some changes

zmhu · Dec 15, 2023 · c03a168 · c03a168
1 parent 906c7df
commit c03a168
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Showing 9 changed files with 141 additions and 134 deletions.
diff --git a/.gitignore b/.gitignore
@@ -28,4 +28,3 @@ migrate_working_dir/
 .dart_tool/
 .packages
 build/
-/test/env.dart
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,3 @@
-## 0.0.1
+## 0.0.1-dev-1
 
-* TODO: Describe initial release.
+* first publish
diff --git a/lib/flutter_gemini.dart b/lib/flutter_gemini.dart
@@ -1,3 +1,7 @@
 library flutter_gemini;
 
 export 'src/init.dart';
+export 'src/models/gemini_response/gemini_response.dart';
+export 'src/models/gemini_safety/gemini_safety.dart';
+export 'src/models/gemini_safety/gemini_safety_category.dart';
+export 'src/models/gemini_safety/gemini_safety_threshold.dart';
diff --git a/lib/src/config/constants.dart b/lib/src/config/constants.dart
@@ -8,110 +8,114 @@ class Constants {
       'https://generativelanguage.googleapis.com/v1beta/';
 
   static List<GeminiModel> get geminiDefaultModels => [
-    {
-      "name": "models/chat-bison-001",
-      "version": "001",
-      "displayName": "Chat Bison",
-      "description": "Chat-optimized generative language model.",
-      "inputTokenLimit": 4096,
-      "outputTokenLimit": 1024,
-      "supportedGenerationMethods": ["generateMessage", "countMessageTokens"],
-      "temperature": 0.25,
-      "topP": 0.95,
-      "topK": 40
-    },
-    {
-      "name": "models/text-bison-001",
-      "version": "001",
-      "displayName": "Text Bison",
-      "description": "Model targeted for text generation.",
-      "inputTokenLimit": 8196,
-      "outputTokenLimit": 1024,
-      "supportedGenerationMethods": [
-        "generateText",
-        "countTextTokens",
-        "createTunedTextModel"
-      ],
-      "temperature": 0.7,
-      "topP": 0.95,
-      "topK": 40
-    },
-    {
-      "name": "models/embedding-gecko-001",
-      "version": "001",
-      "displayName": "Embedding Gecko",
-      "description": "Obtain a distributed representation of a text.",
-      "inputTokenLimit": 1024,
-      "outputTokenLimit": 1,
-      "supportedGenerationMethods": ["embedText", "countTextTokens"]
-    },
-    {
-      "name": "models/embedding-gecko-002",
-      "version": "002",
-      "displayName": "Embedding Gecko 002",
-      "description": "Obtain a distributed representation of a text.",
-      "inputTokenLimit": 2048,
-      "outputTokenLimit": 1,
-      "supportedGenerationMethods": ["embedText", "countTextTokens"]
-    },
-    {
-      "name": "models/gemini-pro",
-      "version": "001",
-      "displayName": "Gemini Pro",
-      "description": "The best model for scaling across a wide range of tasks",
-      "inputTokenLimit": 30720,
-      "outputTokenLimit": 2048,
-      "supportedGenerationMethods": ["generateContent", "countTokens"],
-      "temperature": 0.9,
-      "topP": 1,
-      "topK": 1
-    },
-    {
-      "name": "models/gemini-pro-vision",
-      "version": "001",
-      "displayName": "Gemini Pro Vision",
-      "description":
-          "The best image understanding model to handle a broad range of applications",
-      "inputTokenLimit": 12288,
-      "outputTokenLimit": 4096,
-      "supportedGenerationMethods": ["generateContent", "countTokens"],
-      "temperature": 0.4,
-      "topP": 1,
-      "topK": 32
-    },
-    {
-      "name": "models/gemini-ultra",
-      "version": "001",
-      "displayName": "Gemini Ultra",
-      "description": "The most capable model for highly complex tasks",
-      "inputTokenLimit": 30720,
-      "outputTokenLimit": 2048,
-      "supportedGenerationMethods": ["generateContent", "countTokens"],
-      "temperature": 0.9,
-      "topP": 1,
-      "topK": 32
-    },
-    {
-      "name": "models/embedding-001",
-      "version": "001",
-      "displayName": "Embedding 001",
-      "description": "Obtain a distributed representation of a text.",
-      "inputTokenLimit": 2048,
-      "outputTokenLimit": 1,
-      "supportedGenerationMethods": ["embedContent", "countTextTokens"]
-    },
-    {
-      "name": "models/aqa",
-      "version": "001",
-      "displayName": "Model that performs Attributed Question Answering.",
-      "description":
-          "Model trained to return answers to questions that are grounded in provided sources, along with estimating answerable probability.",
-      "inputTokenLimit": 7168,
-      "outputTokenLimit": 1024,
-      "supportedGenerationMethods": ["generateAnswer"],
-      "temperature": 0.2,
-      "topP": 1,
-      "topK": 40
-    }
-  ].map((e) => GeminiModel.fromJson(e)).toList();
+        {
+          "name": "models/chat-bison-001",
+          "version": "001",
+          "displayName": "Chat Bison",
+          "description": "Chat-optimized generative language model.",
+          "inputTokenLimit": 4096,
+          "outputTokenLimit": 1024,
+          "supportedGenerationMethods": [
+            "generateMessage",
+            "countMessageTokens"
+          ],
+          "temperature": 0.25,
+          "topP": 0.95,
+          "topK": 40
+        },
+        {
+          "name": "models/text-bison-001",
+          "version": "001",
+          "displayName": "Text Bison",
+          "description": "Model targeted for text generation.",
+          "inputTokenLimit": 8196,
+          "outputTokenLimit": 1024,
+          "supportedGenerationMethods": [
+            "generateText",
+            "countTextTokens",
+            "createTunedTextModel"
+          ],
+          "temperature": 0.7,
+          "topP": 0.95,
+          "topK": 40
+        },
+        {
+          "name": "models/embedding-gecko-001",
+          "version": "001",
+          "displayName": "Embedding Gecko",
+          "description": "Obtain a distributed representation of a text.",
+          "inputTokenLimit": 1024,
+          "outputTokenLimit": 1,
+          "supportedGenerationMethods": ["embedText", "countTextTokens"]
+        },
+        {
+          "name": "models/embedding-gecko-002",
+          "version": "002",
+          "displayName": "Embedding Gecko 002",
+          "description": "Obtain a distributed representation of a text.",
+          "inputTokenLimit": 2048,
+          "outputTokenLimit": 1,
+          "supportedGenerationMethods": ["embedText", "countTextTokens"]
+        },
+        {
+          "name": "models/gemini-pro",
+          "version": "001",
+          "displayName": "Gemini Pro",
+          "description":
+              "The best model for scaling across a wide range of tasks",
+          "inputTokenLimit": 30720,
+          "outputTokenLimit": 2048,
+          "supportedGenerationMethods": ["generateContent", "countTokens"],
+          "temperature": 0.9,
+          "topP": 1,
+          "topK": 1
+        },
+        {
+          "name": "models/gemini-pro-vision",
+          "version": "001",
+          "displayName": "Gemini Pro Vision",
+          "description":
+              "The best image understanding model to handle a broad range of applications",
+          "inputTokenLimit": 12288,
+          "outputTokenLimit": 4096,
+          "supportedGenerationMethods": ["generateContent", "countTokens"],
+          "temperature": 0.4,
+          "topP": 1,
+          "topK": 32
+        },
+        {
+          "name": "models/gemini-ultra",
+          "version": "001",
+          "displayName": "Gemini Ultra",
+          "description": "The most capable model for highly complex tasks",
+          "inputTokenLimit": 30720,
+          "outputTokenLimit": 2048,
+          "supportedGenerationMethods": ["generateContent", "countTokens"],
+          "temperature": 0.9,
+          "topP": 1,
+          "topK": 32
+        },
+        {
+          "name": "models/embedding-001",
+          "version": "001",
+          "displayName": "Embedding 001",
+          "description": "Obtain a distributed representation of a text.",
+          "inputTokenLimit": 2048,
+          "outputTokenLimit": 1,
+          "supportedGenerationMethods": ["embedContent", "countTextTokens"]
+        },
+        {
+          "name": "models/aqa",
+          "version": "001",
+          "displayName": "Model that performs Attributed Question Answering.",
+          "description":
+              "Model trained to return answers to questions that are grounded in provided sources, along with estimating answerable probability.",
+          "inputTokenLimit": 7168,
+          "outputTokenLimit": 1024,
+          "supportedGenerationMethods": ["generateAnswer"],
+          "temperature": 0.2,
+          "topP": 1,
+          "topK": 40
+        }
+      ].map((e) => GeminiModel.fromJson(e)).toList();
 }
diff --git a/lib/src/implement/gemini_service.dart b/lib/src/implement/gemini_service.dart
@@ -10,8 +10,8 @@ class GeminiService {
   final Dio dio;
   final String apiKey;
 
-  GeminiService(this.dio, {required this.apiKey}){
-    if(!kReleaseMode && Gemini.enableDebugging){
+  GeminiService(this.dio, {required this.apiKey}) {
+    if (!kReleaseMode && Gemini.enableDebugging) {
       dio.interceptors
           .add(LogInterceptor(requestBody: true, responseBody: true));
     }
@@ -22,7 +22,7 @@ class GeminiService {
 
   Future<Response> post(
     String route, {
-       required Map<String, Object>? data,
+    required Map<String, Object>? data,
     GenerationConfig? generationConfig,
     List<SafetySetting>? safetySettings,
   }) async {

diff --git a/lib/src/init.dart b/lib/src/init.dart
@@ -1,21 +1,17 @@
 import 'dart:async';
 import 'dart:typed_data';
 import 'package:flutter_gemini/src/models/candidates/candidates.dart';
-
 import 'config/constants.dart';
 import 'implement/gemini_service.dart';
 import 'models/embedding/embedding_input_type.dart';
 import 'models/gemini_model/gemini_model.dart';
-import 'models/gemini_response/gemini_response.dart';
 import 'models/generation_config/generation_config.dart';
 import 'repository/gemini_interface.dart';
 import 'package:dio/dio.dart';
-
 import 'implement/gemini_implement.dart';
 import 'models/gemini_safety/gemini_safety.dart';
 
 class Gemini implements GeminiInterface {
-
   /// to see request progress
   static bool enableDebugging = false;
 
@@ -41,13 +37,12 @@ class Gemini implements GeminiInterface {
   GeminiImpl _impl;
 
   /// singleton initialize
-  factory Gemini.init({
-    required String apiKey,
-    List<SafetySetting>? safetySettings,
-    GenerationConfig? generationConfig,
-    bool? enableDebugging
-  }) {
-    if(enableDebugging != null){
+  factory Gemini.init(
+      {required String apiKey,
+      List<SafetySetting>? safetySettings,
+      GenerationConfig? generationConfig,
+      bool? enableDebugging}) {
+    if (enableDebugging != null) {
       Gemini.enableDebugging = enableDebugging;
     }
     if (_firstInit) {

diff --git a/lib/src/repository/gemini_interface.dart b/lib/src/repository/gemini_interface.dart
@@ -1,11 +1,8 @@
 import 'dart:async';
 import 'dart:typed_data';
-
 import 'package:flutter_gemini/src/models/candidates/candidates.dart';
-
 import '../models/embedding/embedding_input_type.dart';
 import '../models/gemini_model/gemini_model.dart';
-import '../models/gemini_response/gemini_response.dart';
 import '../models/gemini_safety/gemini_safety.dart';
 import '../models/generation_config/generation_config.dart';
 

diff --git a/pubspec.yaml b/pubspec.yaml
@@ -1,7 +1,13 @@
 name: flutter_gemini
-description: Flutter Google Gemini SDK
-version: 0.0.1
-homepage:
+description: Flutter Google Gemini SDK. Google Gemini is a set of cutting-edge large language models 
+  (LLMs) designed to be the driving force behind Google's future AI initiatives.
+version: 0.0.1-dev-1
+homepage: https://github.com/babakcode/flutter_gemini
+topics:
+  - gemini
+  - ai
+  - google-gemini
+  - flutter-gemini
 
 environment:
   sdk: '>=3.1.3 <4.0.0'

diff --git a/test/flutter_gemini_test.dart b/test/flutter_gemini_test.dart
@@ -1,15 +1,17 @@
+import 'dart:developer';
+
 import 'package:flutter_test/flutter_test.dart';
 import 'package:flutter_gemini/flutter_gemini.dart';
-import 'env.dart' as env;
 
 void main() {
-  Gemini.init(apiKey: env.geminiKey, enableDebugging: true);
+  Gemini.init(apiKey: '--- Your Gemini Api Key ---', enableDebugging: true);
 
   test('check gemini to generate simple text', () async {
     final gemini = Gemini.instance;
 
-    gemini.textInput("Write a story about a magic backpack.")
-        .then((value) => value?.content?.parts?.last.text)
-        .catchError((e) => print(e));
+    gemini
+        .textInput("Write a story about a magic backpack.")
+        .then((value) => log(value?.content?.parts?.last.text ?? ''))
+        .catchError((e) => log('text input exception', error: e));
   });
 }