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This function creates a stream response for LLM Apps. By using the MorphChatStreamChunk returned by this function and passing it to <LLM/>, you can build a chat application utilizing LLM.
morph_lib.stream
# 📦 Package: morph_lib.stream
# 🛠️ Function: create_chunk

def create_chunk(
    text: Optional[str] = None, content: Optional[str] = None
) -> MorphChatStreamChunk:

​
Parameters

​
text
str
Text to be displayed in the chat stream.
​
content
str
Content to be displayed in the side-by-side layout of <LLM/>.ex.) html, markdown, etc.

​
Example

import os
from morph_lib.stream import create_chunk
from openai import OpenAI
import morph
from morph import MorphGlobalContext

@morph.func(name="test")
@morph.variables("prompt")
def main(context: MorphGlobalContext):
    client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
    propmt = context.vars["prompt"]
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": propmt}],
        stream=True,
    )

    for c in response:
        text = c.model_dump()["choices"][0]["delta"].get("content", "")
        yield create_chunk(text=text)