Upload 23 files

.dockerignore

@@ -1,26 +1,26 @@
-__pycache__/
-*.pyc
-*.pyo
-*.pyd
-.pytest_cache/
-.cache/
-cache/
-.venv/
-venv/
-
-# Plots and binders generated during local exploration
-*.png
-*.pdf
-challenge_description.txt
-obsolete/
-
-# Local secrets — must never enter the image. Use env vars instead.
-seed/service-account.json
-.env
-.env.*
-
-# Editor / OS
-.vscode/
-.idea/
-.DS_Store
-Thumbs.db
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.pytest_cache/
+.cache/
+cache/
+.venv/
+venv/
+
+# Plots and binders generated during local exploration
+*.png
+*.pdf
+challenge_description.txt
+obsolete/
+
+# Local secrets — must never enter the image. Use env vars instead.
+seed/service-account.json
+.env
+.env.*
+
+# Editor / OS
+.vscode/
+.idea/
+.DS_Store
+Thumbs.db

Dockerfile

@@ -1,28 +1,28 @@
-FROM python:3.12-slim
-
-ENV PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1 \
-    MPLBACKEND=Agg \
-    PORT=7860
-
-# Native deps for shapely / pyproj / osmnx.
-RUN apt-get update && apt-get install -y --no-install-recommends \
-        libgeos-dev \
-        libspatialindex-dev \
-        libproj-dev \
-        proj-bin \
-    && rm -rf /var/lib/apt/lists/*
-
-WORKDIR /app
-
-# Install Python deps first so layer caches across code changes.
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-# Copy backend sources. .dockerignore filters out pycache, plots, secrets.
-COPY . .
-
-EXPOSE 7860
-
-# Listen on $PORT (set by HF Spaces, Cloud Run, Fly, Render). Fallback to 7860.
-CMD ["sh", "-c", "uvicorn app:app --host 0.0.0.0 --port ${PORT:-7860} --workers 1"]
+FROM python:3.12-slim
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    MPLBACKEND=Agg \
+    PORT=7860
+
+# Native deps for shapely / pyproj / osmnx.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libgeos-dev \
+        libspatialindex-dev \
+        libproj-dev \
+        proj-bin \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+# Install Python deps first so layer caches across code changes.
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy backend sources. .dockerignore filters out pycache, plots, secrets.
+COPY . .
+
+EXPOSE 7860
+
+# Listen on $PORT (set by HF Spaces, Cloud Run, Fly, Render). Fallback to 7860.
+CMD ["sh", "-c", "uvicorn app:app --host 0.0.0.0 --port ${PORT:-7860} --workers 1"]

app.py

@@ -1,480 +1,480 @@
-"""FastAPI server: OR-tools VRPSPD-TW + analytics layer.
-
-    GET  /health           liveness probe
-    GET  /sample-request   bundled example body
-    POST /optimize         main endpoint, returns plan + polylines + KPIs + explanations
-    POST /whatif           perturb the request (driver out, traffic, stop cancelled) and re-solve
-    POST /baseline         naive comparator alone
-    GET  /docs             auto Swagger UI
-"""
-
-from __future__ import annotations
-
-import json
-from contextlib import asynccontextmanager
-from pathlib import Path
-from typing import Literal
-
-import os
-import httpx
-from anthropic import Anthropic
-import numpy as np
-from fastapi import FastAPI, HTTPException, Response
-from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
-
-from analytics import (
-    CO2_KG_PER_KM, KPIs, compute_kpis, explain_van, load_profile, warehouse_prep,
-)
-from baseline import solve_baseline
-from firestore_writer import build_route_doc, is_enabled as fs_enabled, write_routes
-from geometry import route_polyline
-from graph_manager import get_or_build_graph
-from loader import build_travel_matrix, load
-from solver import solve_vrp
-
-SAMPLE = Path(__file__).with_name("sample_request.json")
-PRODUCTS = Path(__file__).with_name("products.json")
-
-
-# --- Request schema (mirrors sample_request.json) ----------------------
-
-class Coords(BaseModel):
-    lat: float
-    lng: float
-
-
-class TimeWindow(BaseModel):
-    open: str
-    close: str
-
-
-class Line(BaseModel):
-    product_id: str
-    qty: int
-
-
-class StopReq(BaseModel):
-    id: str
-    coords: Coords
-    time_window: TimeWindow
-    deliveries: list[Line]
-    pickups: list[Line] = []
-
-
-class DepotReq(BaseModel):
-    id: str
-    coords: Coords
-    open: str
-    close: str
-
-
-class FleetReq(BaseModel):
-    num_vans: int
-    van_type: str
-    vans_ref: str | None = None
-    products_ref: str | None = None
-
-
-class DriverReq(BaseModel):
-    id: str
-    shift_start: str
-    shift_end: str
-
-
-class OptimizeRequest(BaseModel):
-    request_id: str | None = None
-    date: str | None = None
-    depot: DepotReq
-    fleet: FleetReq
-    drivers: list[DriverReq]
-    stops: list[StopReq]
-
-
-class Disruption(BaseModel):
-    type: Literal["driver_unavailable", "stop_cancelled", "traffic"]
-    driver_id: str | None = None
-    stop_id: str | None = None
-    multiplier: float | None = None     # for "traffic"
-
-
-class WhatIfRequest(BaseModel):
-    request: OptimizeRequest
-    disruption: Disruption
-
-class ChatRequest(BaseModel):
-    transcript: str
-    context: str
-
-class TTSRequest(BaseModel):
-    text: str
-
-
-# --- Response schema ---------------------------------------------------
-
-class StopOut(BaseModel):
-    sequence: int
-    id: str
-    arrival_time: str
-    coords: Coords
-
-
-class LoadPointOut(BaseModel):
-    after_stop: str
-    cells: int
-    kg: int
-
-
-class VanOut(BaseModel):
-    van_idx: int
-    driver_id: str
-    feasible: bool
-    travel_time_min: float
-    total_time_h: float
-    peak_cells: int
-    peak_kg: int
-    stops: list[StopOut]
-    polyline: list[Coords]
-    load_profile: list[LoadPointOut]
-    explanations: list[str]
-
-
-class KPIsOut(BaseModel):
-    fleet_drive_min: float
-    baseline_drive_min: float
-    savings_pct: float
-    fleet_km: float
-    baseline_km: float
-    co2_kg_saved: float
-    driver_utilization_pct: float
-    capacity_utilization_pct: float
-    stops_per_van: list[int]
-    feasible_vans: int
-    total_vans: int
-
-
-class OptimizeResponse(BaseModel):
-    request_id: str | None
-    fleet_drive_min: float
-    fleet_total_h: float
-    all_feasible: bool
-    depot: DepotReq
-    vans: list[VanOut]
-    kpis: KPIsOut
-    warehouse_prep: list[str]
-    firestore_written: int = 0
-
-
-# --- App ---------------------------------------------------------------
-
-@asynccontextmanager
-async def lifespan(_: FastAPI):
-    get_or_build_graph()
-    yield
-
-
-app = FastAPI(title="Damm Smart Truck API", version="2.0.0", lifespan=lifespan)
-app.add_middleware(
-    CORSMiddleware, allow_origins=["*"],
-    allow_methods=["GET", "POST"], allow_headers=["*"],
-)
-
-
-def _hm(s: int) -> str:
-    h, m = divmod(int(s) // 60, 60)
-    return f"{h:02d}:{m:02d}"
-
-
-def _run_pipeline(
-    body: dict,
-    *,
-    write_firestore: bool,
-    traffic_multiplier: float = 1.0,
-    time_limit_s: int = 5,
-) -> OptimizeResponse:
-    """Shared core for /optimize and /whatif."""
-    try:
-        depot, fleet, drivers, stops = load(body)
-    except KeyError as e:
-        raise HTTPException(422, f"unknown reference: {e}")
-    if not drivers:
-        raise HTTPException(422, "no drivers in fleet")
-    if len(drivers) != fleet.num_vans:
-        raise HTTPException(
-            422, f"num_vans={fleet.num_vans} but {len(drivers)} drivers"
-        )
-    if not stops:
-        raise HTTPException(422, "no stops to deliver")
-
-    matrix = build_travel_matrix(depot, stops)
-    if traffic_multiplier != 1.0:
-        matrix.time_s = (matrix.time_s * float(traffic_multiplier)).astype(np.float32)
-
-    plan = solve_vrp(depot, fleet, drivers, stops, matrix, time_limit_s=time_limit_s)
-    if not plan.vans:
-        # The disruption made the day infeasible — return a structured
-        # "no plan" response instead of 500 so the UI can show it.
-        return OptimizeResponse(
-            request_id=body.get("request_id"),
-            fleet_drive_min=0.0,
-            fleet_total_h=0.0,
-            all_feasible=False,
-            depot=DepotReq(**body["depot"]),
-            vans=[],
-            kpis=KPIsOut(
-                fleet_drive_min=0.0, baseline_drive_min=0.0, savings_pct=0.0,
-                fleet_km=0.0, baseline_km=0.0, co2_kg_saved=0.0,
-                driver_utilization_pct=0.0, capacity_utilization_pct=0.0,
-                stops_per_van=[], feasible_vans=0, total_vans=fleet.num_vans,
-            ),
-            warehouse_prep=[
-                "INFEASIBLE: no valid plan exists for this scenario. "
-                "Try relaxing time windows, adding a backup driver, or rescheduling stops."
-            ],
-            firestore_written=0,
-        )
-
-    baseline_plan = solve_baseline(depot, fleet, drivers, stops, matrix)
-
-    stops_by_id = {s.id: s for s in stops}
-    graph = get_or_build_graph()
-
-    vans_out: list[VanOut] = []
-    for v in plan.vans:
-        sequence = ["DEPOT"] + [p.id for p in v.stops] + ["DEPOT"]
-        polyline = (
-            [Coords(lat=lat, lng=lng) for lat, lng in route_polyline(graph, matrix, sequence)]
-            if v.stops else []
-        )
-        prof = load_profile(v, stops_by_id)
-        vans_out.append(VanOut(
-            van_idx=v.van_idx,
-            driver_id=v.driver_id,
-            feasible=v.feasible,
-            travel_time_min=round(v.travel_s / 60, 2),
-            total_time_h=round(v.total_s / 3600, 3),
-            peak_cells=v.peak_cells,
-            peak_kg=v.peak_kg,
-            stops=[
-                StopOut(
-                    sequence=p.sequence, id=p.id,
-                    arrival_time=_hm(p.arrival_s),
-                    coords=Coords(lat=stops_by_id[p.id].lat, lng=stops_by_id[p.id].lng),
-                )
-                for p in v.stops
-            ],
-            polyline=polyline,
-            load_profile=[
-                LoadPointOut(after_stop=lp.after_stop, cells=lp.cells, kg=lp.kg)
-                for lp in prof
-            ],
-            explanations=explain_van(v, stops_by_id, drivers[v.van_idx]),
-        ))
-
-    kpis = compute_kpis(plan, baseline_plan, fleet, drivers, matrix)
-    prep = warehouse_prep(plan, body["stops"], stops_by_id)
-
-    written = 0
-    if write_firestore and fs_enabled():
-        service_times_s = {s.id: s.service_time_s for s in stops}
-        docs = [
-            build_route_doc(
-                driver_id=v.driver_id,
-                truck_id=f"T-{v.van_idx + 1:02d}",
-                van_type=body["fleet"]["van_type"],
-                depot=body["depot"],
-                request_stops=body["stops"],
-                van_plan=v,
-                service_times_s=service_times_s,
-            )
-            for v in plan.vans
-        ]
-        written = write_routes(docs)
-
-    return OptimizeResponse(
-        request_id=body.get("request_id"),
-        fleet_drive_min=round(plan.drive_s / 60, 2),
-        fleet_total_h=round(plan.total_s / 3600, 3),
-        all_feasible=plan.all_feasible,
-        depot=DepotReq(**body["depot"]),
-        vans=vans_out,
-        kpis=KPIsOut(**kpis.__dict__),
-        warehouse_prep=prep,
-        firestore_written=written,
-    )
-
-
-# --- Endpoints ---------------------------------------------------------
-
-@app.get("/health")
-def health():
-    return {"status": "ok"}
-
-
-@app.get("/sample-request", response_model=OptimizeRequest)
-def sample_request():
-    if not SAMPLE.exists():
-        raise HTTPException(404, "sample_request.json missing")
-    return json.loads(SAMPLE.read_text(encoding="utf-8"))
-
-
-@app.get("/products")
-def products():
-    if not PRODUCTS.exists():
-        raise HTTPException(404, "products.json missing")
-    return json.loads(PRODUCTS.read_text(encoding="utf-8"))
-
-
-@app.post("/optimize", response_model=OptimizeResponse)
-def optimize(req: OptimizeRequest) -> OptimizeResponse:
-    return _run_pipeline(req.model_dump(), write_firestore=True)
-
-
-@app.post("/whatif", response_model=OptimizeResponse)
-def whatif(req: WhatIfRequest) -> OptimizeResponse:
-    body = req.request.model_dump()
-    multiplier = 1.0
-    d = req.disruption
-
-    if d.type == "driver_unavailable":
-        if not d.driver_id:
-            raise HTTPException(422, "driver_id required for driver_unavailable")
-        body["drivers"] = [x for x in body["drivers"] if x["id"] != d.driver_id]
-        body["fleet"]["num_vans"] = len(body["drivers"])
-    elif d.type == "stop_cancelled":
-        if not d.stop_id:
-            raise HTTPException(422, "stop_id required for stop_cancelled")
-        body["stops"] = [s for s in body["stops"] if s["id"] != d.stop_id]
-    elif d.type == "traffic":
-        multiplier = float(d.multiplier or 1.3)
-
-    # What-ifs are exploratory; don't overwrite the real plan in Firestore.
-    # Larger time budget — disrupted scenarios are tighter to solve.
-    return _run_pipeline(
-        body, write_firestore=False, traffic_multiplier=multiplier, time_limit_s=15,
-    )
-
-
-@app.post("/baseline", response_model=OptimizeResponse)
-def baseline_endpoint(req: OptimizeRequest) -> OptimizeResponse:
-    """Run only the naive baseline (for explicit comparison demos)."""
-    body = req.model_dump()
-    depot, fleet, drivers, stops = load(body)
-    matrix = build_travel_matrix(depot, stops)
-    plan = solve_baseline(depot, fleet, drivers, stops, matrix)
-    stops_by_id = {s.id: s for s in stops}
-    graph = get_or_build_graph()
-
-    vans_out: list[VanOut] = []
-    for v in plan.vans:
-        sequence = ["DEPOT"] + [p.id for p in v.stops] + ["DEPOT"]
-        polyline = (
-            [Coords(lat=lat, lng=lng) for lat, lng in route_polyline(graph, matrix, sequence)]
-            if v.stops else []
-        )
-        vans_out.append(VanOut(
-            van_idx=v.van_idx, driver_id=v.driver_id, feasible=v.feasible,
-            travel_time_min=round(v.travel_s / 60, 2),
-            total_time_h=round(v.total_s / 3600, 3),
-            peak_cells=v.peak_cells, peak_kg=v.peak_kg,
-            stops=[
-                StopOut(
-                    sequence=p.sequence, id=p.id,
-                    arrival_time=_hm(p.arrival_s),
-                    coords=Coords(lat=stops_by_id[p.id].lat, lng=stops_by_id[p.id].lng),
-                )
-                for p in v.stops
-            ],
-            polyline=polyline,
-            load_profile=[
-                LoadPointOut(after_stop=lp.after_stop, cells=lp.cells, kg=lp.kg)
-                for lp in load_profile(v, stops_by_id)
-            ],
-            explanations=explain_van(v, stops_by_id, drivers[v.van_idx]),
-        ))
-
-    return OptimizeResponse(
-        request_id=req.request_id,
-        fleet_drive_min=round(plan.drive_s / 60, 2),
-        fleet_total_h=round(plan.total_s / 3600, 3),
-        all_feasible=plan.all_feasible,
-        depot=req.depot,
-        vans=vans_out,
-        kpis=KPIsOut(
-            fleet_drive_min=round(plan.drive_s / 60, 2),
-            baseline_drive_min=round(plan.drive_s / 60, 2),
-            savings_pct=0.0,
-            fleet_km=0.0, baseline_km=0.0, co2_kg_saved=0.0,
-            driver_utilization_pct=0.0, capacity_utilization_pct=0.0,
-            stops_per_van=[len(v.stops) for v in plan.vans],
-            feasible_vans=sum(1 for v in plan.vans if v.feasible),
-            total_vans=len(plan.vans),
-        ),
-        warehouse_prep=warehouse_prep(plan, body["stops"], stops_by_id),
-        firestore_written=0,
-    )
-
-@app.post("/api/chat")
-def chat_endpoint(req: ChatRequest):
-    api_key = os.environ.get("ANTHROPIC_API_KEY", "")
-    if not api_key:
-        raise HTTPException(500, "ANTHROPIC_API_KEY not configured")
-    client = Anthropic(api_key=api_key)
-    system = (
-        "You are a hands-free voice assistant for Damm Motion delivery drivers.\n\n"
-        "Current route status:\n" + req.context + "\n\n"
-        "Based on what the driver said, decide the best action and give a short spoken reply (max 2 sentences).\n"
-        "Respond in the same language the driver used. Be concise — this will be read aloud.\n"
-        "You MUST return ONLY valid JSON matching this schema:\n"
-        "{\n"
-        '  "action": "mark_delivered" | "next_stop" | "navigate" | "status" | "unknown",\n'
-        '  "response": "..."\n'
-        "}"
-    )
-    try:
-        response = client.messages.create(
-            model="claude-3-haiku-20240307",
-            max_tokens=200,
-            system=system,
-            messages=[{"role": "user", "content": req.transcript}]
-        )
-        raw_text = response.content[0].text.strip()
-        if raw_text.startswith("```"):
-            lines = raw_text.split("\n")
-            if lines[0].startswith("```"): lines = lines[1:]
-            if lines[-1].startswith("```"): lines = lines[:-1]
-            raw_text = "\n".join(lines).strip()
-        
-        return json.loads(raw_text)
-    except Exception as e:
-        raise HTTPException(500, f"Anthropic API error: {e}")
-
-@app.post("/api/tts")
-def tts_endpoint(req: TTSRequest):
-    api_key = os.environ.get("ELEVENLABS_API_KEY", "")
-    voice_id = os.environ.get("ELEVENLABS_VOICE_ID", "21m00Tcm4TlvDq8ikWAM")
-    if not api_key:
-        raise HTTPException(500, "ELEVENLABS_API_KEY not configured")
-    url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
-    headers = {
-        "xi-api-key": api_key,
-        "Content-Type": "application/json"
-    }
-    payload = {
-        "text": req.text,
-        "model_id": "eleven_multilingual_v2",
-        "voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
-    }
-    try:
-        with httpx.Client() as client:
-            resp = client.post(url, headers=headers, json=payload, timeout=10.0)
-            resp.raise_for_status()
-            return Response(content=resp.content, media_type="audio/mpeg")
-    except Exception as e:
-        raise HTTPException(500, f"ElevenLabs API error: {e}")
-
-
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=False)
+"""FastAPI server: OR-tools VRPSPD-TW + analytics layer.
+
+    GET  /health           liveness probe
+    GET  /sample-request   bundled example body
+    POST /optimize         main endpoint, returns plan + polylines + KPIs + explanations
+    POST /whatif           perturb the request (driver out, traffic, stop cancelled) and re-solve
+    POST /baseline         naive comparator alone
+    GET  /docs             auto Swagger UI
+"""
+
+from __future__ import annotations
+
+import json
+from contextlib import asynccontextmanager
+from pathlib import Path
+from typing import Literal
+
+import os
+import httpx
+from anthropic import Anthropic
+import numpy as np
+from fastapi import FastAPI, HTTPException, Response
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+
+from analytics import (
+    CO2_KG_PER_KM, KPIs, compute_kpis, explain_van, load_profile, warehouse_prep,
+)
+from baseline import solve_baseline
+from firestore_writer import build_route_doc, is_enabled as fs_enabled, write_routes
+from geometry import route_polyline
+from graph_manager import get_or_build_graph
+from loader import build_travel_matrix, load
+from solver import solve_vrp
+
+SAMPLE = Path(__file__).with_name("sample_request.json")
+PRODUCTS = Path(__file__).with_name("products.json")
+
+
+# --- Request schema (mirrors sample_request.json) ----------------------
+
+class Coords(BaseModel):
+    lat: float
+    lng: float
+
+
+class TimeWindow(BaseModel):
+    open: str
+    close: str
+
+
+class Line(BaseModel):
+    product_id: str
+    qty: int
+
+
+class StopReq(BaseModel):
+    id: str
+    coords: Coords
+    time_window: TimeWindow
+    deliveries: list[Line]
+    pickups: list[Line] = []
+
+
+class DepotReq(BaseModel):
+    id: str
+    coords: Coords
+    open: str
+    close: str
+
+
+class FleetReq(BaseModel):
+    num_vans: int
+    van_type: str
+    vans_ref: str | None = None
+    products_ref: str | None = None
+
+
+class DriverReq(BaseModel):
+    id: str
+    shift_start: str
+    shift_end: str
+
+
+class OptimizeRequest(BaseModel):
+    request_id: str | None = None
+    date: str | None = None
+    depot: DepotReq
+    fleet: FleetReq
+    drivers: list[DriverReq]
+    stops: list[StopReq]
+
+
+class Disruption(BaseModel):
+    type: Literal["driver_unavailable", "stop_cancelled", "traffic"]
+    driver_id: str | None = None
+    stop_id: str | None = None
+    multiplier: float | None = None     # for "traffic"
+
+
+class WhatIfRequest(BaseModel):
+    request: OptimizeRequest
+    disruption: Disruption
+
+class ChatRequest(BaseModel):
+    transcript: str
+    context: str
+
+class TTSRequest(BaseModel):
+    text: str
+
+
+# --- Response schema ---------------------------------------------------
+
+class StopOut(BaseModel):
+    sequence: int
+    id: str
+    arrival_time: str
+    coords: Coords
+
+
+class LoadPointOut(BaseModel):
+    after_stop: str
+    cells: int
+    kg: int
+
+
+class VanOut(BaseModel):
+    van_idx: int
+    driver_id: str
+    feasible: bool
+    travel_time_min: float
+    total_time_h: float
+    peak_cells: int
+    peak_kg: int
+    stops: list[StopOut]
+    polyline: list[Coords]
+    load_profile: list[LoadPointOut]
+    explanations: list[str]
+
+
+class KPIsOut(BaseModel):
+    fleet_drive_min: float
+    baseline_drive_min: float
+    savings_pct: float
+    fleet_km: float
+    baseline_km: float
+    co2_kg_saved: float
+    driver_utilization_pct: float
+    capacity_utilization_pct: float
+    stops_per_van: list[int]
+    feasible_vans: int
+    total_vans: int
+
+
+class OptimizeResponse(BaseModel):
+    request_id: str | None
+    fleet_drive_min: float
+    fleet_total_h: float
+    all_feasible: bool
+    depot: DepotReq
+    vans: list[VanOut]
+    kpis: KPIsOut
+    warehouse_prep: list[str]
+    firestore_written: int = 0
+
+
+# --- App ---------------------------------------------------------------
+
+@asynccontextmanager
+async def lifespan(_: FastAPI):
+    get_or_build_graph()
+    yield
+
+
+app = FastAPI(title="Damm Smart Truck API", version="2.0.0", lifespan=lifespan)
+app.add_middleware(
+    CORSMiddleware, allow_origins=["*"],
+    allow_methods=["GET", "POST"], allow_headers=["*"],
+)
+
+
+def _hm(s: int) -> str:
+    h, m = divmod(int(s) // 60, 60)
+    return f"{h:02d}:{m:02d}"
+
+
+def _run_pipeline(
+    body: dict,
+    *,
+    write_firestore: bool,
+    traffic_multiplier: float = 1.0,
+    time_limit_s: int = 5,
+) -> OptimizeResponse:
+    """Shared core for /optimize and /whatif."""
+    try:
+        depot, fleet, drivers, stops = load(body)
+    except KeyError as e:
+        raise HTTPException(422, f"unknown reference: {e}")
+    if not drivers:
+        raise HTTPException(422, "no drivers in fleet")
+    if len(drivers) != fleet.num_vans:
+        raise HTTPException(
+            422, f"num_vans={fleet.num_vans} but {len(drivers)} drivers"
+        )
+    if not stops:
+        raise HTTPException(422, "no stops to deliver")
+
+    matrix = build_travel_matrix(depot, stops)
+    if traffic_multiplier != 1.0:
+        matrix.time_s = (matrix.time_s * float(traffic_multiplier)).astype(np.float32)
+
+    plan = solve_vrp(depot, fleet, drivers, stops, matrix, time_limit_s=time_limit_s)
+    if not plan.vans:
+        # The disruption made the day infeasible — return a structured
+        # "no plan" response instead of 500 so the UI can show it.
+        return OptimizeResponse(
+            request_id=body.get("request_id"),
+            fleet_drive_min=0.0,
+            fleet_total_h=0.0,
+            all_feasible=False,
+            depot=DepotReq(**body["depot"]),
+            vans=[],
+            kpis=KPIsOut(
+                fleet_drive_min=0.0, baseline_drive_min=0.0, savings_pct=0.0,
+                fleet_km=0.0, baseline_km=0.0, co2_kg_saved=0.0,
+                driver_utilization_pct=0.0, capacity_utilization_pct=0.0,
+                stops_per_van=[], feasible_vans=0, total_vans=fleet.num_vans,
+            ),
+            warehouse_prep=[
+                "INFEASIBLE: no valid plan exists for this scenario. "
+                "Try relaxing time windows, adding a backup driver, or rescheduling stops."
+            ],
+            firestore_written=0,
+        )
+
+    baseline_plan = solve_baseline(depot, fleet, drivers, stops, matrix)
+
+    stops_by_id = {s.id: s for s in stops}
+    graph = get_or_build_graph()
+
+    vans_out: list[VanOut] = []
+    for v in plan.vans:
+        sequence = ["DEPOT"] + [p.id for p in v.stops] + ["DEPOT"]
+        polyline = (
+            [Coords(lat=lat, lng=lng) for lat, lng in route_polyline(graph, matrix, sequence)]
+            if v.stops else []
+        )
+        prof = load_profile(v, stops_by_id)
+        vans_out.append(VanOut(
+            van_idx=v.van_idx,
+            driver_id=v.driver_id,
+            feasible=v.feasible,
+            travel_time_min=round(v.travel_s / 60, 2),
+            total_time_h=round(v.total_s / 3600, 3),
+            peak_cells=v.peak_cells,
+            peak_kg=v.peak_kg,
+            stops=[
+                StopOut(
+                    sequence=p.sequence, id=p.id,
+                    arrival_time=_hm(p.arrival_s),
+                    coords=Coords(lat=stops_by_id[p.id].lat, lng=stops_by_id[p.id].lng),
+                )
+                for p in v.stops
+            ],
+            polyline=polyline,
+            load_profile=[
+                LoadPointOut(after_stop=lp.after_stop, cells=lp.cells, kg=lp.kg)
+                for lp in prof
+            ],
+            explanations=explain_van(v, stops_by_id, drivers[v.van_idx]),
+        ))
+
+    kpis = compute_kpis(plan, baseline_plan, fleet, drivers, matrix)
+    prep = warehouse_prep(plan, body["stops"], stops_by_id)
+
+    written = 0
+    if write_firestore and fs_enabled():
+        service_times_s = {s.id: s.service_time_s for s in stops}
+        docs = [
+            build_route_doc(
+                driver_id=v.driver_id,
+                truck_id=f"T-{v.van_idx + 1:02d}",
+                van_type=body["fleet"]["van_type"],
+                depot=body["depot"],
+                request_stops=body["stops"],
+                van_plan=v,
+                service_times_s=service_times_s,
+            )
+            for v in plan.vans
+        ]
+        written = write_routes(docs)
+
+    return OptimizeResponse(
+        request_id=body.get("request_id"),
+        fleet_drive_min=round(plan.drive_s / 60, 2),
+        fleet_total_h=round(plan.total_s / 3600, 3),
+        all_feasible=plan.all_feasible,
+        depot=DepotReq(**body["depot"]),
+        vans=vans_out,
+        kpis=KPIsOut(**kpis.__dict__),
+        warehouse_prep=prep,
+        firestore_written=written,
+    )
+
+
+# --- Endpoints ---------------------------------------------------------
+
+@app.get("/health")
+def health():
+    return {"status": "ok"}
+
+
+@app.get("/sample-request", response_model=OptimizeRequest)
+def sample_request():
+    if not SAMPLE.exists():
+        raise HTTPException(404, "sample_request.json missing")
+    return json.loads(SAMPLE.read_text(encoding="utf-8"))
+
+
+@app.get("/products")
+def products():
+    if not PRODUCTS.exists():
+        raise HTTPException(404, "products.json missing")
+    return json.loads(PRODUCTS.read_text(encoding="utf-8"))
+
+
+@app.post("/optimize", response_model=OptimizeResponse)
+def optimize(req: OptimizeRequest) -> OptimizeResponse:
+    return _run_pipeline(req.model_dump(), write_firestore=True)
+
+
+@app.post("/whatif", response_model=OptimizeResponse)
+def whatif(req: WhatIfRequest) -> OptimizeResponse:
+    body = req.request.model_dump()
+    multiplier = 1.0
+    d = req.disruption
+
+    if d.type == "driver_unavailable":
+        if not d.driver_id:
+            raise HTTPException(422, "driver_id required for driver_unavailable")
+        body["drivers"] = [x for x in body["drivers"] if x["id"] != d.driver_id]
+        body["fleet"]["num_vans"] = len(body["drivers"])
+    elif d.type == "stop_cancelled":
+        if not d.stop_id:
+            raise HTTPException(422, "stop_id required for stop_cancelled")
+        body["stops"] = [s for s in body["stops"] if s["id"] != d.stop_id]
+    elif d.type == "traffic":
+        multiplier = float(d.multiplier or 1.3)
+
+    # What-ifs are exploratory; don't overwrite the real plan in Firestore.
+    # Larger time budget — disrupted scenarios are tighter to solve.
+    return _run_pipeline(
+        body, write_firestore=False, traffic_multiplier=multiplier, time_limit_s=15,
+    )
+
+
+@app.post("/baseline", response_model=OptimizeResponse)
+def baseline_endpoint(req: OptimizeRequest) -> OptimizeResponse:
+    """Run only the naive baseline (for explicit comparison demos)."""
+    body = req.model_dump()
+    depot, fleet, drivers, stops = load(body)
+    matrix = build_travel_matrix(depot, stops)
+    plan = solve_baseline(depot, fleet, drivers, stops, matrix)
+    stops_by_id = {s.id: s for s in stops}
+    graph = get_or_build_graph()
+
+    vans_out: list[VanOut] = []
+    for v in plan.vans:
+        sequence = ["DEPOT"] + [p.id for p in v.stops] + ["DEPOT"]
+        polyline = (
+            [Coords(lat=lat, lng=lng) for lat, lng in route_polyline(graph, matrix, sequence)]
+            if v.stops else []
+        )
+        vans_out.append(VanOut(
+            van_idx=v.van_idx, driver_id=v.driver_id, feasible=v.feasible,
+            travel_time_min=round(v.travel_s / 60, 2),
+            total_time_h=round(v.total_s / 3600, 3),
+            peak_cells=v.peak_cells, peak_kg=v.peak_kg,
+            stops=[
+                StopOut(
+                    sequence=p.sequence, id=p.id,
+                    arrival_time=_hm(p.arrival_s),
+                    coords=Coords(lat=stops_by_id[p.id].lat, lng=stops_by_id[p.id].lng),
+                )
+                for p in v.stops
+            ],
+            polyline=polyline,
+            load_profile=[
+                LoadPointOut(after_stop=lp.after_stop, cells=lp.cells, kg=lp.kg)
+                for lp in load_profile(v, stops_by_id)
+            ],
+            explanations=explain_van(v, stops_by_id, drivers[v.van_idx]),
+        ))
+
+    return OptimizeResponse(
+        request_id=req.request_id,
+        fleet_drive_min=round(plan.drive_s / 60, 2),
+        fleet_total_h=round(plan.total_s / 3600, 3),
+        all_feasible=plan.all_feasible,
+        depot=req.depot,
+        vans=vans_out,
+        kpis=KPIsOut(
+            fleet_drive_min=round(plan.drive_s / 60, 2),
+            baseline_drive_min=round(plan.drive_s / 60, 2),
+            savings_pct=0.0,
+            fleet_km=0.0, baseline_km=0.0, co2_kg_saved=0.0,
+            driver_utilization_pct=0.0, capacity_utilization_pct=0.0,
+            stops_per_van=[len(v.stops) for v in plan.vans],
+            feasible_vans=sum(1 for v in plan.vans if v.feasible),
+            total_vans=len(plan.vans),
+        ),
+        warehouse_prep=warehouse_prep(plan, body["stops"], stops_by_id),
+        firestore_written=0,
+    )
+
+@app.post("/api/chat")
+def chat_endpoint(req: ChatRequest):
+    api_key = os.environ.get("ANTHROPIC_API_KEY", "")
+    if not api_key:
+        raise HTTPException(500, "ANTHROPIC_API_KEY not configured")
+    client = Anthropic(api_key=api_key)
+    system = (
+        "You are a hands-free voice assistant for Damm Motion delivery drivers.\n\n"
+        "Current route status:\n" + req.context + "\n\n"
+        "Based on what the driver said, decide the best action and give a short spoken reply (max 2 sentences).\n"
+        "Respond in the same language the driver used. Be concise — this will be read aloud.\n"
+        "You MUST return ONLY valid JSON matching this schema:\n"
+        "{\n"
+        '  "action": "mark_delivered" | "next_stop" | "navigate" | "status" | "unknown",\n'
+        '  "response": "..."\n'
+        "}"
+    )
+    try:
+        response = client.messages.create(
+            model="claude-3-haiku-20240307",
+            max_tokens=200,
+            system=system,
+            messages=[{"role": "user", "content": req.transcript}]
+        )
+        raw_text = response.content[0].text.strip()
+        if raw_text.startswith("```"):
+            lines = raw_text.split("\n")
+            if lines[0].startswith("```"): lines = lines[1:]
+            if lines[-1].startswith("```"): lines = lines[:-1]
+            raw_text = "\n".join(lines).strip()
+        
+        return json.loads(raw_text)
+    except Exception as e:
+        raise HTTPException(500, f"Anthropic API error: {e}")
+
+@app.post("/api/tts")
+def tts_endpoint(req: TTSRequest):
+    api_key = os.environ.get("ELEVENLABS_API_KEY", "")
+    voice_id = os.environ.get("ELEVENLABS_VOICE_ID", "21m00Tcm4TlvDq8ikWAM")
+    if not api_key:
+        raise HTTPException(500, "ELEVENLABS_API_KEY not configured")
+    url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
+    headers = {
+        "xi-api-key": api_key,
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "text": req.text,
+        "model_id": "eleven_multilingual_v2",
+        "voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
+    }
+    try:
+        with httpx.Client() as client:
+            resp = client.post(url, headers=headers, json=payload, timeout=10.0)
+            resp.raise_for_status()
+            return Response(content=resp.content, media_type="audio/mpeg")
+    except Exception as e:
+        raise HTTPException(500, f"ElevenLabs API error: {e}")
+
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=False)

requirements.txt

@@ -12,4 +12,4 @@ pyproj>=3.6
 ortools>=9.10
 firebase-admin>=6.5
 anthropic>=0.40.0
-httpx>=0.27.2
+httpx>=0.27.2