JusticeBot is an innovative retrieval-augmented generation (RAG)-based chatbot designed to revolutionize access to legal information provided by the Justice Department. Utilizing advanced language models (Gemini Pro) (Aini in Chin Stud 9(1):14–28, 2020) and cutting-edge AI technologies, JusticeBot delivers accurate, user-friendly guidance across various legal services (Gorlamudiveti and Sethu in 2023 International conference on computational intelligence and knowledge economy (ICCIKE), Dubai, UAE, IEEE, pp 1–4, 2023; de Andrade and Oliveira in Proceedings of the Seventh Brazilian Symposium on Information and Human Language Technology, São Carlos, Brazil. IEEE, pp 1–4, 2009). This paper outlines the methodology, which integrates FAISS for efficient data retrieval (Vuong et al. in Artif Intell Law 31:1–4, 2022) and Gemini Pro for contextual language generation (Aini in Chin Stud 9(1):14–28, 2020), combined with a Flask backend and a responsive frontend. The chatbot simplifies legal processes by enabling real-time case searches, hearing schedules, court orders, and fine payments while supporting multilingual capabilities (Biresaw and Saste in Int J Law Soc 5:53–65, 2022; Sugathadasa et al in Intelligent computing, vol 2. Springer, pp 160–175, 2019). Key findings from rigorous testing reveal high accuracy (over 90%) in legal query resolution, an average response time of 1.2 s, and significant user satisfaction. JusticeBot’s scalable and adaptive design addresses challenges like local LLM limitations and the complexity of legal documents (Vuong et al. in Artif Intell Law 31:1–4; Queudot et al. in Stats 3:356–375, 2020). By bridging the gap in legal accessibility and efficiency, this work demonstrates the transformative potential of AI in legal systems (Gorlamudiveti and Sethu in 2023 International conference on computational intelligence and knowledge economy (ICCIKE), Dubai, UAE, IEEE, pp 1–4, 2023; Vuong et al. in Artif Intell Law 31:1–4, 2022) and by promoting legal awareness, reducing operational costs, and minimizing paper usage (Nguyen M-T et al. in Proceedings of the tenth international workshop on juris-informatics (JURISIN 2016) associated with JSAI International Symposia on AI 2016 (IsAI-2016), Kanagawa, Japan, 2016; Anitha et al. in Proceedings of the 2023 9th international conference on smart structures and systems (ICSSS), Chennai, India, 2023), it empowers users and fosters equitable access to justice.

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JusticeBot—A Virtual Legal Assistant

  • E. Sujatha,
  • M. Ulagammai,
  • Ann Blessy Philips,
  • Sabitha Paulraj,
  • G. R. Niraunjana Gayathri

摘要

JusticeBot is an innovative retrieval-augmented generation (RAG)-based chatbot designed to revolutionize access to legal information provided by the Justice Department. Utilizing advanced language models (Gemini Pro) (Aini in Chin Stud 9(1):14–28, 2020) and cutting-edge AI technologies, JusticeBot delivers accurate, user-friendly guidance across various legal services (Gorlamudiveti and Sethu in 2023 International conference on computational intelligence and knowledge economy (ICCIKE), Dubai, UAE, IEEE, pp 1–4, 2023; de Andrade and Oliveira in Proceedings of the Seventh Brazilian Symposium on Information and Human Language Technology, São Carlos, Brazil. IEEE, pp 1–4, 2009). This paper outlines the methodology, which integrates FAISS for efficient data retrieval (Vuong et al. in Artif Intell Law 31:1–4, 2022) and Gemini Pro for contextual language generation (Aini in Chin Stud 9(1):14–28, 2020), combined with a Flask backend and a responsive frontend. The chatbot simplifies legal processes by enabling real-time case searches, hearing schedules, court orders, and fine payments while supporting multilingual capabilities (Biresaw and Saste in Int J Law Soc 5:53–65, 2022; Sugathadasa et al in Intelligent computing, vol 2. Springer, pp 160–175, 2019). Key findings from rigorous testing reveal high accuracy (over 90%) in legal query resolution, an average response time of 1.2 s, and significant user satisfaction. JusticeBot’s scalable and adaptive design addresses challenges like local LLM limitations and the complexity of legal documents (Vuong et al. in Artif Intell Law 31:1–4; Queudot et al. in Stats 3:356–375, 2020). By bridging the gap in legal accessibility and efficiency, this work demonstrates the transformative potential of AI in legal systems (Gorlamudiveti and Sethu in 2023 International conference on computational intelligence and knowledge economy (ICCIKE), Dubai, UAE, IEEE, pp 1–4, 2023; Vuong et al. in Artif Intell Law 31:1–4, 2022) and by promoting legal awareness, reducing operational costs, and minimizing paper usage (Nguyen M-T et al. in Proceedings of the tenth international workshop on juris-informatics (JURISIN 2016) associated with JSAI International Symposia on AI 2016 (IsAI-2016), Kanagawa, Japan, 2016; Anitha et al. in Proceedings of the 2023 9th international conference on smart structures and systems (ICSSS), Chennai, India, 2023), it empowers users and fosters equitable access to justice.