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utils/auth.py

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+import pandas as pd
+import bcrypt
+import os
+
+USERS_CSV = "users.csv"
+
+def initialize_user_csv():
+    if not os.path.exists(USERS_CSV):
+        df = pd.DataFrame(columns=['username', 'password_hash', 'avatar_url'])
+        df.to_csv(USERS_CSV, index=False)
+
+def register_user(username, password, avatar_url=None):
+    initialize_user_csv()
+    df = pd.read_csv(USERS_CSV)
+    if username in df['username'].values:
+        return False, "Username already exists"
+    hashed = bcrypt.hashpw(password.encode(), bcrypt.gensalt())
+    new_user = pd.DataFrame([[username, hashed.decode(), avatar_url or "https://api.dicebear.com/7.x/identicon/svg?seed="+username]], columns=df.columns)
+    df = pd.concat([df, new_user], ignore_index=True)
+    df.to_csv(USERS_CSV, index=False)
+    return True, "Registration successful!"
+
+def authenticate_user(username, password):
+    initialize_user_csv()
+    df = pd.read_csv(USERS_CSV)
+    row = df[df['username'] == username]
+    if row.empty:
+        return False
+    stored = row['password_hash'].iloc[0].encode()
+    return bcrypt.checkpw(password.encode(), stored)
+
+def get_avatar(username):
+    df = pd.read_csv(USERS_CSV)
+    row = df[df['username'] == username]
+    if not row.empty:
+        return row['avatar_url'].iloc[0]
+    return "https://api.dicebear.com/7.x/identicon/svg?seed="+username

utils/feedback.py

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+import os
+import csv
+from datetime import datetime
+
+FEEDBACK = "feedback.csv"
+
+def initialize_feedback():
+    if not os.path.exists(FEEDBACK):
+        with open(FEEDBACK, "w", newline='', encoding="utf-8") as f:
+            writer = csv.writer(f)
+            writer.writerow(["username", "feedback", "timestamp"])
+
+def save_feedback(username, feedback):
+    initialize_feedback()
+    with open(FEEDBACK, "a", newline='', encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow([username, feedback, datetime.now().isoformat()])

utils/leaderboard.py

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+import pandas as pd
+import os
+
+LEADERBOARD = "leaderboard.csv"
+
+def get_leaderboard():
+    if not os.path.exists(LEADERBOARD):
+        return pd.DataFrame(columns=["username", "participation_count"])
+    df = pd.read_csv(LEADERBOARD)
+    df = df.sort_values(by="participation_count", ascending=False)
+    return df

utils/llm_score.py

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+import requests
+
+def llama_score_sentence(user_sentence, correct_answer, api_url="http://localhost:8000/completion"):
+    prompt = (
+        f"Task: Score the learner's answer for a fill-in-the-blank question.\n"
+        f"Question: What is the correct answer? {correct_answer}\n"
+        f"User's answer: {user_sentence}\n"
+        f"Is the answer correct? (yes/no). If not, briefly explain why."
+    )
+    resp = requests.post(
+        api_url,
+        json={"prompt": prompt, "n_predict": 32, "temperature": 0.2, "stream": False}
+    )
+    try:
+        return resp.json().get('content', resp.text)
+    except Exception:
+        return resp.text

utils/localization.py

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+import json
+import os
+
+ASSETS_DIR = os.path.join(os.path.dirname(__file__), '..', 'assets')
+PROMPTS_FILE = os.path.join(ASSETS_DIR, 'prompts.json')
+
+def get_prompts(language):
+    with open(PROMPTS_FILE, "r", encoding="utf-8") as f:
+        all_prompts = json.load(f)
+    return all_prompts.get(language, all_prompts['en'])

utils/storage.py

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+import pandas as pd
+import os
+import csv
+from datetime import datetime
+
+RESPONSES = "responses.csv"
+LEADERBOARD = "leaderboard.csv"
+
+def initialize_csvs():
+    if not os.path.exists(RESPONSES):
+        with open(RESPONSES, "w", newline='', encoding="utf-8") as f:
+            writer = csv.writer(f)
+            writer.writerow([
+                "username", "language", "game_type", "prompt", "response", "correct",
+                "transcript", "audio_file", "latitude", "longitude", "timestamp"
+            ])
+    if not os.path.exists(LEADERBOARD):
+        with open(LEADERBOARD, "w", newline='', encoding="utf-8") as f:
+            writer = csv.writer(f)
+            writer.writerow(["username", "participation_count"])
+
+def save_response(username, language, game_type, prompt, response, correct, transcript, audio_file, lat, lon):
+    initialize_csvs()
+    with open(RESPONSES, "a", newline='', encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow([
+            username, language, game_type, prompt, response, correct,
+            transcript, audio_file, lat, lon, datetime.now().isoformat()
+        ])
+
+def update_leaderboard(username):
+    initialize_csvs()
+    df = pd.read_csv(LEADERBOARD)
+    if username in df['username'].values:
+        df.loc[df['username'] == username, 'participation_count'] += 1
+    else:
+        df.loc[len(df)] = [username, 1]
+    df.to_csv(LEADERBOARD, index=False)
+
+def get_user_data(username):
+    initialize_csvs()
+    df = pd.read_csv(RESPONSES)
+    return df[df['username'] == username]

utils/voice_to_text.py

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+import speech_recognition as sr
+from pydub import AudioSegment
+import io
+
+def transcribe_audio(audio_bytes, out_wav_path):
+    # audio_bytes is bytes
+    audio = AudioSegment.from_file(io.BytesIO(audio_bytes))
+    audio.export(out_wav_path, format="wav")
+    r = sr.Recognizer()
+    with sr.AudioFile(out_wav_path) as source:
+        audio_data = r.record(source)
+    try:
+        text = r.recognize_google(audio_data, language="en-IN")
+        return text
+    except Exception:
+        return ""