AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance

• URL: http://arxiv.org/abs/2511.14043v1
• Date: Tue, 18 Nov 2025 01:51:05 GMT
• Title: AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
• Authors: Chandrachur Bhattacharya, Sibendu Som,
• Abstract summary: AISAC builds on technologies - LangGraph for orchestration, FAISS for vector search, and persistence.<n>System implements prompt-engineered agents coordinated via LangGraph's StatePlanner.<n>A project-driven bootstrap allows research teams to customize tools, prompts, and data sources without modifying core code.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: AI Scientific Assistant Core (AISAC) is an integrated multi-agent system developed at Argonne National Laboratory for scientific and engineering workflows. AISAC builds on established technologies - LangGraph for orchestration, FAISS for vector search, and SQLite for persistence - and integrates them into a unified system prototype focused on transparency, provenance tracking, and scientific adaptability. The system implements a Router-Planner-Coordinator workflow and an optional Evaluator role, using prompt-engineered agents coordinated via LangGraph's StateGraph and supported by helper agents such as a Researcher. Each role is defined through custom system prompts that enforce structured JSON outputs. A hybrid memory approach (FAISS + SQLite) enables both semantic retrieval and structured conversation history. An incremental indexing strategy based on file hashing minimizes redundant re-embedding when scientific corpora evolve. A configuration-driven project bootstrap layer allows research teams to customize tools, prompts, and data sources without modifying core code. All agent decisions, tool invocations, and retrievals are logged and visualized through a custom Gradio interface, providing step-by-step transparency for each reasoning episode. The authors have applied AISAC to multiple research areas at Argonne, including specialized deployments for waste-to-products research and energy process safety, as well as general-purpose scientific assistance, demonstrating its cross-domain applicability.

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