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Update app.py
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app.py
CHANGED
@@ -7,17 +7,17 @@ import whisper
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import asyncio
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import platform
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#
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whisper_model = whisper.load_model("tiny")
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#
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lang_map = {
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"English": "en", "Hindi": "hi", "Telugu": "te", "Spanish": "es",
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"Tamil": "ta", "Gujarati": "gu", "Kannada": "kn", "Bengali": "bn",
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"Marathi": "mr", "Punjabi": "pa", "Urdu": "ur"
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}
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#
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local_foods = {
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"vegetables": [
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{"name": "carrot", "calories": 41, "iron": 0.3, "fiber": 2.8, "vitamin_c": 6},
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@@ -36,7 +36,7 @@ local_foods = {
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]
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}
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#
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def precompute_foods():
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return {
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"grain": random.choice(local_foods['grains']),
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@@ -45,7 +45,7 @@ def precompute_foods():
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"protein": random.choice(local_foods['proteins'])
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}
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#
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def get_output_template(lang):
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templates = {
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"English": """
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@@ -69,278 +69,45 @@ def get_output_template(lang):
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{dinner}
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📊 Summary: Balanced meals with local ingredients.
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""",
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"Hindi": """
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🌾 व्यक्तिगत आहार योजना
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────────────────────────────
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👤 आयु: {age}, लिंग: {gender}
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💼 पेशा: {occupation}
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🏃 गतिविधि स्तर: {activity_level}
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⚕️ स्वास्थ्य स्थितियाँ: {health_conditions}
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🍽️ वरीयताएँ: {dietary_preferences}
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⚠️ एलर्जी: {allergies}
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💰 बजट: ₹{budget}/दिन
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🥣 नाश्ता:
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{breakfast}
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🍛 दोपहर का भोजन:
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{lunch}
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🥗 रात का खाना:
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{dinner}
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📊 सारांश: स्थानीय खाद्य पदार्थों के साथ संतुलित भोजन।
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""",
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"Telugu": """
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🌾 వ్యక్తిగత ఆహార ప్రణాళిక
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────────────────────────────
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👤 వయస్సు: {age}, లింగం: {gender}
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💼 వృత్తి: {occupation}
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🏃 చర్య స్థాయి: {activity_level}
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⚕️ ఆరోగ్య పరిస్థితులు: {health_conditions}
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🍽️ అభిరుచులు: {dietary_preferences}
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⚠️ అలర్జీలు: {allergies}
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💰 బడ్జెట్: ₹{budget}/రోజు
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🥣 అల్పాహారం:
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{breakfast}
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🍛 మధ్యాహ్న భోజనం:
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{lunch}
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🥗 రాత్రి భోజనం:
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{dinner}
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📊 సారాంశం: స్థానిక పదార్థాలతో సంతులిత ఆహారం.
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""",
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"Spanish": """
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🌾 Plan de dieta personalizado
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────────────────────────────
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👤 Edad: {age}, Género: {gender}
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💼 Ocupación: {occupation}
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🏃 Nivel de actividad: {activity_level}
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⚕️ Condiciones de salud: {health_conditions}
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🍽️ Preferencias: {dietary_preferences}
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⚠️ Alergias: {allergies}
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💰 Presupuesto: ₹{budget}/día
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🥣 Desayuno:
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{breakfast}
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🍛 Almuerzo:
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{lunch}
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🥗 Cena:
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{dinner}
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📊 Resumen: Comidas equilibradas con ingredientes locales.
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""",
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"Tamil": """
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🌾 தனிப்பட்ட உணவுக் குறிப்பு
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────────────────────────────
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👤 வயது: {age}, பாலினம்: {gender}
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💼 தொழில்: {occupation}
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🏃 செயல்திறன் அளவு: {activity_level}
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⚕️ உடல்நிலை: {health_conditions}
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🍽️ விருப்பங்கள்: {dietary_preferences}
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⚠️ ஒவ்வாமைகள்: {allergies}
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💰 தினசரி செலவு: ₹{budget}/நாள்
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🥣 காலை உணவு:
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{breakfast}
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🍛 மதிய உணவு:
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{lunch}
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🥗 இரவு உணவு:
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{dinner}
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📊 சுருக்கம்: உள்ளூர் பொருட்களுடன் சமநிலையுடைய உணவு.
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""",
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"Gujarati": """
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🌾 વ્યક્તિગત આહાર યોજના
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────────────────────────────
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👤 ઉંમર: {age}, લિંગ: {gender}
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💼 વ્યવસાય: {occupation}
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🏃 પ્રવૃત્તિ સ્તર: {activity_level}
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⚕️ આરોગ્ય સ્થિતિઓ: {health_conditions}
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🍽️ પસંદગીઓ: {dietary_preferences}
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⚠️ એલર્જી: {allergies}
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💰 બજેટ: ₹{budget}/દિવસ
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🥣 નાસ્તો:
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{breakfast}
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🍛 બપોરનું ભોજન:
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{lunch}
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🥗 રાત્રિ ભોજન:
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{dinner}
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📊 સારાંશ: સ્થાનિક ઘટકો સાથે સંતુલિત ભોજન.
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""",
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"Kannada": """
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🌾 ವೈಯಕ್ತಿಕ ಆಹಾರ ಯೋಜನೆ
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────────────────────────────
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👤 ವಯಸ್ಸು: {age}, ಲಿಂಗ: {gender}
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💼 ಉದ್ಯೋಗ: {occupation}
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🏃 ಚಟುವಟಿಕೆ ಮಟ್ಟ: {activity_level}
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⚕️ ಆರೋಗ್ಯ ಸ್ಥಿತಿಗಳು: {health_conditions}
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🍽️ ಆಯ್ಕೆಗಳು: {dietary_preferences}
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⚠️ ಅಲರ್ಜಿ: {allergies}
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💰 ದಿನವೂ ಖರ್ಚು: ₹{budget}/ದಿನ
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🥣 ಉಪಾಹಾರ:
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{breakfast}
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🍛 ಮಧ್ಯಾಹ್ನ ಭೋಜನ:
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{lunch}
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🥗 ರಾತ್ರಿಯ ಭೋಜನ:
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{dinner}
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📊 ಸಾರಾಂಶ: ಸ್ಥಳೀಯ ಪದಾರ್ಥಗಳಿಂದ ಸಮತೋಲಿತ ಆಹಾರ.
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""",
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"Bengali": """
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🌾 ব্যক্তিগত ডায়েট প্ল্যান
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────────────────────────────
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👤 বয়স: {age}, লিঙ্গ: {gender}
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💼 পেশা: {occupation}
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🏃 কার্যকলাপ স্তর: {activity_level}
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⚕️ স্বাস্থ্য অবস্থা: {health_conditions}
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🍽️ পছন্দ: {dietary_preferences}
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⚠️ অ্যালার্জি: {allergies}
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💰 বাজেট: ₹{budget}/দিন
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🥣 প্রাতঃরাশ:
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{breakfast}
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🍛 মধ্যাহ্নভোজ:
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{lunch}
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🥗 রাতের খাবার:
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{dinner}
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📊 সারাংশ: স্থানীয় উপাদানসহ সুষম আহার।
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""",
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"Marathi": """
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🌾 वैयक्तिक आहार योजना
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────────────────────────────
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👤 वय: {age}, लिंग: {gender}
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💼 व्यवसाय: {occupation}
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🏃 क्रियाशीलतेचा स्तर: {activity_level}
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⚕️ आरोग्य स्थिती: {health_conditions}
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🍽️ प्राधान्ये: {dietary_preferences}
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⚠️ अॅलर्जी: {allergies}
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💰 बजेट: ₹{budget}/दिवस
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🥣 न्याहारी:
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{breakfast}
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🍛 दुपारचे जेवण:
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{lunch}
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🥗 रात्रीचे जेवण:
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{dinner}
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📊 सारांश: स्थानिक घटकांसह संतुलित आहार.
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""",
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"Punjabi": """
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🌾 ਨਿੱਜੀ ਖੁਰਾਕ ਯੋਜਨਾ
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────────────────────────────
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👤 ਉਮਰ: {age}, ਲਿੰਗ: {gender}
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💼 ਪੇਸ਼ਾ: {occupation}
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🏃 ਗਤੀਵਿਧੀ ਪੱਧਰ: {activity_level}
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⚕️ ਸਿਹਤ ਦੀ ਹਾਲਤ: {health_conditions}
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🍽️ ਪਸੰਦਾਂ: {dietary_preferences}
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⚠️ ਐਲਰਜੀ: {allergies}
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💰 ਰੋਜ਼ਾਨਾ ਬਜਟ: ₹{budget}/ਦਿਨ
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🥣 ਨਾਸ਼ਤਾ:
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{breakfast}
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🍛 ਦੁਪਿਹਰ ਦਾ ਭੋਜਨ:
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{lunch}
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🥗 ਰਾਤ ਦਾ ਭੋਜਨ:
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{dinner}
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📊 ਸੰਖੇਪ: ਸਥਾਨਕ ਸਮੱਗਰੀ ਨਾਲ ਸੰਤੁਲਿਤ ਭੋਜਨ।
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""",
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"Urdu": """
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🌾 ذاتی غذا کا منصوبہ
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────────────────────────────
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👤 عمر: {age}, جنس: {gender}
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💼 پیشہ: {occupation}
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🏃 سرگرمی کی سطح: {activity_level}
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⚕️ صحت کی حالتیں: {health_conditions}
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🍽️ ترجیحات: {dietary_preferences}
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⚠️ الرجی: {allergies}
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💰 یومیہ بجٹ: ₹{budget}/دن
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🥣 ناشتہ:
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{breakfast}
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🍛 دوپہر کا کھانا:
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{lunch}
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🥗 رات کا کھانا:
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{dinner}
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📊 خلاصہ: مقامی اجزاء کے ساتھ متوازن غذا۔
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"""
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}
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return templates.get(lang, templates["English"])
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#
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async def transcribe_audio(audio_path, lang):
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try:
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if not audio_path or not os.path.exists(audio_path):
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return "
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temp_wav = f"temp_{uuid.uuid4().hex}.wav"
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audio = AudioSegment.from_file(audio_path)
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audio = audio.set_frame_rate(16000).set_channels(1)
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audio.export(temp_wav, format="wav")
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result = whisper_model.transcribe(temp_wav, language=lang_map.get(lang, "en"), fp16=False)
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os.remove(temp_wav)
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return result.get("text", "❌ Could not understand the speech.").strip()
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except Exception as e:
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return f"❌ Error: {str(e)}"
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#
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async def full_pipeline(health_audio, diet_audio, allergy_audio, health_text, diet_text, allergy_text,
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health_conditions = health_text or await transcribe_audio(health_audio, lang)
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dietary_preferences = diet_text or await transcribe_audio(diet_audio, lang)
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allergies = allergy_text or await transcribe_audio(allergy_audio, lang)
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def generate_diet(age, gender, weight, height, occupation, activity_level, health_conditions, dietary_preferences, allergies, budget, lang):
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# Use precomputed foods
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foods = precompute_foods()
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grain, veg1, veg2, protein = foods['grain'], foods['veg1'], foods['veg2'], foods['protein']
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# Build meals
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breakfast = f"{grain['name']} porridge with {veg1['name']}"
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lunch = f"{protein['name']} with {grain['name']} and {veg2['name']}"
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dinner = f"{veg1['name']} curry, {veg2['name']} salad, and {protein['name']}"
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# Nutritional Totals (optimized)
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nutrients = ["calories", "iron", "fiber", "protein", "vitamin_c"]
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nutrition = {
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veg1.get(nutrient, 0) +
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veg2.get(nutrient, 0) * 2 +
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protein.get(nutrient, 0) * 2, 1
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) for nutrient in nutrients}
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# Plan Output
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plan = get_output_template(lang).format(
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age=age, gender=gender, occupation=occupation, activity_level=activity_level,
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health_conditions=health_conditions or "None",
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allergies=allergies or "None", budget=budget,
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breakfast=breakfast, lunch=lunch, dinner=dinner
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)
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nutrition_summary = f"""
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🍽️ Nutritional Summary:
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------------------------------
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"""
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return plan + nutrition_summary
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#
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def render_ui(default_lang="English"):
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with gr.Blocks(
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lang_sel = gr.Dropdown(label="Language", choices=list(lang_map.keys()), value=default_lang)
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age = gr.Number(label="Age", value=30, minimum=1)
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gender = gr.Radio(["Male", "Female", "Other"], label="Gender")
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@@ -386,19 +152,15 @@ def render_ui(default_lang="English"):
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gr.Button("🎯 Generate Plan").click(
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full_pipeline,
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inputs=[health_audio, diet_audio, allergy_audio, health_text, diet_text, allergy_text,
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-
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-
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)
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-
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return demo
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async def main():
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demo = render_ui()
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await demo.launch()
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if
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asyncio.
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else:
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if __name__ == "__main__":
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asyncio.run(main())
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import asyncio
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import platform
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+
# Load Whisper model
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whisper_model = whisper.load_model("tiny")
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# Supported languages
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lang_map = {
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"English": "en", "Hindi": "hi", "Telugu": "te", "Spanish": "es",
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"Tamil": "ta", "Gujarati": "gu", "Kannada": "kn", "Bengali": "bn",
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"Marathi": "mr", "Punjabi": "pa", "Urdu": "ur"
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}
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# Local food database
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local_foods = {
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"vegetables": [
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{"name": "carrot", "calories": 41, "iron": 0.3, "fiber": 2.8, "vitamin_c": 6},
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]
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}
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# Select random foods
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def precompute_foods():
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return {
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"grain": random.choice(local_foods['grains']),
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"protein": random.choice(local_foods['proteins'])
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}
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+
# Output templates (shortened for brevity here, use your full dictionary)
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def get_output_template(lang):
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templates = {
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"English": """
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{dinner}
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📊 Summary: Balanced meals with local ingredients.
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|
72 |
"""
|
73 |
}
|
74 |
return templates.get(lang, templates["English"])
|
75 |
|
76 |
+
# Transcription
|
77 |
async def transcribe_audio(audio_path, lang):
|
78 |
try:
|
79 |
if not audio_path or not os.path.exists(audio_path):
|
80 |
+
return ""
|
|
|
81 |
temp_wav = f"temp_{uuid.uuid4().hex}.wav"
|
82 |
audio = AudioSegment.from_file(audio_path)
|
83 |
audio = audio.set_frame_rate(16000).set_channels(1)
|
84 |
audio.export(temp_wav, format="wav")
|
|
|
85 |
result = whisper_model.transcribe(temp_wav, language=lang_map.get(lang, "en"), fp16=False)
|
86 |
os.remove(temp_wav)
|
87 |
+
return result.get("text", "").strip()
|
|
|
88 |
except Exception as e:
|
89 |
return f"❌ Error: {str(e)}"
|
90 |
|
91 |
+
# Full pipeline
|
92 |
+
async def full_pipeline(health_audio, diet_audio, allergy_audio, health_text, diet_text, allergy_text,
|
93 |
+
age, gender, weight, height, occupation, activity, budget, lang):
|
94 |
health_conditions = health_text or await transcribe_audio(health_audio, lang)
|
95 |
dietary_preferences = diet_text or await transcribe_audio(diet_audio, lang)
|
96 |
allergies = allergy_text or await transcribe_audio(allergy_audio, lang)
|
97 |
+
return generate_diet(age, gender, weight, height, occupation, activity,
|
98 |
+
health_conditions, dietary_preferences, allergies, budget, lang)
|
99 |
|
100 |
+
# Diet generator
|
101 |
+
def generate_diet(age, gender, weight, height, occupation, activity_level,
|
102 |
+
health_conditions, dietary_preferences, allergies, budget, lang):
|
|
|
|
|
103 |
foods = precompute_foods()
|
104 |
grain, veg1, veg2, protein = foods['grain'], foods['veg1'], foods['veg2'], foods['protein']
|
|
|
|
|
105 |
breakfast = f"{grain['name']} porridge with {veg1['name']}"
|
106 |
lunch = f"{protein['name']} with {grain['name']} and {veg2['name']}"
|
107 |
dinner = f"{veg1['name']} curry, {veg2['name']} salad, and {protein['name']}"
|
|
|
|
|
108 |
nutrients = ["calories", "iron", "fiber", "protein", "vitamin_c"]
|
109 |
+
nutrition = {n: round(grain.get(n, 0) * 2 + veg1.get(n, 0) + veg2.get(n, 0) * 2 + protein.get(n, 0) * 2, 1)
|
110 |
+
for n in nutrients}
|
|
|
|
|
|
|
|
|
|
|
|
|
111 |
plan = get_output_template(lang).format(
|
112 |
age=age, gender=gender, occupation=occupation, activity_level=activity_level,
|
113 |
health_conditions=health_conditions or "None",
|
|
|
115 |
allergies=allergies or "None", budget=budget,
|
116 |
breakfast=breakfast, lunch=lunch, dinner=dinner
|
117 |
)
|
|
|
118 |
nutrition_summary = f"""
|
119 |
🍽️ Nutritional Summary:
|
120 |
------------------------------
|
|
|
126 |
"""
|
127 |
return plan + nutrition_summary
|
128 |
|
129 |
+
# UI
|
130 |
def render_ui(default_lang="English"):
|
131 |
+
with gr.Blocks() as demo:
|
132 |
lang_sel = gr.Dropdown(label="Language", choices=list(lang_map.keys()), value=default_lang)
|
133 |
age = gr.Number(label="Age", value=30, minimum=1)
|
134 |
gender = gr.Radio(["Male", "Female", "Other"], label="Gender")
|
|
|
152 |
|
153 |
gr.Button("🎯 Generate Plan").click(
|
154 |
full_pipeline,
|
155 |
+
inputs=[health_audio, diet_audio, allergy_audio, health_text, diet_text, allergy_text,
|
156 |
+
age, gender, weight, height, occupation, activity, budget, lang_sel],
|
157 |
+
outputs=output
|
158 |
)
|
|
|
159 |
return demo
|
160 |
|
161 |
async def main():
|
162 |
demo = render_ui()
|
163 |
+
await demo.launch(server_name="0.0.0.0", server_port=7860)
|
164 |
|
165 |
+
if __name__ == "__main__":
|
166 |
+
asyncio.run(main())
|
|
|
|
|
|