A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.
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Updated
Feb 6, 2026 - Python
A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.
A Multi-Modal Agentic RAG pipeline designed to handle unstructured documents containing tables, charts, and images. It integrates Docling and ElasticSearch for structured indexing, and leverages LangGraph for agent-based reasoning and dynamic query reformulation.
A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.
This project is a multi-agent system for stock analysis, built using the Google ADK and the Alpha Vantage API. It processes stock-related queries through five modular sub-agents, supporting both natural language and structured inputs. The system provides insights into stock price movements, recent news, and analysis.
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