Description: There was an ask and need for PHAC to start looking into building an ‘ask-the-docs’ type of application that could be stored on Google Cloud Platform (GCP) in a secure way which would allow users to upload or read from local documents and query them with a chat-like interface/feel. Multiple tools could do such a thing and it was my responsibility to learn them, deploy them, and test them to determine which would meet the needs of the team(s).
Roles and Responsibilities: Full-stack and Cloud Developer
- Researched which current methods exist and narrowed down options
- Deployed the options within a GCP environment (using GenAI tools such as VertexAI and DocAI)
- Deployed some local LLMs (using PrivateGPT and Mistral, LLama, OpenAI, and HuggingFace)
- Tested each deployment’s capabilities and use cases along with performance and UAT testing
- Created documents and presentations to brief senior management on the findings and provide recommendations based on the results of the tests
Project Duration: 1 year
Environment:
- Git Bash
- Python
- git
- GCP Cloud SQL
- GCP Container Registry
- GCP Kubernetes clusters
- GCP IAM
- GCP GenAI
- GCP DocAI
- PostgreSQL
- LLMs
- PrivateGPT
- OpenAI
- .docx
- .xlsx
- .csv