LEGAL AID PROVIDER PORTAL

The Legal Aid Provider presents an AI-based approach for improving access to understandable Indian legal information. The proposed system combines structured legal data, semantic embeddings, FAISS-based retrieval, Retrieval-Augmented Generation, and Large Language Models into a single framework. The current implementation has successfully processed the Constitution of India, BNS, and BNSS and created a unified dataset containing 1,783 records. The dataset includes 584 Articles, 934 Sections, 240 Schedules, 24 Appendices, and the Preamble. A dedicated validation pipeline was developed to verify text availability, metadata completeness, provision classification, duplicate identifiers, and record validity. The final validation produced zero missing text records, zero metadata issues, zero duplicate IDs, and zero invalid record objects. This provides a structured foundation for the next stage of development. The proposed RAG pipeline will use Sentence Transformers to generate semantic embeddings and FAISS to retrieve relevant legal provisions. The retrieved information will then be supplied to an LLM to generate understandable legal information and guidance. The complete system will integrate the RAG pipeline with a FastAPI backend, web interface, database, authentication, administration, and source-based response presentation. The system will maintain a strict focus on lawful information and will not be designed to promote or facilitate illegal activities. With further implementation, testing, source verification, and evaluation, the proposed Legal Aid Provider can provide a useful platform for improving access to Indian legal information while maintaining appropriate technical and legal limitations.

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