OpenSSA<
Level-2 Intelligence with Planning, Reasoning, domain-specific Knowledge and diverse Informational Resources¶
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
+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.
-Agents can also be armed with domain-specific Knowledge, connected to diverse Informational Resources
+
OpenSSA agents can also be armed with domain-specific Knowledge, connected to diverse Informational 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.
Open and Extensible Architecture¶
-We are committed to promoting and supporting open development in generative AI,
-and hence OpenSSA would strive to integrate with a diverse array of LLM backends, especially open-source LLMs.
-If you would like a certain LLM to be supported, please suggest through a GitHub issue, or, even better, submit a PR.
+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.
@@ -111,12 +111,14 @@ Open and Extensible Architecture
Small and Resource-Efficient Agents for Practical Real-World Deployment¶
Specialized, Level-2 intelligence allows OpenSSA agents to work well in many applications
-with significantly smaller component models, thereby greatly economizing computing resources.
+using significantly smaller component models, thereby greatly economizing computing resources.
Getting Started¶
-Installation: pip install openssa (Python 3.12 only).
-For bleeding-edge latest capabilities: pip install https://github.com/aitomatic/openssa/archive/main.zip.
+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.