Automated Timeline Generation

def extract_events_from_chat(messages):
    """Use an LLM to extract key events from incident chat."""
    conversation = "\n".join([
        f"[{m['timestamp']}] {m['user']}: {m['text']}"
        for m in messages
    ])

    response = openai.ChatCompletion.create(
        model="gpt-4",
        temperature=0.0,
        messages=[
            {
                "role": "system",
                "content": """Extract key events from this incident channel.
Return JSON array of events, each with:
- timestamp: ISO format
- event_type: one of [alert, investigation, action, observation, decision]
- description: what happened
- actor: who did it (or "system" for automated events)
- impact: effect on the system (if any)

Focus on factual events, not opinions or speculation."""
            },
            {"role": "user", "content": conversation}
        ]
    )
    return json.loads(response["choices"][0]["message"]["content"])

def merge_timeline(chat_events, alert_events, deploy_events):
    """Merge events from multiple sources into a single timeline."""
    all_events = []

    for e in chat_events:
        all_events.append({**e, "source": "chat"})

    for e in alert_events:
        all_events.append({
            "timestamp": e["created_at"],
            "event_type": "alert",
            "description": f"Alert: {e['name']} - {e['description']}",
            "actor": "system",
            "source": "pagerduty"
        })

    for e in deploy_events:
        all_events.append({
            "timestamp": e["deployed_at"],
            "event_type": "deploy",
            "description": f"Deploy: {e['service']} {e['version']}",
            "actor": e["deployer"],
            "source": "deploy_pipeline"
        })

    # Sort by timestamp
    all_events.sort(key=lambda x: x["timestamp"])

    # Deduplicate similar events
    return deduplicate_events(all_events)

def format_timeline(events):
    """Format events into a readable timeline."""
    lines = ["## Incident Timeline\n"]

    current_date = None
    for event in events:
        ts = datetime.fromisoformat(event["timestamp"])
        if ts.date() != current_date:
            current_date = ts.date()
            lines.append(f"\n### {current_date}\n")

        time_str = ts.strftime("%H:%M:%S")
        emoji = {"alert": "🚨", "action": "⚡", "observation": "👁️",
                 "decision": "📋", "deploy": "🚀"}.get(event["event_type"], "•")

        lines.append(f"**{time_str}** {emoji} {event['description']}")
        if event.get("actor") and event["actor"] != "system":
            lines.append(f"  — _{event['actor']}_")

    return "\n".join(lines)