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Docs Map

This page explains what each document is for so readers do not have to guess which page contains narrative guidance versus generated reference.

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Doc Purpose
index.md Landing page and reading order.
getting-started/use-cases.md Practical end-to-end examples for common batchor workflows.
getting-started/python-api.md End-to-end Python usage patterns.
getting-started/cli.md Operator CLI behavior and examples.
reference/api.md Public symbols and generated API reference.

Design docs

Doc Purpose
design_docs/BOUNDARY_AND_PHILOSOPHY.md Ownership boundary between batchor, storage/artifacts, and user pipelines.
design_docs/ARCHITECTURE.md Canonical runtime diagrams, package structure, main flows, and extension seams.
design_docs/OPENAI_BATCHING.md OpenAI request construction, token budgeting, splitting, and batch polling behavior.
design_docs/STORAGE_AND_RUNS.md Durable Run lifecycle, rehydration, checkpoints, control state, artifact retention, and operator semantics.
design_docs/STORAGE_MIGRATIONS.md SQLite schema-versioning and migration guidance.
design_docs/ROADMAP.md Intentionally unimplemented areas and planned work.

Validation and project policy

Doc Purpose
smoke-test.md Minimum validation bar for local work and CI.
policies/support.md Published support policy for the latest released 0.x minor.
policies/versioning.md Versioning expectations for the Python API and CLI.
policies/contributing.md Contribution guidance.

Recent implementation areas

  • Deterministic built-in source checkpoints now cover CSV, JSONL, and Parquet.
  • Library-first run control now includes pause, resume, and drain-style cancel.
  • Incremental terminal-result reads/exports are documented in the Python API and storage docs.
  • Raw output/error artifact retention is now configurable per run through ArtifactPolicy.