diff --git a/README.md b/README.md index 3a9ba9c45..a5f1487a3 100644 --- a/README.md +++ b/README.md @@ -1,51 +1,27 @@ -# `OpenSSA`: Small Specialist Agents for Industrial AI +# OpenSSA: Neurosymbolic Agentic AI for Industrial Problem-Solving -`OpenSSA` is an agentic AI framework for solving complex problems in real-world industry domains, -overcoming the limitations of LLMs and RAG in high-precision settings. +**Why OpenSSA?** +OpenSSA is an open-source Neurosymbolic Agentic AI framework designed to solve complex, high-stakes problems in industries like semiconductors, manufacturing, and finance—where consistency, accuracy, and deterministic outcomes are essential. -At the heart of this framework is a __Domain-Aware Neurosymbolic Agent (DANA)__ architecture, -which treats domain-specific knowledge as a first-class concern -and applies captured knowledge representations in neural and symbolic program search and program execution -to achieve consistency and accuracy in problem-solving. +At the core of OpenSSA is the **Domain-Aware Neurosymbolic Agent (DANA)** architecture, advancing AI from basic pattern-matching and information retrieval to true problem-solving. It overcomes the limitations of traditional **LLMs** and **RAG models** in high-precision, multi-step problem-solving tasks by combining **Hierarchical Task Plans (HTPs)** to structure complex tasks and the **Observe-Orient-Decide-Act (OODAR)** framework for reliable, real-time decision-making. By integrating domain-specific knowledge with neural and symbolic reasoning, OpenSSA consistently delivers accurate solutions for complex industrial challenges. -## Level-2 Intelligence with Domain-Specific Knowledge and Sophisticated Planning & Reasoning - -`OpenSSA` implements a variant of the DANA architecture, -with problem-solving programs represented in a Hierarchical Task Plan (HTP) form -and program execution by powerful Observe-Orient-Decide-Act Reasoning (OODAR) -(see [OODA comparative study](https://arxiv.org/abs/2404.11792)). -`OpenSSA` DANA agents can also be armed with diverse Resources such as files, databases and web search. - -This combination of the knowledge-first DANA architecture with HTP and OODAR implementations -goes far beyond the Level-1 pattern-matching intelligence performed by LLMs and RAG -and achieves superior consistency and accuracy in deliberative/iterative multi-step problem-solving. - -## Small and Resource-Efficient Agents for Practical Real-World Deployment - -Such Level-2 intelligence through domain-specific knowledge and planning and reasoning -allows `OpenSSA` DANA agents to work well in many industry applications -using significantly smaller component models, thereby greatly economizing computing resources. - -## Open and Extensible Architecture - -Committed to promoting and supporting open development in generative AI, -`OpenSSA` would strive to integrate with a diverse array of LLM backends, especially open-source LLMs. -For example, `OpenSSA` supports `Llama` LLMs and models derived or fine-tuned from them. -If you would like certain LLMs to be supported, please suggest through a GitHub issue, or, even better, submit your PRs. - -Additionally, `OpenSSA`'s core Knowledge, Planning, Reasoning and Resource interfaces -are designed with customizability and extensibility as first-class concerns, -in order to enable developers to effectively solve problems in their specific industries and specialized domains. +## Key Benefits of OpenSSA +- **Consistent Results**: Delivers repeatable, high-precision outcomes for complex tasks. +- **Advanced Problem-Solving**: Combines HTPs and OODAR for multi-step reasoning and real-time decision-making. +- **Scalable Expertise**: Leverages domain knowledge to scale AI without heavy data requirements. +- **Resource Efficiency**: Uses smaller, resource-efficient models, minimizing computational costs. +- **Extensible and Developer-Friendly**: Supports diverse LLM backends and is fully customizable for industry-specific needs. ## Getting Started +- Install with __`pip install openssa`__ +(*Supports Python 3.12 or 3.13*) -Install by __`pip install openssa`__ on Python __3.12 or 3.13__. - -- For bleeding-edge latest capabilities: __`pip install https://github.com/aitomatic/openssa/archive/main.zip`__. +- For the latest capabilities: +__`pip install https://github.com/aitomatic/openssa/archive/main.zip`__. -Explore the `examples/` directory and developer guides and tutorials on our [documentation site](https://aitomatic.github.io/openssa). +- Explore the `examples/` directory and developer guides and tutorials on our [documentation site](https://aitomatic.github.io/openssa). ## [API Documentation](https://aitomatic.github.io/openssa/modules) @@ -54,6 +30,6 @@ Explore the `examples/` directory and developer guides and tutorials on our [doc We welcome contributions from the community! - Join the discussion on our [Community Forum](https://github.com/aitomatic/openssa/discussions) -- Submit pull requests for bug fixes, enhancements, or new features +- Submit pull requests for bug fixes, enhancements, or new features. -For more information, see our [Contribution Guide](CONTRIBUTING.md). +For detailed guidelines, refer to our [Contribution Guide](CONTRIBUTING.md).