commit f2788d9e1dbbb9fe4bd517ba41cd5775a748b31b
Author: Ryan Chen <ryan@torrtle.co>
Date:   Mon Jul 27 10:05:29 2026 -0400

    Initial commit: GPX ride viewer with local-LLM coaching insights
    
    Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

diff --git a/.gitignore b/.gitignore
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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
+
+# Personal data — not committed
+garmin_gpx_exports/*.gpx
+insights.json
+
+# Local environment
+.env
diff --git a/.python-version b/.python-version
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+++ b/.python-version
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+3.14
diff --git a/CLAUDE.md b/CLAUDE.md
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+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Commands
+
+```bash
+uv run uvicorn app:app --reload                       # start dev server at http://localhost:8000
+LLAMACPP_BASE_URL=http://host:port/v1 uv run uvicorn app:app --reload  # point at a specific LLM
+uv sync                                               # install/sync dependencies
+uv add <package>                                      # add a new dependency
+```
+
+## Architecture
+
+Two-file app: a FastAPI backend (`app.py`) and a single-page frontend (`static/index.html`).
+
+**`app.py`** parses all GPX files in `garmin_gpx_exports/` at startup into an in-memory dict (`_rides`), keyed by filename stem. Stats (haversine distance, elevation gain/loss, HR zones) are computed once at load time. Three API routes:
+- `GET /api/rides` — summary list (no track points)
+- `GET /api/rides/{id}/points` — full lat/lon/ele/hr array
+- `POST /api/rides/{id}/insights` — streams AI response via OpenAI SDK
+
+**AI integration** uses the OpenAI Python SDK pointed at a local LLM endpoint (`LLAMACPP_BASE_URL` env var, defaults to `http://localhost:8080/v1`). The model name is auto-discovered from `GET /v1/models` at startup (falls back to `"local-model"`). The model is a reasoning model (GLM-4.7-Flash alias) that streams output into `reasoning_content` rather than the standard `content` field — the chunk reader handles both.
+
+**`static/index.html`** is a self-contained SPA (no build step). Leaflet.js draws the route as per-segment polylines colored by HR intensity. Chart.js renders elevation and HR profiles against cumulative distance. AI insights stream via `fetch` + `ReadableStream`.
+
+**`main.py`** is a separate Garmin Connect download script (not part of the web app).
+
+## GPX data notes
+
+- Garmin extension namespace for HR: `http://www.garmin.com/xmlschemas/TrackPointExtension/v1` (`ns3:hr`)
+- One file (`2026-06-21_18-17-11_Indoor Cycling_*`) has an empty `<trkseg/>` — `has_gps: false` in the API, frontend shows no map/charts for it
+- HR zone boundaries: Z1 <120, Z2 120–140, Z3 140–160, Z4 160–180, Z5 >180 bpm
diff --git a/README.md b/README.md
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+# gpxport
+
+A local web app for visualising Garmin cycling GPX files with AI coaching insights powered by a local LLM.
+
+![screenshot placeholder](https://placehold.co/900x500/0f1117/4f8ef7?text=gpxport)
+
+## Features
+
+- **Route map** — Leaflet.js map with per-segment polylines coloured by heart-rate intensity zone
+- **Elevation & HR charts** — Chart.js profiles plotted against cumulative distance
+- **Stats sidebar** — distance, duration, speed, elevation gain, avg/max HR, HR zone breakdown (Karvonen)
+- **AI coaching insights** — streaming post-ride feedback from a local LLM (via OpenAI-compatible API)
+- **Garmin sync** — fetch new rides directly from Garmin Connect, including MFA support
+- **Imperial/metric toggle** — persisted in `localStorage`
+
+## Requirements
+
+- Python 3.14+
+- [uv](https://github.com/astral-sh/uv)
+- A local OpenAI-compatible LLM server (e.g. [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://ollama.com))
+
+## Setup
+
+```bash
+# 1. Clone and install dependencies
+git clone https://github.com/yourname/gpxport
+cd gpxport
+uv sync
+
+# 2. Drop your GPX files into garmin_gpx_exports/
+#    (or use the in-app "Fetch from Garmin" button)
+
+# 3. Start the server
+LLAMACPP_BASE_URL=http://localhost:8080/v1 uv run uvicorn app:app --reload
+```
+
+Open http://localhost:8000 in your browser.
+
+## Configuration
+
+| Env var | Default | Description |
+|---|---|---|
+| `LLAMACPP_BASE_URL` | `http://localhost:8080/v1` | Base URL of your OpenAI-compatible LLM endpoint |
+
+The model name is auto-discovered from `GET /v1/models` at startup. If the endpoint is unreachable, insights generation is still available — only that feature degrades.
+
+## GPX files
+
+Place `.gpx` files exported from Garmin Connect (or any GPX-compliant device) in the `garmin_gpx_exports/` directory. The app parses all files at startup. Supported data:
+
+- Track points with `lat`/`lon`/`ele`/`time`
+- Heart rate via the Garmin extension namespace (`ns3:hr`)
+
+Activities with no track points (e.g. indoor rides) are listed with an "Indoor" badge and shown without a map or charts.
+
+## Standalone GPX downloader
+
+`main.py` is a standalone script for bulk-downloading your Garmin Connect cycling activities as GPX files without running the web server:
+
+```bash
+uv run python main.py
+```
+
+## API
+
+| Method | Path | Description |
+|---|---|---|
+| `GET` | `/api/rides` | Summary list of all rides (no track points) |
+| `GET` | `/api/rides/{id}` | Full ride metadata + cached insight |
+| `GET` | `/api/rides/{id}/points` | Full lat/lon/ele/hr array |
+| `POST` | `/api/rides/{id}/insights?rhr=60` | Stream AI coaching insight |
+| `POST` | `/api/insights/generate-all?rhr=60` | SSE stream — generate insights for all rides |
+| `POST` | `/api/fetch-rides` | SSE stream — fetch new rides from Garmin Connect |
+| `POST` | `/api/mfa` | Submit MFA code for an in-progress Garmin session |
+
+## HR zone boundaries (Karvonen)
+
+Zones are calculated from your resting HR (configurable in the UI) and the lifetime max HR observed across all rides:
+
+| Zone | % of HRR |
+|---|---|
+| Z1 | < 50% |
+| Z2 | 50–60% |
+| Z3 | 60–70% |
+| Z4 | 70–80% |
+| Z5 | > 80% |
+
+## License
+
+MIT
diff --git a/app.py b/app.py
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+++ b/app.py
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+import asyncio
+import json
+import logging
+import math
+import os
+import threading
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from xml.etree import ElementTree as ET
+
+from fastapi import FastAPI, HTTPException, Query, Request
+from fastapi.responses import StreamingResponse
+from fastapi.staticfiles import StaticFiles
+from garminconnect import Garmin, GarminConnectAuthenticationError
+from openai import OpenAI
+
+logging.basicConfig(
+    level=logging.DEBUG,
+    format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+    datefmt="%H:%M:%S",
+)
+log = logging.getLogger("gpxport")
+
+GPX_DIR = Path(__file__).parent / "garmin_gpx_exports"
+INSIGHTS_FILE = Path(__file__).parent / "insights.json"
+LLAMACPP_BASE_URL = os.getenv("LLAMACPP_BASE_URL", "http://localhost:8080/v1")
+MODEL_NAME = "local-model"  # overwritten at startup by auto-discovery
+
+app = FastAPI()
+
+_insights_cache: dict[str, str] = {}
+_mfa_sessions: dict[str, dict] = {}
+
+
+def _save_insights() -> None:
+    INSIGHTS_FILE.write_text(json.dumps(_insights_cache, indent=2, ensure_ascii=False))
+
+# ---------------------------------------------------------------------------
+# GPX parsing helpers
+# ---------------------------------------------------------------------------
+
+NS = {
+    "gpx": "http://www.topografix.com/GPX/1/1",
+    "ns3": "http://www.garmin.com/xmlschemas/TrackPointExtension/v1",
+}
+
+
+def haversine(lat1: float, lon1: float, lat2: float, lon2: float) -> float:
+    """Return distance in metres between two GPS coordinates."""
+    R = 6_371_000
+    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 parse_gpx(path: Path) -> dict:
+    tree = ET.parse(path)
+    root = tree.getroot()
+
+    name_el = root.find(".//gpx:trk/gpx:name", NS)
+    name = name_el.text if name_el is not None else path.stem
+    type_el = root.find(".//gpx:trk/gpx:type", NS)
+    activity_type = type_el.text if type_el is not None else "cycling"
+
+    points = []
+    for pt in root.findall(".//gpx:trkpt", NS):
+        lat = float(pt.get("lat"))
+        lon = float(pt.get("lon"))
+        ele_el = pt.find("gpx:ele", NS)
+        ele = float(ele_el.text) if ele_el is not None else 0.0
+        time_el = pt.find("gpx:time", NS)
+        ts = None
+        if time_el is not None:
+            ts = datetime.fromisoformat(time_el.text.replace("Z", "+00:00"))
+        hr_el = pt.find(".//ns3:hr", NS)
+        hr = int(hr_el.text) if hr_el is not None else None
+        points.append({"lat": lat, "lon": lon, "ele": ele, "time": ts, "hr": hr})
+
+    # Compute stats
+    distance_m = 0.0
+    ele_gain = 0.0
+    ele_loss = 0.0
+    for i in range(1, len(points)):
+        p0, p1 = points[i - 1], points[i]
+        distance_m += haversine(p0["lat"], p0["lon"], p1["lat"], p1["lon"])
+        de = p1["ele"] - p0["ele"]
+        if de > 0:
+            ele_gain += de
+        else:
+            ele_loss += abs(de)
+
+    duration_s = 0
+    start_time = None
+    end_time = None
+    if points and points[0]["time"] and points[-1]["time"]:
+        start_time = points[0]["time"]
+        end_time = points[-1]["time"]
+        duration_s = int((end_time - start_time).total_seconds())
+
+    hrs = [p["hr"] for p in points if p["hr"] is not None]
+    avg_hr = round(sum(hrs) / len(hrs)) if hrs else None
+    max_hr = max(hrs) if hrs else None
+
+    avg_speed_kmh = (distance_m / 1000) / (duration_s / 3600) if duration_s > 0 else 0
+
+    # HR zone distribution (% of points)
+    zone_counts = {"z1": 0, "z2": 0, "z3": 0, "z4": 0, "z5": 0}
+    for h in hrs:
+        if h < 120:
+            zone_counts["z1"] += 1
+        elif h < 140:
+            zone_counts["z2"] += 1
+        elif h < 160:
+            zone_counts["z3"] += 1
+        elif h < 180:
+            zone_counts["z4"] += 1
+        else:
+            zone_counts["z5"] += 1
+    total_hr_pts = len(hrs)
+    hr_zones = {
+        k: round(v / total_hr_pts * 100, 1) if total_hr_pts else 0
+        for k, v in zone_counts.items()
+    }
+
+    ride_id = path.stem  # use filename without extension as ID
+
+    return {
+        "id": ride_id,
+        "name": name,
+        "activity_type": activity_type,
+        "filename": path.name,
+        "start_time": start_time.isoformat() if start_time else None,
+        "end_time": end_time.isoformat() if end_time else None,
+        "duration_s": duration_s,
+        "distance_m": round(distance_m),
+        "distance_km": round(distance_m / 1000, 2),
+        "avg_speed_kmh": round(avg_speed_kmh, 1),
+        "elevation_gain_m": round(ele_gain),
+        "elevation_loss_m": round(ele_loss),
+        "avg_hr": avg_hr,
+        "max_hr": max_hr,
+        "hr_zones": hr_zones,
+        "has_gps": len(points) > 0 and points[0].get("lat") is not None,
+        "points": [
+            {
+                "lat": p["lat"],
+                "lon": p["lon"],
+                "ele": round(p["ele"], 1),
+                "time": p["time"].isoformat() if p["time"] else None,
+                "hr": p["hr"],
+            }
+            for p in points
+        ],
+    }
+
+
+# ---------------------------------------------------------------------------
+# Load all rides at startup
+# ---------------------------------------------------------------------------
+
+_rides: dict[str, dict] = {}
+
+
+@app.on_event("startup")
+def load_rides():
+    global MODEL_NAME
+    # Auto-discover model name from llamacpp
+    try:
+        client = OpenAI(base_url=LLAMACPP_BASE_URL, api_key="not-needed")
+        models = client.models.list()
+        first = next(iter(models), None)
+        if first:
+            MODEL_NAME = first.id
+            log.info("Discovered model: %s", MODEL_NAME)
+        else:
+            log.warning("No models returned from %s — using fallback '%s'", LLAMACPP_BASE_URL, MODEL_NAME)
+    except Exception as exc:
+        log.warning("Could not reach llamacpp at %s (%s) — using fallback '%s'", LLAMACPP_BASE_URL, exc, MODEL_NAME)
+
+    for gpx_file in sorted(GPX_DIR.glob("*.gpx"), reverse=True):
+        try:
+            ride = parse_gpx(gpx_file)
+            _rides[ride["id"]] = ride
+        except Exception as exc:
+            log.error("Failed to parse %s: %s", gpx_file.name, exc)
+    log.info("Loaded %d rides.", len(_rides))
+
+    if INSIGHTS_FILE.exists():
+        try:
+            _insights_cache.update(json.loads(INSIGHTS_FILE.read_text()))
+            cached = sum(1 for rid in _insights_cache if rid in _rides)
+            log.info("Loaded %d cached insights from %s", cached, INSIGHTS_FILE)
+        except Exception as exc:
+            log.warning("Could not load insights cache: %s", exc)
+
+
+# ---------------------------------------------------------------------------
+# API endpoints
+# ---------------------------------------------------------------------------
+
+
+@app.get("/api/rides")
+def list_rides():
+    summary_keys = [
+        "id", "name", "activity_type", "start_time", "duration_s",
+        "distance_km", "avg_speed_kmh", "elevation_gain_m",
+        "avg_hr", "max_hr", "has_gps",
+    ]
+    rides = []
+    for r in _rides.values():
+        rides.append({k: r[k] for k in summary_keys})
+    # Sort by start_time descending
+    rides.sort(key=lambda x: x["start_time"] or "", reverse=True)
+    return rides
+
+
+@app.get("/api/rides/{ride_id}")
+def get_ride(ride_id: str):
+    if ride_id not in _rides:
+        raise HTTPException(status_code=404, detail="Ride not found")
+    r = _rides[ride_id]
+    result = {k: v for k, v in r.items() if k != "points"}
+    result["cached_insight"] = _insights_cache.get(ride_id)
+    return result
+
+
+@app.get("/api/rides/{ride_id}/points")
+def get_ride_points(ride_id: str):
+    if ride_id not in _rides:
+        raise HTTPException(status_code=404, detail="Ride not found")
+    return _rides[ride_id]["points"]
+
+
+def _karvonen_zones(rhr: int, max_hr: int, points: list[dict]) -> dict:
+    hrr = max_hr - rhr
+    bounds = [rhr + p * hrr for p in (0.50, 0.60, 0.70, 0.80)]
+    labels = [
+        f"Z1 <{round(bounds[0])}bpm",
+        f"Z2 {round(bounds[0])}–{round(bounds[1])}bpm",
+        f"Z3 {round(bounds[1])}–{round(bounds[2])}bpm",
+        f"Z4 {round(bounds[2])}–{round(bounds[3])}bpm",
+        f"Z5 >{round(bounds[3])}bpm",
+    ]
+    hrs = [p["hr"] for p in points if p.get("hr") is not None]
+    if not hrs:
+        return {l: 0 for l in labels}
+    counts = [0] * 5
+    for h in hrs:
+        if h < bounds[0]: counts[0] += 1
+        elif h < bounds[1]: counts[1] += 1
+        elif h < bounds[2]: counts[2] += 1
+        elif h < bounds[3]: counts[3] += 1
+        else: counts[4] += 1
+    return {labels[i]: round(counts[i] / len(hrs) * 100, 1) for i in range(5)}
+
+
+def _llm_client() -> OpenAI:
+    return OpenAI(base_url=LLAMACPP_BASE_URL, api_key="not-needed")
+
+
+def _get_previous_insight(ride: dict) -> str | None:
+    """Return the cached insight for the most recent ride before this one, or None."""
+    ride_time = ride["start_time"]
+    if not ride_time:
+        return None
+    gps_rides = [r for r in _rides.values() if r["has_gps"] and r["distance_km"] > 0 and r["start_time"]]
+    prior = sorted(
+        [r for r in gps_rides if r["start_time"] < ride_time and r["id"] in _insights_cache],
+        key=lambda r: r["start_time"],
+    )
+    if not prior:
+        return None
+    return _insights_cache[prior[-1]["id"]]
+
+
+def _build_prompt(ride: dict, rhr: int, global_max_hr: int) -> str:
+    ride_time = ride["start_time"]
+    gps_rides = [r for r in _rides.values() if r["has_gps"] and r["distance_km"] > 0 and r["start_time"]]
+    past_rides = [r for r in gps_rides if r["start_time"] < ride_time]
+
+    zones = _karvonen_zones(rhr, global_max_hr, ride["points"])
+    zone_str = ", ".join(f"{k}={v}%" for k, v in zones.items())
+    duration_min = ride["duration_s"] // 60
+    ride_date = ride_time[:10] if ride_time else "unknown"
+
+    if past_rides:
+        avg_dist = sum(r["distance_km"] for r in past_rides) / len(past_rides)
+        hr_list = [r["avg_hr"] for r in past_rides if r["avg_hr"]]
+        avg_hr = sum(hr_list) / len(hr_list) if hr_list else 0
+        history_str = f"Before today they've completed {len(past_rides)} rides, averaging {avg_dist:.1f} km and {avg_hr:.0f} bpm."
+    else:
+        history_str = "This is one of their earliest recorded rides — no prior history to compare against."
+
+    previous_insight = _get_previous_insight(ride)
+    if previous_insight:
+        prior_section = f"""
+Your feedback from their last ride:
+---
+{previous_insight}
+---
+
+Based on that advice, briefly note (in one sentence woven naturally into your response) whether today's data suggests they followed it or not. Do not lecture about it — just one honest observation."""
+    else:
+        prior_section = ""
+
+    return f"""You are a friendly cycling coach giving post-ride feedback. You are writing this on {ride_date}, the day of the ride. Do not plan, outline, or show any reasoning — just write the response directly.
+
+Today's ride: {duration_min} min, {ride["distance_km"]} km, {ride["avg_speed_kmh"]} km/h, {ride["elevation_gain_m"]} m elevation. Avg HR {ride["avg_hr"]}, max {ride["max_hr"]}, resting HR {rhr} bpm (lifetime max {global_max_hr}). Time in zones: {zone_str}.
+
+Athlete history (as of {ride_date}): {history_str}{prior_section}
+
+Your response must begin with exactly one line in this format:
+TITLE: <a funny, punchy title for this specific ride in 4–8 words>
+
+Then one blank line, then write exactly 3–4 short paragraphs in a warm, direct "you/your" voice: effort level, what the zones reveal about the session type, how it compares to their history so far, one concrete suggestion. No bullet points, no headers, no preamble. Begin writing now."""
+
+
+@app.post("/api/rides/{ride_id}/insights")
+def get_insights(ride_id: str, rhr: int = Query(60, ge=30, le=100)):
+    if ride_id not in _rides:
+        raise HTTPException(status_code=404, detail="Ride not found")
+    ride = _rides[ride_id]
+
+    gps_rides = [r for r in _rides.values() if r["has_gps"] and r["distance_km"] > 0]
+    global_max_hr = max((r["max_hr"] or 0 for r in gps_rides), default=200)
+    prompt = _build_prompt(ride, rhr, global_max_hr)
+
+    client = _llm_client()
+    log.info("POST /insights ride_id=%s rhr=%d", ride_id, rhr)
+    log.debug("Prompt:\n%s", prompt)
+
+    def stream_response():
+        accumulated = []
+        try:
+            log.info("Opening stream...")
+            stream = client.chat.completions.create(
+                model=MODEL_NAME,
+                messages=[{"role": "user", "content": prompt}],
+                stream=True,
+                max_tokens=600,
+                extra_body={"chat_template_kwargs": {"enable_thinking": False}},
+            )
+            chunks_received = 0
+            for chunk in stream:
+                chunks_received += 1
+                if chunks_received <= 3:
+                    log.debug("Chunk #%d raw: %s", chunks_received, chunk.model_dump())
+                d = chunk.choices[0].delta.model_dump()
+                delta = d.get("content") or d.get("reasoning_content")
+                if delta:
+                    accumulated.append(delta)
+                    yield delta
+            log.info("Stream complete — %d chunks, %d chars", chunks_received, sum(len(c) for c in accumulated))
+            _insights_cache[ride_id] = "".join(accumulated)
+            _save_insights()
+            log.info("Saved insight for %s", ride_id)
+        except Exception as exc:
+            log.exception("Error streaming insights: %s", exc)
+            yield f"\n\n[Error: {exc}]"
+
+    return StreamingResponse(stream_response(), media_type="text/plain")
+
+
+@app.post("/api/insights/generate-all")
+def generate_all_insights(rhr: int = Query(60, ge=30, le=100)):
+    gps_rides = [r for r in _rides.values() if r["has_gps"] and r["distance_km"] > 0 and r["start_time"]]
+    global_max_hr = max((r["max_hr"] or 0 for r in gps_rides), default=200)
+    # Chronological order so time-aware context is always correct
+    ordered = sorted(gps_rides, key=lambda r: r["start_time"])
+    to_generate = [r for r in ordered if r["id"] not in _insights_cache]
+    total = len(to_generate)
+    log.info("generate-all: %d rides to generate (rhr=%d)", total, rhr)
+
+    def sse_stream():
+        client = _llm_client()
+        for idx, ride in enumerate(to_generate, 1):
+            ride_id = ride["id"]
+            yield f"data: {json.dumps({'index': idx, 'total': total, 'ride_id': ride_id, 'status': 'generating'})}\n\n"
+            log.info("Generating insight %d/%d: %s", idx, total, ride_id)
+            try:
+                prompt = _build_prompt(ride, rhr, global_max_hr)
+                response = client.chat.completions.create(
+                    model=MODEL_NAME,
+                    messages=[{"role": "user", "content": prompt}],
+                    stream=False,
+                    max_tokens=600,
+                    extra_body={"chat_template_kwargs": {"enable_thinking": False}},
+                )
+                msg = response.choices[0].message.model_dump()
+                text = msg.get("content") or msg.get("reasoning_content") or ""
+                _insights_cache[ride_id] = text
+                _save_insights()
+                yield f"data: {json.dumps({'index': idx, 'total': total, 'ride_id': ride_id, 'status': 'done'})}\n\n"
+            except Exception as exc:
+                log.exception("Failed insight for %s: %s", ride_id, exc)
+                yield f"data: {json.dumps({'index': idx, 'total': total, 'ride_id': ride_id, 'status': 'error', 'error': str(exc)})}\n\n"
+        yield f"data: {json.dumps({'status': 'complete', 'total': total})}\n\n"
+
+    return StreamingResponse(sse_stream(), media_type="text/event-stream")
+
+
+# ---------------------------------------------------------------------------
+# Garmin Connect sync
+# ---------------------------------------------------------------------------
+
+
+@app.post("/api/fetch-rides")
+async def fetch_rides_from_garmin(request: Request):
+    body = await request.json()
+    email = body.get("email", "")
+    password = body.get("password", "")
+
+    session_id = uuid.uuid4().hex
+    queue: asyncio.Queue = asyncio.Queue()
+    loop = asyncio.get_running_loop()
+    mfa_event = threading.Event()
+    _mfa_sessions[session_id] = {"event": mfa_event, "code": None}
+
+    def emit(evt):
+        loop.call_soon_threadsafe(queue.put_nowait, evt)
+
+    def prompt_mfa():
+        emit({"status": "mfa_required", "session_id": session_id})
+        mfa_event.wait(timeout=120)
+        return _mfa_sessions.get(session_id, {}).get("code") or ""
+
+    def garmin_worker():
+        try:
+            emit({"status": "auth"})
+            client = Garmin(email=email, password=password, prompt_mfa=prompt_mfa)
+            client.login()
+
+            emit({"status": "fetching"})
+            activities = client.get_activities(0, 50)
+            cycling = [
+                a for a in activities
+                if "cycling" in a.get("activityType", {}).get("typeKey", "")
+            ]
+
+            to_download = []
+            for act in cycling:
+                act_id = act["activityId"]
+                start = act.get("startTimeLocal", "")
+                name = act.get("activityName", "activity")
+                safe_time = start.replace(":", "-").replace(" ", "_")
+                safe_name = "".join(c for c in name if c.isalnum() or c in (" ", "_", "-")).strip()
+                filename = f"{safe_time}_{safe_name}_{act_id}.gpx"
+                if not (GPX_DIR / filename).exists():
+                    to_download.append((act_id, name, GPX_DIR / filename))
+
+            skipped = len(cycling) - len(to_download)
+            added = 0
+            for idx, (act_id, name, filepath) in enumerate(to_download, 1):
+                emit({"status": "downloading", "index": idx, "total": len(to_download), "name": name})
+                try:
+                    gpx_data = client.download_activity(act_id, dl_fmt=client.ActivityDownloadFormat.GPX)
+                    filepath.write_bytes(gpx_data)
+                    ride = parse_gpx(filepath)
+                    _rides[ride["id"]] = ride
+                    added += 1
+                except Exception as exc:
+                    log.error("Failed to download activity %s: %s", act_id, exc)
+
+            emit({"status": "complete", "added": added, "skipped": skipped})
+        except GarminConnectAuthenticationError:
+            emit({"status": "error", "message": "Login failed. Check your email and password."})
+        except Exception as exc:
+            log.exception("fetch-rides error: %s", exc)
+            emit({"status": "error", "message": str(exc)})
+        finally:
+            _mfa_sessions.pop(session_id, None)
+            emit(None)  # sentinel to end the SSE stream
+
+    async def generate():
+        loop.run_in_executor(None, garmin_worker)
+        while True:
+            evt = await queue.get()
+            if evt is None:
+                break
+            yield f"data: {json.dumps(evt)}\n\n"
+
+    return StreamingResponse(generate(), media_type="text/event-stream")
+
+
+@app.post("/api/mfa")
+async def submit_mfa(request: Request):
+    body = await request.json()
+    session_id = body.get("session_id", "")
+    code = body.get("code", "")
+    session = _mfa_sessions.get(session_id)
+    if not session:
+        raise HTTPException(status_code=404, detail="Session not found or expired")
+    session["code"] = code
+    session["event"].set()
+    return {"ok": True}
+
+
+# ---------------------------------------------------------------------------
+# Serve frontend
+# ---------------------------------------------------------------------------
+
+static_dir = Path(__file__).parent / "static"
+static_dir.mkdir(exist_ok=True)
+app.mount("/", StaticFiles(directory=static_dir, html=True), name="static")
diff --git a/garmin_gpx_exports/.gitkeep b/garmin_gpx_exports/.gitkeep
new file mode 100644
index 0000000..e69de29
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..c2d91cb
--- /dev/null
+++ b/main.py
@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+"""
+Download GPX files for your Garmin Connect activities.
+
+Setup:
+    pip install garminconnect
+
+Usage:
+    python garmin_gpx_export.py
+
+You'll be prompted for your Garmin Connect email and password
+(the same ones you use to log into connect.garmin.com).
+Credentials are only used locally to authenticate with Garmin's
+servers and are never stored or sent anywhere else.
+"""
+
+import getpass
+import os
+from datetime import datetime
+
+from garminconnect import Garmin, GarminConnectAuthenticationError
+
+
+def get_mfa_code():
+    """Called automatically by garminconnect if Garmin requests an MFA code."""
+    return input("Enter the MFA code sent to you by Garmin: ").strip()
+
+
+def main():
+    # --- Login ---
+    email = input("Garmin Connect email: ").strip()
+    password = getpass.getpass("Garmin Connect password: ")
+
+    try:
+        client = Garmin(email=email, password=password, prompt_mfa=get_mfa_code)
+        client.login()
+    except GarminConnectAuthenticationError:
+        print("Login failed. Check your email/password/MFA code.")
+        return
+
+    print(f"Logged in as {client.get_full_name()}")
+
+    # --- Config ---
+    output_dir = "garmin_gpx_exports"
+    os.makedirs(output_dir, exist_ok=True)
+
+    # How many recent activities to check (increase if you want more history)
+    limit = 50
+
+    # Only export activities matching this type, or set to None for all types.
+    # Common values: "cycling", "running", "walking", "hiking", "swimming"
+    activity_type_filter = "cycling"
+
+    # --- Fetch activity list ---
+    activities = client.get_activities(0, limit)
+    print(f"Found {len(activities)} recent activities (checking up to {limit}).")
+
+    exported = 0
+    for act in activities:
+        act_type = act.get("activityType", {}).get("typeKey", "")
+        if activity_type_filter and activity_type_filter not in act_type:
+            continue
+
+        activity_id = act["activityId"]
+        start_time = act.get("startTimeLocal", "unknown_time")
+        name = act.get("activityName", "activity")
+
+        # Sanitize filename
+        safe_time = start_time.replace(":", "-").replace(" ", "_")
+        safe_name = "".join(c for c in name if c.isalnum() or c in (" ", "_", "-")).strip()
+        filename = f"{safe_time}_{safe_name}_{activity_id}.gpx"
+        filepath = os.path.join(output_dir, filename)
+
+        if os.path.exists(filepath):
+            print(f"  Skipping (already downloaded): {filename}")
+            continue
+
+        try:
+            gpx_data = client.download_activity(
+                activity_id, dl_fmt=client.ActivityDownloadFormat.GPX
+            )
+            with open(filepath, "wb") as f:
+                f.write(gpx_data)
+            print(f"  Saved: {filename}")
+            exported += 1
+        except Exception as e:
+            print(f"  Failed to export activity {activity_id}: {e}")
+
+    print(f"\nDone. Exported {exported} new GPX file(s) to ./{output_dir}/")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..251fef9
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,12 @@
+[project]
+name = "gpxport"
+version = "0.1.0"
+description = "GPX ride viewer with Leaflet maps, Chart.js profiles, and local-LLM coaching insights"
+readme = "README.md"
+requires-python = ">=3.14"
+dependencies = [
+    "garminconnect>=0.3.6",
+    "fastapi>=0.115.0",
+    "uvicorn[standard]>=0.30.0",
+    "openai>=1.50.0",
+]
diff --git a/static/index.html b/static/index.html
new file mode 100644
index 0000000..76cd931
--- /dev/null
+++ b/static/index.html
@@ -0,0 +1,810 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Bike Ride Insights</title>
+<link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css"/>
+<script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js"></script>
+<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
+<style>
+  * { box-sizing: border-box; margin: 0; padding: 0; }
+  :root {
+    --bg: #0f1117;
+    --surface: #1a1d27;
+    --surface2: #22263a;
+    --border: #2e3354;
+    --accent: #4f8ef7;
+    --text: #e4e8f0;
+    --muted: #7a83a8;
+    --green: #43d98c;
+    --orange: #f5a524;
+    --red: #f24343;
+    --z1: #60a5fa;
+    --z2: #34d399;
+    --z3: #fbbf24;
+    --z4: #f97316;
+    --z5: #ef4444;
+  }
+  body { background: var(--bg); color: var(--text); font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif; font-size: 13px; display: flex; height: 100vh; overflow: hidden; }
+
+  /* Sidebar */
+  #sidebar { width: 280px; flex-shrink: 0; background: var(--surface); border-right: 1px solid var(--border); display: flex; flex-direction: column; overflow: hidden; }
+  #sidebar-header { padding: 16px; border-bottom: 1px solid var(--border); }
+  #sidebar-header h1 { font-size: 15px; font-weight: 600; color: var(--text); }
+  #sidebar-header p { color: var(--muted); font-size: 11px; margin-top: 2px; }
+  #ride-list { flex: 1; overflow-y: auto; }
+  #ride-list::-webkit-scrollbar { width: 4px; }
+  #ride-list::-webkit-scrollbar-thumb { background: var(--border); border-radius: 2px; }
+
+  .ride-item { padding: 12px 16px; border-bottom: 1px solid var(--border); cursor: pointer; transition: background 0.15s; }
+  .ride-item:hover { background: var(--surface2); }
+  .ride-item.active { background: var(--surface2); border-left: 3px solid var(--accent); padding-left: 13px; }
+  .ride-date { font-size: 11px; color: var(--muted); margin-bottom: 3px; }
+  .ride-name { font-size: 13px; font-weight: 500; color: var(--text); margin-bottom: 6px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+  .ride-stats { display: flex; gap: 10px; flex-wrap: wrap; }
+  .stat-badge { font-size: 11px; color: var(--muted); }
+  .stat-badge span { color: var(--text); font-weight: 500; }
+  .indoor-badge { display: inline-block; font-size: 10px; background: #2e3354; color: var(--muted); padding: 1px 6px; border-radius: 8px; margin-top: 2px; }
+  .rhr-row { display: flex; align-items: center; gap: 6px; margin-top: 8px; padding-top: 8px; border-top: 1px solid var(--border); }
+  .rhr-row label { font-size: 11px; color: var(--muted); flex-shrink: 0; }
+  .rhr-row input { width: 48px; background: var(--surface2); border: 1px solid var(--border); border-radius: 5px; color: var(--text); font-size: 12px; padding: 2px 6px; text-align: center; }
+  .rhr-row input:focus { outline: none; border-color: var(--accent); }
+  .rhr-row span { font-size: 11px; color: var(--muted); }
+  .rhr-maxhr { font-size: 10px; color: var(--muted); margin-left: auto; }
+  #unit-toggle { font-size: 10px; color: var(--muted); background: var(--surface2); border: 1px solid var(--border); border-radius: 4px; padding: 2px 6px; cursor: pointer; transition: border-color 0.15s, color 0.15s; }
+  #unit-toggle:hover { border-color: var(--accent); color: var(--accent); }
+  #gen-all-btn { margin-top: 8px; width: 100%; padding: 6px; background: var(--surface2); border: 1px solid var(--border); border-radius: 6px; color: var(--muted); font-size: 11px; cursor: pointer; transition: all 0.15s; }
+  #gen-all-btn:hover:not(:disabled) { border-color: var(--accent); color: var(--text); }
+  #gen-all-btn:disabled { opacity: 0.5; cursor: not-allowed; }
+  #gen-all-progress { margin-top: 6px; display: none; }
+  #gen-all-bar-bg { background: var(--surface2); border-radius: 3px; height: 4px; overflow: hidden; }
+  #gen-all-bar { height: 100%; background: var(--accent); border-radius: 3px; width: 0%; transition: width 0.3s; }
+  #gen-all-label { font-size: 10px; color: var(--muted); margin-top: 3px; }
+  #fetch-btn { margin-top: 4px; width: 100%; padding: 6px; background: var(--surface2); border: 1px solid var(--border); border-radius: 6px; color: var(--muted); font-size: 11px; cursor: pointer; transition: all 0.15s; }
+  #fetch-btn:hover:not(:disabled) { border-color: var(--green); color: var(--text); }
+  #fetch-btn:disabled { opacity: 0.5; cursor: not-allowed; }
+
+  /* Fetch modal */
+  #fetch-modal-overlay { display: none; position: fixed; inset: 0; background: rgba(0,0,0,0.6); z-index: 1000; align-items: center; justify-content: center; }
+  #fetch-modal-overlay.open { display: flex; }
+  #fetch-modal { background: var(--surface); border: 1px solid var(--border); border-radius: 12px; padding: 20px; width: 300px; display: flex; flex-direction: column; gap: 12px; }
+  #fetch-modal h2 { font-size: 14px; font-weight: 600; color: var(--text); }
+  .fetch-field { display: flex; flex-direction: column; gap: 4px; }
+  .fetch-field label { font-size: 11px; color: var(--muted); }
+  .fetch-field input { background: var(--surface2); border: 1px solid var(--border); border-radius: 6px; color: var(--text); font-size: 13px; padding: 7px 10px; width: 100%; }
+  .fetch-field input:focus { outline: none; border-color: var(--accent); }
+  #fetch-status { font-size: 11px; color: var(--muted); min-height: 16px; }
+  #fetch-status.error { color: var(--red); }
+  #fetch-mfa-section { display: none; flex-direction: column; gap: 8px; padding-top: 4px; border-top: 1px solid var(--border); }
+  #fetch-mfa-section p { font-size: 11px; color: var(--muted); }
+  .fetch-modal-actions { display: flex; gap: 8px; }
+  .fetch-modal-actions button { flex: 1; padding: 8px; border-radius: 7px; font-size: 12px; font-weight: 500; cursor: pointer; border: 1px solid var(--border); transition: all 0.15s; }
+  #fetch-submit-btn { background: var(--accent); color: #fff; border-color: var(--accent); }
+  #fetch-submit-btn:hover:not(:disabled) { opacity: 0.85; }
+  #fetch-submit-btn:disabled { opacity: 0.5; cursor: not-allowed; }
+  #fetch-cancel-btn { background: var(--surface2); color: var(--muted); }
+  #fetch-cancel-btn:hover { color: var(--text); border-color: var(--muted); }
+  #fetch-mfa-submit-btn { background: var(--accent); color: #fff; border-color: var(--accent); }
+  #fetch-mfa-submit-btn:hover:not(:disabled) { opacity: 0.85; }
+  #fetch-mfa-submit-btn:disabled { opacity: 0.5; cursor: not-allowed; }
+
+  /* Main */
+  #main { flex: 1; display: flex; flex-direction: column; overflow: hidden; }
+  #map-container { flex: 1; min-height: 0; position: relative; }
+  #map { width: 100%; height: 100%; }
+  .no-gps-overlay { position: absolute; inset: 0; display: flex; align-items: center; justify-content: center; background: var(--surface); flex-direction: column; gap: 8px; }
+  .no-gps-overlay .icon { font-size: 32px; }
+  .no-gps-overlay p { color: var(--muted); font-size: 13px; }
+  #charts-panel { height: 180px; background: var(--surface); border-top: 1px solid var(--border); display: flex; overflow: hidden; }
+  .chart-wrap { flex: 1; padding: 8px 12px; min-width: 0; position: relative; }
+  .chart-wrap h3 { font-size: 10px; color: var(--muted); font-weight: 500; text-transform: uppercase; letter-spacing: 0.5px; margin-bottom: 4px; }
+  .chart-wrap canvas { width: 100% !important; }
+  .chart-divider { width: 1px; background: var(--border); flex-shrink: 0; }
+  #empty-state { flex: 1; display: flex; align-items: center; justify-content: center; flex-direction: column; gap: 8px; color: var(--muted); }
+  #empty-state .big { font-size: 32px; }
+
+  /* Right panel */
+  #details { width: 300px; flex-shrink: 0; background: var(--surface); border-left: 1px solid var(--border); display: flex; flex-direction: column; overflow: hidden; }
+  #details-scroll { flex: 1; overflow-y: auto; padding: 16px; }
+  #details-scroll::-webkit-scrollbar { width: 4px; }
+  #details-scroll::-webkit-scrollbar-thumb { background: var(--border); border-radius: 2px; }
+  #details-header { margin-bottom: 12px; }
+  #details-title { font-size: 14px; font-weight: 600; color: var(--text); }
+  #details-date { font-size: 11px; color: var(--muted); margin-top: 2px; }
+  .stats-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 8px; margin-bottom: 16px; }
+  .stat-card { background: var(--surface2); border-radius: 8px; padding: 10px; }
+  .stat-card .label { font-size: 10px; color: var(--muted); text-transform: uppercase; letter-spacing: 0.4px; margin-bottom: 4px; }
+  .stat-card .value { font-size: 16px; font-weight: 600; color: var(--text); }
+  .stat-card .unit { font-size: 10px; color: var(--muted); font-weight: 400; }
+  .section-title { font-size: 10px; color: var(--muted); text-transform: uppercase; letter-spacing: 0.5px; margin-bottom: 8px; font-weight: 500; }
+  .hr-zones { margin-bottom: 16px; }
+  .zone-row { display: flex; align-items: center; gap: 8px; margin-bottom: 5px; }
+  .zone-label { width: 60px; font-size: 11px; color: var(--muted); flex-shrink: 0; }
+  .zone-bar-bg { flex: 1; background: var(--surface2); border-radius: 3px; height: 6px; overflow: hidden; }
+  .zone-bar { height: 100%; border-radius: 3px; transition: width 0.4s; }
+  .zone-pct { width: 36px; text-align: right; font-size: 11px; color: var(--muted); }
+  .zone-z1 { background: var(--z1); }
+  .zone-z2 { background: var(--z2); }
+  .zone-z3 { background: var(--z3); }
+  .zone-z4 { background: var(--z4); }
+  .zone-z5 { background: var(--z5); }
+  #insights-section { border-bottom: 1px solid var(--border); padding: 12px 16px; flex-shrink: 0; }
+  #insights-btn { width: 100%; padding: 9px; background: var(--accent); color: #fff; border: none; border-radius: 8px; font-size: 13px; font-weight: 500; cursor: pointer; transition: opacity 0.2s; }
+  #insights-btn:hover { opacity: 0.85; }
+  #insights-btn:disabled { opacity: 0.5; cursor: not-allowed; }
+  #ride-funny-title { margin-top: 12px; font-size: 13px; font-style: italic; font-weight: 600; color: var(--accent); min-height: 0; }
+  #ride-funny-title:empty { display: none; }
+  #insights-text { margin-top: 6px; font-size: 12px; line-height: 1.7; color: var(--text); white-space: pre-wrap; }
+  .blinking { display: inline-block; width: 2px; height: 12px; background: var(--accent); animation: blink 0.8s step-end infinite; margin-left: 2px; vertical-align: middle; }
+  @keyframes blink { 50% { opacity: 0; } }
+  .no-ride-msg { color: var(--muted); font-size: 12px; text-align: center; padding: 24px 16px; }
+</style>
+</head>
+<body>
+
+<div id="sidebar">
+  <div id="sidebar-header">
+    <h1>Bike Rides</h1>
+    <p id="ride-count">Loading...</p>
+    <div class="rhr-row">
+      <label for="rhr-input">Resting HR</label>
+      <input id="rhr-input" type="number" min="30" max="100" value="60">
+      <span>bpm</span>
+      <span class="rhr-maxhr" id="rhr-maxhr"></span>
+      <button id="unit-toggle" title="Toggle units">km</button>
+    </div>
+    <button id="gen-all-btn">Generate all insights</button>
+    <div id="gen-all-progress">
+      <div id="gen-all-bar-bg"><div id="gen-all-bar"></div></div>
+      <div id="gen-all-label"></div>
+    </div>
+    <button id="fetch-btn">Fetch new rides from Garmin</button>
+  </div>
+
+  <div id="fetch-modal-overlay">
+    <div id="fetch-modal">
+      <h2>Fetch rides from Garmin</h2>
+      <div class="fetch-field">
+        <label for="fetch-email">Email</label>
+        <input id="fetch-email" type="email" placeholder="you@example.com" autocomplete="email">
+      </div>
+      <div class="fetch-field">
+        <label for="fetch-password">Password</label>
+        <input id="fetch-password" type="password" placeholder="••••••••" autocomplete="current-password">
+      </div>
+      <div id="fetch-status"></div>
+      <div id="fetch-mfa-section">
+        <p>Garmin sent a verification code to your email or phone.</p>
+        <div class="fetch-field">
+          <label for="fetch-mfa-code">Verification code</label>
+          <input id="fetch-mfa-code" type="text" inputmode="numeric" placeholder="123456" autocomplete="one-time-code">
+        </div>
+        <button id="fetch-mfa-submit-btn">Submit code</button>
+      </div>
+      <div class="fetch-modal-actions">
+        <button id="fetch-cancel-btn">Cancel</button>
+        <button id="fetch-submit-btn">Fetch</button>
+      </div>
+    </div>
+  </div>
+  <div id="ride-list"></div>
+</div>
+
+<div id="main">
+  <div id="map-container">
+    <div id="map"></div>
+    <div class="no-gps-overlay" id="no-gps" style="display:none">
+      <div class="icon">🚴</div>
+      <p>Indoor ride — no GPS data</p>
+    </div>
+  </div>
+  <div id="charts-panel">
+    <div id="empty-state">
+      <div class="big">🗺</div>
+      <span>Select a ride to view details</span>
+    </div>
+    <div class="chart-wrap" id="ele-chart-wrap" style="display:none">
+      <h3>Elevation</h3>
+      <canvas id="ele-chart"></canvas>
+    </div>
+    <div class="chart-divider" id="chart-divider" style="display:none"></div>
+    <div class="chart-wrap" id="hr-chart-wrap" style="display:none">
+      <h3>Heart Rate</h3>
+      <canvas id="hr-chart"></canvas>
+    </div>
+  </div>
+</div>
+
+<div id="details">
+  <div id="insights-section" style="display:none;padding:12px 16px;border-bottom:1px solid var(--border);">
+    <button id="insights-btn">Generate AI Insights</button>
+  </div>
+  <div id="details-scroll">
+    <div class="no-ride-msg" id="no-ride-msg">Select a ride from the list</div>
+    <div id="ride-details" style="display:none">
+      <div id="details-header">
+        <div id="details-title"></div>
+        <div id="details-date"></div>
+      </div>
+      <div class="stats-grid">
+        <div class="stat-card"><div class="label">Distance</div><div class="value" id="d-dist">—</div></div>
+        <div class="stat-card"><div class="label">Duration</div><div class="value" id="d-dur">—</div></div>
+        <div class="stat-card"><div class="label">Avg Speed</div><div class="value" id="d-spd">—</div></div>
+        <div class="stat-card"><div class="label">Elevation ↑</div><div class="value" id="d-ele">—</div></div>
+        <div class="stat-card"><div class="label">Avg HR</div><div class="value" id="d-hr">—</div></div>
+        <div class="stat-card"><div class="label">Max HR</div><div class="value" id="d-maxhr">—</div></div>
+      </div>
+      <div class="section-title">HR Zones</div>
+      <div class="hr-zones" id="hr-zones"></div>
+      <div id="ride-funny-title"></div>
+      <div id="insights-text"></div>
+    </div>
+  </div>
+</div>
+
+<script>
+const map = L.map('map', { zoomControl: true }).setView([37.7749, -122.4194], 11);
+L.tileLayer('https://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}{r}.png', {
+  attribution: '© OpenStreetMap contributors © CARTO', maxZoom: 19, subdomains: 'abcd'
+}).addTo(map);
+
+let allRides = [];
+let currentRide = null;
+let currentRideId = null;
+let currentPoints = [];
+let routeLayer = null;
+let eleChart = null;
+let hrChart = null;
+let globalMaxHr = 200;
+
+// Karvonen: zone boundaries as BPM values
+function zoneBoundaries() {
+  const rhr = parseInt(document.getElementById('rhr-input').value) || 60;
+  const maxHr = globalMaxHr;
+  const hrr = maxHr - rhr;
+  return [
+    rhr + 0.50 * hrr,  // Z1 upper
+    rhr + 0.60 * hrr,  // Z2 upper
+    rhr + 0.70 * hrr,  // Z3 upper
+    rhr + 0.80 * hrr,  // Z4 upper
+  ];
+}
+
+function hrColor(hr) {
+  if (!hr) return '#60a5fa';
+  const [z1, z2, z3, z4] = zoneBoundaries();
+  if (hr < z1) return '#60a5fa';
+  if (hr < z2) return '#34d399';
+  if (hr < z3) return '#fbbf24';
+  if (hr < z4) return '#f97316';
+  return '#ef4444';
+}
+
+// Compute zone % distribution from raw HR points using Karvonen boundaries
+function computeZones(points) {
+  const hrs = points.map(p => p.hr).filter(h => h != null);
+  if (!hrs.length) return null;
+  const [z1, z2, z3, z4] = zoneBoundaries();
+  const counts = [0, 0, 0, 0, 0];
+  for (const h of hrs) {
+    if (h < z1) counts[0]++;
+    else if (h < z2) counts[1]++;
+    else if (h < z3) counts[2]++;
+    else if (h < z4) counts[3]++;
+    else counts[4]++;
+  }
+  return counts.map(c => Math.round(c / hrs.length * 100));
+}
+
+// Unit system
+let imperial = localStorage.getItem('units') === 'imperial';
+function setImperial(val) {
+  imperial = val;
+  localStorage.setItem('units', imperial ? 'imperial' : 'metric');
+  document.getElementById('unit-toggle').textContent = imperial ? 'mi' : 'km';
+}
+function fmtDist(km) {
+  if (!imperial) return `${km}<span class="unit"> km</span>`;
+  return `${(km * 0.621371).toFixed(2)}<span class="unit"> mi</span>`;
+}
+function fmtDistShort(km) {
+  if (!imperial) return `${km}km`;
+  return `${(km * 0.621371).toFixed(1)}mi`;
+}
+function fmtSpeed(kmh) {
+  if (!imperial) return `${kmh}<span class="unit"> km/h</span>`;
+  return `${(kmh * 0.621371).toFixed(1)}<span class="unit"> mph</span>`;
+}
+function fmtEle(m) {
+  if (!imperial) return `${m}<span class="unit"> m</span>`;
+  return `${Math.round(m * 3.28084)}<span class="unit"> ft</span>`;
+}
+
+function fmtDuration(s) {
+  const h = Math.floor(s / 3600), m = Math.floor((s % 3600) / 60);
+  if (h > 0) return `${h}h ${m}m`;
+  return `${m}m`;
+}
+
+function fmtDate(iso) {
+  if (!iso) return '';
+  const d = new Date(iso);
+  return d.toLocaleDateString('en-US', { weekday: 'short', month: 'short', day: 'numeric', year: 'numeric' });
+}
+
+function fmtTime(iso) {
+  if (!iso) return '';
+  return new Date(iso).toLocaleTimeString('en-US', { hour: 'numeric', minute: '2-digit' });
+}
+
+// Persist RHR in localStorage
+const rhrInput = document.getElementById('rhr-input');
+rhrInput.value = localStorage.getItem('rhr') || 60;
+rhrInput.addEventListener('change', () => {
+  localStorage.setItem('rhr', rhrInput.value);
+  if (currentPoints.length) {
+    renderZones(currentPoints);
+    renderMap(currentPoints);
+  }
+});
+
+// Load ride list
+async function loadRides() {
+  const res = await fetch('/api/rides');
+  allRides = await res.json();
+  globalMaxHr = Math.max(...allRides.map(r => r.max_hr || 0), 160);
+  document.getElementById('ride-count').textContent = `${allRides.length} rides`;
+  document.getElementById('rhr-maxhr').textContent = `max ${globalMaxHr}`;
+  renderRideList();
+}
+
+function renderRideList() {
+  const list = document.getElementById('ride-list');
+  list.innerHTML = '';
+  for (const r of allRides) {
+    const el = document.createElement('div');
+    el.className = 'ride-item';
+    el.dataset.id = r.id;
+    const date = r.start_time ? fmtDate(r.start_time) : 'Unknown date';
+    const dist = r.has_gps ? `<span>${fmtDistShort(r.distance_km)}</span>` : '';
+    const dur = r.duration_s ? `<span>${fmtDuration(r.duration_s)}</span>` : '';
+    const hr = r.avg_hr ? `<span>${r.avg_hr}bpm</span>` : '';
+    const indoor = !r.has_gps ? '<span class="indoor-badge">Indoor</span>' : '';
+    el.innerHTML = `
+      <div class="ride-date">${date}</div>
+      <div class="ride-name">${r.name}</div>
+      <div class="ride-stats">
+        ${dist ? `<div class="stat-badge">${dist}</div>` : ''}
+        ${dur ? `<div class="stat-badge">${dur}</div>` : ''}
+        ${hr ? `<div class="stat-badge">${hr}</div>` : ''}
+      </div>
+      ${indoor}
+    `;
+    el.addEventListener('click', () => selectRide(r.id));
+    list.appendChild(el);
+  }
+}
+
+async function selectRide(id) {
+  if (currentRideId === id) return;
+  currentRideId = id;
+
+  // Update active state
+  document.querySelectorAll('.ride-item').forEach(el => {
+    el.classList.toggle('active', el.dataset.id === id);
+  });
+
+  // Fetch full ride metadata
+  const res = await fetch(`/api/rides/${encodeURIComponent(id)}`);
+  currentRide = await res.json();
+
+  renderDetails(currentRide);
+
+  if (currentRide.has_gps) {
+    // Fetch points
+    const pRes = await fetch(`/api/rides/${encodeURIComponent(id)}/points`);
+    currentPoints = await pRes.json();
+    renderMap(currentPoints);
+    renderCharts(currentPoints);
+    renderZones(currentPoints);
+    document.getElementById('no-gps').style.display = 'none';
+    document.getElementById('ele-chart-wrap').style.display = '';
+    document.getElementById('hr-chart-wrap').style.display = '';
+    document.getElementById('chart-divider').style.display = '';
+    document.getElementById('empty-state').style.display = 'none';
+  } else {
+    currentPoints = [];
+    clearMap();
+    clearCharts();
+    document.getElementById('no-gps').style.display = 'flex';
+    document.getElementById('ele-chart-wrap').style.display = 'none';
+    document.getElementById('hr-chart-wrap').style.display = 'none';
+    document.getElementById('chart-divider').style.display = 'none';
+    document.getElementById('empty-state').style.display = 'none';
+  }
+
+  // Show cached insight or reset
+  const insightEl = document.getElementById('insights-text');
+  const insightBtn = document.getElementById('insights-btn');
+  if (currentRide.cached_insight) {
+    renderInsight(currentRide.cached_insight);
+    insightBtn.textContent = 'Regenerate';
+  } else {
+    renderInsight('');
+    insightBtn.textContent = 'Generate AI Insights';
+  }
+  insightBtn.disabled = false;
+}
+
+function renderDetails(ride) {
+  document.getElementById('no-ride-msg').style.display = 'none';
+  document.getElementById('ride-details').style.display = '';
+  document.getElementById('insights-section').style.display = '';
+
+  document.getElementById('details-title').textContent = ride.name;
+  const dateStr = ride.start_time ? `${fmtDate(ride.start_time)} · ${fmtTime(ride.start_time)}` : '';
+  document.getElementById('details-date').textContent = dateStr;
+
+  document.getElementById('d-dist').innerHTML = ride.has_gps ? fmtDist(ride.distance_km) : '—';
+  document.getElementById('d-dur').textContent = ride.duration_s ? fmtDuration(ride.duration_s) : '—';
+  document.getElementById('d-spd').innerHTML = ride.has_gps ? fmtSpeed(ride.avg_speed_kmh) : '—';
+  document.getElementById('d-ele').innerHTML = ride.has_gps ? fmtEle(ride.elevation_gain_m) : '—';
+  document.getElementById('d-hr').innerHTML = ride.avg_hr ? `${ride.avg_hr}<span class="unit"> bpm</span>` : '—';
+  document.getElementById('d-maxhr').innerHTML = ride.max_hr ? `${ride.max_hr}<span class="unit"> bpm</span>` : '—';
+
+}
+
+function renderZones(points) {
+  const pcts = computeZones(points);
+  const bounds = zoneBoundaries();
+  const labels = [
+    `Z1 <${Math.round(bounds[0])}`,
+    `Z2 ${Math.round(bounds[0])}–${Math.round(bounds[1])}`,
+    `Z3 ${Math.round(bounds[1])}–${Math.round(bounds[2])}`,
+    `Z4 ${Math.round(bounds[2])}–${Math.round(bounds[3])}`,
+    `Z5 >${Math.round(bounds[3])}`,
+  ];
+  const classes = ['zone-z1', 'zone-z2', 'zone-z3', 'zone-z4', 'zone-z5'];
+  const zonesEl = document.getElementById('hr-zones');
+  if (!pcts) { zonesEl.innerHTML = ''; return; }
+  zonesEl.innerHTML = labels.map((label, i) => `
+    <div class="zone-row">
+      <div class="zone-label">${label}</div>
+      <div class="zone-bar-bg"><div class="zone-bar ${classes[i]}" style="width:${pcts[i]}%"></div></div>
+      <div class="zone-pct">${pcts[i]}%</div>
+    </div>
+  `).join('');
+}
+
+function clearMap() {
+  if (routeLayer) { map.removeLayer(routeLayer); routeLayer = null; }
+}
+
+function renderMap(points) {
+  clearMap();
+  if (!points.length) return;
+
+  // Draw segments colored by HR
+  const layers = [];
+  for (let i = 1; i < points.length; i++) {
+    const p0 = points[i - 1], p1 = points[i];
+    const color = hrColor(p1.hr || p0.hr);
+    layers.push(L.polyline([[p0.lat, p0.lon], [p1.lat, p1.lon]], { color, weight: 4, opacity: 0.9 }));
+  }
+
+  // Start/end markers
+  const startPt = points[0], endPt = points[points.length - 1];
+  const startIcon = L.divIcon({ html: '<div style="background:#43d98c;width:10px;height:10px;border-radius:50%;border:2px solid white;"></div>', iconSize: [10, 10], iconAnchor: [5, 5], className: '' });
+  const endIcon = L.divIcon({ html: '<div style="background:#f24343;width:10px;height:10px;border-radius:50%;border:2px solid white;"></div>', iconSize: [10, 10], iconAnchor: [5, 5], className: '' });
+
+  routeLayer = L.layerGroup([...layers, L.marker([startPt.lat, startPt.lon], { icon: startIcon }), L.marker([endPt.lat, endPt.lon], { icon: endIcon })]).addTo(map);
+
+  const latlngs = points.map(p => [p.lat, p.lon]);
+  map.fitBounds(L.latLngBounds(latlngs), { padding: [30, 30] });
+}
+
+function clearCharts() {
+  if (eleChart) { eleChart.destroy(); eleChart = null; }
+  if (hrChart) { hrChart.destroy(); hrChart = null; }
+}
+
+function renderCharts(points) {
+  clearCharts();
+  if (!points.length) return;
+
+  // Downsample to at most 500 points for chart performance
+  const step = Math.max(1, Math.floor(points.length / 500));
+  const sampled = points.filter((_, i) => i % step === 0);
+
+  // Compute cumulative distance for x-axis
+  let dist = 0;
+  const xLabels = [], eleData = [], hrData = [];
+  for (let i = 0; i < sampled.length; i++) {
+    if (i > 0) {
+      const p0 = sampled[i - 1], p1 = sampled[i];
+      const d = haversine(p0.lat, p0.lon, p1.lat, p1.lon);
+      dist += d / 1000;
+    }
+    xLabels.push(imperial ? (dist * 0.621371).toFixed(1) : dist.toFixed(1));
+    eleData.push(imperial ? +(sampled[i].ele * 3.28084).toFixed(0) : sampled[i].ele);
+    hrData.push(sampled[i].hr);
+  }
+
+  const chartDefaults = {
+    responsive: true,
+    maintainAspectRatio: false,
+    animation: false,
+    plugins: { legend: { display: false }, tooltip: { mode: 'index', intersect: false, backgroundColor: '#1a1d27', titleColor: '#7a83a8', bodyColor: '#e4e8f0', borderColor: '#2e3354', borderWidth: 1 } },
+    scales: {
+      x: { ticks: { color: '#7a83a8', maxTicksLimit: 6, font: { size: 10 } }, grid: { color: '#1e2235' }, title: { display: true, text: imperial ? 'mi' : 'km', color: '#7a83a8', font: { size: 10 } } },
+      y: { ticks: { color: '#7a83a8', font: { size: 10 } }, grid: { color: '#1e2235' } },
+    },
+    elements: { point: { radius: 0 } },
+  };
+
+  const eleCtx = document.getElementById('ele-chart').getContext('2d');
+  eleChart = new Chart(eleCtx, {
+    type: 'line',
+    data: {
+      labels: xLabels,
+      datasets: [{ data: eleData, borderColor: '#4f8ef7', backgroundColor: 'rgba(79,142,247,0.1)', fill: true, borderWidth: 1.5, tension: 0.3 }],
+    },
+    options: { ...chartDefaults, scales: { ...chartDefaults.scales, y: { ...chartDefaults.scales.y, title: { display: true, text: imperial ? 'ft' : 'm', color: '#7a83a8', font: { size: 10 } } } } },
+  });
+
+  const hrCtx = document.getElementById('hr-chart').getContext('2d');
+  hrChart = new Chart(hrCtx, {
+    type: 'line',
+    data: {
+      labels: xLabels,
+      datasets: [{ data: hrData, borderColor: '#f97316', backgroundColor: 'rgba(249,115,22,0.1)', fill: true, borderWidth: 1.5, tension: 0.3 }],
+    },
+    options: { ...chartDefaults, scales: { ...chartDefaults.scales, y: { ...chartDefaults.scales.y, title: { display: true, text: 'bpm', color: '#7a83a8', font: { size: 10 } } } } },
+  });
+}
+
+function haversine(lat1, lon1, lat2, lon2) {
+  const R = 6371000;
+  const p1 = lat1 * Math.PI / 180, p2 = lat2 * Math.PI / 180;
+  const dp = (lat2 - lat1) * Math.PI / 180, dl = (lon2 - lon1) * Math.PI / 180;
+  const a = Math.sin(dp/2)**2 + Math.cos(p1)*Math.cos(p2)*Math.sin(dl/2)**2;
+  return 2 * R * Math.asin(Math.sqrt(a));
+}
+
+function renderInsight(text) {
+  const titleEl = document.getElementById('ride-funny-title');
+  const bodyEl  = document.getElementById('insights-text');
+  if (text.startsWith('TITLE: ')) {
+    const nl = text.indexOf('\n');
+    titleEl.textContent = nl === -1 ? text.slice(7) : text.slice(7, nl);
+    bodyEl.textContent  = nl === -1 ? '' : text.slice(nl).trimStart();
+  } else {
+    titleEl.textContent = '';
+    bodyEl.textContent  = text;
+  }
+}
+
+// AI Insights
+document.getElementById('insights-btn').addEventListener('click', async () => {
+  if (!currentRideId) return;
+  const btn = document.getElementById('insights-btn');
+  const textEl = document.getElementById('insights-text');
+  btn.disabled = true;
+  btn.textContent = 'Generating...';
+  textEl.innerHTML = '<span class="blinking"></span>';
+
+  try {
+    const rhr = parseInt(document.getElementById('rhr-input').value) || 60;
+    const res = await fetch(`/api/rides/${encodeURIComponent(currentRideId)}/insights?rhr=${rhr}`, { method: 'POST' });
+    if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    const reader = res.body.getReader();
+    const decoder = new TextDecoder();
+    let text = '';
+    renderInsight('');
+
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) break;
+      text += decoder.decode(value, { stream: true });
+      renderInsight(text);
+    }
+    renderInsight(text);
+    if (currentRide) currentRide.cached_insight = text;
+  } catch (e) {
+    textEl.textContent = `Error: ${e.message}`;
+  } finally {
+    btn.disabled = false;
+    btn.textContent = 'Regenerate';
+  }
+});
+
+// Generate All
+document.getElementById('gen-all-btn').addEventListener('click', async () => {
+  const btn = document.getElementById('gen-all-btn');
+  const progress = document.getElementById('gen-all-progress');
+  const bar = document.getElementById('gen-all-bar');
+  const label = document.getElementById('gen-all-label');
+  const rhr = parseInt(document.getElementById('rhr-input').value) || 60;
+
+  btn.disabled = true;
+  progress.style.display = '';
+  bar.style.width = '0%';
+  label.textContent = 'Starting...';
+
+  try {
+    const res = await fetch(`/api/insights/generate-all?rhr=${rhr}`, { method: 'POST' });
+    const reader = res.body.getReader();
+    const decoder = new TextDecoder();
+    let buf = '';
+
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) break;
+      buf += decoder.decode(value, { stream: true });
+      const lines = buf.split('\n');
+      buf = lines.pop();
+      for (const line of lines) {
+        if (!line.startsWith('data: ')) continue;
+        const evt = JSON.parse(line.slice(6));
+        if (evt.status === 'complete') {
+          bar.style.width = '100%';
+          label.textContent = `Done — ${evt.total} insights generated`;
+          btn.textContent = 'Generate all insights';
+        } else if (evt.status === 'done' || evt.status === 'error') {
+          const pct = Math.round(evt.index / evt.total * 100);
+          bar.style.width = pct + '%';
+          label.textContent = `${evt.index} / ${evt.total}`;
+          // If this ride is currently selected, refresh the insight panel
+          if (evt.status === 'done' && evt.ride_id === currentRideId) {
+            const r = await fetch(`/api/rides/${encodeURIComponent(evt.ride_id)}`);
+            currentRide = await r.json();
+            renderInsight(currentRide.cached_insight || '');
+            document.getElementById('insights-btn').textContent = 'Regenerate';
+          }
+        }
+      }
+    }
+  } catch (e) {
+    label.textContent = `Error: ${e.message}`;
+  } finally {
+    btn.disabled = false;
+  }
+});
+
+// Fetch rides from Garmin
+const fetchBtn = document.getElementById('fetch-btn');
+const fetchOverlay = document.getElementById('fetch-modal-overlay');
+const fetchSubmitBtn = document.getElementById('fetch-submit-btn');
+const fetchCancelBtn = document.getElementById('fetch-cancel-btn');
+const fetchStatus = document.getElementById('fetch-status');
+const fetchMfaSection = document.getElementById('fetch-mfa-section');
+const fetchMfaSubmitBtn = document.getElementById('fetch-mfa-submit-btn');
+let pendingSessionId = null;
+
+function openFetchModal() {
+  document.getElementById('fetch-email').value = '';
+  document.getElementById('fetch-password').value = '';
+  document.getElementById('fetch-mfa-code').value = '';
+  fetchStatus.textContent = '';
+  fetchStatus.className = 'fetch-status';
+  fetchMfaSection.style.display = 'none';
+  fetchSubmitBtn.disabled = false;
+  fetchSubmitBtn.textContent = 'Fetch';
+  fetchCancelBtn.disabled = false;
+  fetchOverlay.classList.add('open');
+  document.getElementById('fetch-email').focus();
+}
+
+function closeFetchModal() {
+  fetchOverlay.classList.remove('open');
+}
+
+fetchBtn.addEventListener('click', openFetchModal);
+fetchCancelBtn.addEventListener('click', closeFetchModal);
+fetchOverlay.addEventListener('click', e => { if (e.target === fetchOverlay) closeFetchModal(); });
+
+fetchSubmitBtn.addEventListener('click', async () => {
+  const email = document.getElementById('fetch-email').value.trim();
+  const password = document.getElementById('fetch-password').value;
+  if (!email || !password) { fetchStatus.textContent = 'Email and password required.'; fetchStatus.className = 'error'; return; }
+
+  fetchSubmitBtn.disabled = true;
+  fetchCancelBtn.disabled = true;
+  fetchStatus.className = '';
+  fetchStatus.textContent = 'Connecting…';
+
+  pendingSessionId = null;
+
+  try {
+    const res = await fetch('/api/fetch-rides', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ email, password }),
+    });
+    if (!res.ok) throw new Error(`HTTP ${res.status}`);
+
+    const reader = res.body.getReader();
+    const decoder = new TextDecoder();
+    let buf = '';
+
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) break;
+      buf += decoder.decode(value, { stream: true });
+      const lines = buf.split('\n');
+      buf = lines.pop();
+      for (const line of lines) {
+        if (!line.startsWith('data: ')) continue;
+        const evt = JSON.parse(line.slice(6));
+        if (evt.status === 'auth') {
+          fetchStatus.textContent = 'Logging in to Garmin…';
+        } else if (evt.status === 'mfa_required') {
+          pendingSessionId = evt.session_id;
+          fetchStatus.textContent = 'Waiting for verification code…';
+          fetchMfaSection.style.display = 'flex';
+          document.getElementById('fetch-mfa-code').focus();
+        } else if (evt.status === 'fetching') {
+          fetchMfaSection.style.display = 'none';
+          fetchStatus.textContent = 'Checking for new rides…';
+        } else if (evt.status === 'downloading') {
+          fetchStatus.textContent = `Downloading ${evt.index}/${evt.total}: ${evt.name}`;
+        } else if (evt.status === 'complete') {
+          fetchStatus.textContent = evt.added > 0
+            ? `Done — added ${evt.added} new ride${evt.added !== 1 ? 's' : ''} (${evt.skipped} already up to date)`
+            : `Already up to date (${evt.skipped} ride${evt.skipped !== 1 ? 's' : ''} checked)`;
+          await loadRides();
+          fetchSubmitBtn.disabled = false;
+          fetchSubmitBtn.textContent = 'Fetch again';
+          fetchCancelBtn.disabled = false;
+          fetchCancelBtn.textContent = 'Close';
+        } else if (evt.status === 'error') {
+          fetchStatus.textContent = evt.message;
+          fetchStatus.className = 'error';
+          fetchSubmitBtn.disabled = false;
+          fetchSubmitBtn.textContent = 'Retry';
+          fetchCancelBtn.disabled = false;
+        }
+      }
+    }
+  } catch (e) {
+    fetchStatus.textContent = `Error: ${e.message}`;
+    fetchStatus.className = 'error';
+    fetchSubmitBtn.disabled = false;
+    fetchCancelBtn.disabled = false;
+  }
+});
+
+fetchMfaSubmitBtn.addEventListener('click', async () => {
+  const code = document.getElementById('fetch-mfa-code').value.trim();
+  if (!code) return;
+  fetchMfaSubmitBtn.disabled = true;
+  fetchStatus.textContent = 'Submitting code…';
+  try {
+    const res = await fetch('/api/mfa', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ session_id: pendingSessionId, code }),
+    });
+    if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    fetchMfaSection.style.display = 'none';
+  } catch (e) {
+    fetchStatus.textContent = `Error submitting code: ${e.message}`;
+    fetchStatus.className = 'error';
+    fetchMfaSubmitBtn.disabled = false;
+  }
+});
+
+// Unit toggle
+document.getElementById('unit-toggle').textContent = imperial ? 'mi' : 'km';
+document.getElementById('unit-toggle').addEventListener('click', () => {
+  setImperial(!imperial);
+  renderRideList();
+  if (currentRide) renderDetails(currentRide);
+  if (currentPoints && currentPoints.length) renderCharts(currentPoints);
+});
+
+loadRides();
+</script>
+</body>
+</html>
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..a47cafa
--- /dev/null
+++ b/uv.lock
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