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Route and manage multi-model chats via MCP with fallback and session memory.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "IRIS - Integrated Runtime Intelligence Service" yet — see the docs or source repo.
Help me design a routing policy for IRIS: use a low-cost model for standard Q&A, switch to a high-performance model for complex reasoning, automatically fall back when the primary model times out or fails, and explain the routing rules for each request type.
A clear routing plan with priorities, fallback conditions, request classification, and policy details.
I want to use IRIS to preserve context for a team assistant. Provide a persistent session design covering session IDs, context storage, history trimming, and how to keep a consistent experience across multi-turn conversations.
A session management recommendation explaining how to save, restore, and optimize multi-turn conversation context.
Based on historical invocation performance, create a continuous optimization mechanism for IRIS: track latency, success rate, cost, and answer quality for each model, then dynamically adjust routing decisions using those metrics.
A performance learning and optimization plan with monitoring metrics, evaluation logic, and dynamic tuning methods.
Connect AI assistants to InterSystems IRIS for database and integration tasks.
Search the web, run code, and continue AI-assisted workflows seamlessly.
Manage calendar, tasks, planning, and memory via a self-hosted AI assistant.
Lets AI read latest sensor data from MQTT and Sparkplug B streams.
Route LLM requests across providers and orchestrate MCP tools with local privacy.
Access multiple AI providers in one terminal for generation, search, and comparison.