examples/basic/chat.py - main - githubmirror/langroid

examples/basic/chat.py
95 строк2 KB
Prasad Chalasani
fix: handle None `prompt_token_details`
09 июл 2025, 13:58
09 июл 2025, 13:58f9ff350
# script
# requires-python = ">=3.11"
# dependencies = [
#     "langroid",
# ]
# ///
"""
The most basic chatbot example, using the default settings.
A single Agent allows you to chat with a pre-trained Language Model.

Run like this:

python3 examples/basic/chat.py

Use optional arguments to change the settings, e.g.:

-m <local_model_spec>
-ns # no streaming
-d # debug mode
-nc # no cache
-sm <system_message>
-q <initial user msg>

For details on running with local or non-OpenAI models, see:
https://langroid.github.io/langroid/tutorials/local-llm-setup/
"""

import typer
from dotenv import load_dotenv
from rich import print
from rich.prompt import Prompt

import langroid.language_models as lm
from langroid.agent.chat_agent import ChatAgent, ChatAgentConfig
from langroid.agent.task import Task
from langroid.utils.configuration import Settings, set_global

app = typer.Typer()

# Create classes for non-OpenAI model configs


@app.command()
def main(
    debug: bool = typer.Option(False, "--debug", "-d", help="debug mode"),
    model: str = typer.Option("", "--model", "-m", help="model name"),
    no_stream: bool = typer.Option(False, "--nostream", "-ns", help="no streaming"),
    nocache: bool = typer.Option(False, "--nocache", "-nc", help="don't use cache"),
    sys_msg: str = typer.Option(
        "You are a helpful assistant. Be concise in your answers.",
        "--sysmsg",
        "-sm",
        help="system message",
    ),
) -> None:
    set_global(
        Settings(
            debug=debug,
            cache=not nocache,
            stream=not no_stream,
        )
    )
    print(
        """
        [blue]Welcome to the basic chatbot!
        Enter x or q to quit at any point.
        """
    )

    load_dotenv()

    # use the appropriate config instance depending on model name
    # NOTE: when using Azure, change this to `lm.AzureConfig`
    llm_config = lm.OpenAIGPTConfig(
        chat_model=model or lm.OpenAIChatModel.GPT4o,
        chat_context_length=16_000,  # set based on model
        timeout=45,
    )

    sys_msg = Prompt.ask(
        "[blue]Tell me who I am. Hit Enter for default, or type your own\n",
        default=sys_msg,
    )

    config = ChatAgentConfig(
        system_message=sys_msg,
        llm=llm_config,
    )
    agent = ChatAgent(config)
    task = Task(agent)
    task.run("hello")


if __name__ == "__main__":
    app()