OpenSSA: Small Specialist Agents for Industrial AI
Project description
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.
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