6 Commits

Include renames

Author	SHA1	Message	Date
showtan001	44e1a6651a	Support multimodal planner scenes without OCR	2026-08-30 21:56:11 +08:00
q792602257	358f4623ba	feat(planner): add execution context to prompts	2026-07-16 10:25:20 +08:00
q792602257	d69be48f96	feat(planner): persist reusable action semantics	2026-07-15 18:14:28 +08:00
q792602257	a5aeb8889c	feat(runtime): add planner reflection history with rationale and thinking ... - ToolCallDecision captures thinking blocks and pre-tool text output - AnthropicToolCallingClient supports optional extended thinking (budget_tokens + beta header) - PlannedStep carries rationale and thinking from each LLM decision - WorldEvent replaces scene_summary with rationale/thinking/page fields (backward-compatible) - AI planner system prompt instructs reflection before each tool call - _history_summary() emits compact {page, rationale, action, success} dicts - Cloud DB migration 0011 adds nullable rationale/thinking columns to planner_decision_log - OpenAI client extracts reasoning_content into thinking field	2026-07-15 12:43:22 +08:00
q792602257andClaude Opus 4.6	ec261d57c2	feat: surface task execution progress across Host Agent and Cloud ... Host Agent now persists step-level execution detail locally (via a real TaskMetadataStore/Timeline wired into TaskRunner) and reports a bounded in-progress snapshot piggybacked on lease renewal. Cloud persists that snapshot per active assignment and exposes it through the existing task list/detail query path; Cloud Console renders it as a live badge. Host Agent's local console gains authenticated, read-only task list and detail/timeline pages (same-origin, server-rendered) with inlined screenshots. Also fixes a pre-existing gap in the shared Timeline: the actual per-step LLM prompt is now recorded instead of the task goal, benefiting both Runtime and Host Agent consoles. When a host uses the cloud planner transport, each decide call's prompt and resulting tool decision are durably logged in a new planner_decision_log table (with bounded retention) and browsable from Cloud Console; direct-transport hosts explicitly surface a "not reported" state. Includes Alembic migrations 0008 (progress columns on scheduled_tasks) and 0009 (planner_decision_log), bounded Host-Agent-local retention, dual-backend repository parity, and Vitest + pytest coverage. Task 6.5 (manual end-to-end device verification) remains. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-07-14 12:47:49 +08:00
q792602257andClaude Sonnet 5	61ff3b425d	feat(agent-runtime): add LLM-driven AI Planner with dual-provider tool calling ... Replaces the stub Planner's fixed describe_screen/[] behavior with a real decision-maker: AIPlanner uses native tool/function calling (Anthropic or OpenAI, pluggable via AI_PLANNER_PROVIDER) to select exactly one grounded action per turn, with an explicit finish_task(success, reason) tool for completion/failure instead of an ambiguous "no tool call" signal. Default disabled (AI_PLANNER_ENABLED=false) and additive; TaskRunner falls back to the existing stub Planner unchanged when disabled. Amends CONSTITUTION.md's Perception Boundary with one narrow exception: only the AI Planner may receive the current step's raw screenshot bytes alongside Scene, for vision-grounded coordinate grounding. Also fixes a latent gap in TaskRunner.run(): observe/plan exceptions are now caught per iteration and turned into a failed task with a failure_reason, instead of propagating uncaught. openspec change: ai-planner-runtime. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-12 13:48:50 +08:00