Advanced Document Retrieval: CI/CD Explained | Aarti Dashore

Описание: How I automated Code quality using Code Integration /Code Deployment in GitHub.

This is an extended version of semantic document retrieval system that I build which implements dotenv, CI/CD

GitHub Repo Link: https://github.com/AartiDashore/lab5

In this extended project, I used FastAPI, Sentence Transformers, and ChromaDB to create an AI-powered search engine that converts documents into vector embeddings and retrieves the most relevant results using semantic similarity. Re-ranker has been implemented by reranker.py and BM25 is implemented by hybrid.py. The CI/CD workflow is implemented via ci.yml file.

This extended project is built as part of Lab5 for ARIN 5360.

Tech Stack:
FastAPI
Sentence Transformers (ms-marco-MiniLM-L-6-v2)
ChromaDB
Python
Pytest
uv

Perfect for anyone learning:
AI engineering, semantic search, vector databases, or backend APIs.

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