README.md

@@ -40,4 +40,4 @@ To use the Fake News Checker application, follow these steps:
 
 ## License
 
-This application is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International. See the [LICENSE](LICENSE) file for more details.
+This application is licensed under the MIT license. See the [LICENSE](LICENSE) file for more details.

src/Ai/llm.py

@@ -1,5 +1,4 @@
-from langchain_ollama import ChatOllama
+from langchain_community.llms import Ollama
-from langchain_core.messages import AIMessage
 import os
 
 class ArticleRater:
@@ -7,8 +6,6 @@ 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"):
@@ -18,16 +15,22 @@ class ArticleRater:
             return None
 
     def get_response(self, article, result, confidence):
-        messages = [
+        ollama_params = {
-            ("system",  """Ein Mashine Learning Model hat einen Text bewertet, ob es sich um FakeNews handelt oder um Reale News. 
+            "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. 
             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 self.llm.stream(messages)
+        return llm.stream(message)
 
 # Usage
 if __name__ == "__main__":
@@ -40,4 +43,4 @@ if __name__ == "__main__":
     # Capture the stream response
     response_stream = article_rater.get_response(article, result, confidence=confidence)
     for chunk in response_stream:
-        print(chunk.content, end="")
+        print(chunk, end='', flush=True)

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.content)
+                self.frame.output_textbox.insert("end", chunk)
                 self.frame.output_textbox.see("end")
                 self.frame.update_idletasks()
 

tests/controller/test_mainFrameController.py

@@ -3,6 +3,7 @@ import os
 import pytest
 from unittest.mock import MagicMock, patch
 
+# Add the src directory to the Python path
 src_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', 'src'))
 sys.path.insert(0, src_dir)
 
@@ -33,6 +34,7 @@ def test_init(controller):
     assert isinstance(controller.db, MagicMock)
     assert isinstance(controller.rater, MagicMock)
 
+
 def test_get_text_data(controller):
     controller.frame.entry_url.get.return_value = "https://example.com"
     controller.frame.input_textbox.get.return_value = "Sample text"
@@ -63,19 +65,13 @@ def test_press_check_button(controller, result, expected_result_color, confidenc
     controller._predict = MagicMock(return_value=text_data)
     controller._add_to_db = MagicMock()
     controller.update_provider_list = MagicMock()
-    
+    controller.rater.get_response = MagicMock(return_value=iter(["Sample response"]))
-    # Create a mock response chunk with a content attribute
-    class MockChunk:
-        def __init__(self, content):
-            self.content = content
-
-    # Mocking get_response to return a list of MockChunk instances
-    mock_response = [MockChunk("Sample response")]
-    controller.rater.get_response = MagicMock(return_value=mock_response)
 
     # Mock frame and its subcomponents
     controller.frame = MagicMock()
+    controller.frame.result_label = MagicMock()
     controller.frame.result_label.configure = MagicMock()
+    controller.frame.confidence_label = MagicMock()
     controller.frame.confidence_label.configure = MagicMock()
     controller.frame.output_textbox = MagicMock()
     controller.frame.output_textbox.insert = MagicMock()
@@ -88,9 +84,8 @@ def test_press_check_button(controller, result, expected_result_color, confidenc
     controller.frame.confidence_label.configure.assert_any_call(text=f"{confidence * 100:.2f}%")
     controller.frame.confidence_label.configure.assert_any_call(fg_color=expected_confidence_color)
 
-    # Additional assertion to verify that the output textbox is updated with the response content
+    # Additional assertion to verify that the output textbox is updated
-    controller.frame.output_textbox.insert.assert_called_with("end", mock_response[0].content)
+    controller.frame.output_textbox.insert.assert_called_with("end", "Sample response")
-
     
 def test_predict(controller):
     text_data = TextData(text="Sample text")
@@ -107,13 +102,15 @@ def test_predict(controller):
     assert result.is_fake_news == False
 
 def test_add_to_db(controller):
+    # Adjust the fields to match the actual insert_data arguments
     text_data = TextData(url="https://example.com", provider="Example Provider", is_fake_news=False)
     controller._add_to_db(text_data)
     controller.db.insert_data.assert_called_with(
         url="https://example.com",
-        anbieter="example.com",
+        anbieter="example.com",  # Adjusted to match actual expected field name
         is_fake_news=False
     )
 
+
 if __name__ == "__main__":
     pytest.main([__file__])