Implement customizable post-trek storyteller styles (Minimal Technical Gist & Social Media Post) with robust mock parser fallback

app.py

@@ -1039,7 +1039,7 @@ def handle_clear_journal():
     db.clear_journal_logs()
     return "", [], "<span style='color:#ef4444;'>Cleared all voice journal logs.</span>"
 
-def handle_generate_story(route_state_val):
+def handle_generate_story(route_state_val, style):
     logs = db.get_journal_entries()
     if not logs:
         return "### 📖 No Voice Logs Found\n\nPlease record and save some voice journal entries during your simulated trek before generating your AI story!", None
@@ -1084,10 +1084,26 @@ def handle_generate_story(route_state_val):
     else:
         amenities_text += "- General alpine huts, shelters, and water streams close to the path.\n"
         
+    if style == "Minimal Technical Gist":
+        style_instruction = (
+            "Write a concise, bullet-pointed, and highly technical summary of the trek. "
+            "Focus on the exact telemetry (distances, altitudes, checkpoints reached), voice note transcripts, "
+            "and amenities used (water sources, huts, campsites, viewpoints). Keep it factual, objective, and brief."
+        )
+    else:  # "Social Media Post (Elaborative)"
+        style_instruction = (
+            "Write a highly engaging, elaborative, and inspiring story formatted as a social media post (e.g., for Instagram or LinkedIn) "
+            "targeted at an audience of outdoor enthusiasts.\n"
+            "Include emojis, a narrative hook, paragraphs of descriptions of the journey's highs and lows, "
+            "reflections on the voice notes, details about the amenities (water sources, viewpoints, campsites) encountered, "
+            "and end with relevant hashtags (e.g., #HikingAdventurer, #Trailhead, #BackcountryExploration)."
+        )
+
     system_prompt = (
         "You are a classic wilderness novelist and explorer. Write a compelling, first-person "
         "adventure story summarizing the trek based on the provided trek details, checkpoints, amenities, "
         "and the hiker's voice journal logs.\n"
+        f"Format Style: {style_instruction}\n"
         "Emphasize the hiker's voice notes, detailing their personal reflections, physical state, and "
         "wilderness observations. Incorporate the trek details (distance, elevation, altitude) to frame the physical challenge. "
         "Weave in the amenities (water sources, campsites, alpine huts, shelters, viewpoints) as milestones or locations where the hiker is resting, "
@@ -1308,6 +1324,11 @@ with gr.Blocks(css="assets/custom.css", title="Trailhead — Tactical Trail Comp
                 with gr.Column(scale=2):
                     gr.Markdown("## 📖 Post-Trek AI Storyteller")
                     gr.Markdown("Click below to compile all your saved voice journal logs and route statistics into an AI-narrated story of your adventure!")
+                    story_style = gr.Radio(
+                        choices=["Minimal Technical Gist", "Social Media Post (Elaborative)"],
+                        value="Social Media Post (Elaborative)",
+                        label="Story Style / Format"
+                    )
                     generate_story_btn = gr.Button("🎬 Generate AI Trek Story", variant="primary")
                     story_output = gr.Markdown(value="*Your adventure narrative will be generated here.*")
                 with gr.Column(scale=1):
@@ -1422,7 +1443,7 @@ with gr.Blocks(css="assets/custom.css", title="Trailhead — Tactical Trail Comp
     
     generate_story_btn.click(
         fn=handle_generate_story,
-        inputs=[route_state],
+        inputs=[route_state, story_style],
         outputs=[story_output, story_download]
     )
     

src/llm.py

@@ -221,6 +221,162 @@ def generate_mock(prompt, system="", image_path=None, audio_path=None, history=N
         
     prompt_lower = prompt.lower()
     
+    # 0.5 Check if this is a Storyteller request (before other keyword matches)
+    if "first-person adventure story of my trek" in prompt_lower or "storyteller" in system.lower() or "adventure story" in system.lower():
+        import re
+        
+        # Parse stats
+        total_dist_match = re.search(r"Total Distance: ([\d\.]+) km", prompt)
+        ele_gain_match = re.search(r"Total Elevation Gain: ([\d\.]+) m", prompt)
+        alt_range_match = re.search(r"Altitude Range: (.*?)\n", prompt)
+        
+        total_dist = total_dist_match.group(1) if total_dist_match else "3.49"
+        ele_gain = ele_gain_match.group(1) if ele_gain_match else "120.0"
+        alt_range = alt_range_match.group(1) if alt_range_match else "100m - 250m"
+        
+        # Parse voice logs
+        voice_logs = []
+        log_pattern = r"- Log #(\d+)\s+\((.*?)\)\s+at Km\s+([\d\.]+)\s+\(Alt:\s+([\d\.]+)m\):\s*\"(.*?)\""
+        matches = re.findall(log_pattern, prompt, re.DOTALL)
+        for num, timestamp, km, alt, transcript in matches:
+            voice_logs.append({
+                "num": num,
+                "time": timestamp,
+                "km": float(km),
+                "alt": alt,
+                "transcript": transcript.strip()
+            })
+            
+        if not voice_logs:
+            # Fallback line-by-line parsing
+            lines = prompt.split("\n")
+            current_log = None
+            for line in lines:
+                if "- Log #" in line:
+                    try:
+                        parts = line.split(" at Km ")
+                        header_part = parts[0]
+                        km_alt_part = parts[1]
+                        num_time = header_part.replace("- Log #", "").strip()
+                        num = num_time.split(" ")[0]
+                        time_str = num_time.replace(num, "").strip("() ")
+                        km = km_alt_part.split(" ")[0]
+                        alt = km_alt_part.split("Alt: ")[1].split("m")[0]
+                        current_log = {
+                            "num": num,
+                            "time": time_str,
+                            "km": float(km),
+                            "alt": alt,
+                            "transcript": ""
+                        }
+                    except Exception:
+                        current_log = None
+                elif current_log and line.strip().startswith('"'):
+                    current_log["transcript"] = line.strip().strip('"')
+                    voice_logs.append(current_log)
+                    current_log = None
+
+        # Parse amenities
+        amenities = []
+        amenity_pattern = r"- (.*?)\s+\((.*?)\)\s+at approx\.\s+Km\s+([\d\.]+)\s+\(located\s+([\d\.]+) meters off the trail\)"
+        amenity_matches = re.findall(amenity_pattern, prompt)
+        for name, type_str, km, offset in amenity_matches:
+            amenities.append({
+                "name": name,
+                "type": type_str,
+                "km": float(km),
+                "offset": offset
+            })
+            
+        if not amenities:
+            lines = prompt.split("\n")
+            for line in lines:
+                if "meters off the trail" in line:
+                    try:
+                        clean_line = line.strip().lstrip("- ")
+                        name_part = clean_line.split(" (")[0]
+                        rest = clean_line.split(" (")[1]
+                        type_part = rest.split(") at approx. Km ")[0]
+                        km_offset = rest.split(") at approx. Km ")[1]
+                        km = km_offset.split(" (located ")[0]
+                        offset = km_offset.split(" (located ")[1].split(" meters off the trail")[0]
+                        amenities.append({
+                            "name": name_part,
+                            "type": type_part,
+                            "km": float(km),
+                            "offset": offset
+                        })
+                    except Exception:
+                        pass
+                        
+        voice_logs = sorted(voice_logs, key=lambda x: x["km"])
+        is_technical = "technical" in system.lower()
+        
+        if is_technical:
+            response += "🧭 **Trailhead Technical Trek Report**\n"
+            response += "*Compiled by Trailhead AI Storyteller*\n\n"
+            response += "### 📊 Trek Telemetry\n"
+            response += f"- **Total Distance:** {total_dist} km\n"
+            response += f"- **Total Elevation Gain:** {ele_gain} m\n"
+            response += f"- **Altitude Profile:** {alt_range}\n\n"
+            
+            response += "### 🎒 Amenities & Points of Interest\n"
+            if amenities:
+                for am in amenities:
+                    response += f"- **{am['name']}** ({am['type']}) at approx. Km {am['km']:.2f} ({am['offset']}m off-trail)\n"
+            else:
+                response += "- No significant amenities detected along the route.\n"
+                
+            response += "\n### 🎙️ Geotagged Voice Logs\n"
+            if voice_logs:
+                for log in voice_logs:
+                    response += f"- **Km {log['km']:.2f}** (Alt: {log['alt']}m) | *{log['time']}*:\n  > \"{log['transcript']}\"\n"
+            else:
+                response += "- No voice logs recorded.\n"
+        else:
+            response += "🌲 **MY WILDERNESS EXPEDITION REPORT** 🌲\n"
+            response += "*Powered by Trailhead Tactical Trail Computer*\n\n"
+            response += f"What an absolute journey! 🏔️ Just finished an intense trek covering **{total_dist} km** with **{ele_gain} m** of vertical climb! Here is the live play-by-play of how it went down:\n\n"
+            
+            milestones = []
+            for am in amenities:
+                milestones.append(("amenity", am["km"], am))
+            for log in voice_logs:
+                milestones.append(("log", log["km"], log))
+            milestones = sorted(milestones, key=lambda x: x[1])
+            
+            for m_type, km, data in milestones:
+                if m_type == "amenity":
+                    response += f"📍 **Km {km:.2f} | Amenity Spot** 🎒\n"
+                    response += f"Encountered **{data['name']}** ({data['type']}) situated just {data['offset']}m off the path. A crucial waypoint for resource management!\n\n"
+                elif m_type == "log":
+                    transcript_lower = data['transcript'].lower()
+                    icon = "🎙️"
+                    title = "Hiker Log"
+                    if "water" in transcript_lower:
+                        icon = "💧"
+                        title = "Water Source & Hydration Check"
+                    elif "view" in transcript_lower or "point of view" in transcript_lower:
+                        icon = "👁️"
+                        title = "Scenic Viewpoint Reflection"
+                    elif "finish" in transcript_lower or "complete" in transcript_lower:
+                        icon = "🏁"
+                        title = "Trek Completion Signoff"
+                        
+                    response += f"{icon} **Km {km:.2f} | {title}** 📝\n"
+                    response += f"Recorded voice entry at {data['alt']}m altitude:\n"
+                    response += f"> *\"{data['transcript']}\"*\n\n"
+                    
+            response += "🏁 **Trek Complete!**\n"
+            response += "Every step was worth it. Pushed my limits, managed my resources, and conquered the route. 🥾\n\n"
+            response += "---\n"
+            response += "#HikingAdventure #BackcountryExploration #TrailheadAI #WildernessLiving #TrekTelemetry #OptOutside\n"
+
+        for word in response.split(" "):
+            yield word + " "
+            time.sleep(0.02)
+        return
+    
     # 1. Checkpoint / Narration Queries
     if "checkpoint" in prompt_lower or "narration" in prompt_lower or "current position" in prompt_lower:
         response += (