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name: core-composition description: "Build GenAI Processors pipelines with content, streams, routing, caching, and tracing." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Core composition

Use this sub-skill for the mechanics of GenAI Processors: content wrappers, custom processors, stream transformations, branching, caching, and debugging.

Read when

• The task asks how to create a Processor or PartProcessor.
• The task mentions ProcessorPart, ProcessorContent, ContentStream, MIME types, roles, metadata, or substreams.
• The task needs +, //, parallel_concat, Switch, PartSwitch, streams.split, streams.merge, or queue-based stream wiring.
• The task needs CachedProcessor, CachedPartProcessor, SqlCache, tracing, or a safe local smoke check.

Boundaries

This sub-skill owns library plumbing and reusable processor patterns. It does not own model credentials, audio/video device setup, or full example app wiring:

• Route model wrappers and tool calling to ../model-backends/.
• Route audio/video/PDF/web/Drive/GitHub sources to ../multimodal-i-o/.
• Route CLI demos, AI Studio applets, and full applications to ../examples-and-apps/.

Core workflow

1. Start with content shape: text-only, multimodal, dataclass/proto, function call/response, or device/document parts.
2. Pick Processor for stream-wide/stateful logic, or PartProcessor for independent per-part logic.
3. Accept broad inputs at call sites; implement against processor.ProcessorStream.
4. Use + for sequential chains and // only for independent part processors.
5. Use parallel_concat or streams.split/merge only when the ordering and concurrency behavior matches the user-visible result.
6. Add Switch / PartSwitch for substream or mimetype routing.
7. Add cache/tracing last, after the uncached pipeline is correct.
8. Validate with scripts/smoke_core.py or the root scripts/check_install.py.

References and scripts

• references/api-reference.md lists the public core classes, decorators, stream utilities, and helper modules.
• references/workflows.md gives end-to-end patterns for custom processors, stream routing, caching, and tracing.
• references/troubleshooting.md covers common mistakes with MIME types, .text, caches, task groups, and trace size.
• scripts/smoke_core.py runs a safe in-process processor/stream smoke test.

Native evidence anchors

Behavior is backed by the core package source and tests such as content_api_test.py, processor_test.py, streams_test.py, switch_test.py, cache_test.py, sql_cache_test.py, map_processor_test.py, mime_types_test.py, context_test.py, debug_test.py, preamble_test.py, constrained_decoding_test.py, and trace_file_test.py.

Usability checkpoints

A good answer using this sub-skill should:

• Preserve multimodal parts unless the user explicitly wants text only.
• State when an operation buffers a stream versus preserving streaming behavior.
• Show concrete imports and processor composition code.
• Include validation steps that do not require remote models or hardware.
• Link to sibling sub-skills only when the task crosses into models, I/O, or complete examples.