flutter-gemma-inference

flutter-gemma-inference is a Cross-platform mobile skill for AI agents, published by DenisovAV in the flutter_gemma repository on GitHub. Skillspace rates flutter-gemma-inference D (69/100) and it passed the safety scan; the rating is based on static analysis only.

Use when adding on-device LLM inference to a Flutter app with flutter_gemma — offline chat, running Gemma, Qwen or Phi locally, installing a model from Hugging Face (gated repos included), streaming replies, a system prompt, thinking or reasoning output, image or audio prompts, picking a CPU, GPU or NPU backend, stopping generation — or setting up the recommended .litertlm engine (ModelFileType.litertlm) on Android, iOS, macOS, Windows, Linux or web, including the Android minSdk and internet permission, the Apple entitlements and Podfile, and the web index.html script tags. Also use when a reply comes back empty, the model answers identically every time, maxTokens does not shorten replies, FlutterGemma is an undefined name, getActiveModel throws "No inference engine can handle this model", a session throws "Session is closed", or .litertlm fails to load on Android. For .task or .bin models (ModelFileType.task or ModelFileType.binary), use flutter-gemma-mediapipe.

Grade
D
Quality
69 / 100
Safety
Passed
GitHub stars
621

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubDenisovAV/flutter_gemma

Our review

Architecture
97 / 100
Maturity
Structured: ships references or scripts
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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