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AI Assistant

The Omnismith AI Assistant enables natural language interaction with your workspace. Powered by Large Language Models (Google Gemini), the assistant can scaffold new schemas, execute data queries, generate sample entities, and analyze time-series metrics through conversational prompts.

1. Core Capabilities

Section titled “1. Core Capabilities”
Prompt GoalExample Conversational RequestAssistant Action
Schema Scaffolding”Create a data model for tracking software licenses, renewal dates, and annual cost.”Automatically creates Attributes and attaches them to a new Software License Template.
Data Ingestion”Add a new server entity named ‘prod-api-02’ with CPU usage at 45%.”Creates the entity record with exact attribute values under the Server Node template.
Analytics & Search”Which servers had average CPU load above 80% today?”Queries TimescaleDB metric buckets and returns a summarized markdown table.
Data Summarization”Summarize active high-priority support tickets.”Scans entities and presents key operational recommendations.

2. Real-Time Streaming & Agentic Loops

Section titled “2. Real-Time Streaming & Agentic Loops”

When you send a prompt to the AI Assistant:

  1. Agentic Planning: The assistant breaks your request into a sequence of tool calls (e.g. searching existing templates → creating attributes → instantiating entities).
  2. Streaming Response: Reasoning steps and output text stream in real time into the chat interface.
  3. Context Sensitivity: The assistant respects your current project context, user role permissions, and active template schema.

AI Assistant chat interface showing prompt input and real-time streaming agentic output

3. Best Practices for Effective Prompts

Section titled “3. Best Practices for Effective Prompts”
  • Be Specific: Specify template names, attribute titles, and numeric values when asking for record creation.
  • Iterative Refinement: Ask the assistant to refine a schema (e.g. “Now add an ‘Environment’ list attribute to that server template”).
  • Verification: Inspect generated entities and templates in the standard UI views after scaffolding.

💡 Developer Architecture Note

Section titled “💡 Developer Architecture Note”

[!NOTE] LLM Proxy & Security Isolation: All AI Assistant requests route through llm-proxy, an isolated proxy microservice. The proxy enforces project RBAC security boundaries, preventing unauthorized data access or model prompt injection attacks.

Next Steps

Section titled “Next Steps”

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