Released Versions

Support evaluation of LLM application, and generate detail report
Improve QA to duplicate QA pair
Suppor to scrap web URLs
Knowledge Assistant - an AI agent that can generate abstract for PDF/Word/web links, and accumulate knowledge
Support pgvector as vector store
Support to save chat history to postgresql and return the history
Enhanced AI Agents
- Follow-up questions
- Show the reference of answer
- Show repsonse time
Add a new CRD Agent to provides agent capability in LLM application
Add tools to CRD Agent: bing_search, weather query
Support realtime search using bing
Support common text in knowledgebase
Inference
- Support to use Ray cluster for distributed inference
- Node affinity and use specified GPU on nodes
- Integrate with RDMA to distribute data/models - enterprise version
Support to publish AI agent to built-in store
Add agent-portal project for end user perspective

Dataset Management - manage data, including local files, integrate with object storage(s3), data editing, version control, and file download
Data Processing - data cleaning, text splitting (e.g., text segmentation, QA splitting), file labeling
Knowledge Base - data embedding
Model Management - manage the lifecycle of models.
Model Serving
- Support CPU & GPU Model Serving
- Support both remote and local model inference services, and associate with the knowledge base
- Support local embedding service (bge, m3e)
- Support vLLM inference engine
LLM Applications - prompt engineering, initial implementation of LLM application orchestration capabilities. Manage and orchestrate Prompt, LLM/Retriever Chain nodes, and provide relevant example applications (based on streamlit)
Guided walkthroughs and example scenarios - let the user get started to build LLM application quickly, add momre built-in chat example applications