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 geopy.distance import geodesic  # Pour le calcul des distances

from Gradio_UI import GradioUI

# Fonction pour obtenir les coordonnées GPS d'une adresse
def geocode_address(address):
    response = requests.get(f"https://api-adresse.data.gouv.fr/search/?q={address}")
    data = response.json()
    if not data['features']:
        return None, None
    coordinates = data['features'][0]['geometry']['coordinates']
    return coordinates[1], coordinates[0]  # Retourne latitude, longitude

# Fonction pour récupérer toutes les stations Vélib'
def get_stations():
    response = requests.get("https://velib-metropole-opendata.smovengo.cloud/opendata/Velib_Metropole/station_information.json")
    data = response.json()
    return data['data']['stations']

# Trouver la station Vélib' la plus proche d'une adresse donnée
def find_nearest_station(address):
    user_lat, user_lon = geocode_address(address)
    if user_lat is None or user_lon is None:
        return None

    stations = get_stations()
    min_distance = float('inf')
    nearest_station = None

    for station in stations:
        station_coords = (station['lat'], station['lon'])
        distance = geodesic((user_lat, user_lon), station_coords).meters
        if distance < min_distance:
            min_distance = distance
            nearest_station = station

    return nearest_station

# Fonction pour récupérer le statut d'une station
def get_station_status(station_id):
    response = requests.get("https://velib-metropole-opendata.smovengo.cloud/opendata/Velib_Metropole/station_status.json")
    data = response.json()
    for station in data['data']['stations']:
        if station['station_id'] == station_id:
            return station
    return None

# Outil final qui donne le nombre de vélos disponibles à une adresse donnée
@tool
def get_bike_availability(address: str) -> str:
    """A tool that fetches the number of available Velib' bikes at the nearest station to a given address.
    Args:
        address: The address where the user wants to find a Velib' station.
    """
    nearest_station = find_nearest_station(address)
    if not nearest_station:
        return "Aucune station Vélib' trouvée à proximité."

    status = get_station_status(nearest_station['station_id'])
    if not status:
        return "Impossible de récupérer le statut de la station."

    mechanical_bikes = status['num_bikes_available_types'][0].get('mechanical', 0)
    ebikes = status['num_bikes_available_types'][1].get('ebike', 0)

    return (f"🚲 Station la plus proche : {nearest_station['name']}\n"
            f"🔧 Vélos mécaniques disponibles : {mechanical_bikes}\n"
            f"⚡ Vélos électriques disponibles : {ebikes}")

# Ajout du tool à l'agent
final_answer = FinalAnswerTool()

model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    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_bike_availability],  # Ajout du nouvel outil ici
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

GradioUI(agent).launch()