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Abhay-J-Kashyap/Agentic-RAG-System

An open-source, fully local Agentic RAG system for Indian Law. Features LangGraph multi-agent orchestration, sequential tool-calling, and a DeBERTa NLI guardrail to eliminate LLM hallucinations on consumer-grade GPUs.

⚡ AI-using Python ⑂ 1 forks MIT GitHub ↗
★ 0
stars
75
AI relevance
50
solo dev
0
tool sigs

SUMMARY AI summary by gpt-5-mini

このプロジェクトは、インド法(IPC, CrPC, MVA, CPC, IDA)を対象に、ローカルの消費者向けハードウェア上で動作する誤情報(ハルシネーション)抑止型のRetrieval-Augmented Generation(RAG)パイプラインです。法律実務者や研究者、法務系AI開発者が、条文の抜けや例外を見落とさずに根拠ベースの回答を得ることを目的としています。 主な仕組みは以下です。LangGraphによるマルチエージェントで問い合わせの書き直し・自律的な追加検索・最終応答統合を行い、DeBERTaのNLI(CrossEncoder)で生成文と原文の整合性を数値的に検証してハルシネーションを検出します。消費GPUのVulkan OOMを避けるために順次ツール呼び出し(小分けの検索)を行い、親子チャンク設計で法令の条文構造と重要な例外を保全します。Gradioベースの「Glass Box」UIはエージェントのツール呼び出しを逐次表示します。ローカルQwen 2.5(7B)等を用い、Qdrantとall-mpnet-base-v2埋め込みで動作する設計です。

DETECTED Detected AI stack

AI-related keywords found in this repo's description, topics, or README summary — grouped by category. Each badge links to the corresponding ranking detail page.

🧩 AI frameworks (1)
LangGraph
🤖 LLM models (1)
Qwen
🌐 Web frameworks (1)
Gradio

Language breakdown (by bytes)

Python
70%
Dockerfile
0.8%
Jupyter Notebook
29.2%

Owner

Account
Abhay-J-Kashyap
Type
User
Followers
0

Dates

Created on GitHub 2026-05-04
Last push 2026-05-09
First seen here 2026-05-09
Last fetched 2026-05-09 15:42

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