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Hi, Please review my assignment-2. Thx |
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approved, nice project with good document parsing |
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What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
Added Code and files.
What did you learn from the changes you have made?
Through this project, I gained hands-on experience building an end-to-end chatbot using three AI services. I also learned how embeddings are generated, stored, and integrated into the system to enable semantic understanding and retrieval.
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
I plan to further enhance the chatbot by integrating additional AI services, such as web search, to provide more up-to-date and context-aware responses. I also intend to experiment with larger embedding datasets to improve retrieval quality and overall answer relevance. In addition, I aim to explore and apply the Model Context Protocol (MCP) to better connect external tools and data sources, enabling the chatbot to become more scalable, extensible, and capable of handling complex real-world use cases.
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
Reading PDF documents that contain complex layouts and charts was a significant challenge. Given more time, I would explore using a specialized PDF-reader AI agent to better parse and understand the document structure and visual elements. For now, I used mock data to complete the RAG pipeline and demonstrate the overall workflow.
How were these changes tested?
After running app.py and interacting with the chatbot by asking several questions, the application returned responses as expected. The system functioned correctly, and the chatbot was able to generate relevant and accurate answers based on the implemented logic.
A reference to a related issue in your repository (if applicable)
N/A
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