fix(transcription): Behebt Start- und API-Fehler in der App [2f488f42]

transcription-tool/backend/services/insights_service.py

@@ -2,13 +2,9 @@ import sys
 import os
 from sqlalchemy.orm import Session
 from .. import database
-from .. import prompt_library
-
+from ..prompt_library import get_prompt
 import logging
-from sqlalchemy.orm import Session
-from .. import database
-from .. import prompt_library
-from ..lib.gemini_client import call_gemini_flash
+from .llm_service import call_gemini_api
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -57,18 +53,7 @@ def _format_transcript(chunks: list[database.TranscriptChunk]) -> str:
 
     return "\n".join(full_transcript)
 
-def get_prompt_by_type(insight_type: str) -> str:
-    """
-    Returns the corresponding prompt from the prompt_library based on the type.
-    """
-    if insight_type == "meeting_minutes":
-        return prompt_library.MEETING_MINUTES_PROMPT
-    elif insight_type == "action_items":
-        return prompt_library.ACTION_ITEMS_PROMPT
-    elif insight_type == "sales_summary":
-        return prompt_library.SALES_SUMMARY_PROMPT
-    else:
-        raise ValueError(f"Unknown insight type: {insight_type}")
+
 
 def generate_insight(db: Session, meeting_id: int, insight_type: str) -> database.AnalysisResult:
     """
@@ -102,7 +87,7 @@ def generate_insight(db: Session, meeting_id: int, insight_type: str) -> databas
         # This can happen if all chunks are empty or malformed
         raise ValueError(f"Formatted transcript for meeting {meeting_id} is empty or could not be processed.")
 
-    prompt_template = get_prompt_by_type(insight_type)
+    prompt_template = get_prompt(insight_type)
     final_prompt = prompt_template.format(transcript_text=transcript_text)
 
     # 4. Call the AI model