> ## Documentation Index > Fetch the complete documentation index at: https://docs.fluffbuzz.com/llms.txt > Use this file to discover all available pages before exploring further. # Inference CLI `fluffbuzz infer` is the canonical headless surface for provider-backed inference workflows. It intentionally exposes capability families, not raw gateway RPC names and not raw agent tool ids. ## Turn infer into a skill Copy and paste this to an agent: ```text theme={"theme":{"light":"min-light","dark":"min-dark"}} Read https://docs.fluffbuzz.com/cli/infer, then create a skill that routes my common workflows to `fluffbuzz infer`. Focus on model runs, image generation, video generation, audio transcription, TTS, web search, and embeddings. ``` A good infer-based skill should: * map common user intents to the correct infer subcommand * include a few canonical infer examples for the workflows it covers * prefer `fluffbuzz infer ...` in examples and suggestions * avoid re-documenting the entire infer surface inside the skill body Typical infer-focused skill coverage: * `fluffbuzz infer model run` * `fluffbuzz infer image generate` * `fluffbuzz infer audio transcribe` * `fluffbuzz infer tts convert` * `fluffbuzz infer web search` * `fluffbuzz infer embedding create` ## Why use infer `fluffbuzz infer` provides one consistent CLI for provider-backed inference tasks inside FluffBuzz. Benefits: * Use the providers and models already configured in FluffBuzz instead of wiring up one-off wrappers for each backend. * Keep model, image, audio transcription, TTS, video, web, and embedding workflows under one command tree. * Use a stable `--json` output shape for scripts, automation, and agent-driven workflows. * Prefer a first-party FluffBuzz surface when the task is fundamentally "run inference." * Use the normal local path without requiring the gateway for most infer commands. ## Command tree ```text theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer list inspect model run list inspect providers auth login auth logout auth status image generate edit describe describe-many providers audio transcribe providers tts convert voices providers status enable disable set-provider video generate describe providers web search fetch providers embedding create providers ``` ## Common tasks This table maps common inference tasks to the corresponding infer command. | Task | Command | Notes | | ----------------------- | ----------------------------------------------------------------------- | ----------------------------------------------------- | | Run a text/model prompt | `fluffbuzz infer model run --prompt "..." --json` | Uses the normal local path by default | | Generate an image | `fluffbuzz infer image generate --prompt "..." --json` | Use `image edit` when starting from an existing file | | Describe an image file | `fluffbuzz infer image describe --file ./image.png --json` | `--model` must be an image-capable `` | | Transcribe audio | `fluffbuzz infer audio transcribe --file ./memo.m4a --json` | `--model` must be `` | | Synthesize speech | `fluffbuzz infer tts convert --text "..." --output ./speech.mp3 --json` | `tts status` is gateway-oriented | | Generate a video | `fluffbuzz infer video generate --prompt "..." --json` | | | Describe a video file | `fluffbuzz infer video describe --file ./clip.mp4 --json` | `--model` must be `` | | Search the web | `fluffbuzz infer web search --query "..." --json` | | | Fetch a web page | `fluffbuzz infer web fetch --url https://example.com --json` | | | Create embeddings | `fluffbuzz infer embedding create --text "..." --json` | | ## Behavior * `fluffbuzz infer ...` is the primary CLI surface for these workflows. * Use `--json` when the output will be consumed by another command or script. * Use `--provider` or `--model provider/model` when a specific backend is required. * For `image describe`, `audio transcribe`, and `video describe`, `--model` must use the form ``. * For `image describe`, an explicit `--model` runs that provider/model directly. The model must be image-capable in the model catalog or provider config. `codex/` runs a bounded Codex app-server image-understanding turn; `openai-codex/` uses the OpenAI Codex OAuth provider path. * Stateless execution commands default to local. * Gateway-managed state commands default to gateway. * The normal local path does not require the gateway to be running. ## Model Use `model` for provider-backed text inference and model/provider inspection. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer model run --prompt "Reply with exactly: smoke-ok" --json fluffbuzz infer model run --prompt "Summarize this changelog entry" --provider openai --json fluffbuzz infer model providers --json fluffbuzz infer model inspect --name gpt-5.5 --json ``` Notes: * `model run` reuses the agent runtime so provider/model overrides behave like normal agent execution. * `model auth login`, `model auth logout`, and `model auth status` manage saved provider auth state. ## Image Use `image` for generation, edit, and description. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer image generate --prompt "friendly puppy illustration" --json fluffbuzz infer image generate --prompt "cinematic product photo of headphones" --json fluffbuzz infer image describe --file ./photo.jpg --json fluffbuzz infer image describe --file ./ui-screenshot.png --model openai/gpt-4.1-mini --json fluffbuzz infer image describe --file ./photo.jpg --model ollama/qwen2.5vl:7b --json ``` Notes: * Use `image edit` when starting from existing input files. * For `image describe`, `--model` must be an image-capable ``. * For local Ollama vision models, pull the model first and set `OLLAMA_API_KEY` to any placeholder value, for example `ollama-local`. See [Ollama](/providers/ollama#vision-and-image-description). ## Audio Use `audio` for file transcription. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer audio transcribe --file ./memo.m4a --json fluffbuzz infer audio transcribe --file ./team-sync.m4a --language en --prompt "Focus on names and action items" --json fluffbuzz infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json ``` Notes: * `audio transcribe` is for file transcription, not realtime session management. * `--model` must be ``. ## TTS Use `tts` for speech synthesis and TTS provider state. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer tts convert --text "hello from fluffbuzz" --output ./hello.mp3 --json fluffbuzz infer tts convert --text "Your build is complete" --output ./build-complete.mp3 --json fluffbuzz infer tts providers --json fluffbuzz infer tts status --json ``` Notes: * `tts status` defaults to gateway because it reflects gateway-managed TTS state. * Use `tts providers`, `tts voices`, and `tts set-provider` to inspect and configure TTS behavior. ## Video Use `video` for generation and description. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer video generate --prompt "cinematic sunset over the ocean" --json fluffbuzz infer video generate --prompt "slow drone shot over a forest lake" --json fluffbuzz infer video describe --file ./clip.mp4 --json fluffbuzz infer video describe --file ./clip.mp4 --model openai/gpt-4.1-mini --json ``` Notes: * `--model` must be `` for `video describe`. ## Web Use `web` for search and fetch workflows. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer web search --query "FluffBuzz docs" --json fluffbuzz infer web search --query "FluffBuzz infer web providers" --json fluffbuzz infer web fetch --url https://docs.fluffbuzz.com/cli/infer --json fluffbuzz infer web providers --json ``` Notes: * Use `web providers` to inspect available, configured, and selected providers. ## Embedding Use `embedding` for vector creation and embedding provider inspection. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} fluffbuzz infer embedding create --text "friendly puppy" --json fluffbuzz infer embedding create --text "customer support ticket: delayed shipment" --model openai/text-embedding-3-large --json fluffbuzz infer embedding providers --json ``` ## JSON output Infer commands normalize JSON output under a shared envelope: ```json theme={"theme":{"light":"min-light","dark":"min-dark"}} { "ok": true, "capability": "image.generate", "transport": "local", "provider": "openai", "model": "gpt-image-2", "attempts": [], "outputs": [] } ``` Top-level fields are stable: * `ok` * `capability` * `transport` * `provider` * `model` * `attempts` * `outputs` * `error` ## Common pitfalls ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} # Bad fluffbuzz infer media image generate --prompt "friendly puppy" # Good fluffbuzz infer image generate --prompt "friendly puppy" ``` ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} # Bad fluffbuzz infer audio transcribe --file ./memo.m4a --model whisper-1 --json # Good fluffbuzz infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json ``` ## Notes * `fluffbuzz capability ...` is an alias for `fluffbuzz infer ...`.