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pipelines-and-components

pipelines-and-components

Build, connect, run, serialize, debug, and extend Haystack Pipeline, AsyncPipeline, SuperComponent, and custom @component workflows.

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Documentation de la Skill

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name: pipelines-and-components description: "Build, connect, run, serialize, debug, and extend Haystack Pipeline, AsyncPipeline, SuperComponent, and custom @component workflows." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Pipelines and Components

Use this sub-skill when the task is about Haystack orchestration rather than a specific model, retriever, agent, or repository-maintenance command.

Route Here

  • Create or modify Pipeline and AsyncPipeline graphs with add_component(), connect(), run(), run_async(), and run_async_generator().
  • Write custom @component classes, define input and output sockets, validate socket names/types, or debug component contract errors.
  • Configure loop safety with max_runs_per_component, inspect intermediate outputs with include_outputs_from, and diagnose blocked or over-running graphs.
  • Serialize or load pipelines with to_dict(), from_dict(), dumps(), loads(), dump(), and load().
  • Use pipeline breakpoints, snapshots, drawing, or SuperComponent wrappers.

Reroute

  • Model/provider components, credentials, generation-specific parameters, and embedding/generator selection: ../generation-and-model-components/SKILL.md.
  • RAG retrieval strategy, document stores, rankers, and retriever wiring choices: ../retrieval-and-rag/SKILL.md.
  • Agent loops, tool invocation, and human-in-the-loop workflows: route to the agents-tools-and-hitl sibling when present.
  • Hatch, tests, release notes, or maintainer commands for this repository: route to the repo-development sibling when present.

Core References

  • Start with references/api-reference.md for concrete constructor signatures, component contracts, connection rules, and serialization APIs.
  • Use references/workflows.md for build/debug/async/loop/super-component recipes.
  • Use references/troubleshooting.md when imports, optional integrations, sockets, serialization, snapshots, or runtime execution fail.
  • Run scripts/pipeline_smoke_check.py in any environment with haystack-ai installed to verify the public APIs this sub-skill relies on.

Fast Pattern

from haystack import Pipeline, component

@component
class Uppercase:
    @component.output_types(text=str)
    def run(self, text: str) -> dict[str, str]:
        return {"text": text.upper()}

pipe = Pipeline(max_runs_per_component=5)
pipe.add_component("upper", Uppercase())
result = pipe.run({"upper": {"text": "haystack"}})
assert result["upper"]["text"] == "HAYSTACK"
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