OpenAI Assistant¶

The OpenAI Assistant class provides a wrapper around OpenAI's Assistants API, integrating it with the swarms framework.

Overview¶

The OpenAIAssistant class allows you to create and interact with OpenAI Assistants, providing a simple interface for:

Creating assistants with specific roles and capabilities
Adding custom functions that the assistant can call
Managing conversation threads
Handling tool calls and function execution
Getting responses from the assistant

Insstallation¶

pip install swarms

Basic Usage¶

from swarms import OpenAIAssistant

#Create an assistant
assistant = OpenAIAssistant(
    name="Math Tutor",
    instructions="You are a helpful math tutor.",
    model="gpt-4o",
    tools=[{"type": "code_interpreter"}]
)

#Run a Task
response = assistant.run("Solve the equation: 3x + 11 = 14")
print(response)

# Continue the conversation in the same thread
follow_up = assistant.run("Now explain how you solved it")
print(follow_up)

Function Calling¶

The assistant supports custom function integration:

def get_weather(location: str, unit: str = "celsius") -> str:
    # Mock weather function
    return f"The weather in {location} is 22 degrees {unit}"

# Add function to assistant
assistant.add_function(
    description="Get the current weather in a location",
    parameters={
        "type": "object",
        "properties": {
            "location": {
                "type": "string",
                "description": "City name"
            },
            "unit": {
                "type": "string",
                "enum": ["celsius", "fahrenheit"],
                "default": "celsius"
            }
        },
        "required": ["location"]
    }
)

API Reference¶

Constructor¶

OpenAIAssistant(
    name: str,
    instructions: Optional[str] = None,
    model: str = "gpt-4o",
    tools: Optional[List[Dict[str, Any]]] = None,
    file_ids: Optional[List[str]] = None,
    metadata: Optional[Dict[str, Any]] = None,
    functions: Optional[List[Dict[str, Any]]] = None,
)

Methods¶

run(task: str) -> str¶

Sends a task to the assistant and returns its response. The conversation thread is maintained between calls.

add_function(func: Callable, description: str, parameters: Dict[str, Any]) -> None¶

Adds a callable function that the assistant can use during conversations.

add_message(content: str, file_ids: Optional[List[str]] = None) -> None¶

Adds a message to the current conversation thread.

Error Handling¶

The assistant implements robust error handling: - Retries on rate limits - Graceful handling of API errors - Clear error messages for debugging - Status monitoring for runs and completions

Best Practices¶

Thread Management
Use the same assistant instance for related conversations
Create new instances for unrelated tasks
Monitor thread status during long-running operations
Function Integration
Keep functions simple and focused
Provide clear descriptions and parameter schemas
Handle errors gracefully in custom functions
Test functions independently before integration
Performance
Reuse assistant instances when possible
Monitor and handle rate limits appropriately
Use appropriate polling intervals for status checks
Consider implementing timeouts for long-running operations