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Documentation Index

Fetch the complete documentation index at: https://docs.cycls.com/llms.txt

Use this file to discover all available pages before exploring further.

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The Context Object

The context parameter provides access to conversation history and user data in your agent functions. 
@cycls.app()
async def app(context):
    # Access conversation history
    messages = context.messages

    # Access the latest message
    latest_msg = messages[-1]

    yield f"You said: {latest_msg['content']}"

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Context Properties

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context
Context Object

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Message Format

The context.messages follows the standard OpenAI message format, which can include text and images (multimodal). Here is an example of what context.messages looks like: 
[
    {'role': 'user', 'content': 'hello'},
    {'role': 'assistant', 'content': 'Hello! How can I assist you today?'},
    {'role': 'user', 'content': [
        {'type': 'image_url', 'image_url': {'url': 'https://.../image.png'}}
    ]},
    {'role': 'assistant', 'content': "It looks like you're looking at an image..."},
]

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Working with Messages

You can easily process these messages to extract text or pass them directly to an LLM. 
import cycls

@cycls.app(pip=["openai"])
async def app(context):
    from openai import AsyncOpenAI

    client = AsyncOpenAI()
    response = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=context.messages,
        stream=True
    )
    async for chunk in response:
        content = chunk.choices[0].delta.content
        if content:
            yield content

app.local()

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Next Steps

Customize UI

Tailor the chat interface to match your brand.