app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI



# Below is an example of a tool that does nothing. Amaze us with your creativity !

@tool
def get_movie_recommendation(mood: str, location: str) -> str:
    """A tool that recommends movies based on user's mood and local weather conditions.
    Args:
        mood: The user's current mood (e.g., 'happy', 'sad', 'excited', 'relaxed', 'nostalgic')
        location: The user's location to check weather (e.g., 'London', 'New York')
    """
    # Using a class to maintain state of previously recommended movies
    if not hasattr(get_movie_recommendation, '_previous_recommendations'):
        get_movie_recommendation._previous_recommendations = set()
    
    try:
        # Get weather data using wttr.in (free weather API)
        weather_url = f"https://wttr.in/{location}?format=%C"
        weather_response = requests.get(weather_url)
        if weather_response.status_code != 200:
            return f"Error: Could not fetch weather for {location}"
        
        weather_condition = weather_response.text.strip().lower()

        # Define mood and weather based movie genre mappings
        mood_genres = {
            "happy": ["Comedy", "Musical", "Adventure"],
            "sad": ["Drama", "Romance", "Independent"],
            "excited": ["Action", "Thriller", "Sci-Fi"],
            "relaxed": ["Documentary", "Animation", "Family"],
            "nostalgic": ["Classic", "Drama", "Romance"]
        }

        weather_genres = {
            "clear": ["Adventure", "Comedy", "Action"],
            "rain": ["Drama", "Noir", "Mystery"],
            "clouds": ["Sci-Fi", "Fantasy", "Mystery"],
            "snow": ["Romance", "Family", "Fantasy"],
            "thunderstorm": ["Horror", "Thriller", "Mystery"]
        }

        # Get recommended genres based on mood and weather
        selected_genres = mood_genres.get(mood.lower(), ["Drama"])
        for weather_key in weather_genres:
            if weather_key in weather_condition:
                selected_genres.extend(weather_genres[weather_key])
                break

        # Use OMDB API to fetch movie recommendations
        omdb_api_key = "59341a1e"  # Free tier API key
        primary_genre = selected_genres[0]
        
        # Add page parameter for pagination (1-100)
        import random
        page = random.randint(1, 10)  # Randomly select a page
        movie_url = f"http://www.omdbapi.com/?apikey={omdb_api_key}&s={primary_genre}&type=movie&page={page}"
        
        movie_response = requests.get(movie_url)
        if movie_response.status_code != 200:
            return f"Error: Could not fetch movie recommendation"

        movie_data = movie_response.json()
        if movie_data.get("Response") == "False":
            return f"No movies found for your current mood and weather"

        # Get all movies from the search result
        movies = movie_data.get("Search", [])
        if not movies:
            return f"No movies available for the current criteria"

        # Filter out previously recommended movies
        new_movies = [movie for movie in movies 
                     if movie['imdbID'] not in get_movie_recommendation._previous_recommendations]

        # If all movies on this page have been recommended, clear history and use all movies
        if not new_movies:
            get_movie_recommendation._previous_recommendations.clear()
            new_movies = movies

        # Randomly select a movie from the available ones
        selected_movie = random.choice(new_movies)
        
        # Add the selected movie to previous recommendations
        get_movie_recommendation._previous_recommendations.add(selected_movie['imdbID'])

        # Get detailed information for the selected movie
        detail_url = f"http://www.omdbapi.com/?apikey={omdb_api_key}&i={selected_movie['imdbID']}"
        detail_response = requests.get(detail_url)
        movie_details = detail_response.json()

        # Format the recommendation response
        recommendation = (
            f"Based on your mood ({mood}) and the weather in {location} ({weather_condition}), "
            f"I recommend watching:\n\n"
            f"Title: {movie_details['Title']}\n"
            f"Year: {movie_details['Year']}\n"
            f"Genre: {movie_details['Genre']}\n"
            f"Plot: {movie_details['Plot']}\n"
            f"IMDb Rating: {movie_details.get('imdbRating', 'N/A')}"
        )

        return recommendation

    except Exception as e:
        return f"Error getting movie recommendation: {str(e)}"



@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """A tool that fetches the current local time in a specified timezone.
    Args:
        timezone: A string representing a valid timezone (e.g., 'America/New_York').
    """
    try:
        # Create timezone object
        tz = pytz.timezone(timezone)
        # Get current time in that timezone
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"


final_answer = FinalAnswerTool()

# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 

model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
custom_role_conversions=None,
)


# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)
    
agent = CodeAgent(
    model=model,
    tools=[final_answer, get_current_time_in_timezone, image_generation_tool,get_movie_recommendation], ## add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()