llama_library_flutter 0.0.3

LLaMA Is Library for Inference of Meta's LLaMA model (and others)

Llama Library

Llama Library Is library for inference any model ai LLAMA / LLM On Edge without api or internet quota, but need resources depends model you want run

Copyright (c) 2024 GLOBAL CORPORATION - GENERAL DEVELOPER

📚️ Docs

1. Documentation
2. Youtube
3. Telegram Support Group
4. Contact Developer (check social media or readme profile github)

🔖️ Features

1. ✅ 📱️ Cross Platform support (Device, Edge Severless functions)
2. ✅ 📜️ Standarization Style Code
3. ✅ ⌨️ Cli (Terminal for help you use this library or create project)
4. ✅ 🔥️ Api (If you developer bot / userbot you can use this library without interact cli just add library and use 🚀️)
5. ✅ 🧩️ Customizable Extension (if you want add extension so you can more speed up on development)
6. ✅ ✨️ Pretty Information (user friendly for newbie)

❔️ Fun Fact

• This library 100% use on every my create project (App, Server, Bot, Userbot)

• This library 100% support all models from llama.cpp (depending on your device specs, if high then it can be up to turbo, but if low, just choose tiny/small)

⚠️ Important information

To get good AI results, it's a good idea to have hardware that supports AI, otherwise the results will be inappropriate/bad.

📈️ Proggres

• 10-02-2025 Starting Release Stable With core Features

Resources

1. MODEL

📥️ Install Library

1. Dart

dart pub add llama_library

2. Flutter

flutter pub add llama_library_flutter ggml_library_flutter

🚀️ Quick Start

Example Quickstart script minimal for insight you or make you use this library because very simple

import 'dart:convert';
import 'dart:io';
import 'package:llama_library/llama_library.dart';
import 'package:llama_library/scheme/scheme/api/api.dart';
import 'package:llama_library/scheme/scheme/respond/update_llama_library_message.dart';

void main(List<String> args) async {
  print("start");
  File modelFile = File(
    "../../../../../big-data/deepseek-r1/deepseek-r1-distill-qwen-1.5b-q4_0.gguf",
  );
  final LlamaLibrary llamaLibrary = LlamaLibrary(
    sharedLibraryPath: "libllama.so",
    invokeParametersLlamaLibraryDataOptions:
        InvokeParametersLlamaLibraryDataOptions(
      invokeTimeOut: Duration(minutes: 10),
      isThrowOnError: false,
    ),
  );
  await llamaLibrary.ensureInitialized();
  llamaLibrary.on(
    eventType: llamaLibrary.eventUpdate,
    onUpdate: (data) {
      final update = data.update;
      if (update is UpdateLlamaLibraryMessage) {
        /// streaming update
        if (update.is_done == false) {
          stdout.write(update.text);
        } else if (update.is_done == true) {
          print("\n\n");
          print("-- done --");
        }
      }
    },
  );
  await llamaLibrary.initialized();
  final res = await llamaLibrary.invoke(
    invokeParametersLlamaLibraryData: InvokeParametersLlamaLibraryData(
      parameters: LoadModelFromFileLlamaLibrary.create(
        model_file_path: modelFile.path,
      ),
      isVoid: false,
      extra: null,
      invokeParametersLlamaLibraryDataOptions: null,
    ),
  );
  if (res["@type"] == "ok") {
    print("succes load Model");
  } else {
    print("Failed load Model");
    exit(0);
  }
  stdin.listen((e) async {
    print("\n\n");
    final String text = utf8.decode(e).trim();
    if (text == "exit") {
      llamaLibrary.dispose();
      exit(0);
    } else {
      await llamaLibrary.invoke(
        invokeParametersLlamaLibraryData: InvokeParametersLlamaLibraryData(
          parameters: SendLlamaLibraryMessage.create(
            text: text,
            is_stream: false,
          ),
          isVoid: true,
          extra: null,
          invokeParametersLlamaLibraryDataOptions: null,
        ),
      );
    }
  });
}

Reference

1. Ggerganov-llama.cpp ffi bridge main script so that this program can run

Copyright (c) 2024 GLOBAL CORPORATION - GENERAL DEVELOPER

Example Project Use This Library

• Llama Application

Minimal simple application example of using whisper library Youtube Video

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