Changelog

Stay up to date with the latest changes to Redbit AI Studio.

Unreleased

Agent runtime profiles — Settings can test and save custom describe model capabilities locally, with endpoint-scoped profiles for direct and relay runtimes.
Capability-aware routing — Agent calls now resolve runtime config and capability plans once, then execute with the selected profile instead of re-reading stale Settings state.
Claude-native agent runtime — Custom describe runtimes can use Anthropic’s native Messages API while OpenAI-compatible providers continue to cover DeepSeek/Groq/OpenRouter-style relays.
Provider-first model onboarding — Custom describe setup now offers provider presets plus live model discovery and manual model ID fallback, reducing the work needed to connect new model providers or relays without developer changes.

Vision payload injection now follows the resolved runtime/profile capability, preventing non-vision custom endpoints from receiving image inputs.
Required probe failures no longer persist successful-looking model profiles.

Creative Workshop — Staged creative project flow: Script → Storyboard → Video generation
Desktop Engine (local-core) — Rust-native daemon with SQLite WAL, FFmpeg, and MCP Gateway
Harness Engineering v2 — Tool output self-declaration with Zod schema validation
Confidence Calibrator — Agent self-evaluation and reliability scoring

5-tier Unified Intent Router reduces avoidable full LLM turns for simple commands
DAG concurrency pipeline for parallel tool execution
Intent Drift Detector helps detect and recalibrate drift during long tool loops
Masonry Canvas virtualization for ultra-low RAM consumption

Guarded mutation metadata for destructive and external-effect tools
Sensitive settings fields are encrypted before browser IndexedDB persistence when available
SQLite WAL mode for crash-safe local persistence

We’d love to hear from you. Submit feature requests and bug reports on GitHub.

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