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configuration-extension

configuration-extension

Configure and extend Marker pipelines with ConfigParser, class paths, processors, renderers, providers, and schema/debug guidance.

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Documentation de la Skill

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name: configuration-extension description: "Configure and extend Marker pipelines with ConfigParser, class paths, processors, renderers, providers, and schema/debug guidance." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Marker Configuration And Extension

Use this sub-skill when a task is about changing how Marker parses options, selects pipeline classes, injects processors/renderers/providers, or explains debug/schema output. For routine conversion commands and Python conversion calls, route to ../conversion-cli-api/. For LLM service credentials, extraction schemas, and LLM backend behavior, route to ../llm-extraction-services/. For Streamlit apps, FastAPI server, or deployment, route to ../server-deployment/.

Start Here

  1. Decide whether the user needs configuration, extension design, or debugging:
    • Configuration: inspect ConfigParser output, config_json, generated common options, --processors, --converter_cls, --output_format, and --debug.
    • Extension: choose the right ownership point: provider for input format, builder for document construction, processor for block mutation, renderer for output shape, converter for end-to-end orchestration.
    • Debugging: check JSON validity, falsey values, class-path imports, renderer/output mismatches, provider detection, and debug artifact placement.
  2. Use scripts/inspect_marker_config.py before running conversion when a user asks what CLI/config options pass downstream.
  3. Use scripts/custom_processor_template.py as a safe skeleton or import validator for custom processor class paths.
  4. Keep custom class paths fully qualified, for example marker.converters.table.TableConverter, not TableConverter.

Key References

Fast Routing

  • User asks “How do I convert this folder/PDF?” → ../conversion-cli-api/.
  • User asks “How do I use Gemini/OpenAI/Claude/Ollama or structured extraction?” → ../llm-extraction-services/.
  • User asks “How do I run the API server or GUI?” → ../server-deployment/.
  • User asks “What does this config pass into Marker?” → inspect with scripts/inspect_marker_config.py, then apply references/configuration.md.
  • User asks “Where should I add a custom behavior?” → use the ownership map in references/extension-points.md.

Safe Defaults

  • Prefer dry-run inspection before conversion. Config inspection does not open input documents or call model services.
  • Keep credential setup out of examples unless the LLM sub-skill explicitly owns the task.
  • Avoid editing Marker internals for user projects when a full import path, config key, custom processor, or custom renderer can be passed into existing APIs.
  • Explain that --debug writes extra artifacts under the configured output directory, nested by document base name.
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