OpenSSA
is an agentic AI framework for solving complex problems in real-world industry domains,
overcoming the limitations of LLMs and RAG in such settings.
OpenSSA
agents, built with powerful Hierarchical Task Planning (HTP) and Observe-Orient-Decide-Act Reasoning (OODAR),
go far beyond the Level-1 pattern-matching intelligence performed by LLMs and RAG and achieve superior outcomes
in complex multi-faceted, multi-step tasks. See our comparative study.
OpenSSA
agents can also be armed with domain-specific Knowledge, connected to diverse Resources
(files, databases, web sources, etc.), and/or be guided by specialized industry experts
to maximize the accuracy and comprehensiveness in their planning, reasoning and deliberative/iterative problem-solving.
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.
If you would like certain LLMs to be supported, please suggest through a GitHub issue, or, even better, submit your PRs.
Additionally, OpenSSA
's key Planning, Reasoning, Knowledge 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.
Specialized, Level-2 intelligence allows OpenSSA
agents to work well in many applications
using significantly smaller component models, thereby greatly economizing computing resources.
Install by pip install openssa
(on Python 3.12 only).
- for bleeding-edge 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.
We welcome contributions from the community!
- Join the discussion on our Community Forum
- Submit pull requests for bug fixes, enhancements, or new features
For more information, see our Contribution Guide.