diff --git a/app/services/llm_service.py b/app/services/llm_service.py
index 21dff82..ac3a63b 100644
--- a/app/services/llm_service.py
+++ b/app/services/llm_service.py
@@ -19,12 +19,6 @@ class LLMService(ABC):
     async def chat_to_tasks(self, prompt: str) -> List[Dict]:
         """
         Convert natural language input to structured task objects.
-
-        Args:
-            prompt: User's natural language input describing tasks
-
-        Returns:
-            List of dictionary objects representing tasks
         """
         pass
 
@@ -33,7 +27,6 @@ class OpenAIService(LLMService):
     """OpenAI implementation of LLM service."""
 
     def __init__(self):
-        """Initialize the OpenAI service."""
         try:
             import openai
             self.client = openai.AsyncOpenAI(api_key=settings.OPENAI_API_KEY)
@@ -43,15 +36,6 @@ class OpenAIService(LLMService):
             raise RuntimeError(f"OpenAI service initialization failed: {e}")
 
     async def chat_to_tasks(self, prompt: str) -> List[Dict]:
-        """
-        Convert natural language to tasks using OpenAI.
-        
-        Args:
-            prompt: User's natural language input
-            
-        Returns:
-            List of task dictionaries
-        """
         system_prompt = """
         You are a task extraction assistant. Your job is to convert the user's natural language 
         input into one or more structured task objects. Each task should have these properties:
@@ -63,7 +47,6 @@ class OpenAIService(LLMService):
         
         Return ONLY a JSON array of task objects without any additional text or explanation.
         """
-
         try:
             response = await self.client.chat.completions.create(
                 model=self.model,
@@ -74,7 +57,6 @@ class OpenAIService(LLMService):
                 response_format={"type": "json_object"},
                 temperature=0.2,
             )
-
             content = response.choices[0].message.content
             result = json.loads(content)
 
@@ -91,7 +73,6 @@ class GeminiService(LLMService):
     """Google Gemini implementation of LLM service."""
 
     def __init__(self):
-        """Initialize the Gemini service."""
         try:
             import google.generativeai as genai
             genai.configure(api_key=settings.GEMINI_API_KEY)
@@ -101,15 +82,6 @@ class GeminiService(LLMService):
             raise RuntimeError(f"Gemini service initialization failed: {e}")
 
     async def chat_to_tasks(self, prompt: str) -> List[Dict]:
-        """
-        Convert natural language to tasks using Google Gemini.
-
-        Args:
-            prompt: User's natural language input
-
-        Returns:
-            List of task dictionaries
-        """
         system_prompt = (
             "You are a task extraction assistant. Your job is to convert the user's natural language "
             "input into one or more structured task objects. Each task should have these properties:\n"
@@ -121,27 +93,14 @@ class GeminiService(LLMService):
             "Return ONLY a JSON object with a \"tasks\" key that contains an array of task objects. "
             "Do not include any text or explanation outside the JSON."
         )
-
         try:
             chat = self.model.start_chat(history=[
-                {
-                    "content": {
-                        "parts": [system_prompt]
-                    }
-                }
+                {"role": "user", "parts": [system_prompt]}
             ])
-
-            response = await chat.send_message_async(
-                {
-                    "content": {
-                        "parts": [prompt]
-                    }
-                }
-            )
-
+            response = await chat.send_message_async(prompt)
             content = response.text
 
-            # Remove possible markdown code blocks
+            # Handle markdown-wrapped responses
             if "```json" in content:
                 json_str = content.split("```json")[1].split("```")[0].strip()
             elif "```" in content:
@@ -164,18 +123,8 @@ class MockLLMService(LLMService):
     """Mock LLM service for testing."""
 
     async def chat_to_tasks(self, prompt: str) -> List[Dict]:
-        """
-        Return mock tasks based on the prompt.
-
-        Args:
-            prompt: User's natural language input
-
-        Returns:
-            List of task dictionaries
-        """
         words = prompt.lower().split()
         priority = "medium"
-
         if "urgent" in words or "important" in words:
             priority = "high"
         elif "low" in words or "minor" in words:
@@ -191,12 +140,6 @@ class MockLLMService(LLMService):
 
 
 def get_llm_service() -> LLMService:
-    """
-    Factory function for LLM service dependency injection.
-
-    Returns:
-        An instance of a concrete LLMService implementation
-    """
     llm_provider = settings.LLM_PROVIDER.lower()
 
     if llm_provider == "openai" and settings.OPENAI_API_KEY: