chore(deps): bump flutter_gemma from 0.12.0 to 0.13.2

[dependabot]

Bumps flutter_gemma from 0.12.0 to 0.13.2.

Release notes

Sourced from flutter_gemma's releases.

Release v0.13.1

Changes

• LiteRT-LM 0.10.0: Updated Android and JVM SDK from 0.9.0 to 0.10.0
• Gemma 4 Thinking Mode: isThinking: true now works with Gemma 4 E2B/E4B models via extraContext and streaming thought channels
• Fix cancel download: Cancel download now works correctly (#196)
• Fix large_file_handler platform support: Conditional imports for pub.dev platform analysis compatibility

Release v0.13.0

systemInstruction support

v0.12.7

No release notes provided.

Release v0.12.6

v0.12.6

• LiteRT-LM 0.9.0-beta: Updated from 0.9.0-alpha02 on Android and Desktop (JVM)
• Cancel Generation: Implemented on Android, Desktop, and Web
  • Android LiteRT-LM: Conversation.cancelProcess()
  • Desktop: gRPC CancelGeneration RPC
  • Web: LlmInference.cancelProcessing() (MediaPipe 0.10.26)
• MediaPipe Web 0.10.26: Pinned CDN version
• E2E Integration Tests: Full inference test suite with multimodal support

Release v0.12.5

Pre-converted tokenizer.json files for iOS embedding models (avoids SentencePiece/TFLite protobuf conflict).

Release v0.12.3

JAR for desktop support

Changelog

Sourced from flutter_gemma's changelog.

0.13.2

• FileSource absolute paths: Accept both Unix (/path) and Windows (C:\path) absolute paths in FileSource validation
• Package metadata: Updated pubspec description to reflect current feature set (desktop, vision, audio, function calling, embeddings, on-device RAG)
• Desktop CI: Added Linux smoke tests for gRPC server integration

0.13.1

• LiteRT-LM 0.10.0: Updated Android and JVM SDK from 0.9.0 to 0.10.0
• Gemma 4 Thinking Mode: isThinking: true now works with Gemma 4 E2B/E4B models (Android, iOS, Desktop; not Web)
• Fix cancel download: Cancel download now works correctly (#196)
• Fix large_file_handler platform support: Conditional imports for pub.dev platform analysis compatibility

0.13.0

• Gemma 4 E2B/E4B: Added support for next-gen multimodal models (text + image + audio)
• systemInstruction: New parameter in createChat() and createSession() for setting system-level context
• ModelFileType.litertlm: New file type to properly handle .litertlm models across platforms
• iOS LiteRT-LM support: .litertlm models now work on iOS
• stopGeneration on iOS: Supported for .litertlm models
• MediaPipe GenAI 0.10.33: Updated iOS (from 0.10.24) and Android (from 0.10.29)
  • iOS: GPU backend selection via preferredBackend (Metal delegate now activated)
  • iOS: Audio modality support (addAudio + enableAudioModality)
  • Android: Unified inference engine (CPU-only path removed), improved error handling
  • Web: Updated to 0.10.27
• Example WASM compatibility: Replaced direct dart:io imports with conditional imports for WASM compilation support
• Benchmark integration test: example/integration_test/benchmark_comparison_test.dart for comparing model performance on device

0.12.8

• ToolChoice enum: auto / required / none parameter in createChat() to control tool calling behavior
• Parallel Tool Calls: ParallelFunctionCallResponse for multiple function calls in one response
• Strategy Pattern Parser: Per-model FunctionCallFormat implementations (Gemma, Qwen, DeepSeek, Llama, Phi, FunctionGemma)
• <tool_call> Format: Qwen/Mistral-style function call parsing
• ModelType.phi: Dedicated model type for Phi-4 with <|tool_calls|> format support
• NPU Fix: Pass nativeLibraryDir to LiteRT-LM Backend.NPU()
• Embeddings: Models return L2-normalized vectors (dot product = cosine similarity)
• Windows/Linux Embeddings Fix: TFLite C library now correctly copied to build output (#200)

0.12.7

• Dual-Prefix Embeddings (TaskType): Improved RAG retrieval quality with query/document prefixes
  • TaskType.retrievalQuery (default) — for search queries
  • TaskType.retrievalDocument — for document indexing
  • Follows Google RAG SDK convention (EmbedData.TaskType)
  • All platforms: Android, iOS, Web, Desktop
  • addDocument() automatically uses document prefix
• Desktop Embeddings: Run .tflite embedding models (EmbeddingGemma, Gecko) on macOS, Windows, Linux
  • LiteRT C API via dart:ffi — no gRPC, no JVM overhead
  • Pure Dart tokenizer via dart_sentencepiece_tokenizer (BPE + Unigram, auto-detect format)
  • LiteRT C library built from google-ai-edge/LiteRT v2.1.3
  • XNNPACK delegate with default options (QS8/QU8 quantization support)
  • Desktop scores match Android/Python exactly (cosine similarity 0.708)
  • CI workflow for building LiteRT C library on all 4 platform/arch combinations
• Unified VectorStore: Single Dart implementation using sqlite3 dart:ffi replacing platform-specific code

... (truncated)

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