feat(transcription): v0.4.0 with structured json, inline editing and deletion

- Backend: Switched prompt to JSON output for structured data
- Backend: Added PUT /chunks/{id} endpoint for persistence
- Backend: Fixed app.py imports and initialization logic
- Frontend: Complete rewrite for Unified View (flattened chunks)
- Frontend: Added Inline Editing (Text/Speaker) and Row Deletion
- Docs: Updated TRANSCRIPTION_TOOL.md with v0.4 features

transcription-tool/backend/services/orchestrator.py

@@ -1,4 +1,5 @@
 import logging
+import json
 from sqlalchemy.orm import Session
 from .ffmpeg_service import FFmpegService
 from .transcription_service import TranscriptionService
@@ -7,6 +8,17 @@ from ..config import settings
 
 logger = logging.getLogger(__name__)
 
+def parse_time_to_seconds(time_str):
+    try:
+        parts = time_str.split(':')
+        if len(parts) == 2: # MM:SS
+            return int(parts[0]) * 60 + int(parts[1])
+        elif len(parts) == 3: # HH:MM:SS
+            return int(parts[0]) * 3600 + int(parts[1]) * 60 + int(parts[2])
+    except:
+        return 0
+    return 0
+
 def process_meeting_task(meeting_id: int, db_session_factory):
     db = db_session_factory()
     meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first()
@@ -35,11 +47,30 @@ def process_meeting_task(meeting_id: int, db_session_factory):
             
             result = transcriber.transcribe_chunk(chunk_path, offset)
             
+            # Parse JSON and Adjust Timestamps
+            json_data = []
+            try:
+                raw_json = json.loads(result["raw_text"])
+                if isinstance(raw_json, list):
+                    for entry in raw_json:
+                        seconds = parse_time_to_seconds(entry.get("time", "00:00"))
+                        absolute_seconds = seconds + offset
+                        entry["absolute_seconds"] = absolute_seconds
+                        
+                        h = int(absolute_seconds // 3600)
+                        m = int((absolute_seconds % 3600) // 60)
+                        s = int(absolute_seconds % 60)
+                        entry["display_time"] = f"{h:02}:{m:02}:{s:02}"
+                        json_data.append(entry)
+            except Exception as e:
+                logger.error(f"JSON Parsing failed for chunk {i}: {e}")
+
             # Save chunk result
             db_chunk = TranscriptChunk(
                 meeting_id=meeting.id,
                 chunk_index=i,
-                raw_text=result["raw_text"]
+                raw_text=result["raw_text"],
+                json_content=json_data
             )
             db.add(db_chunk)
             all_text.append(result["raw_text"])

transcription-tool/backend/services/transcription_service.py

@@ -19,8 +19,8 @@ class TranscriptionService:
         """
         logger.info(f"Uploading chunk {file_path} to Gemini...")
         
-        # 1. Upload file
-        media_file = self.client.files.upload(path=file_path)
+        # 1. Upload file (positional argument)
+        media_file = self.client.files.upload(file=file_path)
         
         # 2. Wait for processing (usually fast for audio)
         while media_file.state == "PROCESSING":
@@ -32,12 +32,18 @@ class TranscriptionService:
 
         # 3. Transcribe with Diarization and Timestamps
         prompt = """
-        Transkribiere dieses Audio wortgetreu. 
-        Identifiziere die Sprecher (Sprecher A, Sprecher B, etc.).
-        Gib das Ergebnis als strukturierte Liste mit Timestamps aus.
-        Wichtig: Das Audio ist ein Teil eines größeren Gesprächs. 
-        Antworte NUR mit dem Transkript im Format:
-        [MM:SS] Sprecher X: Text
+        Transkribiere dieses Audio wortgetreu.
+        Identifiziere die Sprecher (Speaker A, Speaker B, etc.).
+        
+        Gib das Ergebnis als JSON-Liste zurück.
+        Format:
+        [
+          {
+            "time": "MM:SS",
+            "speaker": "Speaker A",
+            "text": "..."
+          }
+        ]
         """
         
         logger.info(f"Generating transcription for {file_path}...")
@@ -45,7 +51,8 @@ class TranscriptionService:
             model="gemini-2.0-flash",
             contents=[media_file, prompt],
             config=types.GenerateContentConfig(
-                temperature=0.1, # Low temp for accuracy
+                temperature=0.1,
+                response_mime_type="application/json"
             )
         )
 
@@ -53,6 +60,6 @@ class TranscriptionService:
         self.client.files.delete(name=media_file.name)
 
         return {
-            "raw_text": response.text,
+            "raw_text": response.text, # This is now a JSON string
             "offset": offset_seconds
         }