Quick Start¶
In order to follow this guide, you need to install Dria SDK.
Using Dria is simple:
- Create a dataset
- Attach a dataset generator
- Define your instructions (inputs)
- Define prompts
- Run!
import asyncio
from dria import Prompt, DatasetGenerator, DriaDataset, Model
from pydantic import BaseModel, Field
# Define output schema
class Tweet(BaseModel):
topic: str = Field(..., title="Topic")
tweet: str = Field(..., title="tweet")
# Create dataset
dataset = DriaDataset(name="tweet_test", description="A dataset of tweets!", schema=Tweet)
# Create instructions
instructions = [{"topic": "BadBadNotGood"}, {"topic": "Decentralized synthetic data"}]
# Prompt to apply to your instructions
prompter = Prompt(prompt="Write a tweet about {{topic}}", schema=Tweet)
generator = DatasetGenerator(dataset=dataset)
asyncio.run(
generator.generate(
instructions=instructions, singletons=prompter, models=Model.GPT4O
)
)
dataset.to_pandas()
# topic tweet
# 0 BadBadNotGood 🎶 Thrilled to have discovered #BadBadNotGood! ...
# 1 Decentralized Synthetic Data Exploring the future of #AI with decentralized...
And that's it! This script will run your instructions on models of your choice, execute them on a network of LLMs, and store them on a local database.
Note: Network capacity and data generation volumes are limited during the current phase of Dria.