feat: create Amazon bundle (#7255)

* create Amazon bundle

* Update s3_bucket_uploader.py

* update FE tests

* [autofix.ci] apply automated fixes

* ✅ (dropdownComponent.spec.ts): update test selectors to match the updated component names for better test accuracy
✅ (keyPairListComponent.spec.ts): update test selectors to match the updated component names for better test accuracy

* Update filterEdge-shard-1.spec.ts

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: cristhianzl <cristhian.lousa@gmail.com>

src/backend/base/langflow/base/models/model_input_constants.py

@@ -1,7 +1,7 @@
 from typing_extensions import TypedDict
 
 from langflow.base.models.model import LCModelComponent
-from langflow.components.models.amazon_bedrock import AmazonBedrockComponent
+from langflow.components.amazon.amazon_bedrock_model import AmazonBedrockComponent
 from langflow.components.models.anthropic import AnthropicModelComponent
 from langflow.components.models.azure_openai import AzureChatOpenAIComponent
 from langflow.components.models.google_generative_ai import GoogleGenerativeAIComponent
@@ -140,7 +140,7 @@ def _get_nvidia_inputs_and_fields():
 
 def _get_amazon_bedrock_inputs_and_fields():
     try:
-        from langflow.components.models.amazon_bedrock import AmazonBedrockComponent
+        from langflow.components.amazon.amazon_bedrock_model import AmazonBedrockComponent
 
         amazon_bedrock_inputs = get_filtered_inputs(AmazonBedrockComponent)
     except ImportError as e:

src/backend/base/langflow/components/amazon/__init__.py

@@ -0,0 +1,5 @@
+from .amazon_bedrock_embedding import AmazonBedrockEmbeddingsComponent
+from .amazon_bedrock_model import AmazonBedrockComponent
+from .s3_bucket_uploader import S3BucketUploaderComponent
+
+__all__ = ["AmazonBedrockComponent", "AmazonBedrockEmbeddingsComponent", "S3BucketUploaderComponent"]

src/backend/base/langflow/components/amazon/s3_bucket_uploader.py

@@ -51,7 +51,7 @@ class S3BucketUploaderComponent(Component):
 
     display_name = "S3 Bucket Uploader"
     description = "Uploads files to S3 bucket."
-    icon = "Globe"
+    icon = "Amazon"
     name = "s3bucketuploader"
 
     inputs = [

src/backend/base/langflow/components/data/__init__.py

@@ -3,7 +3,6 @@ from .csv_to_data import CSVToDataComponent
 from .directory import DirectoryComponent
 from .file import FileComponent
 from .json_to_data import JSONToDataComponent
-from .s3_bucket_uploader import S3BucketUploaderComponent
 from .sql_executor import SQLExecutorComponent
 from .url import URLComponent
 from .webhook import WebhookComponent
@@ -14,7 +13,6 @@ __all__ = [
     "DirectoryComponent",
     "FileComponent",
     "JSONToDataComponent",
-    "S3BucketUploaderComponent",
     "SQLExecutorComponent",
     "URLComponent",
     "WebhookComponent",

src/backend/base/langflow/components/embeddings/__init__.py

@@ -1,5 +1,4 @@
 from .aiml import AIMLEmbeddingsComponent
-from .amazon_bedrock import AmazonBedrockEmbeddingsComponent
 from .astra_vectorize import AstraVectorizeComponent
 from .azure_openai import AzureOpenAIEmbeddingsComponent
 from .cloudflare import CloudflareWorkersAIEmbeddingsComponent
@@ -18,7 +17,6 @@ from .watsonx import WatsonxEmbeddingsComponent
 
 __all__ = [
     "AIMLEmbeddingsComponent",
-    "AmazonBedrockEmbeddingsComponent",
     "AstraVectorizeComponent",
     "AzureOpenAIEmbeddingsComponent",
     "CloudflareWorkersAIEmbeddingsComponent",

src/backend/base/langflow/components/models/__init__.py

@@ -1,5 +1,4 @@
 from .aiml import AIMLModelComponent
-from .amazon_bedrock import AmazonBedrockComponent
 from .anthropic import AnthropicModelComponent
 from .azure_openai import AzureChatOpenAIComponent
 from .baidu_qianfan_chat import QianfanChatEndpointComponent
@@ -25,7 +24,6 @@ from .xai import XAIModelComponent
 
 __all__ = [
     "AIMLModelComponent",
-    "AmazonBedrockComponent",
     "AnthropicModelComponent",
     "AzureChatOpenAIComponent",
     "ChatOllamaComponent",

src/backend/tests/unit/components/data/test_s3_uploader_component.py

@@ -5,7 +5,7 @@ from pathlib import Path
 
 import boto3
 import pytest
-from langflow.components.data.s3_bucket_uploader import S3BucketUploaderComponent
+from langflow.components.amazon.s3_bucket_uploader import S3BucketUploaderComponent
 from langflow.schema.data import Data
 
 from tests.base import ComponentTestBaseWithoutClient

src/frontend/src/utils/styleUtils.ts

@@ -567,6 +567,7 @@ export const SIDEBAR_CATEGORIES = [
 ];
 
 export const SIDEBAR_BUNDLES = [
+  { display_name: "Amazon", name: "amazon", icon: "Amazon" },
   { display_name: "Gmail", name: "gmail", icon: "Gmail" },
   // Add apify
   { display_name: "Apify", name: "apify", icon: "Apify" },

src/frontend/tests/core/unit/dropdownComponent.spec.ts

@@ -17,12 +17,12 @@ test(
     await page.getByTestId("sidebar-search-input").click();
     await page.getByTestId("sidebar-search-input").fill("amazon");
 
-    await page.waitForSelector('[data-testid="modelsAmazon Bedrock"]', {
+    await page.waitForSelector('[data-testid="amazonAmazon Bedrock"]', {
       timeout: 3000,
     });
 
     await page
-      .getByTestId("modelsAmazon Bedrock")
+      .getByTestId("amazonAmazon Bedrock")
       .first()
       .dragTo(page.locator('//*[@id="react-flow-id"]'));
     await page.mouse.up();

src/frontend/tests/core/unit/keyPairListComponent.spec.ts

@@ -15,12 +15,12 @@ test(
     await page.getByTestId("sidebar-search-input").click();
     await page.getByTestId("sidebar-search-input").fill("amazon bedrock");
 
-    await page.waitForSelector('[data-testid="modelsAmazon Bedrock"]', {
+    await page.waitForSelector('[data-testid="amazonAmazon Bedrock"]', {
       timeout: 3000,
     });
 
     await page
-      .getByTestId("modelsAmazon Bedrock")
+      .getByTestId("amazonAmazon Bedrock")
       .dragTo(page.locator('//*[@id="react-flow-id"]'));
 
     await adjustScreenView(page);

src/frontend/tests/extended/features/filterEdge-shard-1.spec.ts

@@ -71,7 +71,6 @@ test(
       "outputsChat Output",
       "dataAPI Request",
       "vectorstoresAstra DB",
-      "embeddingsAmazon Bedrock Embeddings",
       "langchain_utilitiesTool Calling Agent",
       "langchain_utilitiesConversationChain",
       "memoriesAstra DB Chat Memory",