feat(c-generative-ui): airline operations KPI dashboard (PR 3 of 4)

cockpit/chat/generative-ui/python/prompts/dashboard.md

@@ -0,0 +1,74 @@
+# Airline Operations Dashboard Agent
+
+You are a dashboard agent that builds interactive airline-operations KPI dashboards using a JSON render spec format. You have access to tools that query an airline's flight, fleet, and on-time performance data.
+
+## Your Behavior
+
+### First message (no existing dashboard)
+
+1. Generate a complete dashboard layout as a JSON render spec (see format below)
+2. Call ALL four data tools to populate the dashboard
+3. After the tools return, provide a brief conversational summary
+
+### Follow-up messages (dashboard already exists)
+
+Categorize the user's request:
+
+- **Data change** (e.g., "show last 6 months", "filter to cancelled flights only"): Call only the relevant tool(s) with updated parameters. Do NOT regenerate the spec. Just respond conversationally confirming the update.
+- **Structural change** (e.g., "add a new chart", "remove the table"): Regenerate the full spec with the modification, then call tools to populate any new components.
+- **Question about data** (e.g., "why did on-time % dip in December?"): Respond conversationally in plain text. Do NOT output JSON or call tools.
+
+## JSON Render Spec Format
+
+Your spec response MUST be raw JSON only — no markdown, no code fences, no surrounding text.
+
+```
+{
+  "elements": { [key: string]: Element },
+  "root": string
+}
+```
+
+An Element has:
+```
+{
+  "type": string,
+  "props": { ... },
+  "children?": string[]
+}
+```
+
+### Props with State Bindings
+
+Use `{ "$state": "/json/pointer/path" }` for props that will be populated by tool results. The dashboard renders skeleton placeholders until the data arrives.
+
+Example: `"value": { "$state": "/on_time/value" }` — this prop will be populated when the `/on_time/value` state path receives data.
+
+## Available Component Types
+
+| Type | Props | Children | Description |
+|------|-------|----------|-------------|
+| `dashboard_grid` | *(none)* | Yes | Top-level vertical layout with section spacing |
+| `container` | `direction` ("row" or "column") | Yes | Flex layout container |
+| `stat_card` | `label` (string), `value` ($state), `delta` ($state) | No | Metric summary card |
+| `line_chart` | `title` (string), `data` ($state array), `xKey` (string), `yKey` (string) | No | SVG line chart |
+| `bar_chart` | `title` (string), `data` ($state array), `labelKey` (string), `valueKey` (string) | No | SVG bar chart |
+| `data_grid` | `title` (string), `rows` ($state array), `columns` (string[]) | No | Data table |
+
+## State Path Conventions
+
+Use these state paths to match what the tools populate:
+
+- `/on_time/value`, `/on_time/delta` — from query_airline_kpis
+- `/flights_today/value`, `/flights_today/delta` — from query_airline_kpis
+- `/avg_delay/value`, `/avg_delay/delta` — from query_airline_kpis
+- `/load_factor/value`, `/load_factor/delta` — from query_airline_kpis
+- `/on_time_trend` — array from query_on_time_trend
+- `/flights_by_airline` — array from query_flights_by_airline
+- `/recent_disruptions` — array from query_recent_disruptions
+
+## Example Spec
+
+For "show me the dashboard":
+
+{"elements":{"root":{"type":"dashboard_grid","children":["stats_row","charts_row","table_section"]},"stats_row":{"type":"container","props":{"direction":"row"},"children":["on_time_card","flights_card","delay_card","load_card"]},"on_time_card":{"type":"stat_card","props":{"label":"On-time %","value":{"$state":"/on_time/value"},"delta":{"$state":"/on_time/delta"}}},"flights_card":{"type":"stat_card","props":{"label":"Flights Today","value":{"$state":"/flights_today/value"},"delta":{"$state":"/flights_today/delta"}}},"delay_card":{"type":"stat_card","props":{"label":"Avg Delay","value":{"$state":"/avg_delay/value"},"delta":{"$state":"/avg_delay/delta"}}},"load_card":{"type":"stat_card","props":{"label":"Load Factor","value":{"$state":"/load_factor/value"},"delta":{"$state":"/load_factor/delta"}}},"charts_row":{"type":"container","props":{"direction":"row"},"children":["trend_chart","airline_chart"]},"trend_chart":{"type":"line_chart","props":{"title":"On-time % Trend","data":{"$state":"/on_time_trend"},"xKey":"month","yKey":"on_time_pct"}},"airline_chart":{"type":"bar_chart","props":{"title":"Flights by Airline","data":{"$state":"/flights_by_airline"},"labelKey":"airline","valueKey":"count"}},"table_section":{"type":"data_grid","props":{"title":"Recent Disruptions","rows":{"$state":"/recent_disruptions"},"columns":["flight_number","type","minutes","route","date"]}}},"root":"root"}

cockpit/chat/generative-ui/python/src/dashboard_tools.py

@@ -1,97 +1,117 @@
-"""Mock SaaS metrics data tools for the generative-ui dashboard example."""
+"""Aviation KPI tools for the c-generative-ui standalone demo.
+
+Standalone copy — analytics constants are inlined here because this
+backend has no shared aviation_data.py module. Mirrors the umbrella
+backend at cockpit/langgraph/streaming/python/src/dashboard_tools.py.
+"""
 
 from langchain_core.tools import tool
 
-# ── Hardcoded SaaS dataset ──────────────────────────────────────────────────
-
-_MRR_TREND = [
-    {"month": "2025-05", "mrr": 28000},
-    {"month": "2025-06", "mrr": 29500},
-    {"month": "2025-07", "mrr": 30200},
-    {"month": "2025-08", "mrr": 31800},
-    {"month": "2025-09", "mrr": 32500},
-    {"month": "2025-10", "mrr": 33000},
-    {"month": "2025-11", "mrr": 34200},
-    {"month": "2025-12", "mrr": 35800},
-    {"month": "2026-01", "mrr": 37000},
-    {"month": "2026-02", "mrr": 38500},
-    {"month": "2026-03", "mrr": 40200},
-    {"month": "2026-04", "mrr": 42000},
+# ── Analytics fixtures (inlined; no aviation_data.py in standalone) ─────────
+
+KPI_SNAPSHOT = {
+    "on_time_pct": 84.2,
+    "on_time_delta": "+1.4%",
+    "flights_today": 312,
+    "flights_today_delta": "+8",
+    "avg_delay_min": 12,
+    "avg_delay_delta": "-2 min",
+    "load_factor_pct": 78.5,
+    "load_factor_delta": "+0.6%",
+}
+
+ON_TIME_TREND = [
+    {"month": "2025-05", "on_time_pct": 82.4},
+    {"month": "2025-06", "on_time_pct": 81.1},
+    {"month": "2025-07", "on_time_pct": 79.8},
+    {"month": "2025-08", "on_time_pct": 80.5},
+    {"month": "2025-09", "on_time_pct": 83.2},
+    {"month": "2025-10", "on_time_pct": 84.0},
+    {"month": "2025-11", "on_time_pct": 82.6},
+    {"month": "2025-12", "on_time_pct": 78.9},
+    {"month": "2026-01", "on_time_pct": 80.2},
+    {"month": "2026-02", "on_time_pct": 81.7},
+    {"month": "2026-03", "on_time_pct": 82.8},
+    {"month": "2026-04", "on_time_pct": 84.2},
 ]
 
-_SUBSCRIBERS_BY_PLAN = [
-    {"plan": "free", "count": 1200},
-    {"plan": "starter", "count": 850},
-    {"plan": "pro", "count": 420},
-    {"plan": "enterprise", "count": 95},
+FLIGHTS_BY_AIRLINE = [
+    {"airline": "American", "count": 87},
+    {"airline": "United",   "count": 92},
+    {"airline": "Delta",    "count": 78},
+    {"airline": "JetBlue",  "count": 55},
 ]
 
-_CHURNED_ACCOUNTS = [
-    {"name": "Acme Corp", "plan": "pro", "mrr_lost": 450, "date": "2026-04-01"},
-    {"name": "Widgetly", "plan": "starter", "mrr_lost": 120, "date": "2026-03-28"},
-    {"name": "DataPipe Inc", "plan": "enterprise", "mrr_lost": 2400, "date": "2026-03-25"},
-    {"name": "NovaTech", "plan": "pro", "mrr_lost": 450, "date": "2026-03-20"},
-    {"name": "CloudSync", "plan": "starter", "mrr_lost": 120, "date": "2026-03-15"},
-    {"name": "ByteForge", "plan": "pro", "mrr_lost": 450, "date": "2026-03-10"},
-    {"name": "Quantum Labs", "plan": "enterprise", "mrr_lost": 2400, "date": "2026-03-05"},
-    {"name": "FlowState", "plan": "starter", "mrr_lost": 120, "date": "2026-02-28"},
-    {"name": "CipherNet", "plan": "pro", "mrr_lost": 450, "date": "2026-02-20"},
-    {"name": "Luminary AI", "plan": "starter", "mrr_lost": 120, "date": "2026-02-15"},
+RECENT_DISRUPTIONS = [
+    {"flight_number": "UA123", "type": "delayed",   "minutes": 45, "route": "LAX→JFK", "date": "2026-05-14"},
+    {"flight_number": "AA456", "type": "cancelled", "minutes": 0,  "route": "JFK→LAX", "date": "2026-05-14"},
+    {"flight_number": "DL789", "type": "delayed",   "minutes": 22, "route": "ATL→ORD", "date": "2026-05-13"},
+    {"flight_number": "B6101", "type": "delayed",   "minutes": 68, "route": "BOS→MIA", "date": "2026-05-13"},
+    {"flight_number": "UA204", "type": "cancelled", "minutes": 0,  "route": "SFO→SEA", "date": "2026-05-12"},
+    {"flight_number": "AA318", "type": "delayed",   "minutes": 15, "route": "DFW→DEN", "date": "2026-05-12"},
+    {"flight_number": "DL552", "type": "delayed",   "minutes": 35, "route": "ATL→MIA", "date": "2026-05-11"},
+    {"flight_number": "B6217", "type": "delayed",   "minutes": 80, "route": "JFK→BOS", "date": "2026-05-11"},
+    {"flight_number": "UA640", "type": "cancelled", "minutes": 0,  "route": "ORD→DEN", "date": "2026-05-10"},
+    {"flight_number": "AA871", "type": "delayed",   "minutes": 25, "route": "LAX→DFW", "date": "2026-05-10"},
 ]
 
 
+# ── Tools ───────────────────────────────────────────────────────────────────
+
 @tool
-def query_mrr() -> dict:
-    """Get current Monthly Recurring Revenue (MRR) with month-over-month delta."""
-    current = _MRR_TREND[-1]["mrr"]
-    previous = _MRR_TREND[-2]["mrr"]
-    delta_pct = ((current - previous) / previous) * 100
-    total_subs = sum(p["count"] for p in _SUBSCRIBERS_BY_PLAN)
-    arpu = round(current / total_subs, 2)
+def query_airline_kpis() -> dict:
+    """Snapshot of operational KPIs across the fleet: on-time %, flights today,
+    average delay (minutes), and load factor."""
+    snap = KPI_SNAPSHOT
     return {
-        "mrr": {"value": current, "delta": f"+{delta_pct:.1f}%", "period": "month"},
-        "subscribers": {"total": total_subs, "delta": "+42"},
-        "churn": {"rate": "3.2%", "delta": "-0.4%"},
-        "arpu": {"value": f"${arpu:.2f}", "delta": "+$1.20"},
+        "on_time":       {"value": f"{snap['on_time_pct']}%",      "delta": snap["on_time_delta"]},
+        "flights_today": {"value": snap["flights_today"],          "delta": snap["flights_today_delta"]},
+        "avg_delay":     {"value": f"{snap['avg_delay_min']} min", "delta": snap["avg_delay_delta"]},
+        "load_factor":   {"value": f"{snap['load_factor_pct']}%",  "delta": snap["load_factor_delta"]},
     }
 
 
 @tool
-def query_subscribers_by_plan(plans: list[str] | None = None) -> list[dict]:
-    """Get subscriber counts broken down by plan tier.
+def query_on_time_trend(months: int = 12) -> list[dict]:
+    """On-time performance over time, as percentage by month.
 
     Args:
-        plans: Optional list of plan names to filter by (e.g., ["pro", "enterprise"]).
-               Returns all plans if not specified.
+        months: Number of months to return (default 12). Valid: 3, 6, 12, 24.
     """
-    if plans:
-        return [p for p in _SUBSCRIBERS_BY_PLAN if p["plan"] in plans]
-    return _SUBSCRIBERS_BY_PLAN
+    months = min(months, len(ON_TIME_TREND))
+    return ON_TIME_TREND[-months:]
 
 
 @tool
-def query_mrr_trend(months: int = 12) -> list[dict]:
-    """Get MRR trend over time.
+def query_flights_by_airline(airlines: list[str] | None = None) -> list[dict]:
+    """Daily flight counts per airline.
 
     Args:
-        months: Number of months to return (default 12). Valid values: 3, 6, 12, 24.
+        airlines: Optional filter list, e.g. ["American", "United"]. All four
+                  returned if omitted.
     """
-    months = min(months, len(_MRR_TREND))
-    return _MRR_TREND[-months:]
+    if airlines:
+        return [a for a in FLIGHTS_BY_AIRLINE if a["airline"] in airlines]
+    return FLIGHTS_BY_AIRLINE
 
 
 @tool
-def query_churned_accounts(limit: int = 5, plan: str | None = None) -> list[dict]:
-    """Get recently churned accounts.
+def query_recent_disruptions(limit: int = 5, type: str | None = None) -> list[dict]:
+    """Recent flight delays or cancellations.
 
     Args:
-        limit: Maximum number of accounts to return (default 5).
-        plan: Optional plan name to filter by (e.g., "enterprise").
+        limit: Maximum entries to return (default 5).
+        type: Optional filter, "delayed" or "cancelled".
     """
-    filtered = _CHURNED_ACCOUNTS
-    if plan:
-        filtered = [a for a in filtered if a["plan"] == plan]
+    filtered = RECENT_DISRUPTIONS
+    if type:
+        filtered = [d for d in filtered if d["type"] == type]
     return filtered[:limit]
 
 
-ALL_TOOLS = [query_mrr, query_subscribers_by_plan, query_mrr_trend, query_churned_accounts]
+ALL_TOOLS = [
+    query_airline_kpis,
+    query_on_time_trend,
+    query_flights_by_airline,
+    query_recent_disruptions,
+]

cockpit/chat/generative-ui/python/src/graph.py

@@ -1,4 +1,4 @@
-"""Multi-node LangGraph graph for the SaaS metrics dashboard.
+"""Multi-node LangGraph graph for the airline operations KPI dashboard.
 
 Flow:
   router → generate_shell (first turn) or plan_tools (follow-up)
@@ -78,17 +78,17 @@ async def emit_state(state: DashboardState) -> DashboardState:
             except (json.JSONDecodeError, TypeError):
                 continue
 
-            if msg.name == "query_mrr":
+            if msg.name == "query_airline_kpis":
                 for section_key, section_val in data.items():
                     if isinstance(section_val, dict):
                         for k, v in section_val.items():
                             tool_results[f"/{section_key}/{k}"] = v
-            elif msg.name == "query_subscribers_by_plan":
-                tool_results["/subscribers_by_plan"] = data
-            elif msg.name == "query_mrr_trend":
-                tool_results["/mrr_trend"] = data
-            elif msg.name == "query_churned_accounts":
-                tool_results["/churned_accounts"] = data
+            elif msg.name == "query_on_time_trend":
+                tool_results["/on_time_trend"] = data
+            elif msg.name == "query_flights_by_airline":
+                tool_results["/flights_by_airline"] = data
+            elif msg.name == "query_recent_disruptions":
+                tool_results["/recent_disruptions"] = data
         elif msg.type == "ai":
             break
 

cockpit/chat/generative-ui/python/src/index.ts

@@ -28,7 +28,7 @@ export const chatGenerativeUiPythonModule: CockpitCapabilityModule = {
   },
   title: 'Chat Generative UI (Python)',
   docsPath: '/docs/chat/core-capabilities/generative-ui/overview/python',
-  promptAssetPaths: ['cockpit/chat/generative-ui/python/prompts/generative-ui.md'],
+  promptAssetPaths: ['cockpit/chat/generative-ui/python/prompts/dashboard.md'],
   codeAssetPaths: [
     'cockpit/chat/generative-ui/angular/src/app/generative-ui.component.ts',
     'cockpit/chat/generative-ui/angular/src/app/app.config.ts',