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QnA Genie Tool
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Custom Copilot
Inspiration
Our inspiration came from the need to provide timely and accurate answers to student queries in an e-learning environment. We wanted to leverage the power of AI and machine learning to automate this process and make it more efficient.
What it does
The tool automates the process of answering common student questions by analyzing articles and generating insightful responses. It uses advanced embedding vectors and efficient information retrieval to provide accurate and timely answers.
How we built it
We built the tool using a combination of LangChain for content extraction, AzureAI for constructing embedding vectors, FAISS for information retrieval, and Streamlit for creating a user-friendly interface. The integration of these technologies allows for seamless content processing and interactive Q&A.
Challenges we ran into
We faced several challenges, including optimizing the processing speed of large datasets, ensuring the accuracy of the embedding vectors, and creating an intuitive user interface. Balancing these aspects while maintaining performance was a significant hurdle.
Accomplishments that we're proud of
We are proud of creating a tool that significantly enhances the efficiency of addressing student queries. The seamless integration of multiple technologies and the creation of an interactive dashboard are accomplishments that stand out.
What we learned
Through this project, we learned the importance of efficient data processing and the power of embedding vectors in analyzing large datasets. We also gained insights into creating user-friendly interfaces that facilitate interaction with AI-powered tools.
What's next for QnA Genie
We plan to enhance the tool's capabilities by incorporating more advanced AI models and expanding its use cases beyond e-learning. We aim to continuously improve the accuracy and efficiency of the tool and explore new ways to leverage AI for automated query responses.
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