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Letting Data Speak, AI Act!
Case Study
Enhancing Spiritual Education with AI-Powered QA System
About the Client
A prominent spiritual foundation dedicated to spreading the teachings of a revered spiritual leader.
Challenge
The foundation needed to develop an advanced question-answering system to make spiritual teachings more accessible and interactive for devotees. They faced challenges in processing and retrieving information from various unstructured data sources, including audio files and books.
Key Results
Improved information retrieval accuracy by 80% through embedding model experimentation.
Solution
JashDS implemented a comprehensive AI-powered solution to address the client's needs:
Created a robust QA evaluation pipeline using Langsmith, enabling efficient testing and iteration of the system.
Conducted extensive experiments with different datasets, comparing results within Langsmith to optimize performance.
Explored various technical parameters to enhance the system's effectiveness:
Experimented with chunk sizes (x=5, 20) to optimize text processing.
Tested multiple embedding models, including OpenAI embeddings and a Hindi fine-tuned Huggingface model, to improve language understanding and context retention.
Proposed a roadmap for future enhancements, including:
Code refactoring for efficient deployment and version control.
Further experimentation with embedding models and prompts to improve accuracy.
Expanding the knowledge base by ingesting data from books written by the spiritual leader.
Integrating voice input capabilities for improved user interaction.
Developing a web interface for broader accessibility.
Creating specialized agents for tasks such as playing kirtans and videos.
Technologies Used
Langsmith
OpenAI Embeddings
Huggingface
Natural Language Processing (NLP)
Machine Learning
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