clean deps

Author: pirocheto

pyproject.toml

@@ -1,21 +1,10 @@
 [project]
-name = "aws-hf-model-deployment"
+name = "aws-sagemaker-hf-model-deployment"
 version = "0.1.0"
-description = "Add your description here"
+description = "AWS SageMaker Hugging Face Model Deployment"
 readme = "README.md"
 requires-python = ">=3.12"
-dependencies = [
-    "huggingface-hub[cli]>=0.27.1",
-    "humanize>=4.11.0",
-    "transformers[torch]>=4.48.0",
-]
-
-[dependency-groups]
-dev = [
-    "boto3>=1.35.97",
-    "pytest>=8.3.4",
-    "sagemaker-huggingface-inference-toolkit>=2.4.1",
-]
+dependencies = ["boto3>=1.35.97"]
 
 [tool.mypy]
 disallow_untyped_calls = true

test_endpoint.py

@@ -3,7 +3,7 @@
 import boto3
 
 AWS_REGION = "us-east-1"
-ENDPOINT_NAME = "dev-multilingual-sentiment-analysis-endpoint"
+ENDPOINT_NAME = "test-multilingual-sentiment-analysis-endpoint"
 
 sagemaker_runtime = boto3.client("sagemaker-runtime", region_name=AWS_REGION)
 
@@ -89,9 +89,13 @@
 response = sagemaker_runtime.invoke_endpoint(
     EndpointName=ENDPOINT_NAME,
     ContentType="application/json",
-    Body=json.dumps(texts),
+    Body=json.dumps({"inputs": texts}),
 )
 
 
-result = json.loads(response["Body"].read().decode())
-print("Predicted sentiment:", result)
+result = json.loads(response["Body"].read())
+
+for text, sentiment in zip(texts, result):
+    print(f"Text: {text}")
+    print(f"Sentiment: {sentiment}")
+    print()