Robust chatbot application powered by LLM

 Spearheaded the backend development and AI development of a robust chatbot application leveraging state-ofthe-art language models(both open and closed models). The entire AI backend was built in Python.

 Implemented Langchain as the large language model framework, utilizing Pinecone as the vector database for fast and efficient data storage and retrieval. Employed optimized metafilters to facilitate diverse company usage without compromising data privacy.

 Engineered a versatile web scraper capable of extracting information from entire website domains, single URLs, sitemaps, GitHub, PDFs, Word documents, PowerPoint presentations, CSVs, Excel files, and Google Drive.

 Employed FastAPI as the web API framework, integrated Pusher for real-time event streaming, and utilized a managed MySQL database on the cloud for storing essential information.

 Leveraged Google Cloud Platform (GCP) as the cloud provider, deploying the application on Google Cloud Run for its exceptional autoscaling capabilities. Utilized various GCP services including monitoring, tasks, scheduler, build, container registry, and more.

 Containerized the entire application using Docker and implemented Grafana for real-time monitoring, enhancing overall performance.

 Adhered to MLOPS and best software engineering practices to ensure smooth operations.

 Implemented GitHub Actions and GCP Cloud Build for robust CI/CD pipelines.

 Collaborated seamlessly with cross-functional teams, especially front-end developers, to ensure the seamless integration and user-friendly implementation of the application.