clean HF deploy (no large files)

.gitattributes

@@ -15,7 +15,6 @@
 *.npz filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
 *.pb filter=lfs diff=lfs merge=lfs -text
 *.pickle filter=lfs diff=lfs merge=lfs -text
 *.pkl filter=lfs diff=lfs merge=lfs -text
@@ -30,6 +29,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.tgz filter=lfs diff=lfs merge=lfs -text
 *.wasm filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jar filter=lfs diff=lfs merge=lfs -text
+data/gtfs_stm.zip !text !filter !merge !diff
+data/quebec-260603.osm.pbf !text !filter !merge !diff

.gitignore

@@ -0,0 +1,26 @@
+# Large GIS / OTP files
+*.pbf
+*.osm.pbf
+*.jar
+graph.obj
+data/quebec-260603.osm.pbf
+
+# Logs
+*.log
+
+# System files
+.DS_Store
+
+# Python cache
+__pycache__/
+*.pyc
+
+# Data folders (optional safety)
+data/
+*.pbf
+*.jar
+*.zip
+data/
+*.log
+.DS_Store
+data/

README.md

@@ -1,8 +1,8 @@
 ---
-title: ExperimentingV2
-emoji: 🏢
-colorFrom: red
-colorTo: blue
+title: UrbanAccessV1
+emoji: 🌍
+colorFrom: blue
+colorTo: indigo
 sdk: gradio
 sdk_version: 6.16.0
 python_version: '3.13'

app.py

@@ -0,0 +1,80 @@
+import os
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+client = InferenceClient(token=os.environ.get("HF_TOKEN"))
+
+STATION_INFO = {
+    'Berri-UQAM': 'Elevator available. Accessible entrance on Berri St. Tactile strips present.',
+    'McGill': 'Elevator under maintenance. Ramp available on McGill College Ave.',
+    'Stop Sherbrooke / St-Denis': 'Standard bus stop. No shelter. Curb cut present.',
+    'Stop McGill College / Sherbrooke': 'Bus stop with shelter. Level boarding platform.',
+}
+
+INCIDENTS = 'Icy sidewalk near Berri St (Jan 2025). Construction blocking curb cut on Ste-Catherine (ongoing).'
+
+SAMPLE_PATHS = """
+Path 1:
+- Walk 5 min (near Berri St)
+- Metro Green line: board at Berri-UQAM, exit at McGill
+- Walk 3 min (near McGill College Ave)
+
+Path 2:
+- Walk 8 min (near Sherbrooke / St-Denis)
+- Bus line 24: board at Stop Sherbrooke / St-Denis, exit at Stop McGill College / Sherbrooke
+- Walk 2 min (near McGill College Ave)
+"""
+
+SYSTEM_PROMPT = (
+    "You are an accessibility routing assistant for Montreal transit.\n\n"
+    "Your task:\n"
+    "1. Rank the routes from most to least accessible for the user's disability type.\n"
+    "2. For each route, briefly note accessibility concerns or advantages.\n"
+    "3. Give a confidence level (Low/Medium/High) for your top recommendation.\n"
+    "4. Consider the date and season when assessing walking conditions.\n"
+    "5. Do not invent information not provided. If data is missing, say so.\n"
+    "6. Be concise and practical."
+)
+
+def build_prompt(origin, destination, disability_type, date):
+    station_context = "\n".join([f"- {k}: {v}" for k, v in STATION_INFO.items()])
+    return (
+        f"User profile:\n"
+        f"- Origin: {origin}\n"
+        f"- Destination: {destination}\n"
+        f"- Disability type: {disability_type}\n"
+        f"- Date: {date}\n\n"
+        f"Station accessibility info:\n{station_context}\n\n"
+        f"Sidewalk/crosswalk incidents:\n{INCIDENTS}\n\n"
+        f"Available paths:\n{SAMPLE_PATHS}\n\n"
+        "Please rank these paths and recommend the best one for this user."
+    )
+
+def get_recommendation(origin, destination, disability_type, date):
+    response = client.chat_completion(
+        model="Qwen/Qwen2.5-72B-Instruct",
+        messages=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user", "content": build_prompt(origin, destination, disability_type, date)},
+        ],
+        max_tokens=1024,
+    )
+    return response.choices[0].message.content
+
+demo = gr.Interface(
+    fn=get_recommendation,
+    inputs=[
+        gr.Textbox(label="Origin", value="Plateau-Mont-Royal, Montreal"),
+        gr.Textbox(label="Destination", value="McGill University, Montreal"),
+        gr.Dropdown(
+            choices=["wheelchair user", "visual impairment", "limited mobility", "hearing impairment"],
+            label="Disability type",
+            value="wheelchair user"
+        ),
+        gr.Textbox(label="Date", value="2025-01-15"),
+    ],
+    outputs=gr.Markdown(label="Route Recommendation"),
+    title="Accessibility Route Advisor",
+)
+
+demo.launch()

montreal_routes.json

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+          [
+            45.4953,
+            -73.57336
+          ],
+          [
+            45.49512,
+            -73.57353
+          ],
+          [
+            45.49523,
+            -73.57375
+          ],
+          [
+            45.49594,
+            -73.57522
+          ],
+          [
+            45.49622,
+            -73.57582
+          ],
+          [
+            45.49643,
+            -73.57626
+          ],
+          [
+            45.49655,
+            -73.57648
+          ],
+          [
+            45.49673,
+            -73.57687
+          ],
+          [
+            45.49683,
+            -73.57709
+          ],
+          [
+            45.49697,
+            -73.57737
+          ],
+          [
+            45.49719,
+            -73.57784
+          ],
+          [
+            45.4973,
+            -73.57805
+          ],
+          [
+            45.49741,
+            -73.57826
+          ],
+          [
+            45.49782,
+            -73.57909
+          ],
+          [
+            45.49801,
+            -73.5795
+          ],
+          [
+            45.49774,
+            -73.57981
+          ],
+          [
+            45.49755,
+            -73.57991
+          ]
+        ]
+      }
+    ]
+  }
+]

requirements.txt

@@ -0,0 +1,6 @@
+fastapi
+uvicorn[standard]
+gradio
+huggingface_hub
+pydantic
+pandas

routing.py

@@ -0,0 +1,112 @@
+import requests
+import json
+import polyline
+import math
+
+OTP_BASE_URL = "http://localhost:8080/otp/routers/default/plan"
+
+def haversine(lat1, lon1, lat2, lon2):
+    R = 6371000  # meters
+    phi1, phi2 = math.radians(lat1), math.radians(lat2)
+    dphi = math.radians(lat2 - lat1)
+    dlambda = math.radians(lon2 - lon1)
+
+    a = math.sin(dphi/2)**2 + math.cos(phi1)*math.cos(phi2)*math.sin(dlambda/2)**2
+    return 2 * R * math.asin(math.sqrt(a))
+
+def sample_along_line(coords, step=50):
+    if len(coords) < 2:
+        return coords
+
+    sampled = [coords[0]]
+    acc_dist = 0
+
+    for i in range(1, len(coords)):
+        lat1, lon1 = coords[i - 1]
+        lat2, lon2 = coords[i]
+
+        seg_dist = haversine(lat1, lon1, lat2, lon2)
+        acc_dist += seg_dist
+
+        if acc_dist >= step:
+            sampled.append((lat2, lon2))
+            acc_dist = 0
+
+    return sampled
+
+def get_routes(from_lat, from_lon, to_lat, to_lon,
+               modes="WALK,TRANSIT",
+               num_itineraries=3):
+
+    params = {
+        "fromPlace": f"{from_lat},{from_lon}",
+        "toPlace": f"{to_lat},{to_lon}",
+        "mode": modes,
+        "numItineraries": num_itineraries,
+        "maxWalkDistance": 1500,
+        "arriveBy": "false",
+        "date": "2026-06-04",
+        "time": "08:00am"
+    }
+
+    response = requests.get(OTP_BASE_URL, params=params)
+    response.raise_for_status()
+    data = response.json()
+
+    itineraries = data.get("plan", {}).get("itineraries", [])
+
+    routes_output = []
+
+    for idx, itin in enumerate(itineraries):
+        route = {
+            "route_id": idx,
+            "duration_sec": itin.get("duration", 0) / 1000,
+            "transfers": itin.get("transfers", 0),
+            "legs": []
+        }
+
+        for leg in itin.get("legs", []):
+
+            leg_data = {
+                "mode": leg.get("mode"),
+                "from": leg.get("from", {}).get("name"),
+                "to": leg.get("to", {}).get("name"),
+                "start_time": leg.get("startTime"),
+                "end_time": leg.get("endTime"),
+                "duration_sec": leg.get("duration", 0) / 1000,
+                "distance_m": leg.get("distance", 0),
+                "route": leg.get("route"),
+                "geometry_sampled_50m": None
+            }
+
+            # ONLY for walking legs
+            if leg.get("mode") == "WALK":
+                geom = leg.get("legGeometry", {}).get("points")
+
+                if geom:
+                    coords = polyline.decode(geom)  # [(lat, lon), ...]
+                    sampled = sample_along_line(coords, step=20)
+                    leg_data["geometry_sampled_50m"] = sampled
+
+            route["legs"].append(leg_data)
+
+        routes_output.append(route)
+
+    return routes_output
+
+
+def save_routes_to_json(routes, filename="otp_routes.json"):
+    with open(filename, "w", encoding="utf-8") as f:
+        json.dump(routes, f, indent=2, ensure_ascii=False)
+    print(f"Saved {len(routes)} routes to {filename}")
+
+
+
+"""exmample in montreal"""
+if __name__ == "__main__":
+    routes = get_routes(
+        from_lat=45.53080483132569, from_lon=-73.61353945157414,   # mila
+        to_lat=45.49758656380192, to_lon=-73.5799738767698        # accio cup
+    )
+
+    save_routes_to_json(routes, "montreal_routes.json")

scripts/run_otp.sh

@@ -0,0 +1,39 @@
+#!/bin/bash
+set -e
+
+echo "🚀 Starting OTP server"
+
+# go to project root (adjust if needed)
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+cd "$SCRIPT_DIR/.."
+
+DATA_DIR="data"
+
+echo "📂 Checking data folder..."
+ls -lh "$DATA_DIR"
+
+echo "☕ Java version:"
+java -version
+
+echo "🔎 Finding OTP jar..."
+
+OTP_JAR=$(find . -maxdepth 3 -name "otp-2.5.0-shaded.jar" | head -n 1)
+
+if [ -z "$OTP_JAR" ]; then
+  echo "❌ OTP jar not found"
+  exit 1
+fi
+
+echo "✅ Using: $OTP_JAR"
+
+echo "🧹 Cleaning old graph (optional)"
+rm -rf "$DATA_DIR/graph" || true
+
+echo "⚙️ Building + starting OTP server..."
+
+java -Xmx6G -jar "$OTP_JAR" \
+  --build "$DATA_DIR" \
+  --serve \
+  --port 8080
+
+echo "✅ OTP running at http://localhost:8080"