ThinkLess 0.2.0

0.2.0 - 2026-09-25

First release on PyPI.

Added

• OpenRouterLLM and the openrouter:<slug> spec: one key for models from
  Anthropic, OpenAI, Google, Qwen, DeepSeek and others.
• Billed cost: Completion.cost_usd and ProviderResult.cost_usd carry the
  cost a backend reports (OpenRouter does); the engine prefers it over the
  price table and records cost_source on spans. Benchmark reports add a
  billed cost row, and the intent benchmark reports cost per 1k per provider
  and per cascade threshold.
• --reasoning for every CLI command that builds an LLM, and
  from_spec(..., reasoning=...), mapped to OpenRouter's reasoning,
  Anthropic's effort and local thinking switches.
• HFClassifier: any Hugging Face text-classification model as a provider for
  the questions it was trained for.
• load_env(), and the CLI reads ./.env without overriding set variables.
• Escalation context: when a question escalates to the LLM decider, the
  engine includes the decisions already settled in the same batch. It removed
  false injection flags on requests for a human that appeared when an LLM saw
  the injection question alone. On by default (Engine(escalation_context=...)).
• The System One wire format is tested against TypeSafe's official SDK models.

Fixed

• LLMDecider detects replies cut off at the token limit, logs why, and
  retries once with a larger budget instead of abstaining silently.
• The OpenAI-compatible client retries once without response_format when an
  endpoint rejects JSON mode.
• A redaction test that failed about one run in fifty when a random span id
  contained its marker.

0.1.0 - 2026-09-25

First public release.

Added

• Typed questions: Choice, Score, YesNo and Extract, following the
  System One wire format.
• Engine with a confidence cascade across providers, batched provider calls,
  accepted, uncertain and abstained statuses, per-question and
  per-provider thresholds ("question@provider"), question-level provider
  allowlists, and async variants of every call.
• Normalized confidence, (k * p_max - 1) / (k - 1), applied uniformly across
  providers.
• Decision providers: Rules, GLiNER (GLiNER 2.5), Laya, SystemOne
  (TypeSafe Jev and compatible servers such as Kev and OpenJev) and
  LLMDecider.
• LLM backends: TransformersLLM, OpenAICompatibleLLM (OpenAI, Ollama, vLLM
  and others) and AnthropicLLM with server-side refusal fallbacks.
• Tracing: spans for runs, steps, decisions, provider attempts, generations,
  tools and rules; JSONL, memory, console and OpenTelemetry sinks; run
  summaries with decisions by plane, escalations, tokens, cost and time by
  plane; content capture switch; a self-contained HTML viewer.
• A price table with sources, overridable with THINKLESS_PRICING.
• The support demo: an agent, a mock store, 53 labeled tickets and a separate
  48-row calibration set.
• Benchmarks: the support benchmark across llm, hybrid and models modes,
  and intent benchmarks on Banking77, CLINC150 and Emotion with a simulated
  cascade.
• thinkless CLI: doctor, demo, bench support, bench intents,
  calibrate, trace ls, trace show and trace view.