chore: update requirements, add local offline map tiles and test scripts

requirements.txt

@@ -1,12 +1,12 @@
-gradio==5.15.0
+gradio[oauth,mcp]==6.18.0
 pandas
 numpy
 requests
-huggingface_hub>=0.25.1,<1.0.0
+huggingface_hub>=1.2.0,<2.0
 gpxpy
 folium
 plotly
-pydantic>=2.0.0,<2.11.0
+pydantic>=2.11.10,<2.12.5
 Pillow
 # ASR: transformers + torch as fallback for Hugging Face (no pywhispercpp available there)
 # transformers

scratch/test_chat.py

@@ -0,0 +1,35 @@
+import os
+from llama_cpp import Llama
+
+model_path = "./model/gemma-1.1-2b-it-Q4_K_M.gguf"
+model = Llama(
+    model_path=model_path,
+    n_ctx=2048,
+    verbose=False
+)
+
+system_prompt = (
+    "You are Trailhead Guide, a wilderness first-aid advisor.\n"
+    "Answer the query using ONLY the provided guide context.\n"
+    "Context:\n### Section 5: Musculoskeletal Injuries (Sprains & Strains)\n"
+    "1. Rest: Avoid weight bearing.\n"
+    "2. Ice: Apply cold compress.\n"
+    "3. Compression: Wrap joint firmly.\n"
+    "4. Elevation: Elevate joint above heart level.\n\n"
+    "Keep the instructions clear, numbered, and precise.\n"
+    "Cite: 'Sources: Section 5'."
+)
+
+messages = [
+    {"role": "user", "content": f"{system_prompt}\n\nUser Query: knee sprain"}
+]
+
+print("Running chat completions...")
+response = model.create_chat_completion(
+    messages=messages,
+    max_tokens=256,
+    temperature=0.3,
+    stream=False
+)
+
+print(response['choices'][0]['message']['content'])

scratch/test_model.py

@@ -0,0 +1,31 @@
+import os
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+
+MODEL_REPO = "bartowski/gemma-1.1-2b-it-GGUF"
+MODEL_FILE = "gemma-1.1-2b-it-Q4_K_M.gguf"
+LOCAL_MODEL_DIR = "./model"
+
+model_path = os.path.join(LOCAL_MODEL_DIR, MODEL_FILE)
+if not os.path.exists(model_path):
+    print("Downloading model...")
+    hf_hub_download(
+        repo_id=MODEL_REPO,
+        filename=MODEL_FILE,
+        local_dir=LOCAL_MODEL_DIR,
+        local_dir_use_symlinks=False
+    )
+
+print("File exists:", os.path.exists(model_path))
+print("File size:", os.path.getsize(model_path))
+
+try:
+    model = Llama(
+        model_path=model_path,
+        n_ctx=2048,
+        verbose=True
+    )
+    print("Success loading model!")
+except Exception as e:
+    import traceback
+    traceback.print_exc()

scratch/test_phase3.py

@@ -0,0 +1,80 @@
+import os
+import sys
+import json
+import sqlite3
+
+# Ensure src directory is in path
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+
+import src.database as db
+import src.gpx_parser as gpx_parser
+from app import generate_elevation_plot, handle_generate_story
+
+def run_tests():
+    print("=== STARTING PHASE 3 FUNCTIONAL TESTS ===")
+    
+    # 1. Test SQLite Database Operations
+    print("\n--- Test 1: SQLite Database Operations ---")
+    db.init_db()
+    
+    # Clear tables to start clean
+    db.clear_journal_logs()
+    db.clear_custom_waypoints()
+    
+    # Insert custom waypoint
+    db.add_custom_waypoint(46.0734, 11.1717, 350.0, "drinking_water", "Test Water Source", "Fresh cold spring")
+    wps = db.get_custom_waypoints()
+    assert len(wps) == 1, "Waypoint count should be 1"
+    assert wps[0]["name"] == "Test Water Source", "Waypoint name mismatch"
+    assert wps[0]["type"] == "drinking_water", "Waypoint type mismatch"
+    print("✅ Custom waypoint read/write verified successfully.")
+    
+    # Insert journal log
+    db.add_journal_entry(46.0735, 11.1718, 352.0, 0.5, "Hiked up the trail, found fresh water at custom tagged point.")
+    logs = db.get_journal_entries()
+    assert len(logs) == 1, "Journal logs count should be 1"
+    assert logs[0]["transcript"] == "Hiked up the trail, found fresh water at custom tagged point.", "Transcript mismatch"
+    print("✅ Voice log entry read/write verified successfully.")
+    
+    # 2. Test Tile Coordinate Conversion
+    print("\n--- Test 2: OSM Tile Conversion Maths ---")
+    lat, lon, zoom = 46.0734974, 11.1717214, 13
+    x, y = gpx_parser.deg2num(lat, lon, zoom)
+    print(f"Coordinates {lat}, {lon} at Zoom {zoom} -> Tile X: {x}, Y: {y}")
+    assert x == 4350, f"Expected X = 4350, got {x}"
+    assert y == 2911, f"Expected Y = 2911, got {y}"
+    print("✅ OSM tile maths verified successfully (match Trento coordinates Z13).")
+    
+    # 3. Test Plotly Elevation Chart Generation
+    print("\n--- Test 3: Plotly Elevation Chart Generation ---")
+    mock_points = [
+        {"lat": 46.073, "lon": 11.171, "ele": 300.0, "cum_dist": 0.0},
+        {"lat": 46.074, "lon": 11.172, "ele": 320.0, "cum_dist": 150.0},
+        {"lat": 46.075, "lon": 11.173, "ele": 350.0, "cum_dist": 300.0},
+        {"lat": 46.076, "lon": 11.174, "ele": 380.0, "cum_dist": 450.0}
+    ]
+    fig = generate_elevation_plot(mock_points, current_idx=2)
+    assert fig is not None, "Plotly figure should not be None"
+    # Inspect plotly layout
+    assert fig.layout.title.text == "🏔️ ELEVATION PROFILE", "Title mismatch"
+    print("✅ Plotly elevation profile chart generated successfully.")
+    
+    # 4. Test Post-Trek AI Storyteller prompt compile & fallback generation
+    print("\n--- Test 4: AI Storyteller Narrative ---")
+    mock_route = {
+        "total_distance_km": 0.45,
+        "elevation_gain_m": 80.0,
+        "min_elevation_m": 300.0,
+        "max_elevation_m": 380.0
+    }
+    story, file_path = handle_generate_story(mock_route)
+    assert story is not None, "Generated story should not be None"
+    assert "Hiker" in story or "Trail" in story or "adventure" in story, "Story content is too generic"
+    assert os.path.exists(file_path), f"Story file should be saved at {file_path}"
+    print(f"✅ AI Storyteller executed successfully. Story saved to {file_path}")
+    print(f"Story teaser:\n{story[:150]}...")
+    
+    print("\n=== ALL PHASE 3 FUNCTIONAL TESTS PASSED SUCCESSFULLY! ===")
+    
+if __name__ == "__main__":
+    run_tests()