diff --git a/README.md b/README.md
index 84c0e48..bdc49e7 100644
--- a/README.md
+++ b/README.md
@@ -40,4 +40,4 @@ To use the Fake News Checker application, follow these steps:
 
 ## License
 
-This application is licensed under the MIT license. See the [LICENSE](LICENSE) file for more details.
\ No newline at end of file
+This application is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International. See the [LICENSE](LICENSE) file for more details.
\ No newline at end of file
diff --git a/docs/use-case-diagram.png b/docs/use-case-diagram.png
new file mode 100644
index 0000000..56927d8
Binary files /dev/null and b/docs/use-case-diagram.png differ
diff --git a/src/Ai/llm.py b/src/Ai/llm.py
index f2a566c..c907087 100644
--- a/src/Ai/llm.py
+++ b/src/Ai/llm.py
@@ -1,4 +1,5 @@
-from langchain_community.llms import Ollama
+from langchain_ollama import ChatOllama
+from langchain_core.messages import AIMessage
 import os
 
 class ArticleRater:
@@ -6,6 +7,8 @@ class ArticleRater:
         self.client = "https://ai.fabelous.app/v1/ollama/generic"
         self.token = self._get_token()
         self.headers = {"Authorization": f"Token {self.token}"}
+        self.model = "phi3.5:3.8b-mini-instruct-q4_K_M"
+        self.llm = ChatOllama(model=self.model, client_kwargs={'headers': self.headers}, base_url=self.client)
 
     def _get_token(self):
         if os.path.exists("Token/Token.txt"):
@@ -15,22 +18,16 @@ class ArticleRater:
             return None
 
     def get_response(self, article, result, confidence):
-        ollama_params = {
-            "base_url": self.client,
-            "model": "mistral-nemo:12b-instruct-2407-q8_0",
-            "headers": self.headers,
-            "system": """Ein Mashine Learning Model hat einen Text bewertet, ob es sich um FakeNews handelt oder um Reale News. 
+        messages = [
+            ("system",  """Ein Mashine Learning Model hat einen Text bewertet, ob es sich um FakeNews handelt oder um Reale News. 
             Erkläre in 1-2 Sätzen warum dieses Modell zu dieser Entscheidung. 
-            DU SOLLST KEINE ÜBERSCHRIFTEN oder ähnliches ERKLÄREN. Du erhählst einen TEXT und sollst erklären wie das RESULTAT zustande kam"""
-        }
+            DU SOLLST KEINE ÜBERSCHRIFTEN oder ähnliches ERKLÄREN. Du erhählst einen TEXT und sollst erklären wie das RESULTAT zustande kam"""),
+            ("human", f"{article}, result: {result}, confidence {confidence}")
+        ]
 
-        message = (f"{article}, result: {result}, confidence {confidence}")
-
-        # Initialize the Ollama object with the prepared parameters
-        llm = Ollama(**ollama_params)
 
         # Return the response stream
-        return llm.stream(message)
+        return self.llm.stream(messages)
 
 # Usage
 if __name__ == "__main__":
@@ -43,4 +40,4 @@ if __name__ == "__main__":
     # Capture the stream response
     response_stream = article_rater.get_response(article, result, confidence=confidence)
     for chunk in response_stream:
-        print(chunk, end='', flush=True)
+        print(chunk.content, end="")
diff --git a/src/controller/mainFrameController.py b/src/controller/mainFrameController.py
index bf51879..d990722 100644
--- a/src/controller/mainFrameController.py
+++ b/src/controller/mainFrameController.py
@@ -67,7 +67,7 @@ class MainFrameController:
             response_stream = self.rater.get_response(text_data.text, text_data.result, confidence)
 
             for chunk in response_stream:
-                self.frame.output_textbox.insert("end", chunk)
+                self.frame.output_textbox.insert("end", chunk.content)
                 self.frame.output_textbox.see("end")
                 self.frame.update_idletasks()