ممكن تعدل لي هذا الكود
from gradio_client import Client

client = Client("quardo/gpt-4o-mini-small")
result = client.predict(
                message="hello",
                model_name="o1-preview",
                max_tokens=4096,
                temperature=0.7,
                top_p=0.95,
                api_name="/chat"
)
print(result)
الى انه يدعم انشاء صور من gradio
وهذا اسم ال space
prodia/FLUX.1-dev
وهذا السورس كود حقها
يعني عشان تعرف كيفيه عملها
import gradio as gr import numpy as np import os import random import requests from PIL import Image from io import BytesIO MAX_SEED = np.iinfo(np.int32).max MAX_IMAGE_SIZE = 2048 class APIClient: def __init__(self, api_key=os.getenv("API_KEY"), base_url="inference.prodia.com"): self.headers = { "Content-Type": "application/json", "Accept": "image/jpeg", "Authorization": f"Bearer {api_key}" } self.base_url = f"https://{base_url}" def _post(self, url, json=None): r = requests.post(url, headers=self.headers, json=json) r.raise_for_status() return Image.open(BytesIO(r.content)).convert("RGB") def job(self, config): body = {"type": "inference.flux.dev.txt2img.v1", "config": config} return self._post(f"{self.base_url}/v2/job", json=body) def infer(prompt, seed=42, randomize_seed=False, resolution="1024x1024", guidance_scale=5.0, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)): if randomize_seed: seed = random.randint(0, MAX_SEED) width, height = resolution.split("x") image = generative_api.job({ "prompt": prompt, "width": int(width), "height": int(height), "seed": seed, "steps": num_inference_steps, "guidance_scale": guidance_scale }) return image, seed generative_api = APIClient() with open("header.md", "r") as file: header = file.read() examples = [ "a tiny astronaut hatching from an egg on the moon", "a cat holding a sign that says hello world", "an anime illustration of a wiener schnitzel", ] css=""" #col-container { margin: 0 auto; max-width: 520px; } .image-container img { max-width: 512px; max-height: 512px; margin: 0 auto; border-radius: 0px; } """ with gr.Blocks(css=css) as demo: with gr.Column(elem_id="col-container"): gr.Markdown(header) with gr.Row(): prompt = gr.Text( label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt" ) run_button = gr.Button("Run", scale=0) result = gr.Image(label="Result", show_label=False, format="jpeg") with gr.Accordion("Advanced Settings", open=False): seed = gr.Slider( label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, ) randomize_seed = gr.Checkbox(label="Randomize seed", value=True) with gr.Row(): resolution = gr.Dropdown( label="Resolution", value="1024x1024", choices=[ "1024x1024", "1024x576", "576x1024" ] ) with gr.Row(): guidance_scale = gr.Slider( label="Guidance Scale", minimum=1, maximum=15, step=0.1, value=3.5, ) num_inference_steps = gr.Slider( label="Number of inference steps", minimum=1, maximum=50, step=1, value=28, ) gr.Examples( examples = examples, fn = infer, inputs = [prompt], outputs = [result, seed], cache_examples="lazy" ) gr.on( triggers=[run_button.click, prompt.submit], fn = infer, inputs = [prompt, seed, randomize_seed, resolution, guidance_scale, num_inference_steps], outputs = [result, seed] ) demo.queue(default_concurrency_limit=8, max_size=10, api_open=False).launch(max_threads=32, show_api=False)