2 Commits

Include renames

Author	SHA1	Message	Date
dongarandClaude Opus 5.5	b934c46714	Enforce the tool-call contract, asking servers only where it works ... 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>	2026-09-24 22:54:49 +00:00
dongarandClaude Opus 5.5	494715efa9	Fit every model request to its context window ... 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>	2026-09-24 00:26:30 +00:00