Langchain is an application that utilizes advanced natural language processing (NLP) and machine learning (ML) techniques to enable efficient interaction with PDF documents. It excels in understanding and retrieving information from PDFs, providing accurate responses to user queries.

• Text Vectorization: Langchain employs cutting-edge vectorization techniques to represent document content in a meaningful way.
• Conversational Retrieval: Utilizes a conversational retrieval chain to generate contextually accurate responses.
• User-friendly Interface: Designed with a user-friendly interface for seamless interaction.

Usage Upload PDF documents through the user interface. Ask questions related to the uploaded documents. Evaluate the system's responses based on BLEU Score, ROUGE-L Score, and other metrics. Evaluation Metrics Langchain is evaluated based on the following metrics:

Vectorization Quality: Mean Squared Error (MSE) of the cosine similarity matrix. Response Evaluation: BLEU Score and ROUGE-L Score for generated responses. System Performance: Real-world testing with PDF documents and user queries. Hypothetical Test Results For hypothetical test results and comparison with other models, refer to the provided data in the test_results.xlsx file.

Contributing We welcome contributions! If you find a bug or have suggestions for improvement, please open an issue or create a pull request.