Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: Test
-emoji: 🏆
-colorFrom: indigo
-colorTo: red
+title: test
+app_file: app.py
 sdk: gradio
 sdk_version: 3.46.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

TomWalker-ScriptAI.py

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+import boto3
+import paramiko
+import time
+#ssh -i "my_kayname_01.pem" root@ec2-54-90-175-47.compute-1.amazonaws.com
+# Replace these values with your actual values
+access_key = "AKIAYIBNUHKTYGACURPX"
+secret_key = "q8uXKrUQZx50zyIrPCUrnH/zvXNqv6QaR20O3Gaz"
+region = "us-east-1"
+image_id = "ami-088f3457fef51ee50"
+instance_type = "r5.large"           # Instance type with 32GB RAM
+key_name = "my_kayname_01"      # Replace with your key pair name
+security_group_ids = ["sg-0452fd39f8266308d"]
+
+def create_instance():
+    global access_key
+    global secret_key
+    global region
+    global image_id
+    global key_name
+    global security_group_ids
+
+    # Create a Boto3 EC2 client
+    ec2 = boto3.client("ec2", aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=region)
+
+    # Launch an EC2 instance
+    response = ec2.run_instances(
+        ImageId=image_id,
+        InstanceType=instance_type,
+        KeyName=key_name,
+        MinCount=1,
+        MaxCount=1,
+        SecurityGroupIds=security_group_ids  # Set the security group IDs here
+    )
+
+    instance = response["Instances"][0]
+
+    instance_id = response["Instances"][0]["InstanceId"]
+
+    print("Instance created:", instance_id)
+
+    response = ec2.describe_instances(InstanceIds=[instance_id])
+
+    # Extract the public IP address from the response
+    instance = response["Reservations"][0]["Instances"][0]
+    public_ip = instance.get("PublicIpAddress")
+
+    print(f"Instance created with IP: {public_ip}")
+    
+    while True:
+        # Describe the status of the EC2 instance
+        response = ec2.describe_instance_status(InstanceIds=[instance_id])
+
+        # Extract system status and instance status details if available
+        if "InstanceStatuses" in response and len(response["InstanceStatuses"]) > 0:
+            instance_status = response["InstanceStatuses"][0]
+            system_status = response["InstanceStatuses"][0].get("SystemStatus", {})
+            instance_status_value = instance_status['InstanceStatus']['Status']
+            system_status_value = system_status.get('Status', 'N/A')
+            print(f"Instance Status: {instance_status_value}")
+            print(f"System Status: {system_status_value}")
+
+            if instance_status_value == "ok" and system_status_value == "ok":
+                break
+
+            time.sleep(10)
+        else:
+            print("Status checks not available for the instance.")
+
+    return instance_id, public_ip
+
+def delete_instance(instance_id):
+    global access_key
+    global secret_key
+    global region
+
+    # Create a Boto3 EC2 client
+    ec2 = boto3.client("ec2", aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=region)
+
+    # Terminate the EC2 instance
+    response = ec2.terminate_instances(InstanceIds=[instance_id])
+
+    # Print the response
+    print("Instance termination response:", response)
+
+def ssh_connect(hostname):
+    #paramiko.util.log_to_file('paramiko.log')
+    #paramiko.common.logging.basicConfig(level=paramiko.common.DEBUG)
+    # Replace these values with your actual ones
+    port = 22
+    username = "ec2-user"
+    #username = "ubuntu"
+    #username = "root"
+    
+    key_filename = "my_kayname_01.pem"  # Path to your private key file
+
+    # Create an SSH client instance
+    ssh_client = paramiko.SSHClient()
+
+    # Automatically add the server's host key (this is insecure and not recommended for production)
+    ssh_client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
+    
+    try:
+        # Connect to the EC2 instance
+        ssh_client.connect(hostname, port, username, key_filename=key_filename)
+
+        
+        # Execute a command on the remote instance (e.g., list directory contents)
+        stdin, stdout, stderr = ssh_client.exec_command("ls -l")
+
+        # Print the output of the command
+        print(stdout.read().decode("utf-8"))
+
+        # Install Jupyter Notebook using pip
+        install_command = "pip install jupyter"
+        stdin, stdout, stderr = ssh_client.exec_command(install_command)
+        print(stdout.read().decode("utf-8"))
+
+        # Start the Jupyter Notebook server (you can specify your desired options)
+        jupyter_command = "jupyter notebook --ip=0.0.0.0 --port=8888 --no-browser"
+        ssh_client.exec_command(jupyter_command)
+
+        print("Jupyter Notebook installed and server started.")
+        
+        # Start the Jupyter Notebook server (you can specify your desired options)
+        jupyter_command = "jupyter server list"
+        while True:
+            stdin, stdout, stderr = ssh_client.exec_command(jupyter_command)
+            stdout_value = stdout.read().decode("utf-8")
+
+            if stdout_value.find("http:") != -1:
+                break
+            
+            time.sleep(3)
+
+        print(stdout_value)
+        
+        p = stdout_value.find("http:")
+        if p != -1:
+            temp = stdout_value[p:]
+            p = temp.find("?token")
+            if p != -1:
+                temp = temp[p + 7:]
+                p = temp.find(" :: ")
+                token_value = temp[: p]
+                print("token=", token_value)
+
+        # Close the SSH connection
+        ssh_client.close()
+
+    except Exception as e:
+        print(f"Error: {e}")
+    
+
+
+if __name__ == "__main__":
+
+    instance_id, public_ip = create_instance()
+    
+    ssh_connect(public_ip)
+    #ssh_connect("44.210.108.226")
+
+    #delete_instance(instance_id)

app.py

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+import os
+import boto3
+import sagemaker
+from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
+import gradio as gr
+
+predictor = None
+
+def deploy_and_get_interface(hf_model_url):
+    global predictor
+
+    os.system("pip install awscli boto3 sagemaker gradio")
+
+    os.system("aws configure set aws_access_key_id AKIAYIBNUHKT6GS5HZ6V")
+    os.system("aws configure set aws_secret_access_key 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")
+    os.system("aws configure set default.region us-east-1")
+    os.system("aws configure set default.output json")
+
+    try:
+        role = sagemaker.get_execution_role()
+    except ValueError:
+        iam = boto3.client('iam')
+        role = iam.get_role(RoleName='Moh-work')['Role']['Arn']
+
+    hf_model_id = hf_model_url.split('/')[-2]
+
+    hub = {
+        'HF_MODEL_ID': hf_model_id,
+        'SM_NUM_GPUS': '1'
+    }
+
+    huggingface_model = HuggingFaceModel(
+        image_uri=get_huggingface_llm_image_uri("huggingface", version="1.0.3"),
+        env=hub,
+        role=role
+    )
+
+    predictor = huggingface_model.deploy(
+        initial_instance_count=1,
+        instance_type="ml.g5.2xlarge",
+        container_startup_health_check_timeout=300,
+    )
+
+    def get_prediction(input_text):
+        response = predictor.predict({"inputs": input_text})
+        return response[0]['generated_text']
+
+    iface = gr.Interface(fn=get_prediction, 
+                         inputs="text", 
+                         outputs="text",
+                        
+                         title="HuggingFace Model Predictor",
+                         description="Enter some text and get the model's prediction!")
+
+    return iface
+
+def get_prediction(input_text):
+    response = predictor.predict({"inputs": input_text})
+    return response[0]['generated_text']
+
+def trigger_deploy(hf_model_url):
+    deploy_and_get_interface(hf_model_url)
+    iface = gr.Interface(fn=get_prediction, 
+                         inputs="text", 
+                         outputs="text",
+                         
+                         title="HuggingFace Model Predictor",
+                         description="Enter some text and get the model's prediction!")
+    iface.launch(share=True)
+
+def setup_interface():
+    iface = gr.Interface(fn=trigger_deploy,
+                     inputs="text", 
+                     outputs="text",
+                     live=True,
+                     title="Enter HuggingFace Model URL",
+                     description="Please input the URL of the desired HuggingFace model and submit to deploy.")
+    iface.launch(share=True)
+
+setup_interface()

deploy_model.py

@@ -0,0 +1,39 @@
+import json
+import sagemaker
+import boto3
+from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
+
+try:
+	role = sagemaker.get_execution_role()
+except ValueError:
+	iam = boto3.client('iam')
+	role = iam.get_role(RoleName='Moh-work')['Role']['Arn']
+
+# Hub Model configuration. https://huggingface.co/models
+hub = {
+	'HF_MODEL_ID':'WizardLM/WizardMath-7B-V1.0',
+	'SM_NUM_GPUS': json.dumps(1)
+}
+
+
+
+# create Hugging Face Model Class
+huggingface_model = HuggingFaceModel(
+	image_uri=get_huggingface_llm_image_uri("huggingface",version="1.0.3"),
+	env=hub,
+	role=role, 
+)
+
+# deploy model to SageMaker Inference
+predictor = huggingface_model.deploy(
+	initial_instance_count=1,
+	instance_type="ml.g5.2xlarge",
+	container_startup_health_check_timeout=300,
+  )
+  
+# send request
+predictor.predict({
+	"inputs": "create an E-Commernce platform in Next.js 13",
+})
+
+predictor.delete_endpoint()

flagged/log.csv

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+hf_model_url,output,flag,username,timestamp
+,,,,2023-10-03 21:45:03.128289

key.txt

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+{
+    "Id": "key-consolepolicy-3",
+    "Version": "2012-10-17",
+    "Statement": [
+        {
+            "Sid": "Enable IAM User Permissions",
+            "Effect": "Allow",
+            "Principal": {
+                "AWS": "arn:aws:iam::567031380647:root"
+            },
+            "Action": "kms:*",
+            "Resource": "*"
+        },
+        {
+            "Sid": "Allow access for Key Administrators",
+            "Effect": "Allow",
+            "Principal": {
+                "AWS": "arn:aws:iam::567031380647:user/Mohammed"
+            },
+            "Action": [
+                "kms:Create*",
+                "kms:Describe*",
+                "kms:Enable*",
+                "kms:List*",
+                "kms:Put*",
+                "kms:Update*",
+                "kms:Revoke*",
+                "kms:Disable*",
+                "kms:Get*",
+                "kms:Delete*",
+                "kms:TagResource",
+                "kms:UntagResource",
+                "kms:ScheduleKeyDeletion",
+                "kms:CancelKeyDeletion"
+            ],
+            "Resource": "*"
+        },
+        {
+            "Sid": "Allow use of the key",
+            "Effect": "Allow",
+            "Principal": {
+                "AWS": "arn:aws:iam::567031380647:user/Mohammed"
+            },
+            "Action": [
+                "kms:Encrypt",
+                "kms:Decrypt",
+                "kms:ReEncrypt*",
+                "kms:GenerateDataKey*",
+                "kms:DescribeKey"
+            ],
+            "Resource": "*"
+        },
+        {
+            "Sid": "Allow attachment of persistent resources",
+            "Effect": "Allow",
+            "Principal": {
+                "AWS": "arn:aws:iam::567031380647:user/Mohammed"
+            },
+            "Action": [
+                "kms:CreateGrant",
+                "kms:ListGrants",
+                "kms:RevokeGrant"
+            ],
+            "Resource": "*",
+            "Condition": {
+                "Bool": {
+                    "kms:GrantIsForAWSResource": "true"
+                }
+            }
+        }
+    ]
+}

needed.txt

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+the AWS account:
+
+https://567031380647.signin.aws.amazon.com/console
+
+
+User name - Mohammed
+
+
+
+Console password - |tVY5gY[
+
+
+\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
+
+chatgpt analysis:
+
+https://chat.openai.com/share/c0831a5a-387e-4eda-86cc-7eb84b5fe5e9
+
+
+AWS Access Key ID [****************c07f]: AKIAYIBNUHKT6GS5HZ6V
+AWS Secret Access Key [None]: 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
+
+RoleName='Moh-work'