Build a system that uses Large Language Models (LLMs) to process natural language queries and retrieve relevant information from large unstructured documents such as policy documents, contracts, and emails.Objective:The system should take an input query like:“46-year-old male, knee surgery in Pune, 3-month-old insurance policy”It must then:Parse and structure the query to identify key details such as age, procedure, location, and policy duration.Search and retrieve relevant clauses or rules from the provided documents using semantic understanding rather than simple keyword matching.Evaluate the retrieved information to determine the correct decision, such as approval status or payout amount, based on the logic defined in the clauses.Return a structured JSON response containing: Decision (e.g., approved or rejected), Amount (if applicable), and Justification, including mapping of each decision to the specific clause(s) it was based on.Requirements:Input documents may include PDFs, Word files, or emails.The query processing and retrieval must work even if the query is vague, incomplete, or written in plain English.The system must be able to explain its decision by referencing the exact clauses used from the source documents.The output should be consistent, interpretable, and usable for downstream applications such as claim processing or audit tracking.Applications:This system can be applied in domains such as insurance, legal compliance, human resources, and contract management.Sample Query:"46M, knee surgery, Pune, 3-month policy"Sample Response:"Yes, knee surgery is covered under the policy."the datasets are attached for sample. Write the full project code with execution