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Documentation Index

Fetch the complete documentation index at: https://developers.autoplay.ai/llms.txt

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

Use compose_chat_pipeline(...) when you want one callback (pipeline.on_actions) that wires context storage and agent-context writing without callback clobbering.

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Import

from autoplay_sdk import compose_chat_pipeline

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Signature

compose_chat_pipeline(
    *,
    llm,
    threshold=10,
    lookback_seconds=300.0,
    max_actions=20,
    write_actions=None,
    overwrite_with_summary=None,
    debounce_ms=0,
)
  • llm: async callable (prompt: str) -> str.
  • threshold: summarizer trigger (action count).
  • lookback_seconds, max_actions: AsyncContextStore bounds.
  • write_actions: optional push callback for raw action text.
  • overwrite_with_summary: optional callback invoked when summary is emitted.
  • debounce_ms: forwarded to AsyncAgentContextWriter.

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Minimal setup

from autoplay_sdk import compose_chat_pipeline

pipeline = compose_chat_pipeline(
    llm=my_async_llm,
    threshold=10,
    lookback_seconds=300,
    max_actions=20,
    write_actions=my_write_actions_cb,
    overwrite_with_summary=my_overwrite_cb,
)

client.on_actions(pipeline.on_actions)

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Ordering guarantee

pipeline.on_actions(payload) runs in canonical order:
  1. context_store.add(payload) updates retrieval state.
  2. agent_writer.add(payload) handles push and summary logic.
Summary callbacks are fanned out so both context-store and writer-side overwrite paths receive updates. This prevents accidental callback overwrite behavior in custom wiring.

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When to use this helper

  • You want the default chat ingestion wiring without hand-rolling callback orchestration.
  • You need predictable summary propagation to both storage and UI push callbacks.