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Mechanisms for passing growing context and outputs from agent to agent, allowing later stages to incorporate prior findings.
Distinct from Context Sharing: Distinct from Context Sharing: focuses on cumulative, sequentially growing context passed across agents rather than general request-scoped state sharing.
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AgentLaboratory is a multi-agent research system that automates the entire scientific experimentation process, from literature review through experiment execution to report generation, using a sequence of specialized AI agents. The system orchestrates a team of language-model-driven agents—a literature reviewer, experimental planner, executor, and report writer—to autonomously complete an end-to-end research workflow. The system distinguishes itself by saving progress at every checkpoint, enabling seamless recovery and continuation after interruptions or failures. Agents build on each other's
Passes outputs and growing context from agent to agent, allowing later stages to incorporate prior findings.