examples/LLM_Workflows/langchain_comparison/hamilton_streamed.py

# hamilton_streamed.py
from typing import Iterator, List

import openai


def llm_client() -> openai.OpenAI:
    return openai.OpenAI()


def joke_prompt(topic: str) -> str:
    return f"Tell me a short joke about {topic}"


def joke_messages(joke_prompt: str) -> List[dict]:
    return [{"role": "user", "content": joke_prompt}]


def joke_response(llm_client: openai.OpenAI, joke_messages: List[dict]) -> Iterator[str]:
    stream = llm_client.chat.completions.create(
        model="gpt-3.5-turbo", messages=joke_messages, stream=True
    )
    for response in stream:
        content = response.choices[0].delta.content
        if content is not None:
            yield content


if __name__ == "__main__":
    import hamilton_streaming

    from hamilton import driver

    dr = driver.Builder().with_modules(hamilton_streaming).build()
    dr.display_all_functions("hamilton-streaming.png")
    result = dr.execute(["joke_response"], inputs={"topic": "ice cream"})
    for chunk in result["joke_response"]:
        print(chunk, end="", flush=True)