3.4History Management Strategies

The history buffer directly affects agent performance. Too little history causes loops; too much wastes tokens.

Strategy 1: Fixed Window

# Keep the last N steps
self.history = self.history[-5:]

Simple and predictable. Works well for tests under 15 steps.

Strategy 2: Summarized History

def summarize_history(self) -> str:
    """Compress history into a summary to save tokens."""
    if len(self.history) <= 3:
        return json.dumps(self.history)

    # Keep first step, summary of middle, and last 2 steps
    summary = f"Started at {self.history[0]['state_url']}. "
    summary += f"Took {len(self.history) - 3} intermediate steps. "
    if any(h.get('result') == 'error' for h in self.history[1:-2]):
        summary += "Encountered errors along the way. "
    summary += f"Recent actions: {json.dumps(self.history[-2:])}"
    return summary

Saves tokens while preserving context for long-running agents.

Strategy 3: Milestone-Based History

def milestone_history(self) -> list[dict]:
    """Keep only steps that represent significant state changes."""
    milestones = []
    last_url = None
    for step in self.history:
        # URL changed = navigation milestone
        if step.get("state_url") != last_url:
            milestones.append(step)
            last_url = step.get("state_url")
        # Error occurred = error milestone
        elif step.get("result") == "error":
            milestones.append(step)
        # Assertion made = assertion milestone
        elif "ASSERT" in step.get("action", ""):
            milestones.append(step)
    return milestones[-5:]  # Keep last 5 milestones

Best for long multi-page workflows where only navigation and assertions matter.