Log 4 ๐ซ
ยท 2 min read
Objectivesโ
- Deploy watsonx.ai on self-managed AWS infrastructure.
Accomplishmentsโ
AWS
- Reviewed list of missing values able to be added to role via Policy
- Sent parameter overrides list to be populated for CloudFormation template installation.
- Creation of three separate CloudFormation template Roles.
- Updated CloudFormation templates to use STS.
RAG
- Creation of cronjob to capture logs from Python app.
- Enabled metadata insertion into chunks in vector store -> (hopefully) increases retrieval accuracy
- Return context to user (shows sources used to generate responses)
- Added mixtral model support
- Enable functionality for user to give custom rag parameters
- Migrated vector DB from FAISS to chromaDB to enable the metadata functionality
- Script written to easily test rag implementation and save results in csv
- Implemented cache logic to make sure it considers combination of parameters as well before chosing to send a cached response
In Progressโ
- End-to-end deployment of OCP, CP4D, and watsonx.ai (with GPU node)
- Tagging cp-deployer.sh generated resources.
Next Stepsโ
- Continue over the shoulder working sessions
- Kick off CloudFormation template install
- Compilation of required endpoints
- Fill out required network values required for OCP deployment.
- Deploy latest RAG version on AWS
- Build out actions & flow in Watsonx Assistant after properly defining personas & objectives.
Tracking (Issues)โ
- Require sign-off on final CloudFormation template.
- Getting access to CoreOS AMI.