xybrid_flutter 0.2.2

Xybrid Flutter SDK — run ML models on-device or in the cloud with intelligent hybrid routing and streaming inference.

Changelog

0.2.2

Structured output on Flutter. Local llama generation can now be constrained to a JSON Schema so small models emit guaranteed-valid JSON for on-device data extraction: FfiGenerationConfig gains a grammar field, and a new jsonSchemaToGbnf helper converts a JSON Schema to the GBNF grammar the backend enforces (xybrid-ai/xybrid#310, xybrid-ai/xybrid#311).

0.2.1

Vision (VLM) now runs on every Flutter target. 0.2.0 shipped on-device vision on Android and iOS; 0.2.1 brings the native VLM backend (llm-llamacpp-vision, llama.cpp's mtmd) to the desktop targets too — macOS, Linux, and Windows — so a Flutter desktop app can run a vision-language model out of the box, matching mobile (xybrid-ai/xybrid#296).

• Fixed: GGUF models with custom or non-standard chat templates now load and run — when llama.cpp's built-in template matcher rejects the embedded template, it is rendered via a real Jinja engine (minijinja) instead of failing (xybrid-ai/xybrid#304)

0.2.0-rc1

Release candidate for 0.2.0, published so consumers can validate the vision binding against real integrations ahead of the stable tag. No functional changes from 0.2.0 — see the 0.2.0 entry below for the full change set.

0.2.0-alpha

Prerelease of 0.2.0, published to validate the release pipeline ahead of the stable tag. No functional changes from 0.2.0 — see the 0.2.0 entry below for the full change set.

0.2.0

The vision release. The binding gains on-device multimodal input and the real-time camera vision primitives behind Studio's live loop.

• On-device vision (VLM): new XybridEnvelope.image (encoded PNG/JPEG/WebP), XybridEnvelope.imageRaw (raw camera/canvas pixel frames), and XybridEnvelope.multiPart (user-role message with image attachments) for running vision-language models from Dart (xybrid-ai/xybrid#245, #265)
• Reachable streaming cancellation: new CancellationToken whose cancel() drives a real runtime abort end-to-end — the generation halts at the next token and releases the model lock, instead of the old behavior where "stop" only unsubscribed while the runtime kept generating (xybrid-ai/xybrid#245)
• Live-loop run options on the model handle: preempt (latest-frame-wins — a new run preempts the in-flight one so a live loop no longer head-of-line-blocks behind a stale frame) and frameSessionId for tagging live inferences (xybrid-ai/xybrid#245)
• Raw-frame path avoids per-frame JPEG re-encoding: imageRaw packs RGB pixel buffers straight through to the multimodal runtime; the encoded image path remains the fallback (xybrid-ai/xybrid#245)
• Streaming TTS support on top of the new audio generation path (xybrid-ai/xybrid#245)
• Live-mode telemetry is rate-limited by a per-session sampler (≈1 row/sec/session), so live camera sessions no longer emit a telemetry row per frame (xybrid-ai/xybrid#245)
• XybridModel.warmup / unload are now exposed on the Flutter binding, completing the sync/async method symmetry (xybrid-ai/xybrid#293)
• Fixed: TTS text chunking is now UTF-8-safe — multi-byte codepoints are no longer split mid-character (xybrid-ai/xybrid#249)
• Fixed: .npz voice files are detected by magic header rather than file extension (xybrid-ai/xybrid#252)
• Fixed: tokens_out is now emitted on local LLM telemetry paths (xybrid-ai/xybrid#253)

0.1.2

• Audio inputs now detect MP3, OGG, and FLAC in addition to WAV, and mono audio is upmixed to stereo when a model expects two channels (xybrid-ai/xybrid#132, #141)
• Robustness: the underlying SDK/core no longer panics on poisoned locks, unchecked length headers, or non-contiguous ONNX output tensors — these are recovered or handled gracefully (xybrid-ai/xybrid#233, #234, #235, #231, #232, #237)
• The Xybrid API key is no longer placed in the process environment (xybrid-ai/xybrid#214)
• Registry requests now honor Retry-After on 429 responses (xybrid-ai/xybrid#134)

0.1.1

• New bundled init() entry point starts anonymous-by-default telemetry from an API key; the standalone initTelemetry is now legacy (xybrid-ai/xybrid#188, #195)
• PlatformEvent payloads now carry sdk_version and binding, so telemetry is attributable to the SDK build and the Flutter binding that emitted it (xybrid-ai/xybrid#183)
• Fixed: the SDK no longer leaks the leading bytes of its own API key into emitted telemetry (xybrid-ai/xybrid#209)
• Fixed: cache TTL handling is panic-safe — a backwards system clock no longer panics the cache layer (xybrid-ai/xybrid#203)
• Example app now reads XYBRID_API_KEY from the environment at init (xybrid-ai/xybrid#207)

0.1.0

Production release of the 0.1.0 line. No Flutter-binding code changes since rc4 — closes the rc series.

Cumulative since the last published-to-pub.dev release (rc3):

• XybridResult now exposes typed InferenceMetrics (CPU / memory / GPU / wall-clock per inference); the underlying telemetry is also surfaced in the bundled Flutter demos
• Streaming-LLM cloud fallback now routes off live device pressure signals (CPU / memory / thermal) instead of static thresholds
• ModelWarmup events emit from XybridModel.warmup and arrive in the binding's telemetry stream, so first-token latency is attributable to warmup vs. inference
• streaming is now a top-level field on PlatformEvent payloads instead of nested under metadata
• GGUF bundles without an explicit backend annotation now report llamacpp in telemetry instead of unknown
• New Denormalize postprocessing step in the SDK core (mirror of Normalize), useful for round-tripping model output back into input-space coordinates
• Fixed: ModelComplete events were dropped on streaming fast-path inference; now emitted on every code path
• Fixed: internal orchestrator pipeline-frame events no longer leak to the binding as opaque payloads

0.1.0-rc4

• XybridResult now exposes typed InferenceMetrics (CPU / memory / GPU / wall-clock per inference); the underlying telemetry is also surfaced in the bundled Flutter demos
• Streaming-LLM cloud fallback now routes off live device pressure signals (CPU / memory / thermal) instead of static thresholds
• ModelWarmup events emit from XybridModel.warmup and arrive in the binding's telemetry stream, so first-token latency is attributable to warmup vs. inference
• streaming is now a top-level field on PlatformEvent payloads instead of nested under metadata
• GGUF bundles without an explicit backend annotation now report llamacpp in telemetry instead of unknown
• New Denormalize postprocessing step in the SDK core (mirror of Normalize), useful for round-tripping model output back into input-space coordinates
• Fixed: ModelComplete events were dropped on streaming fast-path inference; now emitted on every code path
• Fixed: internal orchestrator pipeline-frame events no longer leak to the binding as opaque payloads

0.1.0-rc3

• Adaptive cloud fallback for streaming LLM: pipelines can now transparently fall back to a cloud runtime when on-device streaming generation stalls or errors mid-stream; configurable via new run options on the underlying SDK
• Streaming and chat-context LLM telemetry spans now include backend and quantization tags (previously dropped on these code paths)
• Hybrid LLM architectures (Mamba / SSM-style) now load and run cleanly through the bundled llama.cpp runtime

0.1.0-rc2

• Republishes 0.1.0-rc1 — the rc1 pub.dev publish was skipped due to an upstream compile failure in xybrid-core on aarch64-linux-android (fixed in xybrid-ai/xybrid#112). No API or behavior changes in the Flutter binding itself.

0.1.0-rc1

• Registry calls now send the X-Xybrid-Client telemetry header identifying the Flutter binding, SDK / core versions, platform, and enabled backends; respects the XYBRID_TELEMETRY_OPTOUT env var
• Per-inference resource telemetry: CPU / memory / GPU pressure metrics now flow into telemetry events from the underlying SDK
• Cloud LLM telemetry exposes provider-agnostic prompt-cache token counts (cache_creation / cache_read)

0.1.0-beta12

• LLM telemetry expansion: swim-lane spans, device profile metadata, and Pipeline::run hardening on top of beta11's streaming telemetry
• Fixed Windows precompile path mangling that was blocking native binaries from publishing to pub.dev

0.1.0-beta11

• Added LLM streaming telemetry: TTFT, decode/prefill TPS, and ITL now exposed via the SDK for both llama_cpp and mistral backends
• Added Device struct with a stable cross-platform device identifier
• Added NeuTTS codec TTS support
• Improved offline behavior: actionable errors and cached-models fallback when the registry is unreachable

0.1.0-beta10

• Version bump to track core release. No Flutter API changes.

0.1.0-beta9

• Added fromDirectory() for loading custom local models
• Added fromHuggingFace() for loading models directly from HuggingFace Hub
• Fixed cargokit version hash not triggering rebuilds across releases

0.1.0-beta8

• Fixed LLM model loading failing with "Unknown frame descriptor" on all platforms — passthrough GGUF models now load correctly (#16)

0.1.0-beta7

• Fixed libc++_shared.so missing from Android APK — replaced symlinks with NDK copy task
• Fixed Android 16KB page alignment for newer devices

0.1.0-beta6

• Version bump to track core release. No Flutter API changes.

0.1.0-beta5

• Qwen 3.5 model support via updated llama.cpp backend
• Automatic <think> tag stripping for reasoning models

0.1.0-beta4

• Version bump to track core release. No Flutter API changes.

0.1.0-beta3

• Version bump to track core release. No Flutter API changes.

0.1.0-beta2

• Version bump — core runtime fix (reverted ORT to 2.0.0-rc.11). No Flutter API changes.

0.1.0-beta1

• Version bump to track core release. No Flutter API changes.

0.1.0-alpha8

• Version bump to track core release. No Flutter API changes.

0.1.0-alpha7

Features

• GenerationConfig: Control LLM generation parameters (temperature, top_p, max_tokens, etc.) via optional config parameter on all XybridModel run and streaming methods
• GenerationConfig presets: GenerationConfig.greedy() and GenerationConfig.creative() named constructors for common configurations

0.1.0-alpha6

Features

• Xybrid Studio video polish and UI improvements

0.1.0-alpha5

Features

• Registry model loading: Load models directly from the xybrid registry with Xybrid.model(modelId: '...')
• LLM chat streaming: Real-time token-by-token streaming for LLM inference
• Conversation context: Multi-turn conversation memory with ConversationContext
• Pipeline execution: Run multi-stage ML pipelines from YAML definitions
• 5-platform support: macOS, iOS, Android, Linux, Windows

Improvements

• Remote model usage example added to Flutter example app
• Updated LLM demo screen in Flutter example app
• Kotlin SDK published to Maven Central (ai.xybrid:xybrid-kotlin:0.1.0-alpha3)

0.1.0-alpha4

Features

• TTS quality improvements: Silence token handling, center-break chunking, voice mixing, CJK punctuation, inter-chunk crossfading, configurable speed
• Composable model system: Metadata-driven TTS input mapping, voice selection strategy
• KittenTTS phonemizer fix: Switched from CmuDict to MisakiDictionary for correct phoneme output

Improvements

• Model naming convention standardized (e.g., kitten-tts-nano-0.2)
• TTS registry cleaned up with proper model versioning

0.1.0-alpha3

Features

• LLM hardening: Thread-safe llama.cpp wrapper, multi-token EOG, min_p sampling
• Windows support: MSVC CRT mismatch resolved, Git Bash CFLAGS fix
• Unity iOS build: C FFI library building for iOS targets

Improvements

• Release CI fixes across all platforms
• Test CI and release workflow updates
• Metadata generation tooling for automated model config

0.1.0-alpha2

Features

• Conversation memory: ConversationContext with configurable FIFO pruning, ChatTemplateFormatter (ChatML, Llama 2)
• Unified ORT iOS: Shared vendor/ort-ios/ xcframework across all build paths
• xtask auto-detection: Build commands automatically select platform features based on target triple

Breaking Changes

• Feature flag cascade fix: ort-download + ort-dynamic now caught at compile time
• Platform presets renamed for clarity

0.1.0-alpha1

Features

• Platform SDK restructure: UniFFI bindings (Swift/Kotlin), xybrid-ffi (C API)
• Thin Flutter FFI: ~150 LOC Dart bridge via flutter_rust_bridge
• xtask build commands: cargo xtask build-ffi, build-uniffi, build-xcframework, build-android, build-flutter
• GitHub Actions CI: Automated builds for all platforms

Breaking Changes

• xybrid_core::llm module renamed to xybrid_core::cloud
• PipelineLoader renamed to PipelineRef
• XybridPipeline renamed to Pipeline
• Direct TTS API removed (use pipeline execution instead)

Platform Support

Platform	ONNX Runtime	Candle	LLM
macOS	download-binaries	Metal	llama.cpp
iOS	vendor/ort-ios/	Metal	llama.cpp
Android	load-dynamic	-	llama.cpp
Linux	download-binaries	CPU	llama.cpp
Windows	download-binaries	CPU	llama.cpp