[2f988f42] Moltbot hat das Tool kaputt gemacht. Habe es jetzt wieder mit Gemini CLI gefixt. Ist aber noch immer nicht ganz sauber - Optik ist kaputt, viele ja ja ja in der Transkription.

Moltbot hat das Tool kaputt gemacht. Habe es jetzt wieder mit Gemini CLI gefixt. Ist aber noch immer nicht ganz sauber - Optik ist kaputt, viele ja ja ja in der Transkription.

.dev_session/SESSION_INFO

@@ -1 +1 @@
-{"task_id": "2f988f42-8544-8100-9dba-e69ee2376730", "token": "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", "session_start_time": "2026-01-31T05:48:55.785384"}
+{"task_id": "2f988f42-8544-81bc-97b2-ccd361f116a4", "token": "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", "session_start_time": "2026-01-31T08:29:52.360032"}

dashboard/index.html

@@ -190,7 +190,7 @@
             <p>
                 Transkribieren Sie Meetings (MP3/WAV) mit automatischer Sprechererkennung und Timestamps via Gemini 2.0.
             </p>
-            <a href="/tr/" class="btn">Starten &rarr;</a>
+            <a href="http://192.168.0.2:8001/tr/" class="btn">Starten &rarr;</a>
         </div>
         
     </div>

debug_meeting.py

@@ -0,0 +1,71 @@
+
+import sqlite3
+import json
+import os
+
+DB_PATH = "transcription-tool/backend/meetings.db"
+MEETING_ID = 5
+
+def debug_meeting(db_path, meeting_id):
+    if not os.path.exists(db_path):
+        print(f"ERROR: Database file not found at {db_path}")
+        return
+
+    try:
+        conn = sqlite3.connect(db_path)
+        cursor = conn.cursor()
+
+        # Get Meeting Info
+        cursor.execute("SELECT id, title, status, duration_seconds FROM meetings WHERE id = ?", (meeting_id,))
+        meeting = cursor.fetchone()
+
+        if not meeting:
+            print(f"ERROR: No meeting found with ID {meeting_id}")
+            return
+
+        print("--- MEETING INFO ---")
+        print(f"ID: {meeting[0]}")
+        print(f"Title: {meeting[1]}")
+        print(f"Status: {meeting[2]}")
+        print(f"Duration (s): {meeting[3]}")
+        print("-" * 20)
+
+        # Get Chunks
+        cursor.execute("SELECT id, chunk_index, json_content FROM transcript_chunks WHERE meeting_id = ? ORDER BY chunk_index", (meeting_id,))
+        chunks = cursor.fetchall()
+
+        print(f"--- CHUNKS FOUND: {len(chunks)} ---")
+        for chunk in chunks:
+            chunk_id, chunk_index, json_content_str = chunk
+            print(f"\n--- Chunk ID: {chunk_id}, Index: {chunk_index} ---")
+            
+            if not json_content_str:
+                print("  -> JSON content is EMPTY.")
+                continue
+
+            try:
+                json_content = json.loads(json_content_str)
+                print(f"  -> Number of entries: {len(json_content)}")
+                
+                if json_content:
+                    # Print first 2 and last 2 entries to check for the "Ja" loop
+                    print("  -> First 2 entries:")
+                    for entry in json_content[:2]:
+                        print(f"    - {entry.get('display_time')} [{entry.get('speaker')}]: {entry.get('text')[:80]}...")
+                    
+                    if len(json_content) > 4:
+                        print("  -> Last 2 entries:")
+                        for entry in json_content[-2:]:
+                            print(f"    - {entry.get('display_time')} [{entry.get('speaker')}]: {entry.get('text')[:80]}...")
+
+            except json.JSONDecodeError:
+                print("  -> ERROR: Failed to decode JSON content.")
+
+    except sqlite3.Error as e:
+        print(f"Database error: {e}")
+    finally:
+        if 'conn' in locals() and conn:
+            conn.close()
+
+if __name__ == "__main__":
+    debug_meeting(DB_PATH, MEETING_ID)

transcription-tool/backend/services/llm_service.py

@@ -27,8 +27,9 @@ def call_gemini_api(prompt: str, temperature: float = 0.7, retries: int = 3, tim
         logging.error("GEMINI_API_KEY environment variable not set.")
         raise ValueError("API key not found.")
 
-    # Fallback to v1 (stable) and gemini-pro
-    url = f"https://generativelanguage.googleapis.com/v1/models/gemini-pro:generateContent?key={api_key}"
+    # As per documentation, use the established v1beta endpoint and gemini-2.0-flash model
+    model_name = "gemini-2.0-flash" 
+    url = f"https://generativelanguage.googleapis.com/v1beta/models/{model_name}:generateContent?key={api_key}"
     headers = {'Content-Type': 'application/json'}
     payload = {
         "contents": [{