Delete app.py

app.py

@@ -1,100 +0,0 @@
-# -*- coding: utf-8 -*-
-"""app.ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1EyjV73NmmvRi7U_r_GxUjz4X-5-6yMgE
-"""
-
-# load_and_run_pkl_model.py
-# This script ONLY loads a pre-saved PKL file and runs a Gradio interface for it.
-
-import gradio as gr
-import pickle
-import os
-
-# --- Dependencies required ONLY for the class definition used by pickle ---
-# We are NOT calling pipeline() here to load models from Hugging Face.
-# Pickle just needs to know the *structure* of the saved object.
-from transformers import pipeline
-import torch
-
-# --- Define the Class Structure ---
-# IMPORTANT: This MUST exactly match the class definition used when
-# the .pkl file was SAVED. Pickle needs this to reconstruct the object.
-
-# --- Configuration: Path to your saved PKL file ---
-PICKLE_FILENAME = "combined_analyzer.pkl"
-MODEL_DIR = "saved_model" # Directory where the PKL file is located
-PICKLE_FILEPATH = os.path.join(MODEL_DIR, PICKLE_FILENAME)
-
-# --- Global Variable to hold the loaded analyzer ---
-LOADED_ANALYZER = None
-LOAD_ERROR_MESSAGE = None
-
-# --- Load the Saved Model from PKL File ---
-print("-" * 40)
-print(f"Attempting to load analyzer object from: {PICKLE_FILEPATH}")
-try:
-    # Security Note: Only unpickle files you trust.
-    if not os.path.exists(PICKLE_FILEPATH):
-         raise FileNotFoundError(f"Cannot find the model file at '{PICKLE_FILEPATH}'. Make sure it exists.")
-
-    with open(PICKLE_FILEPATH, 'rb') as f:
-        # The actual loading happens here
-        LOADED_ANALYZER = pickle.load(f)
-
-    # Validate the loaded object (basic check)
-    if not isinstance(LOADED_ANALYZER, CombinedAnalyzer) or not callable(getattr(LOADED_ANALYZER, 'analyze', None)):
-        LOADED_ANALYZER = None # Invalidate if it's not the right type or lacks the method
-        raise TypeError("The loaded object from the PKL file is not a valid 'CombinedAnalyzer' instance or is corrupted.")
-    else:
-        print(">>> Successfully loaded analyzer object from PKL file.")
-
-except Exception as e:
-    LOAD_ERROR_MESSAGE = f"ERROR: Failed to load model from '{PICKLE_FILEPATH}'.\nDetails: {e}"
-    print(LOAD_ERROR_MESSAGE)
-    LOADED_ANALYZER = None # Ensure it's None if any error occurred
-
-print("-" * 40)
-
-# --- Gradio Function (Uses the globally loaded object) ---
-def perform_analysis(input_text):
-    """This function is called by the Gradio interface."""
-    if LOADED_ANALYZER is None:
-        # If loading failed earlier, return the error message
-        return LOAD_ERROR_MESSAGE or "Error: Analyzer model is not loaded."
-
-    if not input_text or not input_text.strip():
-        return "Please enter some text to analyze."
-
-    # Use the 'analyze' method of the object loaded from the PKL file
-    try:
-        results = LOADED_ANALYZER.analyze(input_text)
-        return results
-    except Exception as e:
-        # Catch errors during the analysis itself
-        print(f"Error during analysis execution: {e}")
-        return f"An error occurred during analysis:\n{e}"
-
-# --- Create the Gradio Interface ---
-gradio_app_description = f"Enter text to analyze using the model loaded from `{PICKLE_FILEPATH}`."
-if LOADED_ANALYZER is None:
-    gradio_app_description += "\n\n**WARNING: Model failed to load. Analysis will not function.**"
-
-interface = gr.Interface(
-    fn=perform_analysis, # The function that runs the analysis
-    inputs=gr.Textbox(lines=8, placeholder="Enter text here...", label="Input Text"),
-    outputs=gr.Textbox(lines=8, label="Analysis Results", interactive=False),
-    title="Analyze Text with Saved Model",
-    description=gradio_app_description,
-    allow_flagging='never'
-)
-
-# --- Launch the Gradio App ---
-if __name__ == "__main__":
-    print("Launching Gradio interface...")
-    if LOADED_ANALYZER is None:
-        print("!!! Warning: Launching interface, but model loading failed. Check errors above. !!!")
-    interface.launch()