Files
infospace-bench/docs/generic-source-generator.md
tegwick debd2b8e69 IB-WP-0020-T04: example routing config + live routing smoke
examples/routing/trading-literature.yaml is the checked-in starting
config for a Lefevre-style run. It applies the IB-WP-0018 task-type
taxonomy: cheap candidates for summary + evaluation, smart candidates
for entity + relation extraction, and a separate baseline rule wiring
claude_code for a follow-on T05 ShadowingAdapter step. Workspace-
relative ledger_path keeps adaptive observations with the workspace.

tests/test_routing_config.py gains a regression test that asserts the
shipped example parses cleanly, every stage in stage_to_task_type maps
to a declared task type, and the baseline candidate uses the
claude_code provider — so the example will not bit-rot silently.

tests/test_openrouter_live.py gains test_provider_routing_one_chapter_live_smoke
gated on the same INFOSPACE_BENCH_ENABLE_LIVE_OPENROUTER + OPENROUTER_API_KEY
opt-in as the existing static smoke. It builds a one-candidate routing
config, runs a single chapter through --provider routing, and asserts
the per-stage adapter-choices report section names the routed model
and the routed artifacts carry adapter_id provenance.

docs/generic-source-generator.md gains a "Live runs with --provider
routing" subsection that walks through the one-command routed run,
explains the --quality-floor override, and points at the parallel
live smoke test.

174 tests pass, 2 skipped (both live smokes, correctly gated).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-18 22:19:54 +02:00

245 lines
8.6 KiB
Markdown

# Generic Source Generator
Date: 2026-05-14
## Purpose
`infospace-bench generate` turns a local article, ebook-like file, or folder of
knowledge sources into a manifest-backed infospace. It generalizes the
Wealth/VSM pilot into an explicit workflow path with deterministic fixture
support and an optional OpenRouter provider.
## Deterministic Run
Use fixture responses for repeatable tests and demos:
```bash
infospace-bench generate from-source ./examples/article.md \
--workspace . \
--slug article-space \
--name "Article Space" \
--profile general-knowledge \
--fixture-responses ./examples/responses.yaml \
--apply
```
The command creates normalized source chunks, installs the selected profile,
runs the declared workflows, writes entities, relations, evaluations, metrics,
history, and a generation report, then registers artifacts in
`artifacts/index.yaml`.
## Stepwise Workflow
```bash
infospace-bench generate init ./book.epub \
--workspace . \
--slug book-space \
--name "Book Space" \
--profile general-knowledge \
--max-chunks 3
infospace-bench generate plan ./infospaces/book-space --stage all
infospace-bench generate run ./infospaces/book-space \
--fixture-responses ./responses.yaml
infospace-bench generate status ./infospaces/book-space
```
`--max-chunks` caps early experiments and provider cost. `generate status`
shows chunk counts, generated artifact counts, evaluations, metrics, history,
and stale source/profile inputs.
### Live OpenRouter runs (handle with care)
A single-chapter live run is the only OpenRouter shape the test suite
covers today. Use `--chapter` (or `--from-chapter` / `--to-chapter`) on
`generate init` or `generate from-source` to scope what gets registered
before any provider calls happen:
```bash
export OPENROUTER_API_KEY=...
# Preview the cost first
infospace-bench generate plan ./infospaces/foo --chapter I --cost-per-1k 0.30
# Run only Chapter I against a cheap model
infospace-bench generate from-source ./LEFEVRE.epub \
--workspace ./infospaces \
--slug reminiscences-ch1 \
--name "Reminiscences (Ch I)" \
--profile trading-literature \
--provider openrouter \
--model openai/gpt-4o-mini \
--chapter I \
--apply
```
`output/budget/plans.yaml`, `usage.yaml`, and `summary.yaml` record what
was estimated, what was actually spent, and the plan-vs-actual delta.
`output/workflows/runs/*.yaml` carry the OpenRouter request_id, model,
token usage, retry count, and per-call duration; the same metadata
reaches the entity/relation/evaluation artifacts via
`provenance.provider_metadata`.
Before scaling to the full book:
- Inspect each chapter's outputs and `generation-summary.md`
- Multiply the per-chapter `total_provider_calls_estimate` and
`estimated_cost_usd` by the chapter count and compare to your budget
- Decide on a final model and confirm the rate-table entry exists in
`src/infospace_bench/model_rates.yaml` or your workspace override
The optional live-smoke test in `tests/test_openrouter_live.py` is
skipped unless both `OPENROUTER_API_KEY` and
`INFOSPACE_BENCH_ENABLE_LIVE_OPENROUTER=1` are set. It runs a single
chapter through the same path and asserts the provider metadata
plumb-through.
### Live runs with `--provider routing`
When the routing CLI is what you want to exercise live, swap
`--provider openrouter --model ...` for the routing pair:
```bash
infospace-bench generate from-source ./LEFEVRE.epub \
--workspace ./infospaces \
--slug reminiscences-routed \
--name "Reminiscences (Routed)" \
--profile trading-literature \
--provider routing \
--routing-config ./examples/routing/trading-literature.yaml \
--chapter I \
--apply
```
`examples/routing/trading-literature.yaml` is a checked-in starting
config: cheap candidates for summary/evaluation, smart candidates for
entity/relation, a `claude_code` baseline rule for future shadow
sampling, and a workspace-relative `output/routing/quality.jsonl`
ledger so adaptive observations stay with the workspace.
`--quality-floor <float>` on the same command overrides the config's
`default_quality_floor` for a single invocation — useful for
tightening the bar for a specific run without editing the file. The
ledger fills up as the `AdaptiveRoutingPolicy` records each
observation; later runs against the same workspace get the benefit
without re-grading from scratch.
The parallel live-smoke test
(`test_provider_routing_one_chapter_live_smoke`) is also gated on
`INFOSPACE_BENCH_ENABLE_LIVE_OPENROUTER=1` + `OPENROUTER_API_KEY` and
asserts the per-stage adapter-choices report section names the routed
model.
### Budget and usage registry
Every `generate plan` invocation appends a compact snapshot to
`output/budget/plans.yaml` (deterministic 12-char `snapshot_id`, 50-entry
sliding retention). Every `generate run` invocation appends a usage
rollup to `output/budget/usage.yaml`, bucketed by `(workflow_id,
stage_id, provider, model)` with prompt and completion token counts,
known cost (when the adapter returned it), and estimated cost (when a
rate table entry matches the model).
The default rate table is bundled at
`src/infospace_bench/model_rates.yaml` and covers a handful of common
OpenRouter models at list price (see the file for the captured-at
timestamp). A workspace can override or extend entries by placing
`model-rates.yaml` next to its `infospaces/` directory; the workspace
file is overlaid on top of the package default so partial overrides
are fine.
Cost resolution order on each run: adapter-returned `cost` first, then
the rate table, then `cost_status="unknown"` (recorded explicitly,
never silently zeroed). The plan-vs-actual variance summary lands in
follow-on task T04.
### Profiles
Two profiles ship today:
- `general-knowledge` — durable concepts, claims, methods, people,
places, works, and objects across any source
- `trading-literature` — trading memoirs and market-structure texts;
tunes entity categories (`trader`, `market`, `strategy`, `error`,
`psychological_pattern`, `institution`, `instrument`,
`evidence_bearing_claim`), relation types (`cause_effect`,
`lesson_evidence`, `risk_mitigation`, `actor_venue`,
`strategy_outcome`), and evaluation criteria (`groundedness`,
`lesson_clarity`, `historical_context`, `overgeneralization_risk`)
Select via `--profile trading-literature` on `generate init` or
`generate from-source`. The generic profile remains the default.
### Scale-aware plan
`generate plan` returns a compact estimate by default — counts of selected
chunks, calls per workflow, prompt-word and token estimates, and a rough
USD cost when `--cost-per-1k` is supplied. Long corpora no longer dump
hundreds of full prompts unless `--full` is set.
```bash
infospace-bench generate plan ./infospaces/book-space \
--from-chapter 1 --to-chapter 3 \
--cost-per-1k 0.30 \
--max-calls 50 \
--cost-cap 2.00
```
Selection filters:
- `--chapter LABEL` (repeatable) — match a chapter by roman/arabic label
or numeric value (e.g. `--chapter I` or `--chapter 2`)
- `--from-chapter N` / `--to-chapter N` — numeric chapter range
- `--chunk ID` (repeatable) — exact source chunk id (e.g.
`chapter-01-part-002`)
Budget flags `--max-calls` and `--cost-cap` are reported as
`exceeds_max_calls` / `exceeds_cost_cap` booleans in the summary, so a
caller can fail fast before invoking `run`. Use `--full` to opt back into
the full per-workflow plan with prompts for deep inspection.
## OpenRouter
Live model calls are explicit:
```bash
export OPENROUTER_API_KEY=...
infospace-bench generate run ./infospaces/book-space \
--provider openrouter \
--model openai/gpt-4o-mini \
--stage all
```
Choose the `--model` value from OpenRouter model IDs. The API key is read from
`OPENROUTER_API_KEY`; it is not written to `infospace.yaml`. Default tests never
make live provider calls.
## Resume
Use resume for interrupted or reviewed runs:
```bash
infospace-bench generate resume ./infospaces/book-space \
--provider openrouter \
--model openai/gpt-4o-mini
```
Unchanged completed runs are skipped. Use `--force` when you intentionally want
to rerun completed work. Stale status is reported when source artifact digests
or installed profile/template files change.
## Review Path
After generation:
- inspect `artifacts/sources/` for normalized input chunks
- inspect `artifacts/entities/` and `artifacts/relations/` for generated claims
- inspect `output/evaluations/` for rubric output
- run `infospace-bench validate <root>` and `infospace-bench graph <root>`
- review `reports/generation-summary.md`
Move from the generic profile to a specialized profile when the source domain
needs stricter terminology, narrower extraction granularity, or a discipline
lens such as VSM.