Costs a trace using each step's own model and counting only the calls that
were issued: a call served from a gr_cache() or a
gr_replay_client() spent nothing, however many tokens its prompt contained.
Value
A data frame with one row per model: model, calls, paid_calls,
paid_in, paid_out, usd. sum(x$usd) is the run's cost. A model with
no registered price contributes NA, so a total that silently omitted an
unpriced model is impossible.
Details
This is why the token totals on gr_trace_summary() are not a bill. They
report how large the prompts and replies were, which is the right measure of
a run's shape; a fully cached re-run has the same shape as the original and
cost nothing at all.
Examples
cl <- gr_mock_client(function(m, p) "Revenue was 45.2 million dollars.")
ans <- answer_document(readgpt_example(), "What was revenue?", "fast", client = cl)
#> Using cached ingestion for this document + settings.
#> Segmenting with 'paragraph' (cap 4000 tokens, overlap 0).
#> Reading with 'stuff' (all|1|none) over 1 chunk(s).
gr_trace_cost(ans$trace)
#> model calls paid_calls paid_in paid_out usd
#> 1 gpt-5.6-terra 1 1 595 13 0.001346
# Priced by the model on the STEP (the recipe's model), not by the mock
# that answered. A cached re-run costs nothing for a different reason:
# paid_calls falls to zero while calls does not.
cache <- gr_cache(file.path(tempdir(), "readgpt-cost-example"))
again <- answer_document(readgpt_example(), "What was revenue?", "fast",
client = gr_cache_client(cl, cache))
#> Using cached ingestion for this document + settings.
#> Segmenting with 'paragraph' (cap 4000 tokens, overlap 0).
#> Reading with 'stuff' (all|1|none) over 1 chunk(s).
twice <- answer_document(readgpt_example(), "What was revenue?", "fast",
client = gr_cache_client(cl, cache))
#> Using cached ingestion for this document + settings.
#> Segmenting with 'paragraph' (cap 4000 tokens, overlap 0).
#> Reading with 'stuff' (all|1|none) over 1 chunk(s).
gr_trace_cost(twice$trace)[c("calls", "paid_calls", "usd")]
#> calls paid_calls usd
#> 1 1 0 0