Ship a starter model rate table at src/infospace_bench/model_rates.yaml (prompt_per_1k / completion_per_1k for the OpenRouter models we have actually touched: gpt-4o, gpt-4o-mini, gpt-4-turbo, claude 3.5 sonnet and haiku, claude 3 opus, gemini 1.5 flash/pro, llama 3.1 70b) and a load_rate_table() / estimate_cost_usd() pair that overlays an optional <workspace>/model-rates.yaml on top of the bundled defaults. generate run now passes a workspace-aware cost_resolver into record_run_usage, so cost_usd_estimated lands on every usage bucket whose model matches the table. Adapter-returned cost still wins (cost_status="known"); rate-table cost is reported under cost_status="estimated"; unmatched models are recorded as cost_status="unknown" rather than silently zeroed. Rate-table file is listed in pyproject.toml package-data so pip-installed users keep the defaults. 106 tests pass. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
5.5 KiB
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:
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
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.
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 sourcetrading-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.
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 Ior--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:
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:
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/andartifacts/relations/for generated claims - inspect
output/evaluations/for rubric output - run
infospace-bench validate <root>andinfospace-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.