ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/gaia-experience/AWorld/examples/browser_use/common.py

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+# coding: utf-8
+
+import json
+import traceback
+import uuid
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Optional, Dict, List
+
+from openai import RateLimitError
+from pydantic import BaseModel, ConfigDict, Field
+
+from aworld.core.common import ActionResult
+
+
+class PolicyMetadata(BaseModel):
+    """Metadata for a single step including timing information"""
+    start_time: float
+    end_time: float
+    number: int
+    input_tokens: int
+
+    @property
+    def duration_seconds(self) -> float:
+        """Calculate step duration in seconds"""
+        return self.end_time - self.start_time
+
+
+class AgentBrain(BaseModel):
+    """Current state of the agent"""
+    evaluation_previous_goal: str = None
+    memory: str = None
+    thought: str = None
+    next_goal: str = None
+
+
+class AgentHistory(BaseModel):
+    """History item for agent actions"""
+    model_output: Optional[BaseModel] = None
+    result: List[ActionResult]
+    metadata: Optional[PolicyMetadata] = None
+    content: Optional[str] = None
+    base64_img: Optional[str] = None
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    def model_dump(self, **kwargs) -> Dict[str, Any]:
+        """Custom serialization handling"""
+        return {
+            'model_output': self.model_output.model_dump() if self.model_output else None,
+            'result': [r.model_dump(exclude_none=True) for r in self.result],
+            'metadata': self.metadata.model_dump() if self.metadata else None,
+            'content': self.xml_content,
+            'base64_img': self.base64_img
+        }
+
+
+class AgentHistoryList(BaseModel):
+    """List of agent history items"""
+    history: List[AgentHistory]
+
+    def total_duration_seconds(self) -> float:
+        """Get total duration of all steps in seconds"""
+        total = 0.0
+        for h in self.history:
+            if h.metadata:
+                total += h.metadata.duration_seconds
+        return total
+
+    def save_to_file(self, filepath: str | Path) -> None:
+        """Save history to JSON file with proper serialization"""
+        try:
+            Path(filepath).parent.mkdir(parents=True, exist_ok=True)
+            data = self.model_dump()
+            with open(filepath, 'w', encoding='utf-8') as f:
+                json.dump(data, f, indent=2)
+        except Exception as e:
+            raise e
+
+    def model_dump(self, **kwargs) -> Dict[str, Any]:
+        """Custom serialization that properly uses AgentHistory's model_dump"""
+        return {
+            'history': [h.model_dump(**kwargs) for h in self.history],
+        }
+
+    @classmethod
+    def load_from_file(cls, filepath: str | Path) -> 'AgentHistoryList':
+        """Load history from JSON file"""
+        with open(filepath, 'r', encoding='utf-8') as f:
+            data = json.load(f)
+        return cls.model_validate(data)
+
+
+class AgentError:
+    """Container for agent error handling"""
+    VALIDATION_ERROR = 'Invalid model output format. Please follow the correct schema.'
+    RATE_LIMIT_ERROR = 'Rate limit reached. Waiting before retry.'
+    NO_VALID_ACTION = 'No valid action found'
+
+    @staticmethod
+    def format_error(error: Exception, include_trace: bool = False) -> str:
+        """Format error message based on error type and optionally include trace"""
+        if isinstance(error, RateLimitError):
+            return AgentError.RATE_LIMIT_ERROR
+        if include_trace:
+            return f'{str(error)}\nStacktrace:\n{traceback.format_exc()}'
+        return f'{str(error)}'
+
+
+class AgentState(BaseModel):
+    """Holds all state information for an Agent"""
+
+    agent_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
+    n_steps: int = 1
+    consecutive_failures: int = 0
+    last_result: Optional[List['ActionResult']] = None
+    history: AgentHistoryList = Field(default_factory=lambda: AgentHistoryList(history=[]))
+    last_plan: Optional[str] = None
+    paused: bool = False
+    stopped: bool = False
+
+
+@dataclass
+class AgentStepInfo:
+    number: int
+    max_steps: int
+
+    def is_last_step(self) -> bool:
+        """Check if this is the last step"""
+        return self.number >= self.max_steps - 1