diff --git a/servers/fastapi/models/presentation_outline_model.py b/servers/fastapi/models/presentation_outline_model.py
index 4f3bd377..ed06485b 100644
--- a/servers/fastapi/models/presentation_outline_model.py
+++ b/servers/fastapi/models/presentation_outline_model.py
@@ -15,7 +15,7 @@ class PresentationOutlineModel(BaseModel):
     title: str = Field(
         description="Title of the presentation in about 3 to 8 words",
     )
-    notes: Optional[List[str]] = Field(description="Notes for the presentation")
+    notes: Optional[List[str]] = Field(default=None, description="Notes for the presentation")
     slides: List[SlideOutlineModel] = Field(description="List of slides")
 
     def to_string(self):
diff --git a/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py b/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py
index 90be3f9e..b7ba983e 100644
--- a/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py
+++ b/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py
@@ -1,5 +1,4 @@
 from typing import Optional
-from openai.lib.streaming.chat._events import ContentDeltaEvent
 from google.genai.types import GenerateContentConfig
 
 from utils.async_iterator import iterator_to_async
@@ -11,7 +10,7 @@ from utils.llm_provider import (
     get_nano_model,
     is_google_selected,
 )
-
+from pydantic import BaseModel
 
 system_prompt = """
 You are an expert presentation creator. Generate structured presentations based on user requirements and format them according to the specified JSON schema with markdown content.
@@ -75,7 +74,14 @@ def get_prompt_template(prompt: str, n_slides: int, language: str, content: str)
         },
     ]
 
-
+def get_response_format(response_model: BaseModel):
+    return {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "PresentationOutlineModel",
+                "schema": response_model.model_json_schema(),
+            },
+        }
 async def generate_ppt_outline(
     prompt: Optional[str],
     n_slides: int,
@@ -83,7 +89,9 @@ async def generate_ppt_outline(
     content: Optional[str] = None,
 ):
     model = get_large_model()
+    print(f"Using model: {model}")
     response_model = get_presentation_outline_model_with_n_slides(n_slides)
+    print(response_model.model_json_schema())
 
     if not is_google_selected():
         client = get_llm_client()
@@ -91,9 +99,16 @@ async def generate_ppt_outline(
             model=model,
             messages=get_prompt_template(prompt, n_slides, language, content),
             stream=True,
-            response_format=response_model,
+            response_format = get_response_format(response_model)
         ):
-            yield response.choices[0].delta
+            delta = response.choices[0].delta
+            content = None
+            if isinstance(delta, dict):
+                content = delta.get("content")
+            else:
+                content = getattr(delta, "content", None)
+            if content:
+                yield content
 
     else:
         client = get_google_llm_client()