diff --git a/app/services/llm_service.py b/app/services/llm_service.py
index 97f52e4..09665d5 100644
--- a/app/services/llm_service.py
+++ b/app/services/llm_service.py
@@ -6,7 +6,6 @@ import logging
 from abc import ABC, abstractmethod
 from typing import Dict, List
 
-
 from app.core.config import settings
 
 # Configure logger
@@ -37,7 +36,7 @@ class OpenAIService(LLMService):
         """Initialize the OpenAI service."""
         try:
             import openai
-            self.client = openai.AsyncOpenAI(api_key=settings.openai_api_key)
+            self.client = openai.AsyncOpenAI(api_key=settings.OPENAI_API_KEY)
             self.model = settings.OPENAI_MODEL
         except (ImportError, AttributeError) as e:
             logger.error(f"Failed to initialize OpenAI service: {e}")
@@ -122,21 +121,21 @@ class GeminiService(LLMService):
         - priority: The priority level (high, medium, low)
         - status: The status (defaults to "pending")
         
-        Return ONLY a JSON array of task objects without any additional text or explanation.
-        Format your response as valid JSON with a "tasks" key that contains an array of task objects.
+        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:
+            # Start the chat session with the system prompt
             chat = self.model.start_chat(history=[
-                {"role": "user", "parts": [system_prompt]},
-                {"role": "model", "parts": ["I understand. I'll convert user inputs into JSON task objects with the specified properties."]}
+                {"role": "system", "content": system_prompt}
             ])
             
+            # Send the user prompt asynchronously
             response = await chat.send_message_async(prompt)
             content = response.text
             
-            # Extract JSON from the response
-            # This handles cases where the model might add markdown code blocks
+            # Remove possible markdown code blocks wrapping the JSON response
             if "```json" in content:
                 json_str = content.split("```json")[1].split("```")[0].strip()
             elif "```" in content:
@@ -144,12 +143,13 @@ class GeminiService(LLMService):
             else:
                 json_str = content.strip()
             
+            # Parse JSON response
             result = json.loads(json_str)
             
-            # Expect a "tasks" key in the response JSON
+            # Return the list under "tasks" or the whole as single-item list
             if "tasks" in result:
                 return result["tasks"]
-            return [result]  # Return as a single-item list if no "tasks" key
+            return [result]
             
         except Exception as e:
             logger.error(f"Gemini API error: {e}")
@@ -169,7 +169,6 @@ class MockLLMService(LLMService):
         Returns:
             List of task dictionaries
         """
-        # Simple parsing logic for testing
         words = prompt.lower().split()
         priority = "medium"
         
@@ -178,7 +177,6 @@ class MockLLMService(LLMService):
         elif "low" in words or "minor" in words:
             priority = "low"
             
-        # Create a basic task from the prompt
         return [{
             "title": prompt[:50] + ("..." if len(prompt) > 50 else ""),
             "description": prompt,
@@ -188,7 +186,6 @@ class MockLLMService(LLMService):
         }]
 
 
-# Factory function to create the appropriate LLM service
 def get_llm_service() -> LLMService:
     """
     Factory function for LLM service dependency injection.
@@ -197,15 +194,13 @@ def get_llm_service() -> LLMService:
         An instance of a concrete LLMService implementation
     """
     llm_provider = settings.LLM_PROVIDER.lower()
-    
-    if llm_provider == "openai" and settings.OPEANAI_API_KEY:
+
+    if llm_provider == "openai" and settings.OPENAI_API_KEY:
         return OpenAIService()
     elif llm_provider == "gemini" and settings.GEMINI_API_KEY:
         return GeminiService()
     elif llm_provider == "mock" or settings.environment == "test":
-        # Use mock service for testing or when configured
         return MockLLMService()
     else:
-        # Default to mock service if configuration is incomplete
         logger.warning(f"LLM provider '{llm_provider}' not properly configured - using mock service")
-        return MockLLMService()
\ No newline at end of file
+        return MockLLMService()