Update app.py

app.py

@@ -1,60 +1,94 @@
-import os
 import gradio as gr
 import requests
+import json
+import datetime
 
-# Nebius environment variables from Hugging Face secrets
-FOLDER_ID = os.environ.get("FOLDER_ID")
-NEBIUS_API_KEY = os.environ.get("NEBIUS_API_KEY")
+# Load credentials from secrets
+import os
+NEBIUS_API_KEY = os.getenv("NEBIUS_API_KEY")
+FOLDER_ID = os.getenv("FOLDER_ID")
 
-# Function to call Nebius API
-def call_nebius(prompt):
-    url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
-    
+# === Nebius API Function ===
+def ask_nebius(prompt):
     headers = {
         "Authorization": f"Bearer {NEBIUS_API_KEY}",
         "Content-Type": "application/json"
     }
-
-    data = {
+    body = {
         "modelUri": f"gpt://{FOLDER_ID}/yandexgpt/latest",
-        "completionOptions": {
-            "stream": False,
-            "temperature": 0.7,
-            "maxTokens": 500
-        },
-        "messages": [
-            {"role": "system", "text": "You are a smart kitchen agent. Suggest healthy and delicious recipes."},
-            {"role": "user", "text": prompt}
-        ]
+        "completionOptions": {"stream": False, "temperature": 0.5, "maxTokens": 1000},
+        "messages": [{"role": "user", "text": prompt}]
     }
 
-    response = requests.post(url, headers=headers, json=data)
+    res = requests.post("https://llm.api.cloud.yandex.net/foundationModels/v1/completion", headers=headers, json=body)
+    if res.status_code == 200:
+        return res.json()['result']['alternatives'][0]['message']['text']
+    else:
+        return f"Error: {res.status_code} - {res.text}"
+
+# === Recipe Planner Function ===
+def generate_recipe(diet, pantry):
+    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."
+    return ask_nebius(prompt)
+
+# === Weekly Meal Planner Function ===
+def weekly_meal_plan(diet):
+    prompt = f"Generate a full 7-day meal plan (Breakfast, Lunch, Dinner) for a {diet} diet. Include variety and healthy options."
+    return ask_nebius(prompt)
+
+# === PDF Download ===
+def download_text_as_pdf(text):
+    from fpdf import FPDF
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    for line in text.split('\n'):
+        pdf.cell(200, 10, txt=line, ln=True)
+    filename = f"meal_plan_{datetime.datetime.now().strftime('%Y%m%d%H%M%S')}.pdf"
+    pdf.output(filename)
+    return filename
+
+# === Gradio Interface ===
+with gr.Blocks(theme=gr.themes.Base(), title="AgentChef") as demo:
+    gr.Markdown("""
+    ## 🍳 AgentChef: AI Recipe Planner & Smart Kitchen Assistant
     
-    try:
-        result = response.json()
-        return result["result"]["alternatives"][0]["message"]["text"]
-    except Exception as e:
-        return f"❌ Error: {e}\n\nResponse: {response.text}"
-
-# Gradio UI logic
-def generate_recipe(ingredients, preference):
-    if not ingredients:
-        return "⚠️ Please enter some ingredients."
-    prompt = f"Give me a recipe using the following ingredients: {ingredients}. Make it {preference.lower()} and healthy."
-    return call_nebius(prompt)
-
-# UI layout
-with gr.Blocks(theme=gr.themes.Base()) as demo:
-    gr.Markdown("👨‍🍳 **AgentChef: AI Recipe Planner & Smart Kitchen Assistant**")
+    Plan meals, check pantry items, generate weekly diet charts, and download PDFs — all with AI!
+    """)
 
     with gr.Row():
-        ingredients_input = gr.Textbox(label="🛒 Ingredients (comma-separated)", placeholder="e.g. tomato, onion, rice")
-        preference_input = gr.Dropdown(label="🥗 Dietary Preferences", choices=["Vegetarian", "Vegan", "Keto", "No Preference"], value="Vegetarian")
+        diet_input = gr.Dropdown(label="🍽️ Dietary Preferences", choices=["Vegetarian", "Vegan", "Keto", "Paleo", "Regular"], value="Vegetarian")
+        pantry_input = gr.Textbox(label="🌾 Pantry Items (comma-separated)", placeholder="e.g. tomato, rice, beans")
+
+    with gr.Row():
+        mic = gr.Audio(type="filepath", label="🎤 Speak Ingredients (Optional)")
+        transcript_output = gr.Textbox(label="Speech-to-text Result")
+
+    with gr.Row():
+        generate_button = gr.Button("🍽 Generate Recipe")
+        meal_button = gr.Button("🍒 Weekly Meal Plan")
+
+    result = gr.Textbox(label="🌱 Output")
+    pdf_button = gr.Button("📄 Download as PDF")
+    file_output = gr.File(label="Download Link")
+
+    # === Callbacks ===
+    def transcribe_audio(audio_file):
+        import speech_recognition as sr
+        recognizer = sr.Recognizer()
+        with sr.AudioFile(audio_file) as source:
+            audio_data = recognizer.record(source)
+            return recognizer.recognize_google(audio_data)
+
+    mic.change(transcribe_audio, inputs=mic, outputs=transcript_output)
 
-    submit_btn = gr.Button("🍽️ Generate Recipe")
-    output = gr.Textbox(label="📋 Recipe Result", lines=10)
+    def handle_generate(diet, pantry, spoken):
+        pantry_all = (spoken or '') + ", " + (pantry or '')
+        return generate_recipe(diet, pantry_all)
 
-    submit_btn.click(generate_recipe, inputs=[ingredients_input, preference_input], outputs=output)
+    generate_button.click(handle_generate, inputs=[diet_input, pantry_input, transcript_output], outputs=result)
+    meal_button.click(weekly_meal_plan, inputs=diet_input, outputs=result)
+    pdf_button.click(download_text_as_pdf, inputs=result, outputs=file_output)
 
-# Launch
+# === Launch ===
 demo.launch()