Python SDK
The official Python SDK for Sim Studio
The official Python SDK for Sim Studio allows you to execute workflows programmatically from your Python applications.
The Python SDK supports Python 3.8+ and provides synchronous workflow execution. All workflow executions are currently synchronous.
Installation
Install the SDK using pip:
pip install simstudio-sdk
Quick Start
Here's a simple example to get you started:
from simstudio import SimStudioClient
# Initialize the client
client = SimStudioClient(
api_key="your-api-key-here",
base_url="https://simstudio.ai" # optional, defaults to https://simstudio.ai
)
# Execute a workflow
try:
result = client.execute_workflow("workflow-id")
print("Workflow executed successfully:", result)
except Exception as error:
print("Workflow execution failed:", error)
API Reference
SimStudioClient
Constructor
SimStudioClient(api_key: str, base_url: str = "https://simstudio.ai")
Parameters:
api_key
(str): Your Sim Studio API keybase_url
(str, optional): Base URL for the Sim Studio API
Methods
execute_workflow()
Execute a workflow with optional input data.
result = client.execute_workflow(
"workflow-id",
input_data={"message": "Hello, world!"},
timeout=30.0 # 30 seconds
)
Parameters:
workflow_id
(str): The ID of the workflow to executeinput_data
(dict, optional): Input data to pass to the workflowtimeout
(float, optional): Timeout in seconds (default: 30.0)
Returns: WorkflowExecutionResult
get_workflow_status()
Get the status of a workflow (deployment status, etc.).
status = client.get_workflow_status("workflow-id")
print("Is deployed:", status.is_deployed)
Parameters:
workflow_id
(str): The ID of the workflow
Returns: WorkflowStatus
validate_workflow()
Validate that a workflow is ready for execution.
is_ready = client.validate_workflow("workflow-id")
if is_ready:
# Workflow is deployed and ready
pass
Parameters:
workflow_id
(str): The ID of the workflow
Returns: bool
execute_workflow_sync()
Currently, this method is identical to execute_workflow()
since all executions are synchronous. This method is provided for future compatibility when asynchronous execution is added.
Execute a workflow (currently synchronous, same as execute_workflow()
).
result = client.execute_workflow_sync(
"workflow-id",
input_data={"data": "some input"},
timeout=60.0
)
Parameters:
workflow_id
(str): The ID of the workflow to executeinput_data
(dict, optional): Input data to pass to the workflowtimeout
(float): Timeout for the initial request in seconds
Returns: WorkflowExecutionResult
set_api_key()
Update the API key.
client.set_api_key("new-api-key")
set_base_url()
Update the base URL.
client.set_base_url("https://my-custom-domain.com")
close()
Close the underlying HTTP session.
client.close()
Data Classes
WorkflowExecutionResult
@dataclass
class WorkflowExecutionResult:
success: bool
output: Optional[Any] = None
error: Optional[str] = None
logs: Optional[List[Any]] = None
metadata: Optional[Dict[str, Any]] = None
trace_spans: Optional[List[Any]] = None
total_duration: Optional[float] = None
WorkflowStatus
@dataclass
class WorkflowStatus:
is_deployed: bool
deployed_at: Optional[str] = None
is_published: bool = False
needs_redeployment: bool = False
SimStudioError
class SimStudioError(Exception):
def __init__(self, message: str, code: Optional[str] = None, status: Optional[int] = None):
super().__init__(message)
self.code = code
self.status = status
Examples
Basic Workflow Execution
Set up the SimStudioClient with your API key.
Check if the workflow is deployed and ready for execution.
Run the workflow with your input data.
Process the execution result and handle any errors.
import os
from simstudio import SimStudioClient
client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
def run_workflow():
try:
# Check if workflow is ready
is_ready = client.validate_workflow("my-workflow-id")
if not is_ready:
raise Exception("Workflow is not deployed or ready")
# Execute the workflow
result = client.execute_workflow(
"my-workflow-id",
input_data={
"message": "Process this data",
"user_id": "12345"
}
)
if result.success:
print("Output:", result.output)
print("Duration:", result.metadata.get("duration") if result.metadata else None)
else:
print("Workflow failed:", result.error)
except Exception as error:
print("Error:", error)
run_workflow()
Error Handling
Handle different types of errors that may occur during workflow execution:
from simstudio import SimStudioClient, SimStudioError
import os
client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
def execute_with_error_handling():
try:
result = client.execute_workflow("workflow-id")
return result
except SimStudioError as error:
if error.code == "UNAUTHORIZED":
print("Invalid API key")
elif error.code == "TIMEOUT":
print("Workflow execution timed out")
elif error.code == "USAGE_LIMIT_EXCEEDED":
print("Usage limit exceeded")
elif error.code == "INVALID_JSON":
print("Invalid JSON in request body")
else:
print(f"Workflow error: {error}")
raise
except Exception as error:
print(f"Unexpected error: {error}")
raise
Context Manager Usage
Use the client as a context manager to automatically handle resource cleanup:
from simstudio import SimStudioClient
import os
# Using context manager to automatically close the session
with SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY")) as client:
result = client.execute_workflow("workflow-id")
print("Result:", result)
# Session is automatically closed here
Batch Workflow Execution
Execute multiple workflows efficiently:
from simstudio import SimStudioClient
import os
client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
def execute_workflows_batch(workflow_data_pairs):
"""Execute multiple workflows with different input data."""
results = []
for workflow_id, input_data in workflow_data_pairs:
try:
# Validate workflow before execution
if not client.validate_workflow(workflow_id):
print(f"Skipping {workflow_id}: not deployed")
continue
result = client.execute_workflow(workflow_id, input_data)
results.append({
"workflow_id": workflow_id,
"success": result.success,
"output": result.output,
"error": result.error
})
except Exception as error:
results.append({
"workflow_id": workflow_id,
"success": False,
"error": str(error)
})
return results
# Example usage
workflows = [
("workflow-1", {"type": "analysis", "data": "sample1"}),
("workflow-2", {"type": "processing", "data": "sample2"}),
]
results = execute_workflows_batch(workflows)
for result in results:
print(f"Workflow {result['workflow_id']}: {'Success' if result['success'] else 'Failed'}")
Environment Configuration
Configure the client using environment variables:
import os
from simstudio import SimStudioClient
# Development configuration
client = SimStudioClient(
api_key=os.getenv("SIMSTUDIO_API_KEY"),
base_url=os.getenv("SIMSTUDIO_BASE_URL", "https://simstudio.ai")
)
Getting Your API Key
Navigate to Sim Studio and log in to your account.
Navigate to the workflow you want to execute programmatically.
Click on "Deploy" to deploy your workflow if it hasn't been deployed yet.
During the deployment process, select or create an API key.
Copy the API key to use in your Python application.
Keep your API key secure and never commit it to version control. Use environment variables or secure configuration management.
Requirements
- Python 3.8+
- requests >= 2.25.0
License
Apache-2.0