23730b1d36d33e2cb4ae4491116574cdc0c15424c4894a045eedb5e35371
MD5 16cdec9a217e5b4b92d366461318dbc5
BLAKE2b-256 40da87326abb870e01612ed2194c50bfe374a8537f0b51d75603865287f2c85c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page