Indukuri Venkata worked on the nikbearbrown/INFO_7390_Art_and_Science_of_Data repository, delivering an end-to-end multimodal retrieval-augmented generation system over one month. They engineered a production-ready pipeline that ingests data from Google Cloud Storage, processes PDFs with image description generation, and normalizes web content through URL scraping. Using Python and Jupyter Notebook, Indukuri developed scripts for data handling and built a FastAPI service for user management and vector search, integrating Pinecone as the vector database. The solution was containerized with Docker for scalable deployment. This work demonstrated depth in data engineering, cloud integration, and modern API development within a short timeframe.
April 2025 (nikbearbrown/INFO_7390_Art_and_Science_of_Data) — Delivered end-to-end multimodal retrieval-augmented generation (RAG) system setup, enabling scalable data ingestion, processing, and retrieval workflows. Implemented Python scripts and a Jupyter notebook for data loading from Google Cloud Storage, PDF processing with image description generation, and URL scraping/normalization. Built a FastAPI service for user management and vector search integration with Pinecone; included a Dockerfile for deployment and a LICENSE file for open-source readiness. Established a production-ready pipeline from data ingestion to retrieval with containerized deployment.
April 2025 (nikbearbrown/INFO_7390_Art_and_Science_of_Data) — Delivered end-to-end multimodal retrieval-augmented generation (RAG) system setup, enabling scalable data ingestion, processing, and retrieval workflows. Implemented Python scripts and a Jupyter notebook for data loading from Google Cloud Storage, PDF processing with image description generation, and URL scraping/normalization. Built a FastAPI service for user management and vector search integration with Pinecone; included a Dockerfile for deployment and a LICENSE file for open-source readiness. Established a production-ready pipeline from data ingestion to retrieval with containerized deployment.
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