<!-- markdownlint-disable MD013 MD043 MD050 -->
# OpenSSA: Neurosymbolic Agentic AI for Industrial Problem-Solving
OpenSSA is an open-source neurosymbolic agentic AI framework
designed to solve complex, high-stakes problems in industries like semiconductor, energy and finance,
where consistency, accuracy and deterministic outcomes are paramount.
At the core of OpenSSA is the [__Domain-Aware Neurosymbolic Agent (DANA)__](https://arxiv.org/abs/2410.02823) architecture,
advancing generative AI from basic pattern matching and information retrieval to industrial-grade problem solving.
By integrating domain-specific knowledge with neural and symbolic planning and reasoning,
such as __Hierarchical Task Planning (HTP)__ for structuring programs
and __Observe-Orient-Decide-Act Reasoning (OODAR)__ for executing such programs,
OpenSSA DANA agents consistently deliver accurate solutions, often using much smaller models.
## Key Benefits of OpenSSA
- __Consistent and Accurate Results__ for complex industrial problems
- __Scalable Expertise__ through AI agents incorporating deep domain knowledge from human experts
- __Economical and Efficient Computation__ thanks to usage of small models
- __Full Ownership__ of intellectual property when used with open-source models such as Llama
## Getting Started
- Install with __`pip install openssa`__ _(Python 3.12 and 3.13)_
- For bleeding-edge 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)
## [API Documentation](https://aitomatic.github.io/openssa/modules)
## Contributing
We welcome contributions from the community!
- Join discussions on our [Community Forum](https://github.com/aitomatic/openssa/discussions)
- Submit pull requests for bug fixes, enhancements and new features
For detailed guidelines, refer to our [Contribution Guide](CONTRIBUTING.md).
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"description": "<!-- markdownlint-disable MD013 MD043 MD050 -->\n\n# OpenSSA: Neurosymbolic Agentic AI for Industrial Problem-Solving\n\nOpenSSA is an open-source neurosymbolic agentic AI framework\ndesigned to solve complex, high-stakes problems in industries like semiconductor, energy and finance,\nwhere consistency, accuracy and deterministic outcomes are paramount.\n\nAt the core of OpenSSA is the [__Domain-Aware Neurosymbolic Agent (DANA)__](https://arxiv.org/abs/2410.02823) architecture,\nadvancing generative AI from basic pattern matching and information retrieval to industrial-grade problem solving.\nBy integrating domain-specific knowledge with neural and symbolic planning and reasoning,\nsuch as __Hierarchical Task Planning (HTP)__ for structuring programs\nand __Observe-Orient-Decide-Act Reasoning (OODAR)__ for executing such programs,\nOpenSSA DANA agents consistently deliver accurate solutions, often using much smaller models.\n\n## Key Benefits of OpenSSA\n\n- __Consistent and Accurate Results__ for complex industrial problems\n- __Scalable Expertise__ through AI agents incorporating deep domain knowledge from human experts\n- __Economical and Efficient Computation__ thanks to usage of small models\n- __Full Ownership__ of intellectual property when used with open-source models such as Llama\n\n## Getting Started\n\n- Install with __`pip install openssa`__ _(Python 3.12 and 3.13)_\n - For bleeding-edge capabilities: __`pip install https://github.com/aitomatic/openssa/archive/main.zip`__\n\n- Explore the `examples/` directory and developer guides and tutorials on our [documentation site](https://aitomatic.github.io/openssa)\n\n## [API Documentation](https://aitomatic.github.io/openssa/modules)\n\n## Contributing\n\nWe welcome contributions from the community!\n\n- Join discussions on our [Community Forum](https://github.com/aitomatic/openssa/discussions)\n- Submit pull requests for bug fixes, enhancements and new features\n\nFor detailed guidelines, refer to our [Contribution Guide](CONTRIBUTING.md).\n\n",
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