Version: v0.6.1

QuickStart Basic AWEL Workflow

Install

At first, install dbgpt, and necessary dependencies:

pip install dbgpt --upgrade
pip install openai

Create a python file simple_sdk_llm_example_dag.py and write the following content:

import asyncio
from dbgpt.core.awel import DAG
from dbgpt.core.operators import (
    PromptBuilderOperator,
    RequestBuilderOperator,
)
from dbgpt.model.proxy import OpenAILLMClient
from dbgpt.model.operators import LLMOperator

with DAG("simple_sdk_llm_example_dag") as dag:
    prompt_task = PromptBuilderOperator(
        "Write a SQL of {dialect} to query all data of {table_name}."
    )
    model_pre_handle_task = RequestBuilderOperator(model="gpt-3.5-turbo")
    llm_task = LLMOperator(OpenAILLMClient())
    prompt_task >> model_pre_handle_task >> llm_task
    
output = asyncio.run(
    llm_task.call({
        "dialect": "MySQL", 
        "table_name": "users"
    }
))
print(output)

Configure the environment variables for OpenAI API:

export OPENAI_API_KEY=sk-xx
export OPENAI_API_BASE=https://xx:80/v1

Run the python file:

python simple_sdk_llm_example_dag.py

The output will like this:

ModelOutput(text='SELECT * FROM users;', error_code=0, model_context=None, finish_reason=None, usage={'completion_tokens': 5, 'prompt_tokens': 19, 'total_tokens': 24}, metrics=None)

Congratulations! You have already mastered the basic usage of AWEL. For more examples, please refer to the cookbook.

And we suggest you to read the book AWEL Tutorial to learn more about AWEL.

QuickStart Basic AWEL Workflow

Install​

Install