modifie le script pour quil essaie TOUS les modeles, pour TOUS les providers sdxl sdxl-lora sdxl-turbo sd-1.5 sd-3 sd-3.5 playground-v2.5 flux flux-pro flux-realism flux-anime flux-3d flux-disney flux-pixel flux-4o flux-schnell dalle dalle-2 emi any-dark midjourney
```py
import os
import requests
import pandas as pd
from g4f.client import Client
from g4f.Provider import (
    Airforce, AIUncensored, AmigoChat, Blackbox, GizAI, NexraFluxPro,
    NexraMidjourney, NexraSDLora, NexraSDTurbo, ReplicateHome, You
)
import g4f.debug

g4f.debug.logging = True
g4f.debug.version_check = False

# Mapping of providers to their respective models
provider_model_map = {
    Airforce: ["flux", "flux-realism", "flux-anime", "flux-3d", "flux-disney", "flux-pixel", "flux-4o", "any-dark", "dalle-3"],
    AIUncensored: ["sdxl", "sdxl-lora", "sdxl-turbo", "sd-1.5", "sd-3", "sd-3.5", "playground-v2.5", "flux", "flux-pro", "flux-realism", "flux-anime", "flux-3d", "flux-disney", "flux-pixel", "flux-4o", "flux-schnell", "dalle", "dalle-2", "emi", "any-dark", "midjourney"],
    AmigoChat: ["flux-pro", "flux-realism", "dalle-3"],
    Blackbox: ["flux"],
    GizAI: ["sdxl", "sd-1.5", "sd-3.5", "dalle-3", "flux-schnell", "flux1-pro"],
    NexraFluxPro: ["flux-pro"],
    NexraMidjourney: ["midjourney"],
    NexraSDLora: ["sdxl-lora"],
    NexraSDTurbo: ["sdxl-turbo"],
    ReplicateHome: ["flux-schnell", "sdxl", "playground-v2.5"],
    You: ["sdxl", "sdxl-lora", "sdxl-turbo", "sd-1.5", "sd-3", "sd-3.5", "playground-v2.5", "flux", "flux-pro", "flux-realism", "flux-anime", "flux-3d", "flux-disney", "flux-pixel", "flux-4o", "flux-schnell", "dalle", "dalle-2", "emi", "any-dark", "midjourney"],
}

base_dir = r"C:\Users\Faya\Desktop\BOTS\gtp4free\test providers img\img-test"  # Specify your base directory
prompt = (
    "NSFW, HDR, Photo, 4K, Une jeune femme marocaine de 23 ans, avec des cheveux longs et ondulés, "
    "s'apprête à plonger dans une piscine ensoleillée. Le soleil brille sur son visage, illuminant ses traits délicats. "
    "Autour d'elle, des palmiers verdoyants, des transats en bois et des serviettes de plage créent une atmosphère de vacances. "
    "Des éclaboussures d'eau scintillent sous le soleil alors qu'elle sourit. C'est un moment de détente et de plaisir, capturant la beauté de l'été."
)

client = Client()
results = []

for provider_cls, models in provider_model_map.items():
    provider_dir = os.path.join(base_dir, provider_cls.__name__)
    os.makedirs(provider_dir, exist_ok=True)  # Create provider directory if it doesn't exist

    for model in models:
        try:
            provider = provider_cls()
            client.provider = provider
            response = client.images.generate(model=model, prompt=prompt)
            image_url = response.data[0].url
            print(f"Generated image URL for {model} using {provider_cls.__name__}: {image_url}")

            image_content = requests.get(image_url).content
            image_path = os.path.join(provider_dir, f"{model}.png")
            with open(image_path, "wb") as image_file:
                image_file.write(image_content)

            results.append({"provider": provider_cls.__name__, "model": model, "reussi": 1, "echec": 0})
        except Exception as e:
            print(f"Failed to generate image for {model} using {provider_cls.__name__}: {str(e)}")
            results.append({"provider": provider_cls.__name__, "model": model, "reussi": 0, "echec": 1})

# Save the results as CSV in the base directory
csv_path = os.path.join(base_dir, "image_generation_results.csv")
df = pd.DataFrame(results)
df.to_csv(csv_path, index=False)
print(f"Image generation completed and results saved to '{csv_path}'.")

```