run.py

import argparse

import os
import json

from salesgpt.agents import SalesGPT
from langchain.chat_models import ChatOpenAI


if __name__ == "__main__":

    # import your OpenAI key (put in your .env file)
    with open('.env','r') as f:
        env_file = f.readlines()
    envs_dict = {key.strip("'") :value.strip("\n") for key, value in [(i.split('=')) for i in env_file]}
    os.environ['OPENAI_API_KEY'] = envs_dict['OPENAI_API_KEY']

    # Initialize argparse
    parser = argparse.ArgumentParser(description='Description of your program')

    # Add arguments
    parser.add_argument('--config', type=str, help='Path to agent config file', default='')
    parser.add_argument('--verbose', type=bool, help='Verbosity', default=False)
    parser.add_argument('--max_num_turns', type=int, help='Maximum number of turns in the sales conversation', default=10)

    # Parse arguments
    args = parser.parse_args()

    # Access arguments
    config_path = args.config
    verbose = args.verbose
    max_num_turns = args.max_num_turns

    llm = ChatOpenAI(temperature=0.9, stop = "<END_OF_TURN>")

    if config_path=='':
        print('No agent config specified, using a standard config')
        sales_agent = SalesGPT.from_llm(llm, verbose=verbose)
    else:
        with open(config_path,'r') as f:
            config = json.load(f)
        print(f'Agent config {config}')
        sales_agent = SalesGPT.from_llm(llm, verbose=verbose, **config)

    sales_agent.seed_agent()
    print('='*10)
    cnt = 0
    while cnt !=max_num_turns:
        cnt+=1
        if cnt==max_num_turns:
            print('Maximum number of turns reached - ending the conversation.')
            break
        sales_agent.step()

        # end conversation 
        if '<END_OF_CALL>' in sales_agent.conversation_history[-1]:
            print('Sales Agent determined it is time to end the conversation.')
            break
        human_input = input('Your response: ')
        sales_agent.human_step(human_input)
        print('='*10)