Merge pull request 'new_ui' (#15) from new_ui into develop
Reviewed-on: Berufsschule/Veracity_AI#15
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f832779fc3
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@ -12,7 +12,7 @@ class ArticleRater:
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"model": "mistral-nemo:12b-instruct-2407-q8_0",
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"headers": self.headers,
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"system": """Ein Mashine Learning Model hat einen Text bewertet, ob es sich um FakeNews handelt oder um Reale News.
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Erkläre in 1-3 Sätzen warum dieses Modell zu dieser Entscheidung. Beginne die Antwort IMMER mit den Resultaten und Konfidenzen des Models.
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Erkläre in 1-2 Sätzen warum dieses Modell zu dieser Entscheidung.
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DU SOLLST KEINE ÜBERSCHRIFTEN oder ähnliches ERKLÄREN. Du erhählst einen TEXT und sollst erklären wie das RESULTAT zustande kam"""
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}
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@ -7,12 +7,7 @@ from utils.database.database import FakeNewsChecker
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from models.provider import Provider
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from collections import Counter
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from Ai.llm import ArticleRater
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BAD_WORDS = ["FAKE", "SATIRE", "Fake", "fake", "fake news", "Fake News", "FakeNews"]
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GOOD_WORDS = ["REAL", "real ", "Real", "Reale News", "reale", "reale News", "realen", "Real News"]
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BAD_COLOR = "#ff8080"
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GOOD_COLOR = "#80ff8f"
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WORDS = BAD_WORDS + GOOD_WORDS
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from Ai.Token import get_token
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class MainFrameController:
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@ -47,63 +42,36 @@ class MainFrameController:
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return text_data
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def press_check_button(self):
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self.frame.result_label.configure(text="", fg_color="#333333")
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self.frame.confidence_label.configure(text="", fg_color="#333333")
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text_data = self.get_text_data()
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if not text_data.text.strip():
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return
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text_data = self._predict(text_data)
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self._add_to_db(text_data)
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self.frame.output_textbox.configure(state="normal")
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self.frame.output_textbox.delete("0.0", "end")
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response_stream = self.rater.get_response(text_data.text, text_data.result, float(f"{text_data.confidence * 100:.2f}"))
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confidence = text_data.confidence * 100
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self.frame.confidence_label.configure(text=f"{confidence:.2f}%")
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highlight_buffer = deque(maxlen=5)
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result_color = "green" if text_data.result == "REAL" else "red"
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self.frame.result_label.configure(text=text_data.result, fg_color=result_color)
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for chunk in response_stream:
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# Display the chunk immediately
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self.frame.output_textbox.insert("end", chunk)
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self.frame.output_textbox.see("end")
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self.frame.update_idletasks()
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confidence_color = "green" if confidence > 80 else ("orange" if confidence > 50 else "red")
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self.frame.confidence_label.configure(fg_color=confidence_color)
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if get_token().strip():
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response_stream = self.rater.get_response(text_data.text, text_data.result, confidence)
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# Add to highlight buffer
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highlight_buffer.append(chunk)
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for chunk in response_stream:
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self.frame.output_textbox.insert("end", chunk)
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self.frame.output_textbox.see("end")
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self.frame.update_idletasks()
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# Process highlighting when buffer is full
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if len(highlight_buffer) == 5:
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self._process_highlighting(highlight_buffer)
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# Process any remaining chunks in the buffer
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if highlight_buffer:
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self._process_highlighting(highlight_buffer)
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self.frame.output_textbox.configure(state="disabled")
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self.update_provider_list()
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def _process_highlighting(self, highlight_buffer):
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start_index = self.frame.output_textbox.index(f"end-{sum(len(c) for c in highlight_buffer)}c")
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end_index = self.frame.output_textbox.index("end")
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self._highlight_words(start_index, end_index)
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# Keep overlap of 2 chunks
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highlight_buffer = deque(list(highlight_buffer)[-3:], maxlen=5)
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def _highlight_words(self, start_index, end_index):
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content = self.frame.output_textbox.get(start_index, end_index)
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for word in WORDS:
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start = 0
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while True:
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pos = content.find(word, start)
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if pos == -1:
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break
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word_start = f"{start_index}+{pos}c"
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word_end = f"{word_start}+{len(word)}c"
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tag_name = f"{word.lower()}_color"
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self.frame.output_textbox.tag_add(tag_name, word_start, word_end)
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if word in BAD_WORDS:
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self.frame.output_textbox.tag_config(tag_name, foreground=BAD_COLOR)
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elif word in GOOD_WORDS:
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self.frame.output_textbox.tag_config(tag_name, foreground=GOOD_COLOR)
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start = pos + len(word)
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def _predict(self, text_data: TextData) -> TextData:
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"""
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Make a prediction using the VeraMind model.
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@ -1,44 +1,64 @@
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from typing import Any
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import customtkinter as ctk
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class MainFrame(ctk.CTkFrame):
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class MainFrame(ctk.CTkFrame):
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def __init__(self, master: Any, **kwargs):
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super().__init__(master, **kwargs)
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self.controller = None
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# Konfiguriere das Hauptframe, um sich zu dehnen
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# Configure the main frame to stretch
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self.grid_rowconfigure(0, weight=1)
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self.grid_columnconfigure(0, weight=1) # Linke Spalte soll sich dehnen
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self.grid_columnconfigure(1, weight=0) # Mittlere Spalte (Button) soll sich nicht dehnen
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self.grid_columnconfigure(2, weight=1) # Rechte Spalte soll sich dehnen
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self.grid_columnconfigure(0, weight=1) # Left column should stretch
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self.grid_columnconfigure(1, weight=0) # Middle column (button) should not stretch
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self.grid_columnconfigure(2, weight=1) # Right column should stretch
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# Linkes Frame
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# Left frame
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self.frame1 = ctk.CTkFrame(self)
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self.frame1.grid(row=0, column=0, sticky="nsew", padx=10, pady=10)
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self.frame1.grid_rowconfigure(2, weight=1) # Lasse die Output-Textbox wachsen
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self.frame1.grid_columnconfigure(0, weight=1) # Lasse frame1 horizontal wachsen
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self.frame1.grid_rowconfigure(3, weight=1)
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self.frame1.grid_columnconfigure(0, weight=1)
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self.entry_url = ctk.CTkEntry(self.frame1, placeholder_text='Enter the article link', height=50)
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self.entry_url.grid(row=0, column=0, padx=10, pady=10, sticky="ew")
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self.entry_url.grid(row=0, column=0,columnspan=2, padx=10, pady=10, sticky="ew")
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self.input_textbox = ctk.CTkTextbox(self.frame1, height=150)
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self.input_textbox.grid(row=1, column=0, columnspan=2, padx=10, pady=10, sticky="nsew")
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self.output_textbox = ctk.CTkTextbox(self.frame1, height=200, state="disabled")
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self.output_textbox.grid(row=2, column=0, columnspan=2, padx=10, pady=10, sticky="nsew")
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# Mittlerer Button
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# Middle button
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self.check_button = ctk.CTkButton(self.frame1, text="Check", width=60, height=50, command=self.check_button_event)
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self.check_button.grid(row=0, column=1, padx=10, pady=10, sticky="w")
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self.check_button.grid(row=0, column=2,columnspan=1, padx=10, pady=10, sticky="e")
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# Rechte scrollbare Ansicht
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# Input Checkbox
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self.input_textbox = ctk.CTkTextbox(self.frame1, height=125)
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self.input_textbox.grid(row=1, column=0,columnspan=3, padx=10, pady=10, sticky="nsew")
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# Frame for Result and Confidence labels
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self.label_frame = ctk.CTkFrame(self.frame1, fg_color="#333333")
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self.label_frame.grid(row=2, column=0, columnspan=3, padx=10, pady=10, sticky="ew")
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self.label_frame.grid_columnconfigure(0, weight=1)
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self.label_frame.grid_columnconfigure(1, weight=1)
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# Result label
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self.result_label = ctk.CTkLabel(self.label_frame, text="", height=50, fg_color="#333333", corner_radius=5)
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self.result_label.grid(row=0, column=0, padx=(0, 5), pady=0, sticky="ew")
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# Confidence label
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self.confidence_label = ctk.CTkLabel(self.label_frame, text="", height=50, fg_color="#333333", corner_radius=5)
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self.confidence_label.grid(row=0, column=1, padx=(5, 0), pady=0, sticky="ew")
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# Ensure equal width for both labels
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self.label_frame.grid_columnconfigure(0, weight=1, minsize=200)
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self.label_frame.grid_columnconfigure(1, weight=1, minsize=200)
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self.output_textbox = ctk.CTkTextbox(self.frame1, height=175, state="disabled")
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self.output_textbox.grid(row=3, column=0, columnspan=3, padx=10, pady=10, sticky="nsew")
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# Right scrollable view
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self.scrollview = ctk.CTkScrollableFrame(self)
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self.scrollview.grid(row=0, column=2, padx=10, pady=10, sticky="nsew")
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# Überschrift hinzufügen
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# Add header
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self.header = ctk.CTkLabel(self.scrollview, text="Leaderboard", font=("Arial", 24, "bold"))
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self.header.pack(pady=10, padx=10, anchor="w")
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# Container für Provider-Einträge
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# Container for provider entries
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self.provider_container = ctk.CTkFrame(self.scrollview)
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self.provider_container.pack(fill="both", expand=True)
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