Prueba asistente jurídico Daniel Leonardo Gonzalez Torres
| dc.contributor.advisor | Gonzalez Torres, Daniel Leonardo | |
| dc.contributor.advisor | Santa Quintero, Ricardo Andres | |
| dc.contributor.author | Gonzalez Torres, Daniel Leonardo | |
| dc.coverage.spatial | Bogotá | spa |
| dc.creator.email | daniell-gonzalezt@unilibre.edu.co | spa |
| dc.date.accessioned | 2025-05-16T13:52:55Z | |
| dc.date.available | 2025-05-16T13:52:55Z | |
| dc.date.created | 2024-10-15 | |
| dc.description.abstract | La presentacion muestra de manera grafica una serie de pruebas iniciales para desarrollar un consultorio jurídico asistido por inteligencia artificial. Se exploraron dos métodos para mejorar la precisión de las respuestas legales: uno que busca información relevante en documentos legales al momento de cada consulta (RAG) y otro que ajusta el modelo de lenguaje con ejemplos específicos del ámbito legal (fine-tuning). Además, se evaluó la posibilidad de implementar este sistema en servidores locales utilizando herramientas como AnythingLLM y LM Studio, que permiten gestionar modelos de lenguaje de forma privada y segura . Estas pruebas proporcionan una base para futuras investigaciones en la aplicación de IA en servicios legales. | spa |
| dc.description.abstractenglish | The presentation graphically shows a series of initial tests to develop an artificial intelligence-assisted legal consultancy. Two methods were explored to improve the accuracy of legal answers: one that searches for relevant information in legal documents at the time of each query (RAG) and another that adjusts the language model with specific examples from the legal domain (fine-tuning). In addition, the possibility of implementing this system on local servers was evaluated using tools such as AnythingLLLM and LM Studio, which allow managing language models privately and securely. These tests provide a basis for future research in the application of AI in legal services. | spa |
| dc.description.sponsorship | Universidad Libre -- Ingenieria -- Ingenieria de sistemas | spa |
| dc.format | spa | |
| dc.identifier.uri | https://hdl.handle.net/10901/31147 | |
| dc.relation.references | Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2024). Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools. arXiv. https://arxiv.org/abs/2405.20362 | spa |
| dc.relation.references | Arredondo, P., & Lewis, P. (2024, junio 14). Reduce AI Hallucinations With This Neat Software Trick. WIRED. https://www.wired.com/story/reduce-ai-hallucinations-with-rag | spa |
| dc.relation.references | Yue, S., Chen, W., Wang, S., Li, B., Shen, C., Liu, S., Zhou, Y., Xiao, Y., Yun, S., Huang, X., & Wei, Z. (2023). DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services. arXiv. https://arxiv.org/abs/2309.11325 | spa |
| dc.relation.references | Lin, C.-H., & Cheng, P.-J. (2024). Legal Documents Drafting with Fine-Tuned Pre-Trained Large Language Model. arXiv. https://arxiv.org/abs/2406.04202 | spa |
| dc.relation.references | AnythingLLM. (s.f.). AnythingLLM: All-in-One AI Application. https://anythingllm.com/ | spa |
| dc.relation.references | LM Studio. (s.f.). LM Studio: Local LLM Configuration. https://docs.useanything.com/setup/llm-configuration/local/lmstudio | spa |
| dc.relation.references | PyImageSearch. (2024, junio 24). Integrating Local LLM Frameworks: A Deep Dive into LM Studio and AnythingLLM. https://pyimagesearch.com/2024/06/24/integrating-local-llm-frameworks-a-deep-dive-into-lm-studio-and-anythingllm/ | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
| dc.rights.license | Atribución-NoComercial-SinDerivadas 2.5 Colombia | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | spa |
| dc.subject | Consultorio jurídico inteligente | spa |
| dc.subject | inteligencia artificial legal | spa |
| dc.subject | RAG (Retrieval-Augmented Generation) | spa |
| dc.subject | Fine-tuning | spa |
| dc.subject | LLM (Large Language Models) | spa |
| dc.subject | AnythingLLM | spa |
| dc.subject | LM Studio | spa |
| dc.subject | Despliegue local de IA | spa |
| dc.subject | Docker | spa |
| dc.subject | ngrok | spa |
| dc.subject.subjectenglish | Legal AI | spa |
| dc.subject.subjectenglish | Intelligent Legal Services | spa |
| dc.subject.subjectenglish | RAG (Retrieval-Augmented Generation) | spa |
| dc.subject.subjectenglish | Fine-tuning | spa |
| dc.subject.subjectenglish | LLM (Large Language Models) | spa |
| dc.subject.subjectenglish | AnythingLLM | spa |
| dc.subject.subjectenglish | LM Studio | spa |
| dc.subject.subjectenglish | On-premises Deployment | spa |
| dc.subject.subjectenglish | Docker | spa |
| dc.subject.subjectenglish | ngrok | spa |
| dc.title | Prueba asistente jurídico Daniel Leonardo Gonzalez Torres | spa |
| dc.title.alternative | Legal Assistant Test Daniel Leonardo Gonzalez Torres | spa |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
| dc.type.local | Tesis de Pregrado | spa |
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