q792602257
a5aeb8889c
Tests / Test failed: 2, passed: 849
- 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
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
from __future__ import annotations
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from collections import deque
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from dataclasses import dataclass, field
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from datetime import datetime
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from typing import Any
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from core.models import Scene, utc_now
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from semantic.models import SemanticScene
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from world.config import DEFAULT_HISTORY_SIZE
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@dataclass(frozen=True)
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class WorldEvent:
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action: str
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success: bool
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# Optional for backward compatibility; new entries created by AIPlanner
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# paths leave this as None and use rationale/thinking instead.
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scene_summary: SemanticScene | Scene | None = None
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rationale: str | None = None
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thinking: str | None = None
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page: str | None = None
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timestamp: datetime = field(default_factory=utc_now)
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def to_dict(self) -> dict[str, Any]:
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return {
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"scene_summary": self.scene_summary.to_dict() if self.scene_summary is not None else None,
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"action": self.action,
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"success": self.success,
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"rationale": self.rationale,
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"thinking": self.thinking,
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"page": self.page,
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"timestamp": self.timestamp.isoformat(),
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}
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@dataclass
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class WorldState:
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current_app: str | None = None
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current_page: str | None = None
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variables: dict[str, Any] = field(default_factory=dict)
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history: deque[WorldEvent] = field(
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default_factory=lambda: deque(maxlen=DEFAULT_HISTORY_SIZE)
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)
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@classmethod
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def with_history_bound(cls, history_size: int) -> "WorldState":
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maxlen = history_size if history_size > 0 else DEFAULT_HISTORY_SIZE
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return cls(history=deque(maxlen=maxlen))
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def to_dict(self) -> dict[str, Any]:
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return {
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"current_app": self.current_app,
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"current_page": self.current_page,
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"variables": dict(self.variables),
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"history": [event.to_dict() for event in self.history],
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}
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