SelfInstruct

Overview

SelfInstruct is a singleton template designed to generate user queries for AI applications based on specific criteria and context. It automates the process of creating relevant instructions or queries that can be used to test or train AI systems.

Inputs

Field	Type	Description
num_instructions	conint(ge=1)	The number of user queries to generate
criteria_for_query_generation	str	The criteria for generating the queries
application_description	str	A description of the AI application
context	str	The context to which the queries should be applicable

Outputs

Field	Type	Description
instructions	List[str]	List of generated instructions
model	str	The AI model used for generation

Usage

SelfInstruct instance can be used in data generation as follows:

from dria.factory import SelfInstruct

my_dataset = DriaDataset(
    name="SelfInstruct",
    description="A dataset for self-instructed query generation",
    schema=SelfInstruct.OutputSchema,
)
generator = DatasetGenerator(dataset=my_dataset)

Expected output

{
   "instructions":[
      "Prioritize my upcoming deadlines, considering project dependencies. ",
      "Can you schedule a meeting with the marketing team for next week to discuss the Q3 campaign?",
      "Generate a comprehensive list of actionable steps required for completing the client proposal.",
      "What tasks are currently assigned to me that are due within the next 7 days?",
      "Remind me to follow up with John about the budget approval at 2 PM tomorrow."
   ],
   "model":"gemma2:9b-instruct-fp16"
}