openssa 0.24.9.30

OpenSSA: Small Specialist Agents for Industrial AI

OpenSSA: Neurosymbolic Agentic AI for Industrial Problem-Solving

Why OpenSSA? OpenSSA is an open-source neurosymbolic agentic AI framework designed to solve complex, high-stakes problems in industries like semiconductor, manufacturing and finance, where consistency, accuracy and deterministic outcomes are essential.

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 in high-precision, multi-step problem-solving by combining Hierarchical Task Plans (HTPs) to structure complex programs and the Observe-Orient-Decide-Act Reasoning (OODAR) paradigm to execute such programs. By integrating domain-specific knowledge with neural and symbolic planning and reasoning, OpenSSA consistently delivers accurate solutions for complex industrial challenges.

Key Benefits of OpenSSA

• Consistent Results: Delivers repeatable, high-precision outcomes for complex tasks.
• Advanced Problem-Solving: Combines HTPs and OODAR for multi-step planning and reasoning.
• 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 and 3.13)

• 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.

API Documentation

Contributing

We welcome contributions from the community!

• Join the discussion on our Community Forum
• Submit pull requests for bug fixes, enhancements, or new features

For detailed guidelines, refer to our Contribution Guide.