Magemaker aws credentials testing

.dockerignore

@@ -0,0 +1,10 @@
+echo """
+venv/
+*.pyc
+__pycache__
+.git
+.env
+*.egg-info
+dist/
+build/
+""" > .dockerignore

.gitignore

@@ -204,5 +204,4 @@ cython_debug/
 models/
 configs/
 .pdm-python
-.magemaker_configs
 .env.save

Dockerfile-server

@@ -1,22 +1,55 @@
-# Use an official Python runtime as a parent image
-FROM python:3.12-slim
+FROM python:3.11-slim
 
-# Set environment variables
-ENV PYTHONDONTWRITEBYTECODE 1
-ENV PYTHONUNBUFFERED 1
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    curl \
+    build-essential \
+    unzip \
+    nano \
+    vim \
+    gnupg \
+    lsb-release \
+    ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
 
-# Set the working directory in the container
+# Set working directory
 WORKDIR /app
 
-# Copy the project files to the working directory
-COPY . .
+# Copy your magemaker package
+COPY . /app/
 
-# Install PDM and use it to install dependencies
-RUN pip install --no-cache-dir pdm \
-    && pdm install --no-interactive
+# Install package and dependencies
+RUN pip install --no-cache-dir -e .
 
-# Expose port 8000 to the outside world
-EXPOSE 8000
+# Install AWS CLI
+RUN curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip" \
+    && unzip awscliv2.zip \
+    && ./aws/install \
+    && rm awscliv2.zip \
+    && rm -rf aws
 
-# Run uvicorn when the container launches
-CMD ["pdm", "run", "uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8000"]
+# Install Google Cloud SDK
+RUN curl https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-cli-458.0.0-linux-x86_64.tar.gz -o google-cloud-sdk.tar.gz \
+    && tar -xf google-cloud-sdk.tar.gz \
+    && ./google-cloud-sdk/install.sh --quiet \
+    && rm google-cloud-sdk.tar.gz
+
+# Install Azure CLI
+RUN mkdir -p /etc/apt/keyrings && \
+    curl -sLS https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor | tee /etc/apt/keyrings/microsoft.gpg > /dev/null && \
+    chmod go+r /etc/apt/keyrings/microsoft.gpg && \
+    echo "deb [arch=`dpkg --print-architecture` signed-by=/etc/apt/keyrings/microsoft.gpg] https://packages.microsoft.com/repos/azure-cli/ $(lsb_release -cs) main" | tee /etc/apt/sources.list.d/azure-cli.list && \
+    apt-get update && \
+    apt-get install -y azure-cli && \
+    rm -rf /var/lib/apt/lists/*
+
+# Add Google Cloud SDK to PATH
+ENV PATH $PATH:/app/google-cloud-sdk/bin
+
+# Copy and setup entrypoint
+COPY magemaker/docker/entrypoint.sh /usr/local/bin/
+RUN chmod +x /usr/local/bin/entrypoint.sh
+
+ENTRYPOINT ["entrypoint.sh"]
+CMD ["bash"]

magemaker/docker/entrypoint.sh

@@ -0,0 +1,14 @@
+#!/bin/bash
+set -e
+
+# Setup AWS credentials if mounted
+if [ -f "/root/.aws/credentials" ]; then
+    export AWS_SHARED_CREDENTIALS_FILE="/root/.aws/credentials"
+fi
+
+# Setup GCP credentials if mounted
+if [ -f "/root/.config/gcloud/application_default_credentials.json" ]; then
+    export GOOGLE_APPLICATION_CREDENTIALS="/root/.config/gcloud/application_default_credentials.json"
+fi
+
+exec "$@"

magemaker/main.py

@@ -41,7 +41,10 @@ class Actions(StrEnum):
 # set AWS_REGION in env
 os.environ["AWS_REGION"] = "us-west-2"
 
-
+NC='\033[0m'
+YELLOW='\033[1;33m'
+GREEN='\033[0;32m'
+RED='\033[0;31m'
 
 
 def deploy_huggingface_model(deployment: Deployment, model: Model):
@@ -129,9 +132,15 @@ def query_endpoint(endpoint, query):
         if config:
             config = (config.deployment, config.models[0])
             make_query_request(name, query, config)
-
-        print('Config for this model not found, try another model')
+            return
 
+        else:
+            expected_path = os.path.join(os.getcwd(), 'configs', f"{name}.yml")
+            print(f"[red]Config for this model not found![/red]")
+            print(f"Expected config location: [green]{expected_path}[/green]")
+            print(f"[yellow]Please ensure config file exists before querying.[/yellow]")
+            return
+
     if provider == 'VertexAI':
         endpoint_id = resource_name.split('/')[-1] 
         query_vertexai_endpoint_rest(endpoint_id, query.query)

magemaker/runner.py

@@ -2,6 +2,7 @@
 import logging
 import sys
 import traceback
+from magemaker.schemas.query import Query
 from magemaker.version import VERSION
 import yaml
 logging.getLogger("sagemaker.config").setLevel(logging.WARNING)
@@ -12,7 +13,7 @@
 from magemaker.schemas.deployment import Deployment
 from magemaker.schemas.model import Model, ModelSource
 import subprocess
-from magemaker.main import main, deploy_model
+from magemaker.main import main, deploy_model, query_endpoint
 
 RED='\033[0;31m'  #red
 NC='\033[0m' # No Color
@@ -26,6 +27,10 @@ def runner():
     #     os.system("bash setup.sh")
     if '--version' not in sys.argv:
         print(f"{GREEN}magemaker v{VERSION}{NC}")
+
+    if os.path.exists('.env'):
+        from dotenv import load_dotenv
+        load_dotenv()
 
     parser = argparse.ArgumentParser(
         description="Create, deploy, query against models.",
@@ -70,6 +75,11 @@ def runner():
         choices=['aws', 'gcp', 'azure', 'all'], 
         help="Specify the cloud provider for configuration and deployment"
     )
+    parser.add_argument(
+        "--query",
+        help="path to YAML query configuration file",
+        type=str
+    )
     if len(sys.argv) == 1:
         # just for the case of magemaker
         # parser.print_help()
@@ -142,6 +152,38 @@ def runner():
 
         quit()
 
+    if args.query is not None:
+        try:
+            with open(args.query) as config:
+                configuration = yaml.safe_load(config)
+
+                # Extract deployment and model info
+                deployment = configuration.get('deployment')
+                model = configuration.get('models')[0]
+                query_text = configuration.get('query')
+
+                if not all([deployment, model, query_text]):
+                    print(f"[red]Error: Invalid query configuration. Required fields missing.[/red]")
+                    sys.exit(1)
+
+                endpoint = (
+                    deployment['endpoint_name'],  # name
+                    'Sagemaker' if deployment['destination'] == 'aws' else deployment['destination'],  # provider
+                    ''  # resource_name
+                )
+
+
+                query = Query(query=query_text)
+
+
+                query_endpoint(endpoint, query)
+                sys.exit(0)
+
+        except Exception as e:
+            print(f"[red]Error reading query configuration: {str(e)}[/red]")
+            sys.exit(1)
+
+
     main(args, loglevel)
 
 if __name__ == '__main__':
@@ -192,6 +234,11 @@ def runner():
         choices=['aws', 'gcp', 'azure'], 
         help="Specify the cloud provider for configuration and deployment"
     )
+    parser.add_argument(
+    "--query",
+    help="path to YAML query configuration file",
+    type=str
+    )
     args = parser.parse_args()
 
     cmd = ["bash", "scripts/preflight.sh"]

magemaker/sagemaker/create_model.py

@@ -1,4 +1,5 @@
 import json
+import os
 from dotenv import dotenv_values
 from rich.table import Table
 from sagemaker import image_uris, model_uris, script_uris
@@ -20,7 +21,9 @@
 from magemaker.huggingface import HuggingFaceTask
 from magemaker.huggingface.hf_hub_api import get_hf_task
 
-
+NC='\033[0m' # No Color
+YELLOW='\033[1;33m'
+GREEN='\033[0;32m'
 
 def deploy_huggingface_model_to_sagemaker(deployment, model):
     HUGGING_FACE_HUB_TOKEN = dotenv_values(".env").get("HUGGING_FACE_HUB_KEY")
@@ -93,6 +96,10 @@ def deploy_huggingface_model_to_sagemaker(deployment, model):
 
     print_success(
         f"{model.id} is now up and running at the endpoint [blue]{predictor.endpoint_name}")
+
+    config_path = os.path.join(os.getcwd(), 'configs', f"{predictor.endpoint_name}.yml")
+    print(f"\n{YELLOW}Important:{NC} Configuration saved at: {GREEN}{config_path}{NC}")
+    print(f"You'll need this path for querying the model later.")
 
     write_config(deployment, model)
     return predictor
@@ -215,4 +222,4 @@ def create_and_deploy_jumpstart_model(deployment: Deployment, model: Model):
     print_success(
         f"{model.id} is now up and running at the endpoint [blue]{predictor.endpoint_name}")
 
-    return predictor
+    return predictor

magemaker/sagemaker/delete_model.py

@@ -14,4 +14,4 @@ def delete_sagemaker_model(endpoint_names: List[str] = None):
     # Add validation / error handling
     for endpoint in endpoint_names:
         print(f"Deleting [blue]{endpoint}")
-        sagemaker_client.delete_endpoint(EndpointName=endpoint)
+        sagemaker_client.delete_endpoint(EndpointName=endpoint)

magemaker/sagemaker/fine_tune_model.py

@@ -116,4 +116,4 @@ def get_hyperparameters_for_model(training: Training, model: Model):
     if training.hyperparameters is not None:
         hyperparameters.update(
             (k, v) for k, v in training.hyperparameters.model_dump().items() if v is not None)
-    return hyperparameters
+    return hyperparameters

magemaker/sagemaker/query_endpoint.py

@@ -202,4 +202,4 @@ def test(endpoint_name: str):
     text2 = 'simply stupid , irrelevant and deeply , truly , bottomlessly cynical '
 
     for text in [text1, text2]:
-        query_sagemaker_endpoint(endpoint_name, text.encode('utf-8'))
+        query_sagemaker_endpoint(endpoint_name, text.encode('utf-8'))

magemaker/scripts/preflight.sh

@@ -25,43 +25,60 @@ log_error() {
 # Configuration functions
 configure_aws() {
 echo "Configuring AWS..."
-echo "you need to create an aws user with access to Sagemaker"
-echo "if you don't know how to do that follow this doc https://docs.google.com/document/d/1NvA6uZmppsYzaOdkcgNTRl7Nb4LbpP9Koc4H_t5xNSg/edit?usp=sharing"
-
-
-# green
-if ! command -v aws &> /dev/null
-then
-    OS="$(uname -s)"
-    case "${OS}" in
-        Linux*)     
-            curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
-            unzip awscliv2.zip
-            sudo ./aws/install
-            ;;
-        Darwin*)    
-            curl "https://awscli.amazonaws.com/AWSCLIV2.pkg" -o "AWSCLIV2.pkg"
-            sudo installer -pkg AWSCLIV2.pkg -target /
-            ;;
-        *)          
-            echo "Unsupported OS: ${OS}. See https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html"
-            exit 1
-            ;;
-    esac
-fi
+    if [ -f ".env" ] && grep -q "AWS_ACCESS_KEY_ID" ".env" && grep -q "AWS_SECRET_ACCESS_KEY" ".env"; then
+        echo -e "${GREEN}Using AWS credentials from .env file${NC}"
+        export $(grep "AWS_" .env | xargs)
+
+        aws configure set aws_access_key_id $AWS_ACCESS_KEY_ID
+        aws configure set aws_secret_access_key $AWS_SECRET_ACCESS_KEY
+        aws configure set default.region $AWS_DEFAULT_REGION
+
+    else
+        echo "you need to create an aws user with access to Sagemaker"
+        echo "if you don't know how to do that follow this guide https://magemaker.slashml.com/configuration/AWS"
+
+        if ! command -v aws &> /dev/null
+        then
+            OS="$(uname -s)"
+            case "${OS}" in
+                Linux*)     
+                    curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
+                    unzip awscliv2.zip
+                    sudo ./aws/install
+                    ;;
+                Darwin*)    
+                    curl "https://awscli.amazonaws.com/AWSCLIV2.pkg" -o "AWSCLIV2.pkg"
+                    sudo installer -pkg AWSCLIV2.pkg -target /
+                    ;;
+                *)          
+                    echo "Unsupported OS: ${OS}. See https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html"
+                    exit 1
+                    ;;
+            esac
+        fi
 
 # echo green that press enter if you have already done this
-echo -e "${GREEN}Press enter in the following configuration steps if you have already done this${NC}"
+        echo -e "${GREEN}Press enter in the following configuration steps if you have already done this${NC}"
 
-aws configure set region us-east-1 && aws configure
-touch .env
+        read -p "AWS Access Key ID: " aws_access_key_id
+        read -p "AWS Secret Access Key: " aws_secret_access_key
+        read -p "Default region name: " aws_region
 
+        echo "AWS_ACCESS_KEY_ID=$aws_access_key_id" >> .env
+        echo "AWS_SECRET_ACCESS_KEY=$aws_secret_access_key" >> .env
+        echo "AWS_DEFAULT_REGION=$aws_region" >> .env
+        echo -e "${GREEN}AWS credentials saved to .env file${NC}"
 
-if ! grep -q "SAGEMAKER_ROLE" .env
-then
+        aws configure set aws_access_key_id $aws_access_key_id
+        aws configure set aws_secret_access_key $aws_secret_access_key
+        aws configure set default.region $aws_region
+    fi
+
+    if ! grep -q "SAGEMAKER_ROLE" .env
+    then
     # bash ./setup_role.sh
-    bash "$SCRIPT_DIR/setup_role.sh"
-fi
+        bash "$SCRIPT_DIR/setup_role.sh"
+    fi
 }
 
 
@@ -70,7 +87,7 @@ fi
 configure_gcp() {
     echo "Configuring GCP..."
 echo "you need to create a GCP service account with access to GCS and vertex ai"
-echo "if you don't know how to do that follow this doc https://docs.google.com/document/d/1NvA6uZmppsYzaOdkcgNTRl7Nb4LbpP9Koc4H_t5xNSg/edit?usp=sharing"
+echo "if you don't know how to do that follow this doc https://magemaker.slashml.com/configuration/GCP"
 
 if ! command -v gcloud &> /dev/null
 then
@@ -153,6 +170,8 @@ fi
 # AZURE
 configure_azure() {
 echo "Configuring Azure..."
+echo "you need to create a Azure service account"
+echo "if you don't know how to do that follow this doc https://magemaker.slashml.com/configuration/Azure"
 echo "Checking for Azure CLI installation..."
 if ! command -v az &> /dev/null
 then