Fit every model request to its context window
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Every turn re-sent the whole transcript with nothing checking it against
the model's window. On a local model that fails silently: Ollama drops
the start of an over-long prompt, which is where the system prompt and
the plan are. Measured on the Jetson's llama3.2, cut at 4096 tokens with
no error.

- The model catalog reads max_input_tokens and max_output_tokens from
  LiteLLM's model_info, and startup refuses a role on a model with no
  declared window
- BudgetedClient wraps both routes. It fits the canonical events before
  rendering: older tool results cut to head and tail, then the oldest
  turns dropped with a note, keeping calls with their results; a request
  that still cannot fit fails with ContextOverflow and is never sent.
  The output ceiling is the smaller of config and the model's limit
- Tokens are estimated from characters, pessimistically, and the
  estimate is corrected from reported prompt sizes, only ever upward
- The executor takes its scope from the log: the latest plan, which is
  the approved milestone plan, goes in its system prompt, and it sees
  only events after it
- Tool output keeps its head and, mostly, its tail, so a test runner's
  failure summary survives truncation
- tuning.context.keep_recent_turns and safety_margin are new knobs
- scripts/probe_context.py checks a declared window against what the
  server does; it confirmed llama3.2 cuts at the declared 4096
- The tuning guide covers the budget, declaring a local model's limits,
  and the probe

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
This commit is contained in:
dongarandClaude Opus 5.5 committed 2026-09-24 00:26:30 +00:00
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@@ -3,7 +3,9 @@
import pytest
from nisse_dev.canonical import AssistantText, StoredEvent, UserMessage
from nisse_dev.catalog import ModelCatalog
from nisse_dev.config import AgentConfig
from nisse_dev.context import BudgetedClient
from nisse_dev.llm import LiteLLMClient
pytestmark = pytest.mark.integration
@@ -25,3 +27,35 @@ def test_executor_model_completes_via_litellm(
texts = [e.text for e in result if isinstance(e, AssistantText)]
assert texts, f"no assistant text in {result!r}"
assert "pong" in texts[0].lower()
def test_declared_limits_reach_a_budgeted_request(
litellm: LiteLLMClient, live_config: AgentConfig
) -> None:
"""The whole chain: LiteLLM's model_info, the catalog, the budget, and a
real request through the proxy with the ceiling the budget chose."""
catalog = ModelCatalog.discover(live_config.llm_base_url, live_config.llm_token)
roles = live_config.roles.pinned()
catalog.require_limits(roles) # every test role has a declared window
model = live_config.roles.executor
facts = catalog.facts(model)
client = BudgetedClient(
litellm,
lambda m: (
catalog.facts(m).max_input_tokens,
catalog.facts(m).max_output_tokens,
),
max_output_tokens=live_config.max_output_tokens,
)
assert client.budget_for(model).window == facts.max_input_tokens
events = [
StoredEvent(
id=1, ts="t", event=UserMessage(text="Reply with exactly: pong", source="t")
)
]
produced = client.complete(events, None, model, system="Be terse.")
texts = [e.text for e in produced if isinstance(e, AssistantText)]
assert texts and "pong" in texts[0].lower()
assert client.last_usage.get("input", 0) > 0