added app.py and requirements.txt
Browse files- app.py +76 -0
- requirements.txt +2 -0
app.py
ADDED
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import os
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import json
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import threading
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import gradio as gr
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import statistics
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from scipy import stats
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DATA_DIR = './storage'
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DATA_FILE = os.path.join(DATA_DIR, 'guesses.json')
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lock = threading.Lock()
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def ensure_data_directory():
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os.makedirs(DATA_DIR, exist_ok=True)
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def load_guesses():
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ensure_data_directory()
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if not os.path.exists(DATA_FILE):
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with open(DATA_FILE, 'w') as f:
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json.dump([], f)
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with open(DATA_FILE, 'r') as f:
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return json.load(f)
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def save_guesses(guesses):
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with open(DATA_FILE, 'w') as f:
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json.dump(guesses, f)
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def add_guess(guess):
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with lock:
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guesses = load_guesses()
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guesses.append(guess)
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save_guesses(guesses)
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n = len(guesses)
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average = sum(guesses) / n
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if n >= 2:
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# Calculate sample standard deviation
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s = statistics.stdev(guesses)
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# Calculate standard error
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SE = s / (n ** 0.5)
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# Degrees of freedom
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df = n - 1
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# Confidence level (e.g., 95%)
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confidence_level = 0.95
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alpha = 1 - confidence_level
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# Calculate critical t-value
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t_value = stats.t.ppf(1 - alpha/2, df)
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# Calculate margin of error
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ME = t_value * SE
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# Calculate confidence interval
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ci_lower = average - ME
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ci_upper = average + ME
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# Prepare output message
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return (
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f"Your guess has been recorded.\n"
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f"Current average of all guesses: {average:.2f}\n"
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f"95% confidence interval: ({ci_lower:.2f}, {ci_upper:.2f})"
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)
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else:
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# Not enough data to compute confidence interval
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return (
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f"Your guess has been recorded.\n"
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f"Current average of all guesses: {average:.2f}\n"
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f"Not enough data to compute confidence interval."
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)
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demo = gr.Interface(
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fn=add_guess,
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inputs=gr.Number(label="Enter your guess"),
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outputs="text",
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title="Collective Guessing Game",
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description="Submit your guess and contribute to the global average!"
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)
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demo.launch()
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requirements.txt
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gradio==5.4.0
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scipy==1.14.1
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