Create app.py

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import requests
+import base64
+from PIL import Image
+import io
+
+# NVIDIA API Configuration
+INVOKE_URL = "https://ai.api.nvidia.com/v1/genai/black-forest-labs/flux.2-klein-4b"
+HEADERS = {
+    "Authorization": "Bearer $NVIDIA_API_KEY", # अपना API KEY यहाँ डालें या Environment Variable का उपयोग करें
+    "Accept": "application/json",
+}
+
+def generate_or_edit(prompt, input_image=None):
+    payload = {
+        "prompt": prompt,
+        "width": 1024,
+        "height": 1024,
+        "seed": 0,
+        "steps": 4
+    }
+
+    # अगर इमेज एडिटिंग है, तो इमेज को बेस64 में बदलें
+    if input_image is not None:
+        buffered = io.BytesIO()
+        input_image.save(buffered, format="PNG")
+        img_str = base64.b64encode(buffered.getvalue()).decode()
+        payload["image"] = [img_str]
+
+    response = requests.post(INVOKE_URL, headers=HEADERS, json=payload)
+    response.raise_for_status()
+    
+    # यहाँ API रिस्पॉन्स से इमेज निकालें (API के स्ट्रक्चर के अनुसार)
+    result = response.json()
+    # मान लें कि रिस्पॉन्स में इमेज बेस64 में आ रही है
+    image_data = base64.b64decode(result["image"])
+    return Image.open(io.BytesIO(image_data))
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Vedika AI - Image Editor & Generator")
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
+            image_input = gr.Image(label="Upload Image (For Editing)", type="pil")
+            submit_btn = gr.Button("Generate / Edit")
+        
+        with gr.Column():
+            result_output = gr.Image(label="Result")
+
+    submit_btn.click(fn=generate_or_edit, inputs=[prompt, image_input], outputs=result_output)
+
+demo.launch()