diff --git a/transcription-tool/backend/services/insights_service.py b/transcription-tool/backend/services/insights_service.py
index 28236d8e..8ba529ad 100644
--- a/transcription-tool/backend/services/insights_service.py
+++ b/transcription-tool/backend/services/insights_service.py
@@ -95,7 +95,7 @@ def generate_insight(db: Session, meeting_id: int, insight_type: str) -> databas
     db.commit()
 
     try:
-        generated_text = call_gemini_flash(prompt=final_prompt, temperature=0.5)
+        generated_text = call_gemini_api(prompt=final_prompt, temperature=0.5)
         
         # 5. Store the new insight
         new_insight = database.AnalysisResult(
diff --git a/transcription-tool/backend/services/llm_service.py b/transcription-tool/backend/services/llm_service.py
index 2ea72ebd..67583e22 100644
--- a/transcription-tool/backend/services/llm_service.py
+++ b/transcription-tool/backend/services/llm_service.py
@@ -6,12 +6,13 @@ import time
 # Configure logging
 logging.basicConfig(level=logging.INFO)
 
-def call_gemini_api(prompt: str, retries: int = 3, timeout: int = 600) -> str:
+def call_gemini_api(prompt: str, temperature: float = 0.7, retries: int = 3, timeout: int = 600) -> str:
     """
     Calls the Gemini Pro API with a given prompt.
 
     Args:
         prompt: The text prompt to send to the API.
+        temperature: Controls randomness in output.
         retries: The number of times to retry on failure.
         timeout: The request timeout in seconds.
 
@@ -33,7 +34,7 @@ def call_gemini_api(prompt: str, retries: int = 3, timeout: int = 600) -> str:
             "parts": [{"text": prompt}]
         }],
         "generationConfig": {
-            "temperature": 0.7,
+            "temperature": temperature,
             "topK": 40,
             "topP": 0.95,
             "maxOutputTokens": 8192,