OpenSaC: A Python Library for Search as Code in Deep Research Agents
To support this workflow in existing coding agents, we present OpenSaC, an open-source Python library with a companion Search as Code skill.
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Key points
- Deep research agents investigate complex questions through iterative search, source examination, and evidence synthesis.
- A conventional workflow alternates reasoning with individual search and reading actions.
- Search as Code introduces a new paradigm: agents write programs that compose search, source reading, reranking, model calls, and local processing, returning selected observations for further reasoning.
- We aim to lower the barrier to adopting Search as Code and provide an open foundation for community development and transparent research on deep research agents.
Sources (1)
- [1]OpenSaC: A Python Library for Search as Code in Deep Research AgentsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 04:46 AM
To support this workflow in existing coding agents, we present OpenSaC, an open-source Python library with a companion Search as Code skill.
Deep research agents investigate complex questions through iterative search, source examination, and evidence synthesis.
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