src/Ai/interence.py

@@ -34,5 +34,6 @@ class VeraMindInference:
 
         return {
             "result": "FAKE" if is_fake else "REAL",
-            "confidence": float(confidence)
+            "confidence": float(confidence),
+            "is_fake": is_fake
         }

src/controller/mainFrameController.py

@@ -1,36 +1,188 @@
+from collections import deque
+import customtkinter as ctk
 from views.mainScreen import MainFrame
 from models.data import TextData
 from Ai.interence import VeraMindInference
+from utils.database.database import FakeNewsChecker
+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_COLOR = "#ff8080"
+GOOD_COLOR = "#80ff8f"
+WORDS = BAD_WORDS + GOOD_WORDS
 
 
 class MainFrameController:
+    """
+    Controller class for the main frame of the application.
+    Handles user interactions, data processing, and database operations.
+    """
 
     def __init__(self, frame: MainFrame) -> None:
+        """
+        Initialize the controller with the main frame and required components.
+
+        :param frame: The main frame of the application
+        """
         self.frame = frame
         self.model_inference = VeraMindInference('VeraMind-Mini')
+        self.db = FakeNewsChecker()
+        self.update_provider_list()
+        self.rater = ArticleRater()
 
+    def get_text_data(self) -> TextData:
+        """
+        Retrieve text data from the UI input fields.
 
-    def get_textdata(self) -> TextData:
+        :return: TextData object containing URL and text content
+        """
         text_data = TextData()
         text_data.url = self.frame.entry_url.get()
-        if text_data.text_from_url():
+        if not text_data.text_from_url():
             text_data.text = self.frame.input_textbox.get("0.0", "end")
-        
         return text_data
 
     def press_check_button(self):
         text_data = self.get_textdata()
-        print(f"text:{text_data.text}")
+        print(text_data.text)
-        self.prediction(text_data)
+        self._predict(text_data)
         self.frame.output_textbox.configure(state="normal")
         self.frame.output_textbox.delete("0.0", "end")
-        self.frame.output_textbox.insert("0.0",f"{text_data.get_output()}")
-        self.frame.output_textbox.configure(state="disabled")
 
-    def prediction(self, text_data:TextData) -> TextData:
+        response_stream = self.rater.get_response(text_data.text, text_data.result, float(f"{text_data.confidence * 100:.2f}"))
+
+        highlight_buffer = deque(maxlen=5)
+
+        for chunk in response_stream:
+            # Display the chunk immediately
+            self.frame.output_textbox.insert("end", chunk)
+            self.frame.output_textbox.see("end")
+            self.frame.update_idletasks()
+
+            # Add to highlight buffer
+            highlight_buffer.append(chunk)
+
+            # Process highlighting when buffer is full
+            if len(highlight_buffer) == 5:
+                self.process_highlighting(highlight_buffer)
+
+        # Process any remaining chunks in the buffer
+        if highlight_buffer:
+            self.process_highlighting(highlight_buffer)
+
+        self.frame.output_textbox.configure(state="disabled")
+        self.update_provider_list()
+    
+    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)
+
+        # Keep overlap of 2 chunks
+        highlight_buffer = deque(list(highlight_buffer)[-2:], maxlen=5)
+
+    def highlight_words(self, start_index, end_index):
+        content = self.frame.output_textbox.get(start_index, end_index)
+
+        for word in WORDS:
+            start = 0
+            while True:
+                pos = content.find(word, start)
+                if pos == -1:
+                    break
+                word_start = f"{start_index}+{pos}c"
+                word_end = f"{word_start}+{len(word)}c"
+                tag_name = f"{word.lower()}_color"
+                self.frame.output_textbox.tag_add(tag_name, word_start, word_end)
+                if word in BAD_WORDS:
+                    self.frame.output_textbox.tag_config(tag_name, foreground=BAD_COLOR)
+                elif word in GOOD_WORDS:
+                    self.frame.output_textbox.tag_config(tag_name, foreground=GOOD_COLOR)
+                start = pos + len(word)
+
+    def _predict(self, text_data: TextData) -> TextData:
+        """
+        Make a prediction using the VeraMind model.
+
+        :param text_data: TextData object containing the text to analyze
+        :return: Updated TextData object with prediction results
+        """
         result = self.model_inference.predict(text_data.text)
         text_data.confidence = result["confidence"]
         text_data.result = result["result"]
-        print(f"Prediction: {text_data.result}")
+        text_data.is_fake_news = result["is_fake"]
-        print(f"Confidence: {text_data.confidence}")
         return text_data
+
+    def _add_to_db(self, text_data: TextData) -> None:
+        """
+        Add the analyzed data to the database.
+
+        :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)
+        
+    def _fetch_db_data(self):
+        self.text_data_list = []
+        data = self.db.fetch_data()
+        if data:
+            for row in data:
+                print(f"ID: {row[0]}, URL: {row[1]}, Anbieter: {row[2]}, Fake News: {'Ja' if row[3] else 'Nein'}")
+                text_data = TextData(url=row[1], provider=row[2], is_fake_news= row[3])
+                self.text_data_list.append(text_data)
+        
+    def sort_provider(self, text_data_list):
+        # Gruppiere TextData-Objekte nach Provider
+        provider_groups = {}
+        for text_data in text_data_list:
+            if text_data.provider:
+                if text_data.provider not in provider_groups:
+                    provider_groups[text_data.provider] = []
+                provider_groups[text_data.provider].append(text_data)
+
+        # 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 = [
+            Provider(name, count, provider_groups.get(name, []))
+            for name, count in sorted(provider_counts.items(), key=lambda x: x[1], reverse=True)
+        ]
+
+        return sorted_providers
+
+    def update_provider_list(self):
+        self._fetch_db_data()
+        # Lösche vorhandene Einträge in der scrollbaren Ansicht
+        for widget in self.frame.provider_container.winfo_children():
+            widget.destroy()
+
+        # Sortiere und zähle die Provider
+        sorted_providers = self.sort_provider(self.text_data_list)
+
+        # Füge die sortierten Provider zur scrollbaren Ansicht hinzu
+        for i, provider in enumerate(sorted_providers):
+            provider_frame = ctk.CTkFrame(self.frame.provider_container)
+            provider_frame.pack(fill="x", padx=5, pady=2)
+
+            name_label = ctk.CTkLabel(provider_frame, text=provider.title)
+            name_label.pack(side="left", padx=5)
+
+            count_label = ctk.CTkLabel(provider_frame, text=str(provider.get_fake_percentage())+"%")
+            count_label.pack(side="right", padx=5)
+
+    def _update_output(self, output: str) -> None:
+        """
+        Update the output text box with the result.
+
+        :param output: String containing the output to display
+        """
+        self.frame.output_textbox.configure(state="normal")
+        self.frame.output_textbox.delete("0.0", "end")
+        self.frame.output_textbox.insert("0.0", output)
+        self.frame.output_textbox.configure(state="disabled")
+
+    

src/models/data.py

@@ -1,10 +1,15 @@
+from urllib.parse import urlparse
+from typing import Optional
+
 from utils.webTextExtractor import WebTextExtractor
 
 class TextData:
-    def __init__(self, url: str = "") -> None:
+    def __init__(self, url: str = "",text: str = "",result: str = "", is_fake_news: bool = False, provider: str = "") -> None:
         self.url = url
-        self.text = ""
+        self.text = text
-        self.result = ""
+        self.result = result
+        self.is_fake_news = is_fake_news
+        self.provider = provider
         self.confidence = None
         self._extractor = None
 
@@ -32,3 +37,33 @@ class TextData:
             output = f"Prediction: {self.result}" + f"   Confidence: {self.confidence:.4f}"
             print(output)
             return output
+
+    def get_provider(self)-> str:
+        self.extract_provider()
+        return self.provider
+    
+    def extract_provider(self):
+        """
+        Extract the domain (anbieter) from a given URL.
+
+        :param url: The URL to process
+        :return: The extracted domain or None if the URL is invalid
+        """
+        if not self._is_valid_url(self.url):
+            self.provider = "None"
+        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" 
+
+    def _is_valid_url(self, url: str) -> bool:
+        """
+        Check if a given URL is valid.
+
+        :param url: The URL to validate
+        :return: True if the URL is valid, False otherwise
+        """
+        try:
+            result = urlparse(url)
+            return all([result.scheme, result.netloc])
+        except ValueError:
+            return False

src/models/provider.py

@@ -0,0 +1,24 @@
+class Provider():
+     
+    def __init__(self, title: str, count: int, text_data_list) -> None:
+        self.title = title
+        self.count = count
+        self.text_data_list = text_data_list
+        
+    def get_fake_percentage(self) -> float:
+        
+        count_all = 0
+        count_fake = 0
+        for text_data in self.text_data_list:
+            #print(text_data.provider)
+            #print("FAKE" if text_data.is_fake_news else "REAL")
+            count_all += 1  
+            if text_data.is_fake_news:
+                count_fake += 1  
+        
+        if count_all == 0:  
+            return 0.0
+
+        return (count_fake / count_all) * 100
+            
+            

src/utils/database/database.py

@@ -1,4 +1,4 @@
-import sqlite3
+import duckdb
 
 class FakeNewsChecker:
     def __init__(self, db_name='fake_news_checker.db'):
@@ -6,47 +6,48 @@ class FakeNewsChecker:
         self.create_table()
 
     def create_connection(self):
-        return sqlite3.connect(self.db_name)
+        return duckdb.connect(self.db_name)
 
     def create_table(self):
         conn = self.create_connection()
-        cursor = conn.cursor()
+        conn.execute('''
-        cursor.execute('''
             CREATE TABLE IF NOT EXISTS url_info (
-                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                id INTEGER PRIMARY KEY,
-                url TEXT NOT NULL,
+                url VARCHAR NOT NULL,
-                anbieter TEXT NOT NULL,
+                anbieter VARCHAR NOT NULL,
                 is_fake_news BOOLEAN NOT NULL
             )
         ''')
-        conn.commit()
         conn.close()
 
+    def get_next_id(self):
+        conn = self.create_connection()
+        result = conn.execute('SELECT COALESCE(MAX(id), 0) + 1 FROM url_info').fetchone()
+        conn.close()
+        return result[0]
+
     def insert_data(self, url, anbieter, is_fake_news):
         conn = self.create_connection()
-        cursor = conn.cursor()
+        next_id = self.get_next_id()
-        cursor.execute('''
+        conn.execute('''
-            INSERT INTO url_info (url, anbieter, is_fake_news)
+            INSERT INTO url_info (id, url, anbieter, is_fake_news)
-            VALUES (?, ?, ?)
+            VALUES (?, ?, ?, ?)
-        ''', (url, anbieter, is_fake_news))
+        ''', [next_id, url, anbieter, bool(is_fake_news)])
-        conn.commit()
         conn.close()
 
     def fetch_data(self):
         conn = self.create_connection()
-        cursor = conn.cursor()
+        result = conn.execute('SELECT * FROM url_info').fetchall()
-        cursor.execute('SELECT * FROM url_info')
-        rows = cursor.fetchall()
         conn.close()
-        return rows
+        return result
 
 # Beispielnutzung der Klasse
 if __name__ == '__main__':
     checker = FakeNewsChecker()
 
     # Daten hinzufügen
-    checker.insert_data('https://example.com/news/123', 'Example News', 0)
+    checker.insert_data('https://example.com/news/123', 'Example News', False)
-    checker.insert_data('https://fakenews.com/article/456', 'Fake News', 1)
+    checker.insert_data('https://fakenews.com/article/456', 'Fake News', True)
 
     # Daten abrufen
     data = checker.fetch_data()

src/views/mainScreen.py

@@ -38,6 +38,10 @@ class MainFrame(ctk.CTkFrame):
         self.header = ctk.CTkLabel(self.scrollview, text="Leaderboard", font=("Arial", 24, "bold"))
         self.header.pack(pady=10, padx=10, anchor="w")
         
+        # Container für Provider-Einträge
+        self.provider_container = ctk.CTkFrame(self.scrollview)
+        self.provider_container.pack(fill="both", expand=True)
+        
     def set_controller(self, controller):
         self.controller = controller