The call record: every model call, for the operator's study (M6.6a)
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nisse-core records each model call of every agent into a file beside its
state store (<state>.calls.db), for the status page (L7, X6):

- the request body exactly as sent (never headers), the raw response with
  its reasoning, the model asked and the one that answered, time, tokens
  and llama-server's own prompt reuse (timings.cache_n);
- its work item, role, run and purpose: Driver.run and nisse-dev's
  delegation loop open runs, nested; compaction, expert consults, the
  classifier and the go-ahead reader label their calls;
- provenance, worked out in BudgetedClient by comparing the events at
  each stage: each event sent with its log id and content as sent, which
  a compaction replaced, which fitting shortened (by how much) and
  dropped.

Content is stored once by hash, compressed. It is diagnostic only: the
agent never reads it, a failed write is logged once and recording stops
while the call goes on, and the file is deleted when the agent starts,
so its layout never migrates; CallReader refuses a layout it doesn't
know. While recording, the system prompt ends with one sentence saying
so. `call_record: false` in either agent's YAML turns it off.

The benchmark records each run beside that run's own state store, and
`--keep-runs DIR` keeps both for the page.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk
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dongarandClaude Opus 5.5 committed 2026-10-24 06:28:53 +00:00
1 parent cba35eb7d4
commit dd060566b2
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@@ -14,6 +14,7 @@ from nisse_core.gitea import GiteaClient
from nisse_core.knowledge.memory import Memory
from nisse_core.knowledge.vault import Vault
from nisse_core.loop.driver import Driver
from nisse_core.models import calls
from nisse_core.models.catalog import ModelCatalog, select_client
from nisse_core.models.compact import Compactor
from nisse_core.models.context import BudgetedClient
@@ -126,6 +127,9 @@ def make_llm_clients(
assert facts.max_input_tokens is not None # require_limits checked
return facts.max_input_tokens, facts.max_output_tokens
# Both routes record into one file (L7).
recorder = calls.recorder_for(config.state_db, config.call_record, oplog)
def budgeted(client: object) -> BudgetedClient:
# Every request, on either route, is fitted to its model's window.
return BudgetedClient(
@@ -138,6 +142,7 @@ def make_llm_clients(
catalog.facts(m).supports_tool_choice is True
),
oplog=oplog, # a cut that fitting has to make is logged
call_recorder=recorder,
)
normalized = budgeted(