app.py

import os
import gradio as gr
import requests

# Get API keys from Secrets
spoonacular_api_key = os.getenv('SPOONACULAR_API_KEY')  # Spoonacular API key
hf_api_key = os.getenv('HF_API_KEY')  # Hugging Face API key

# Translation function using Hugging Face
def translate_text_hf(text):
    url = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-et-en"
    headers = {"Authorization": f"Bearer {hf_api_key}"}
    payload = {"inputs": text}
    response = requests.post(url, headers=headers, json=payload)
    if response.status_code == 200:
        translation = response.json()[0]['translation_text']
        print("Translated ingredients:", translation)  # Debug: Print translation
        return translation
    else:
        print("Translation failed with status:", response.status_code)  # Debug: Print failure
        return "Translation failed!"

# Recipe search function using Spoonacular API
def get_recipes(ingredients, max_calories=None, min_protein=None, max_fat=None, max_carbs=None):
    # Translate ingredients to English
    translated_ingredients = translate_text_hf(ingredients)
    url = "https://api.spoonacular.com/recipes/complexSearch"
    
    # Base parameters for the API request
    params = {
        "query": translated_ingredients,
        "apiKey": spoonacular_api_key,
        "number": 5  # Return up to 5 recipes
    }
    
    # Add optional parameters only if they are provided and not zero
    if max_calories and max_calories > 0:
        params["maxCalories"] = max_calories
    if min_protein and min_protein > 0:
        params["minProtein"] = min_protein
    if max_fat and max_fat > 0:
        params["maxFat"] = max_fat
    if max_carbs and max_carbs > 0:
        params["maxCarbs"] = max_carbs

    # Send the API request
    response = requests.get(url, params=params)

    # Check if the request was successful
    if response.status_code == 200:
        recipes = response.json().get('results', [])
        if recipes:
            # Format and return the list of recipes as HTML links
            html_links = "<br>".join(
                [f'<a href="https://spoonacular.com/recipes/{recipe["title"].replace(" ", "-").lower()}-{recipe["id"]}" target="_blank">{recipe["title"]}</a>'
                 for recipe in recipes]
            )
            # Debug: Print each generated URL for the recipes
            for recipe in recipes:
                print(f"Generated URL: https://spoonacular.com/recipes/{recipe['title'].replace(' ', '-').lower()}-{recipe['id']}")
            return html_links
        else:
            return "No suitable recipes found."
    else:
        return f"Error fetching recipes: {response.status_code}"

# Gradio Interface
def recipe_app(ingredients, max_calories, min_protein, max_fat, max_carbs):
    return get_recipes(ingredients, max_calories, min_protein, max_fat, max_carbs)

# Create Gradio interface
interface = gr.Interface(
    fn=recipe_app,
    inputs=[
        gr.Textbox(label="Sisesta koostisained"),
        gr.Number(label="Maksimaalne kalorikogus (valikuline)"),
        gr.Number(label="Minimaalne valk (g, valikuline)"),
        gr.Number(label="Maksimaalne rasvasisaldus (g, valikuline)"),
        gr.Number(label="Maksimaalne süsivesikute sisaldus (g, valikuline)"),
    ],
    outputs=gr.HTML(label="Recipes"),  # Ensure output is HTML
    title="Retseptiotsija",
    description="Sisestage koostisosad eesti keeles ja määrake sobivate retseptide leidmiseks valikulised kalorite, valkude, rasvade ja süsivesikute piirangud."
)

interface.launch()