dongarandClaude Opus 5.5
b934c46714
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The executor ended a milestone on any reply without a tool call, and
nothing held a model to the offered tools. Measured on the 4070:
tool_choice "required" is enforced by vLLM (local-fast) and Anthropic,
but qwen3-14b (local-coder) under it cannot stop and writes until the
output ceiling, a known model bug. So enforcement is asked for per
model, and the loop holds the contract itself everywhere.
- The catalog reads supports_tool_choice from LiteLLM's model_info;
BudgetedClient sends tool_choice only to models declared true, as
"required" on the normalized route and {"type": "any"} on the
Anthropic passthrough, and only when tools are offered
- The executor gains an explicit finish tool, the only way to end a
milestone. Finishing with nothing changed is refused once; a prose
reply gets one nudge, then escalates; a call to a tool not offered
counts toward failure_limit, like a failed command; calls after
finish are recorded as not run
- Clients record the model that actually answered. ModelFacts.answered
recognises a proxy fallback, which once credited Claude's answers to
a local model that could not call tools at all
- The context probe reports a fallback instead of trusting it; rerun,
both local models now refuse over-long prompts, as they should
- The capability matrix checks every answer came from the model asked,
that models call only offered tools, and that a declared
supports_tool_choice is true
- Spec A15 and the tuning guide say how enforcement is requested,
declared and backed up
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
"""Check a model's declared context window against what its server does.
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uv run python scripts/probe_context.py ALIAS [--config PATH]
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ALIAS is a LiteLLM model alias. The LiteLLM URL and token come from the agent
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config (NISSE_CONFIG, ./nisse-dev.yaml, or --config), with its secrets from
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the environment or .env. See docs/Tuning-Guide.md, "Declaring a local model's
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limits", and nisse_dev/probe.py for what the verdicts mean.
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"""
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import argparse
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import os
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import sys
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from pathlib import Path
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import httpx
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from nisse_dev.catalog import ModelCatalog
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from nisse_dev.config import AgentConfig, ConfigError
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from nisse_dev.envfile import load_env_file
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from nisse_dev.probe import probe
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def main() -> int:
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parser = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
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parser.add_argument("alias", help="LiteLLM model alias to probe")
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parser.add_argument("--config", help="agent config file to take LiteLLM from")
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parser.add_argument(
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"--max-probe-tokens",
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type=int,
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default=64_000,
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help="refuse to send a prompt larger than this (default: %(default)s)",
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)
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args = parser.parse_args()
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load_env_file(Path(os.environ.get("NISSE_ENV", ".env")).expanduser())
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try:
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config = (
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AgentConfig.from_file(Path(args.config))
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if args.config
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else AgentConfig.load()
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)
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except ConfigError as exc:
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print(exc, file=sys.stderr)
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return 2
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catalog = ModelCatalog.discover(config.llm_base_url, config.llm_token)
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facts = catalog.facts(args.alias)
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declared = facts.max_input_tokens
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if declared is None:
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print(
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f"LiteLLM declares no max_input_tokens for {args.alias}; set one first",
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file=sys.stderr,
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)
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return 1
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if declared * 1.5 > args.max_probe_tokens:
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print(
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f"{args.alias} declares {declared} tokens; probing would send about "
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f"{int(declared * 1.5)}. Raise --max-probe-tokens to allow it.",
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file=sys.stderr,
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)
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return 1
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with httpx.Client(
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base_url=config.llm_base_url.rstrip("/"),
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headers={"Authorization": f"Bearer {config.llm_token}"},
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timeout=600,
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) as http:
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result = probe(http, args.alias, declared, facts.backing)
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print(f"{args.alias}: {result.message}")
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return 0 if result.verdict in ("matches", "refuses", "declared_conservative") else 1
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if __name__ == "__main__":
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raise SystemExit(main())
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