Merge pull request 'bug-fix' (#14) from bug-fix into develop

Reviewed-on: Berufsschule/Veracity_AI#14

.gitignore

@@ -155,7 +155,7 @@ cython_debug/
 
 #ML
 VeraMind-Mini/
-Token.txt
+Token.py
 
 # OS generated files #
 ######################

src/Ai/llm.py

@@ -1,14 +1,10 @@
 from langchain_community.llms import Ollama
+from Ai.Token import get_token
 
 class ArticleRater:
     def __init__(self):
         self.client = "https://ai.fabelous.app/v1/ollama/generic"
-        self.headers = self._load_token("Token.txt")
-
-    def _load_token(self, token_path):
-        with open(token_path, "r") as f:
-            token = f.read().strip()
-        return {"Authorization": f"Token {token}"}
+        self.headers = {"Authorization": f"Token {get_token()}"}
 
     def get_response(self, article, result, confidence):
         ollama_params = {

src/controller/mainFrameController.py

@@ -8,8 +8,8 @@ from models.provider import Provider
 from collections import Counter
 from Ai.llm import ArticleRater
 
-BAD_WORDS = ["FAKE", "SATIRE", "Fake", "fake"]
-GOOD_WORDS = ["REAL", "real", "Real"]
+BAD_WORDS = ["FAKE", "SATIRE", "Fake", "fake", "fake news", "Fake News", "FakeNews"]
+GOOD_WORDS = ["REAL", "real ", "Real", "Reale News", "reale", "reale News", "realen", "Real News"]
 BAD_COLOR = "#ff8080"
 GOOD_COLOR = "#80ff8f"
 WORDS = BAD_WORDS + GOOD_WORDS
@@ -43,12 +43,13 @@ class MainFrameController:
         text_data.url = self.frame.entry_url.get()
         if not text_data.text_from_url():
             text_data.text = self.frame.input_textbox.get("0.0", "end")
+            text_data.provider = "Unknown"
         return text_data
 
     def press_check_button(self):
         text_data = self.get_text_data()
-        print(text_data.text)
-        self._predict(text_data)
+        text_data = self._predict(text_data)
+        self._add_to_db(text_data)
         self.frame.output_textbox.configure(state="normal")
         self.frame.output_textbox.delete("0.0", "end")
 
@@ -67,24 +68,24 @@ class MainFrameController:
 
             # Process highlighting when buffer is full
             if len(highlight_buffer) == 5:
-                self.process_highlighting(highlight_buffer)
+                self._process_highlighting(highlight_buffer)
 
         # Process any remaining chunks in the buffer
         if highlight_buffer:
-            self.process_highlighting(highlight_buffer)
+            self._process_highlighting(highlight_buffer)
 
         self.frame.output_textbox.configure(state="disabled")
         self.update_provider_list()
     
-    def process_highlighting(self, highlight_buffer):
+    def _process_highlighting(self, highlight_buffer):
         start_index = self.frame.output_textbox.index(f"end-{sum(len(c) for c in highlight_buffer)}c")
         end_index = self.frame.output_textbox.index("end")
-        self.highlight_words(start_index, end_index)
+        self._highlight_words(start_index, end_index)
 
         # Keep overlap of 2 chunks
-        highlight_buffer = deque(list(highlight_buffer)[-2:], maxlen=5)
+        highlight_buffer = deque(list(highlight_buffer)[-3:], maxlen=5)
 
-    def highlight_words(self, start_index, end_index):
+    def _highlight_words(self, start_index, end_index):
         content = self.frame.output_textbox.get(start_index, end_index)
 
         for word in WORDS:
@@ -123,7 +124,7 @@ class MainFrameController:
         :param text_data: TextData object containing the analyzed information
         """
         
-        self.db.insert_data(url=text_data.url, anbieter=text_data.get_provider(),is_fake_news= text_data.is_fake_news)
+        self.db.insert_data(url=text_data.url, anbieter=text_data.get_provider(), is_fake_news= text_data.is_fake_news)
         
     def _fetch_db_data(self):
         self.text_data_list = []
@@ -146,14 +147,18 @@ class MainFrameController:
         # Zähle die Häufigkeit jedes Providers
         provider_counts = Counter(text_data.provider for text_data in text_data_list if text_data.provider)
 
-        # Erstelle und sortiere die Provider-Liste
-        sorted_providers = [
+        # Erstelle die Provider-Liste
+        providers = [
             Provider(name, count, provider_groups.get(name, []))
-            for name, count in sorted(provider_counts.items(), key=lambda x: x[1], reverse=True)
+            for name, count in provider_counts.items()
         ]
 
+        # Sortiere die Provider-Liste nach dem Fake-Prozentsatz (absteigend)
+        sorted_providers = sorted(providers, key=lambda x: x.get_fake_percentage(), reverse=True)
+
         return sorted_providers
 
+
     def update_provider_list(self):
         self._fetch_db_data()
         # Lösche vorhandene Einträge in der scrollbaren Ansicht

src/models/data.py

@@ -21,7 +21,7 @@ class TextData:
     def text_from_url(self)-> bool:
         if not self.url:
             print("No url")
-            return True
+            return False
 
         if not self.text:
             print("Extrahiere Text von URL...")
@@ -29,7 +29,7 @@ class TextData:
             self._extractor.fetch_content()
             self._extractor.extract_text()
             self.text = self._extractor.get_text()
-            return False
+            return True
     
     def get_output(self):
         
@@ -50,10 +50,10 @@ class TextData:
         :return: The extracted domain or None if the URL is invalid
         """
         if not self._is_valid_url(self.url):
-            self.provider = "None"
+            self.provider = "Unknown"
         parsed_url = urlparse(self.url)
         domain_parts = parsed_url.netloc.split('.')
-        self.provider = f"{domain_parts[-2]}.{domain_parts[-1]}" if len(domain_parts) >= 2 else "None" 
+        self.provider = f"{domain_parts[-2]}.{domain_parts[-1]}" if len(domain_parts) >= 2 else "Unknown" 
 
     def _is_valid_url(self, url: str) -> bool:
         """