streaming_generator_example.py

import os

from dotenv import load_dotenv
from langchain_community.chat_models import ChatLiteLLM

from salesgpt.agents import SalesGPT

load_dotenv()

llm = ChatLiteLLM(temperature=0.9, model_name="gpt-3.5-turbo-0613")

sales_agent = SalesGPT.from_llm(
    llm,
    verbose=False,
    salesperson_name="Ted Lasso",
    salesperson_role="Sales Representative",
    company_name="Sleep Haven",
    company_business="""Sleep Haven 
                            is a premium mattress company that provides
                            customers with the most comfortable and
                            supportive sleeping experience possible. 
                            We offer a range of high-quality mattresses,
                            pillows, and bedding accessories 
                            that are designed to meet the unique 
                            needs of our customers.""",
)

sales_agent.seed_agent()

# get generator of the LLM output
generator = sales_agent.step(stream=True)

# operate on streaming LLM output in near-real time
# for instance, do something after each full sentence is generated
for chunk in generator:
    print(chunk)