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Update app.py
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app.py
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import gradio as gr
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import requests
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import json
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import datetime
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headers = {
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"Authorization": f"Bearer {NEBIUS_API_KEY.strip()}",
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"Content-Type": "application/json"
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}
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body = {
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"folderId": FOLDER_ID,
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"texts": [input_text],
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"temperature": 0.6,
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"maxTokens": "2000"
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}
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res = requests.post("https://llm.api.cloud.yandex.net/foundationModels/v1/completion", headers=headers, json=body)
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if res.status_code == 200:
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return res.json()['result']['alternatives'][0]['message']['text']
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else:
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return f"Error: {res.status_code} - {res.text}"
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# === Recipe Planner Function ===
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def generate_recipe(diet, pantry):
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prompt = f"You are a smart kitchen assistant. Suggest a detailed recipe for a {diet} user with ingredients from the pantry: {pantry}. Include cooking steps and nutritional info."
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return ask_nebius(prompt)
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# === Weekly Meal Planner Function ===
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def weekly_meal_plan(diet):
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prompt = f"Generate a full 7-day meal plan (Breakfast, Lunch, Dinner) for a {diet} diet. Include variety and healthy options."
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return ask_nebius(prompt)
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# === PDF Download ===
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def download_text_as_pdf(text):
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from fpdf import FPDF
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pdf = FPDF()
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pdf.add_page()
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pdf.set_font("Arial", size=12)
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for line in text.split('\n'):
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pdf.cell(200, 10, txt=line, ln=True)
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filename = f"meal_plan_{datetime.datetime.now().strftime('%Y%m%d%H%M%S')}.pdf"
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pdf.output(filename)
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return filename
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pantry_input = gr.Textbox(label="🌾 Pantry Items (comma-separated)", placeholder="e.g. tomato, rice, beans")
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with gr.Row():
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mic = gr.Audio(type="filepath", label="🎤 Speak Ingredients (Optional)")
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transcript_output = gr.Textbox(label="Speech-to-text Result")
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with gr.Row():
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import speech_recognition as sr
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recognizer = sr.Recognizer()
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with sr.AudioFile(audio_file) as source:
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audio_data = recognizer.record(source)
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return recognizer.recognize_google(audio_data)
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pantry_all = (spoken or '') + ", " + (pantry or '')
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return generate_recipe(diet, pantry_all)
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meal_button.click(weekly_meal_plan, inputs=diet_input, outputs=result)
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pdf_button.click(download_text_as_pdf, inputs=result, outputs=file_output)
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# === Launch ===
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demo.launch()
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import gradio as gr
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import requests
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NEBIUS_API_KEY = "your_nebius_api_key"
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FOLDER_ID = "your_folder_id"
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def generate_recipe(dietary_pref, ingredients):
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input_text = f"Create a recipe using these ingredients: {ingredients}. It should be {dietary_pref}."
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headers = {
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"Authorization": f"Api-Key {NEBIUS_API_KEY}",
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"Content-Type": "application/json"
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}
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body = {
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"folderId": FOLDER_ID,
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"texts": [input_text],
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"temperature": 0.6,
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"maxTokens": "2000"
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}
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try:
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response = requests.post(
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"https://llm.api.cloud.yandex.net/foundationModels/v1/textCompletion",
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headers=headers,
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json=body
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)
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result = response.json()
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return result["result"]["alternatives"][0]["text"]
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except Exception as e:
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return f"❌ Error: {e}"
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("🍳 **AgentChef: AI Recipe Planner & Smart Kitchen Assistant**")
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with gr.Row():
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dietary = gr.Dropdown(
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label="Dietary Preferences",
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choices=["Vegetarian", "Non-Vegetarian", "Vegan", "Keto", "Other"],
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value="Vegetarian"
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)
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ingredients = gr.Textbox(
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label="Ingredients Available",
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placeholder="e.g., tomato, onion, garlic, paneer..."
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)
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submit = gr.Button("🍽️ Generate Recipe")
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recipe_output = gr.Textbox(label="AI-Generated Recipe", lines=10)
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submit.click(fn=generate_recipe, inputs=[dietary, ingredients], outputs=recipe_output)
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demo.launch()
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