fluid ai

Configure the AI / LLM provider used by Forge Copilot and inspect the current AI configuration.

Syntax

fluid ai setup [--clear]
fluid ai setup --source CATALOG --name NAME
fluid ai status
fluid ai models [--provider PROVIDER] [--json]

Running fluid ai with no subcommand falls through to status.

Key options

ai setup

fluid ai setup --source CATALOG --name NAME configures source-catalog credentials for fluid forge data-model from-source and MCP forge_from_source calls. --source is the catalog type (snowflake, unity, bigquery, dataplex, glue, datahub, or datamesh_manager); --name is the saved credential id.

ai status

No options. Prints whether AI is configured and shows the active provider and model.

ai models

Shows provider defaults, routing model, and tiered model plan. It does not require an API key because it reads the bundled model catalog.

Examples

fluid ai setup
fluid ai setup --source snowflake --name snowflake-prod
fluid ai setup --clear
fluid ai status
fluid ai
fluid ai models
fluid ai models --provider gemini
fluid ai models --provider openai --json

Notes

• setup is interactive and requires a TTY with rich installed. It walks through provider choice (Google Gemini, OpenAI, Anthropic, Ollama, or skip), validates the API key with a lightweight call, and persists settings.
• setup --source configures source-catalog credentials separately from LLM provider selection.
• Provider config is written to ~/.fluid/ai_config.json (chmod 600). API keys are stored in the OS keyring when available and are not written to the JSON file by default.
• If no keyring backend is available, the API key is kept only for the current process. Set FLUID_ALLOW_PLAINTEXT_AI_SECRETS=1 only when you deliberately want plaintext local persistence.
• OLLAMA_HOST is restricted to localhost addresses for SSRF protection; non-local hosts are ignored and replaced with http://localhost:11434.
• The same setup flow is invoked inline on first use of fluid forge when no provider is configured.
• Provider environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, etc.) are respected as a fallback.
• For strict provider validation, run fluid forge data-model from-intent ... --require-llm so provider failures do not silently fall back to heuristics.
• For tiered per-stage model selection, pass --tiered on the forge command. Tiering stays within the active provider and collapses to single-model mode when the provider has no distinct tier catalog.
• Use fluid doctor to see AI status as part of a broader environment check.
• Full AI and model-first journeys are documented in AI Forge And Data-Model Journeys.

See LLM Providers for provider defaults, tiering, strict mode, and Ollama notes.