feat: Add streaming support to googleai_dart client (#299)

Co-authored-by: David Miguel <me@davidmiguel.com>

packages/googleai_dart/README.md

@@ -15,12 +15,9 @@ Unofficial Dart client for [Google AI](https://ai.google.dev) for Developers (Ge
 - Custom base URL, headers and query params support (e.g. HTTP proxies)
 - Custom HTTP client support (e.g. SOCKS5 proxies or advanced use cases)
 
-> [!NOTE]
-> Streaming support coming soon.
-
 **Supported endpoints:**
 
-- Generate content
+- Generate content (with streaming support)
 - Count tokens
 - Embed content
 - Models info
@@ -35,6 +32,7 @@ Unofficial Dart client for [Google AI](https://ai.google.dev) for Developers (Ge
     + [Text-only input](#text-only-input)
     + [Text-and-image input](#text-and-image-input)
     + [Multi-turn conversations (chat)](#multi-turn-conversations-chat)
+    + [Streaming generated content](#streaming-generated-content)
   * [Count tokens](#count-tokens)
   * [Embedding](#embedding)
   * [Model info](#model-info)
@@ -167,6 +165,33 @@ print(res.candidates?.first.content?.parts?.first.text);
 // In the heart of a tranquil village nestled amidst the rolling hills of 17th century France...
 ```
 
+#### Streaming generated content
+
+By default, `generateContent` returns a response after completing the entire generation process. You can achieve faster interactions by not waiting for the entire result, and instead use `streamGenerateContent` to handle partial results as they become available.
+
+```dart
+final stream = await client.streamGenerateContent(
+  modelId: 'gemini-pro',
+  request: const GenerateContentRequest(
+    contents: [
+      Content(
+        parts: [
+          Part(text: 'Write a story about a magic backpack.'),
+        ],
+      ),
+    ],
+    generationConfig: GenerationConfig(
+      temperature: 0.8,
+    ),
+  ),
+);
+
+stream.listen((final res) P
+  print(res.candidates?.first.content?.parts?.first.text);
+  // In a quaint little town nestled amidst rolling hills, there lived a...
+)
+```
+
 ### Count tokens
 
 When using long prompts, it might be useful to count tokens before sending any content to the model.

packages/googleai_dart/example/googleai_dart_example.dart

@@ -1,4 +1,5 @@
 // ignore_for_file: avoid_print, avoid_redundant_argument_values
+import 'dart:async';
 import 'dart:convert';
 import 'dart:io';
 
@@ -14,6 +15,9 @@ Future<void> main() async {
   await _generateContentTextAndImageInput(client);
   await _generateContentMultiTurnConversations(client);
 
+  // Stream generate content
+  await _streamGenerateContentTextInput(client);
+
   // Count tokens
   await _countTokens(client);
 
@@ -114,6 +118,31 @@ Future<void> _generateContentMultiTurnConversations(
   // In the heart of a tranquil village nestled amidst the rolling hills of 17th century France...
 }
 
+Future<void> _streamGenerateContentTextInput(
+  final GoogleAIClient client,
+) async {
+  final stream = client.streamGenerateContent(
+    modelId: 'gemini-pro',
+    request: const GenerateContentRequest(
+      contents: [
+        Content(
+          parts: [
+            Part(text: 'Write a story about a magic backpack.'),
+          ],
+        ),
+      ],
+      generationConfig: GenerationConfig(
+        temperature: 0.8,
+      ),
+    ),
+  );
+
+  await for (final res in stream) {
+    print(res.candidates?.first.content?.parts?.first.text);
+    // In a quaint little town nestled amidst rolling hills, there lived a...
+  }
+}
+
 Future<void> _countTokens(final GoogleAIClient client) async {
   final res = await client.countTokens(
     modelId: 'gemini-pro',

packages/googleai_dart/lib/src/client.dart

@@ -1,7 +1,11 @@
 // ignore_for_file: use_super_parameters
+import 'dart:async';
+import 'dart:convert';
+
 import 'package:http/http.dart' as http;
 
 import 'generated/client.dart' as g;
+import 'generated/schema/schema.dart';
 import 'http_client/http_client.dart';
 
 /// Client for Google AI API (Gemini API).
@@ -39,8 +43,54 @@ class GoogleAIClient extends g.GoogleAIClient {
           client: client ?? createDefaultHttpClient(),
         );
 
+  // ------------------------------------------
+  // METHOD: streamGenerateContent
+  // ------------------------------------------
+
+  /// Generates a streamed response from the model given an input `GenerateContentRequest`.
+  ///
+  /// `modelId`: The id of the model to use.
+  ///
+  /// `request`: Request to generate a completion from the model.
+  ///
+  /// `POST` `https://generativelanguage.googleapis.com/v1/models/{modelId}:streamGenerateContent`
+  Stream<GenerateContentResponse> streamGenerateContent({
+    final String modelId = 'gemini-pro',
+    final GenerateContentRequest? request,
+  }) async* {
+    final streamedResponse = await makeRequestStream(
+      baseUrl: 'https://generativelanguage.googleapis.com/v1',
+      queryParams: {
+        'alt': 'sse',
+      },
+      path: '/models/$modelId:streamGenerateContent',
+      method: g.HttpMethod.post,
+      requestType: 'application/json',
+      responseType: 'application/json',
+      body: request,
+    );
+
+    yield* streamedResponse.stream
+        .transform(const _GoogleAIStreamTransformer())
+        .map((final d) => GenerateContentResponse.fromJson(json.decode(d)));
+  }
+
   @override
   Future<http.BaseRequest> onRequest(final http.BaseRequest request) {
     return onRequestHandler(request);
   }
 }
+
+class _GoogleAIStreamTransformer
+    extends StreamTransformerBase<List<int>, String> {
+  const _GoogleAIStreamTransformer();
+
+  @override
+  Stream<String> bind(final Stream<List<int>> stream) {
+    return stream
+        .transform(utf8.decoder)
+        .transform(const LineSplitter())
+        .where((final s) => s.isNotEmpty)
+        .map((final s) => s.substring(6));
+  }
+}

packages/googleai_dart/lib/src/generated/client.dart

@@ -583,33 +583,6 @@ class GoogleAIClient {
     return BatchEmbedContentsResponse.fromJson(_jsonDecode(r));
   }
 
-  // ------------------------------------------
-  // METHOD: streamGenerateContent
-  // ------------------------------------------
-
-  /// Generates a streamed response from the model given an input `GenerateContentRequest`.
-  ///
-  /// `modelId`: The id of the model to use.
-  ///
-  /// `request`: Request to generate a completion from the model.
-  ///
-  /// `POST` `https://generativelanguage.googleapis.com/v1/models/{modelId}:streamGenerateContent`
-  Future<GenerateContentResponse> streamGenerateContent({
-    String modelId = 'gemini-pro',
-    GenerateContentRequest? request,
-  }) async {
-    final r = await makeRequest(
-      baseUrl: 'https://generativelanguage.googleapis.com/v1',
-      path: '/models/$modelId:streamGenerateContent',
-      method: HttpMethod.post,
-      isMultipart: false,
-      requestType: 'application/json',
-      responseType: 'application/json',
-      body: request,
-    );
-    return GenerateContentResponse.fromJson(_jsonDecode(r));
-  }
-
   // ------------------------------------------
   // METHOD: embedContent
   // ------------------------------------------

packages/googleai_dart/oas/googleai_openapi_curated.yaml

@@ -1020,33 +1020,6 @@ paths:
           schema:
             type: string
             default: embedding-001
-  /models/{modelId}:streamGenerateContent:
-    post:
-      description: >-
-        Generates a streamed response from the model given an input
-        `GenerateContentRequest`.
-      operationId: streamGenerateContent
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/GenerateContentRequest'
-      security: [ ]
-      responses:
-        '200':
-          description: Successful response
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/GenerateContentResponse'
-      parameters:
-        - in: path
-          name: modelId
-          description: The id of the model to use.
-          required: false
-          schema:
-            type: string
-            default: gemini-pro
   /models/{modelId}:embedContent:
     post:
       description: Generates an embedding from the model given an input `Content`.

packages/googleai_dart/test/count_tokens_test.dart

@@ -1,4 +1,3 @@
-// ignore_for_file: avoid_redundant_argument_values
 @TestOn('vm')
 library; // Uses dart:io
 

packages/googleai_dart/test/embed_content_test.dart

@@ -1,4 +1,3 @@
-// ignore_for_file: avoid_redundant_argument_values
 @TestOn('vm')
 library; // Uses dart:io
 

packages/googleai_dart/test/generate_content_test.dart

@@ -1,4 +1,3 @@
-// ignore_for_file: avoid_redundant_argument_values
 @TestOn('vm')
 library; // Uses dart:io
 

packages/googleai_dart/test/model_info_test.dart

@@ -1,4 +1,3 @@
-// ignore_for_file: avoid_redundant_argument_values
 @TestOn('vm')
 library; // Uses dart:io