Currently Instructor Agents only work with OpenAI models.

​
Initialization

​
Parameters

The InstructorTextAgent is initialized with two arguments:

InstructorTextAgent(response_model, model(Optional))
​
response_model
BaseModel
required

Specifies the structure of the data that the OpenAI API is expected to return. This structured model helps in parsing and validating the data returned from the API, ensuring it adheres to the expected format.

This parameter expects a class that is a subclass of BaseModel from the pydantic library.

​
model
Optional[String]

Specifies the model identifier used by the OpenAI API to process the image. The default value is "gpt-4o".

You can find a comprehensive list of all OpenAI API models here.

​
Execution

​
Parameters

The Workflow is expected to have some sort of text input that needs to be processed.

​
Example

Here is an example of the InstructorTextAgent as part of a Workflow for counting vehicles.

Step 1. Define a response_model.

example.py
from pydantic import BaseModel

class TrafficAnalysisResponse(BaseModel):
    cars: int
    trucks: int

This model expects the analysis to return the counts of different types of vehicles and a timestamp indicating the time of the image capture.

Step 2. Use InstructorTextAgent.

example.py
InstructorTextAgent(response_model=TrafficAnalysisResponse)
Text Prompt AgentClass Map Agent