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Release Notes: Intel® AI for Enterprise Agent Toolkit – Version 1.0.0
Tag: release-1.0.0 | License: Apache 2.0
System Requirements
| Category | Minimum | Recommended |
|---|---|---|
| OS | Ubuntu 22.04, Ubuntu 24.04 | |
| CPU | Intel® Xeon® Scalable (x86_64), 96 cores | 96+ cores |
| RAM | 256 GB | 256+ GB |
| Disk | 150 GB (varies by model) | 200 GB |
| Architecture | x86_64 | x86_64 |
Additional requirements: internet access, SSH key pair, SSL/TLS certificates, Hugging Face API token with read access to gated models.
Deployment Modes
-
Single Node (all-in-one, development / demos)
-
Single Master + Multiple Workers (higher throughput, staging / Prod)
Key Features
Multi-Node Kubernetes Support
Full multi-node cluster deployment is enabled.
Memory
(Redis + RediSearch (short-term) · PostgreSQL + pgvector (long-term)
Full-lifecycle agent memory: short-term session context and long-term cross-session knowledge. Enables RAG, semantic search, and stateful multi-turn workflows.
Intelligent Routing
Routes LLM workloads to the optimal compute target by task intent — reasoning tasks to to GPU or cloud/MaaS endpoints; execution, encoding, and coordination tasks are routed to CPU on Xeon. Configurable per application, model-agnostic.
KubeRay Distributed Computing
KubeRay operator (v1.3.0) and RayCluster CR are deployed via Helm (core/helm-charts/kuberay/). Supports autoscaling head/worker group specs with security hardening. KubeRay configuration is managed through a dedicated kuberay-config.yaml file. Enables parallel tool calling for AI agent workflows. Controlled via the deploy_kuberay toggle in agentic-config.cfg.
Agent Sandbox
Isolated, ephemeral Kubernetes pod environments for safe code execution by AI agents (based on kubernetes-sigs/agent-sandbox v0.4.6). Each sandbox pod has its own filesystem, network namespace, and process tree. Controlled via deploy_agent_sandbox in agentic-config.cfg.
Flowise Integration
Flowise (low-code visual agent pipeline builder) is deployed as an optional plugin with PostgreSQL and Redis backends. A sample software-team multi-agent template is included. Controlled via the deploy_agenticai_plugin toggle.
New and Updated Model Support
The following models are available for CPU deployment via the interactive model selection menu:
| # | Model | Type |
|---|---|---|
| 21 | Qwen/Qwen3-Coder-30B-A3B-Instruct |
LLM (Coding) |
| 22 | Qwen/Qwen2.5-Coder-14B-Instruct |
LLM (Coding) |
| 23 | BAAI/bge-base-en-v1.5 |
Embedding |
| 24 | BAAI/bge-reranker-base |
Reranker |
| 25 | Qwen/Qwen3-30B-A3B-Instruct-2507 |
LLM |
| 26 | google/gemma-4-26B-A4B-it |
LLM |
vLLM Upgrade
vLLM CPU image upgraded to v0.23.0. Embedding and reranker model identifiers updated. Unused vault_pass_file variable removed.
Proxy Support
Corporate HTTP/HTTPS proxy support for fresh installs and multi-node cluster operations. All Ansible playbooks (cluster.yml, scale.yml) propagate proxy_env to package installs, kubeadm join, image pulls, and containerd systemd drop-in configuration.
Component Versions
| Component | Version |
|---|---|
| vLLM CPU Image | v0.23.0 |
| KubeRay Operator | 1.3.0 |
| Agent Sandbox | v0.4.6 |
| Kubespray | v2.27.0 |
| Observability Stack Chart | 72.5.1 |
| Langfuse Trace Chart | 1.5.30 |
| Ingress Controller | 4.12.2 |
Resources
License
- Licensed under the Apache License 2.0.
Thank you for using Intel® AI for Enterprise Agent Toolkit!