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·
eb2147a
1
Parent(s):
69d37ef
update
Browse files- app.py +87 -112
- templates/index.html +8 -8
app.py
CHANGED
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@@ -5,6 +5,7 @@ import os
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import string
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import logging
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from datetime import datetime
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# Set up logging
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logging.basicConfig(level=logging.INFO,
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@@ -15,144 +16,129 @@ logging.basicConfig(level=logging.INFO,
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])
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logger = logging.getLogger(__name__)
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app = Flask(__name__)
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app.config['SECRET_KEY'] = 'supersecretkey' # Change this to a random secret key
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# Directories for visualizations
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"
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"
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"
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"
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}
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VISUALIZATION_DIRS_CHAIN_OF_TABLE = {
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"TP": "htmls_COT/TP",
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"TN": "htmls_COT/TN",
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"FP": "htmls_COT/FP",
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"FN": "htmls_COT/FN"
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}
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def save_session_data(username, data):
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try:
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except Exception as e:
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logger.exception(f"Error saving session data for user {username}: {e}")
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# Similarly, update the load_session_data function
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def load_session_data(username):
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try:
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with open(file_path, 'r') as f:
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data = json.load(f)
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logger.info(f"Session data loaded for user {username} from {file_path}")
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return data
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except FileNotFoundError:
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logger.warning(f"No session data found for user {username}")
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return None
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except Exception as e:
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logger.exception(f"Error loading session data for user {username}: {e}")
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return None
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if method == "Chain-of-Table":
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visualization_dirs = VISUALIZATION_DIRS_CHAIN_OF_TABLE
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else:
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visualization_dirs = VISUALIZATION_DIRS_PLAN_OF_SQLS
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# Randomly select balanced samples
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def select_balanced_samples(samples):
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try:
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except Exception as e:
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logger.exception("Error selecting balanced samples")
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return []
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def generate_random_string(length=8):
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return ''.join(random.choices(string.ascii_letters + string.digits, k=length))
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@app.route('/', methods=['GET', 'POST'])
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def index():
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logger.info("Rendering index page.")
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if request.method == 'POST':
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username = request.form.get('username')
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seed = request.form.get('seed')
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if not username or not seed:
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return "Missing username or seed", 400
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try:
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seed = int(seed)
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random.seed(seed)
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# Use only one method (e.g., "Chain-of-Table")
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method = "Chain-of-Table"
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all_samples = load_samples(method)
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selected_samples = select_balanced_samples(all_samples)
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logger.info(f"Number of selected samples: {len(selected_samples)}")
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if len(selected_samples) == 0:
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return "No samples were selected", 500
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filename = f'{username}_{seed}_{method}_{generate_random_string()}.json'
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logger.info(f"Generated filename: {filename}")
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# Save session data
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session_data = {
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'responses': [],
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'username': username,
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'
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'method': method,
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'
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'current_index': 0
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}
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save_session_data(username, session_data)
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logger.info(f"Session data saved for user: {username}")
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return redirect(url_for('experiment', username=username))
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except Exception as e:
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logger.exception(f"Error in index route: {e}")
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return "An error occurred", 500
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return render_template('index.html')
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@app.route('/experiment/<username>', methods=['GET', 'POST'])
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def experiment(username):
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try:
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session_data = load_session_data(username)
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if not session_data:
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logger.error(f"No session data found for user: {username}")
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return redirect(url_for('index'))
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selected_samples = session_data['selected_samples']
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if current_index >= len(selected_samples):
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return redirect(url_for('completed', username=username))
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# Determine the correct visualization directory based on the category
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for category, dir_path in VISUALIZATION_DIRS_CHAIN_OF_TABLE.items():
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if visualization_file in os.listdir(dir_path):
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visualization_path = os.path.join(vis_dir, category, visualization_file)
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break
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else:
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logger.error(f"Visualization file {visualization_file} not found.")
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return "Visualization file not found", 404
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logger.info(f"Rendering experiment page with visualization: {visualization_path}")
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statement = """
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Based on the explanation provided, what do you think the AI model will predict?
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sample_id=current_index,
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statement=statement,
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visualization=url_for('send_visualization', filename=visualization_path),
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username=username
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except Exception as e:
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logger.exception(f"An error occurred in the experiment route: {e}")
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return "An error occurred", 500
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@app.route('/feedback', methods=['POST'])
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def feedback():
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try:
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logger.error(f"No session data found for user: {username}")
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return redirect(url_for('index'))
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# Store the user's prediction
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session_data['responses'].append({
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'sample_id': session_data['current_index'],
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'user_prediction': prediction
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})
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# Move to the next sample
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session_data['current_index'] += 1
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# Save updated session data
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save_session_data(username, session_data)
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logger.info(f"Prediction saved for user {username}, sample {session_data['current_index'] - 1}")
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logger.exception(f"Error in feedback route: {e}")
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return "An error occurred", 500
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@app.route('/completed/<username>')
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def completed(username):
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try:
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logger.error(f"No session data found for user: {username}")
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return redirect(url_for('index'))
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responses = session_data['responses']
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method = session_data['method']
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json_file = '
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with open(json_file, 'r') as f:
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ground_truth = json.load(f)
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for response in responses:
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sample_id = response['sample_id']
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user_prediction = response['user_prediction']
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visualization_file = session_data['selected_samples'][sample_id]
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index = visualization_file.split('-')[1].split('.')[0]
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ground_truth_key = f"
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if ground_truth_key in ground_truth:
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model_prediction = ground_truth[ground_truth_key]['answer'].upper()
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true_percentage = round(true_percentage, 2)
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false_percentage = round(false_percentage, 2)
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return render_template('completed.html',
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accuracy=accuracy,
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true_percentage=true_percentage,
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logger.exception(f"An error occurred in the completed route: {e}")
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return "An error occurred", 500
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@app.route('/visualizations/<path:filename>')
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def send_visualization(filename):
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logger.info(f"Attempting to serve file: {filename}")
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# Ensure the path is safe and doesn't allow access to files outside the intended directory
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base_dir = os.getcwd()
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file_path = os.path.normpath(os.path.join(base_dir, filename))
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if not file_path.startswith(base_dir):
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logger.info(f"Serving file from directory: {directory}, filename: {file_name}")
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return send_from_directory(directory, file_name)
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if __name__ == "__main__":
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os.makedirs('session_data', exist_ok=True) # Ensure the directory for session files exists
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app.run(host="0.0.0.0", port=7860, debug=True)
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import string
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import logging
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from datetime import datetime
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from huggingface_hub import login, HfApi, hf_hub_download
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# Set up logging
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logging.basicConfig(level=logging.INFO,
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])
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logger = logging.getLogger(__name__)
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# Use the Hugging Face token from environment variables
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hf_token = os.environ.get("HF_TOKEN")
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if hf_token:
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login(token=hf_token)
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else:
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logger.error("HF_TOKEN not found in environment variables")
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app = Flask(__name__)
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app.config['SECRET_KEY'] = 'supersecretkey' # Change this to a random secret key
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# Directories for visualizations
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VISUALIZATION_DIRS = {
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"No-XAI": "htmls_NO_XAI",
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"Dater": "htmls_DATER",
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"Chain-of-Table": "htmls_COT",
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"Plan-of-SQLs": "htmls_POS"
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}
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METHODS = ["No-XAI", "Dater", "Chain-of-Table", "Plan-of-SQLs"]
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def save_session_data(username, data):
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try:
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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file_name = f'{username}_{timestamp}_session.json'
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json_data = json.dumps(data, indent=4)
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temp_file_path = f"/tmp/{file_name}"
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with open(temp_file_path, 'w') as f:
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f.write(json_data)
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api = HfApi()
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api.upload_file(
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path_or_fileobj=temp_file_path,
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path_in_repo=f"session_data_foward_simulation/{file_name}",
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repo_id="luulinh90s/Tabular-LLM-Study-Data",
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repo_type="space",
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)
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os.remove(temp_file_path)
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logger.info(f"Session data saved for user {username} in Hugging Face Data Space")
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except Exception as e:
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logger.exception(f"Error saving session data for user {username}: {e}")
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def load_session_data(username):
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try:
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api = HfApi()
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files = api.list_repo_files(repo_id="luulinh90s/Tabular-LLM-Study-Data", repo_type="space")
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user_files = [f for f in files if f.startswith(f'session_data_graded/{username}_') and f.endswith('_session.json')]
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if not user_files:
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logger.warning(f"No session data found for user {username}")
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return None
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latest_file = sorted(user_files, reverse=True)[0]
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file_path = hf_hub_download(repo_id="luulinh90s/Tabular-LLM-Study-Data", repo_type="space", filename=latest_file)
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with open(file_path, 'r') as f:
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data = json.load(f)
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logger.info(f"Session data loaded for user {username} from Hugging Face Data Space")
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return data
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except Exception as e:
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logger.exception(f"Error loading session data for user {username}: {e}")
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return None
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def load_samples():
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common_samples = []
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categories = ["TP", "TN", "FP", "FN"]
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for category in categories:
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files = set(os.listdir(f'htmls_NO_XAI/{category}'))
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for method in ["Dater", "Chain-of-Table", "Plan-of-SQLs"]:
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method_dir = VISUALIZATION_DIRS[method]
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files &= set(os.listdir(f'{method_dir}/{category}'))
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for file in files:
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common_samples.append({'category': category, 'file': file})
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logger.info(f"Found {len(common_samples)} common samples across all methods")
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return common_samples
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def select_balanced_samples(samples):
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try:
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if len(samples) < 10:
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logger.warning(f"Not enough common samples. Only {len(samples)} available.")
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return samples
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selected_samples = random.sample(samples, 10)
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logger.info(f"Selected 10 unique samples")
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return selected_samples
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except Exception as e:
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logger.exception("Error selecting balanced samples")
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return []
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@app.route('/', methods=['GET', 'POST'])
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def index():
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if request.method == 'POST':
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username = request.form.get('username')
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seed = request.form.get('seed')
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method = request.form.get('method')
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if not username or not seed or not method:
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return "Please fill in all fields and select a method.", 400
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try:
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seed = int(seed)
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random.seed(seed)
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all_samples = load_samples()
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selected_samples = select_balanced_samples(all_samples)
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if len(selected_samples) == 0:
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return "No common samples were found", 500
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session_data = {
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'username': username,
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'seed': seed,
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'method': method,
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'selected_samples': selected_samples,
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'current_index': 0,
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'responses': [],
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'start_time': datetime.now().isoformat()
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}
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save_session_data(username, session_data)
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return redirect(url_for('experiment', username=username))
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except Exception as e:
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logger.exception(f"Error in index route: {e}")
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return "An error occurred", 500
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return render_template('index.html')
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@app.route('/experiment/<username>', methods=['GET', 'POST'])
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def experiment(username):
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try:
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session_data = load_session_data(username)
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if not session_data:
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return redirect(url_for('index'))
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selected_samples = session_data['selected_samples']
|
|
|
|
| 148 |
if current_index >= len(selected_samples):
|
| 149 |
return redirect(url_for('completed', username=username))
|
| 150 |
|
| 151 |
+
sample = selected_samples[current_index]
|
| 152 |
+
visualization_dir = VISUALIZATION_DIRS[method]
|
| 153 |
+
visualization_path = f"{visualization_dir}/{sample['category']}/{sample['file']}"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 154 |
|
| 155 |
statement = """
|
| 156 |
Based on the explanation provided, what do you think the AI model will predict?
|
|
|
|
| 161 |
sample_id=current_index,
|
| 162 |
statement=statement,
|
| 163 |
visualization=url_for('send_visualization', filename=visualization_path),
|
| 164 |
+
username=username,
|
| 165 |
+
method=method)
|
| 166 |
except Exception as e:
|
| 167 |
logger.exception(f"An error occurred in the experiment route: {e}")
|
| 168 |
return "An error occurred", 500
|
| 169 |
|
| 170 |
+
|
| 171 |
@app.route('/feedback', methods=['POST'])
|
| 172 |
def feedback():
|
| 173 |
try:
|
|
|
|
| 179 |
logger.error(f"No session data found for user: {username}")
|
| 180 |
return redirect(url_for('index'))
|
| 181 |
|
|
|
|
| 182 |
session_data['responses'].append({
|
| 183 |
'sample_id': session_data['current_index'],
|
| 184 |
'user_prediction': prediction
|
| 185 |
})
|
| 186 |
|
|
|
|
| 187 |
session_data['current_index'] += 1
|
|
|
|
|
|
|
| 188 |
save_session_data(username, session_data)
|
| 189 |
logger.info(f"Prediction saved for user {username}, sample {session_data['current_index'] - 1}")
|
| 190 |
|
|
|
|
| 196 |
logger.exception(f"Error in feedback route: {e}")
|
| 197 |
return "An error occurred", 500
|
| 198 |
|
|
|
|
| 199 |
@app.route('/completed/<username>')
|
| 200 |
def completed(username):
|
| 201 |
try:
|
|
|
|
| 204 |
logger.error(f"No session data found for user: {username}")
|
| 205 |
return redirect(url_for('index'))
|
| 206 |
|
| 207 |
+
session_data['end_time'] = datetime.now().isoformat()
|
| 208 |
responses = session_data['responses']
|
| 209 |
method = session_data['method']
|
| 210 |
|
| 211 |
+
json_file = f'Tabular_LLMs_human_study_vis_6_{method.upper().replace("-", "_")}.json'
|
| 212 |
|
| 213 |
with open(json_file, 'r') as f:
|
| 214 |
ground_truth = json.load(f)
|
|
|
|
| 220 |
for response in responses:
|
| 221 |
sample_id = response['sample_id']
|
| 222 |
user_prediction = response['user_prediction']
|
| 223 |
+
visualization_file = session_data['selected_samples'][sample_id]['file']
|
| 224 |
+
index = visualization_file.split('-')[1].split('.')[0]
|
| 225 |
|
| 226 |
+
ground_truth_key = f"{method.upper().replace('-', '_')}_test-{index}.html"
|
| 227 |
|
| 228 |
if ground_truth_key in ground_truth:
|
| 229 |
model_prediction = ground_truth[ground_truth_key]['answer'].upper()
|
|
|
|
| 246 |
true_percentage = round(true_percentage, 2)
|
| 247 |
false_percentage = round(false_percentage, 2)
|
| 248 |
|
| 249 |
+
session_data['accuracy'] = accuracy
|
| 250 |
+
session_data['true_percentage'] = true_percentage
|
| 251 |
+
session_data['false_percentage'] = false_percentage
|
| 252 |
+
|
| 253 |
+
save_session_data(username, session_data)
|
| 254 |
+
|
| 255 |
return render_template('completed.html',
|
| 256 |
accuracy=accuracy,
|
| 257 |
true_percentage=true_percentage,
|
|
|
|
| 260 |
logger.exception(f"An error occurred in the completed route: {e}")
|
| 261 |
return "An error occurred", 500
|
| 262 |
|
|
|
|
| 263 |
@app.route('/visualizations/<path:filename>')
|
| 264 |
def send_visualization(filename):
|
| 265 |
logger.info(f"Attempting to serve file: {filename}")
|
|
|
|
| 266 |
base_dir = os.getcwd()
|
| 267 |
file_path = os.path.normpath(os.path.join(base_dir, filename))
|
| 268 |
if not file_path.startswith(base_dir):
|
|
|
|
| 276 |
logger.info(f"Serving file from directory: {directory}, filename: {file_name}")
|
| 277 |
return send_from_directory(directory, file_name)
|
| 278 |
|
|
|
|
| 279 |
if __name__ == "__main__":
|
|
|
|
| 280 |
app.run(host="0.0.0.0", port=7860, debug=True)
|
templates/index.html
CHANGED
|
@@ -43,12 +43,12 @@
|
|
| 43 |
.method-buttons {
|
| 44 |
display: flex;
|
| 45 |
flex-wrap: wrap;
|
| 46 |
-
justify-content:
|
| 47 |
margin-bottom: 20px;
|
| 48 |
gap: 20px;
|
| 49 |
}
|
| 50 |
.method-button {
|
| 51 |
-
width: calc(
|
| 52 |
padding: 15px;
|
| 53 |
font-size: 20px;
|
| 54 |
border-radius: 10px;
|
|
@@ -66,11 +66,11 @@
|
|
| 66 |
background-color: #ffcc80;
|
| 67 |
color: #e65100;
|
| 68 |
}
|
| 69 |
-
.method-button.
|
| 70 |
background-color: #e8f5e9;
|
| 71 |
color: #4caf50;
|
| 72 |
}
|
| 73 |
-
.method-button.
|
| 74 |
background-color: #fff3e0;
|
| 75 |
color: #ff9800;
|
| 76 |
}
|
|
@@ -139,11 +139,11 @@
|
|
| 139 |
<div class="method-button pos" onclick="selectMethod('Plan-of-SQLs')">
|
| 140 |
Plan-of-SQLs
|
| 141 |
</div>
|
| 142 |
-
<div class="method-button
|
| 143 |
-
|
| 144 |
</div>
|
| 145 |
-
<div class="method-button
|
| 146 |
-
|
| 147 |
</div>
|
| 148 |
</div>
|
| 149 |
|
|
|
|
| 43 |
.method-buttons {
|
| 44 |
display: flex;
|
| 45 |
flex-wrap: wrap;
|
| 46 |
+
justify-content: center;
|
| 47 |
margin-bottom: 20px;
|
| 48 |
gap: 20px;
|
| 49 |
}
|
| 50 |
.method-button {
|
| 51 |
+
width: calc(45% - 10px);
|
| 52 |
padding: 15px;
|
| 53 |
font-size: 20px;
|
| 54 |
border-radius: 10px;
|
|
|
|
| 66 |
background-color: #ffcc80;
|
| 67 |
color: #e65100;
|
| 68 |
}
|
| 69 |
+
.method-button.dater {
|
| 70 |
background-color: #e8f5e9;
|
| 71 |
color: #4caf50;
|
| 72 |
}
|
| 73 |
+
.method-button.no-xai {
|
| 74 |
background-color: #fff3e0;
|
| 75 |
color: #ff9800;
|
| 76 |
}
|
|
|
|
| 139 |
<div class="method-button pos" onclick="selectMethod('Plan-of-SQLs')">
|
| 140 |
Plan-of-SQLs
|
| 141 |
</div>
|
| 142 |
+
<div class="method-button dater" onclick="selectMethod('Dater')">
|
| 143 |
+
Dater
|
| 144 |
</div>
|
| 145 |
+
<div class="method-button no-xai" onclick="selectMethod('No-XAI')">
|
| 146 |
+
No-XAI
|
| 147 |
</div>
|
| 148 |
</div>
|
| 149 |
|