Ponencia Prueba asistente jurídico Conference On Innovation 2024-2
La ponencia describe 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...
- Autores:
-
Gonzalez Torres, Daniel Leonardo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad Libre
- Repositorio:
- RIU - Repositorio Institucional UniLibre
- Idioma:
- OAI Identifier:
- oai:repository.unilibre.edu.co:10901/31146
- Acceso en línea:
- https://hdl.handle.net/10901/31146
- Palabra clave:
- consultorio jurídico IA
inteligencia artificial legal
RAG (Retrieval-Augmented Generation)
fine-tuning
LLM (Large Language Models)
AnythingLLM
LM Studio
despliegue local de IA
Docker
ngrok
Legal AI
Intelligent Legal Services
Retrieval-Augmented Generation (RAG)
Fine-tuning
Large Language Models (LLMs)
AnythingLLM
LM Studio
On-premises Deployment
Docker
ngrok
Derecho
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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| dc.title.spa.fl_str_mv |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| dc.title.alternative.spa.fl_str_mv |
Legal Assistant Test Presentation Conference On Innovation 2024-2 |
| title |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| spellingShingle |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 consultorio jurídico IA inteligencia artificial legal RAG (Retrieval-Augmented Generation) fine-tuning LLM (Large Language Models) AnythingLLM LM Studio despliegue local de IA Docker ngrok Legal AI Intelligent Legal Services Retrieval-Augmented Generation (RAG) Fine-tuning Large Language Models (LLMs) AnythingLLM LM Studio On-premises Deployment Docker ngrok Derecho |
| title_short |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| title_full |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| title_fullStr |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| title_full_unstemmed |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| title_sort |
Ponencia Prueba asistente jurídico Conference On Innovation 2024-2 |
| dc.creator.fl_str_mv |
Gonzalez Torres, Daniel Leonardo |
| dc.contributor.advisor.none.fl_str_mv |
Gonzalez Torres, Daniel Leonardo Santa Quintero, Ricardo Andres |
| dc.contributor.author.none.fl_str_mv |
Gonzalez Torres, Daniel Leonardo |
| dc.subject.spa.fl_str_mv |
consultorio jurídico IA inteligencia artificial legal RAG (Retrieval-Augmented Generation) fine-tuning LLM (Large Language Models) AnythingLLM LM Studio despliegue local de IA Docker ngrok |
| topic |
consultorio jurídico IA inteligencia artificial legal RAG (Retrieval-Augmented Generation) fine-tuning LLM (Large Language Models) AnythingLLM LM Studio despliegue local de IA Docker ngrok Legal AI Intelligent Legal Services Retrieval-Augmented Generation (RAG) Fine-tuning Large Language Models (LLMs) AnythingLLM LM Studio On-premises Deployment Docker ngrok Derecho |
| dc.subject.subjectenglish.spa.fl_str_mv |
Legal AI Intelligent Legal Services Retrieval-Augmented Generation (RAG) Fine-tuning Large Language Models (LLMs) AnythingLLM LM Studio On-premises Deployment Docker ngrok |
| dc.subject.lemb.spa.fl_str_mv |
Derecho |
| description |
La ponencia describe 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. |
| publishDate |
2024 |
| dc.date.created.none.fl_str_mv |
2024-10-15 |
| dc.date.accessioned.none.fl_str_mv |
2025-05-16T13:32:59Z |
| dc.date.available.none.fl_str_mv |
2025-05-16T13:32:59Z |
| dc.type.local.spa.fl_str_mv |
Tesis de Pregrado |
| dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/bachelorThesis |
| format |
http://purl.org/coar/resource_type/c_7a1f |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/10901/31146 |
| url |
https://hdl.handle.net/10901/31146 |
| dc.relation.references.spa.fl_str_mv |
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 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 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 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 AnythingLLM. (s.f.). AnythingLLM: All-in-One AI Application. https://anythingllm.com/ LM Studio. (s.f.). LM Studio: Local LLM Configuration. https://docs.useanything.com/setup/llm-configuration/local/lmstudio |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/2.5/co/ |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial-SinDerivadas 2.5 Colombia |
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info:eu-repo/semantics/openAccess |
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http://purl.org/coar/access_right/c_abf2 |
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http://creativecommons.org/licenses/by-nc-nd/2.5/co/ Atribución-NoComercial-SinDerivadas 2.5 Colombia http://purl.org/coar/access_right/c_abf2 |
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openAccess |
| dc.format.spa.fl_str_mv |
PDF |
| dc.coverage.spatial.spa.fl_str_mv |
Bogotá |
| institution |
Universidad Libre |
| bitstream.url.fl_str_mv |
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Repositorio Institucional Unilibre |
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repositorio@unilibrebog.edu.co |
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Gonzalez Torres, Daniel LeonardoSanta Quintero, Ricardo AndresGonzalez Torres, Daniel LeonardoBogotá2025-05-16T13:32:59Z2025-05-16T13:32:59Z2024-10-15https://hdl.handle.net/10901/31146La ponencia describe 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.Universidad Libre -- Ingenieria -- Ingenieria de sistemasThe presentation describes 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.PDFhttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Atribución-NoComercial-SinDerivadas 2.5 Colombiainfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2consultorio jurídico IAinteligencia artificial legalRAG (Retrieval-Augmented Generation)fine-tuningLLM (Large Language Models)AnythingLLMLM Studiodespliegue local de IADockerngrokLegal AIIntelligent Legal ServicesRetrieval-Augmented Generation (RAG)Fine-tuningLarge Language Models (LLMs)AnythingLLMLM StudioOn-premises DeploymentDockerngrokDerechoPonencia Prueba asistente jurídico Conference On Innovation 2024-2Legal Assistant Test Presentation Conference On Innovation 2024-2Tesis de Pregradohttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesisMagesh, 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/2405.20362Arredondo, P., & Lewis, P. (2024, junio 14). Reduce AI Hallucinations With This Neat Software Trick. WIRED. https://www.wired.com/story/reduce-ai-hallucinations-with-ragYue, 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/2309.11325Lin, C.-H., & Cheng, P.-J. (2024). Legal Documents Drafting with Fine-Tuned Pre-Trained Large Language Model. arXiv. https://arxiv.org/abs/2406.04202AnythingLLM. (s.f.). AnythingLLM: All-in-One AI Application. https://anythingllm.com/LM Studio. (s.f.). LM Studio: Local LLM Configuration. https://docs.useanything.com/setup/llm-configuration/local/lmstudioTHUMBNAILPonencia Prueba asistente jurídico Conference On Innovation 2024-2.pdf.jpgPonencia Prueba asistente jurídico Conference On Innovation 2024-2.pdf.jpgimage/jpeg33805http://repository.unilibre.edu.co/bitstream/10901/31146/4/Ponencia%20Prueba%20asistente%20jur%c3%addico%20Conference%20On%20Innovation%202024-2.pdf.jpg200bb48f720c455ea8c8c68d9ab04238MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repository.unilibre.edu.co/bitstream/10901/31146/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53ORIGINALPonencia Prueba asistente jurídico Conference On Innovation 2024-2.pdfPonencia Prueba asistente jurídico Conference On Innovation 2024-2.pdfapplication/pdf162356http://repository.unilibre.edu.co/bitstream/10901/31146/1/Ponencia%20Prueba%20asistente%20jur%c3%addico%20Conference%20On%20Innovation%202024-2.pdff7a4f7dd1de1acfe6768392c875228f6MD51Formato autorización PUBLICACIÓN DE OBRAS - Ponencia Conference On Innovation 2024-2.pdfFormato autorización PUBLICACIÓN DE OBRAS - Ponencia Conference On Innovation 2024-2.pdfapplication/pdf187706http://repository.unilibre.edu.co/bitstream/10901/31146/2/Formato%20autorizaci%c3%b3n%20PUBLICACI%c3%93N%20DE%20OBRAS%20-%20Ponencia%20Conference%20On%20Innovation%202024-2.pdff5eb27d5fe3ee3d6dc9055ddf872b733MD5210901/31146oai:repository.unilibre.edu.co:10901/311462025-05-27 16:35:14.309Repositorio Institucional Unilibrerepositorio@unilibrebog.edu.coTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo= |