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app.py

@@ -97,32 +97,24 @@ def generate_image(prompt):
     if not prompt.strip(): return None, 'Please enter a description.'
     if not HF_TOKEN: return None, 'Error: Add HF_TOKEN to Space Settings Secrets.'
     try:
-        # Add biomedical context to prompt
-        full_prompt = 'Highly detailed scientific biomedical illustration of: ' + prompt + ', professional medical diagram, high quality, detailed, photorealistic'
-        headers = {'Authorization': 'Bearer ' + HF_TOKEN}
-        payload = {'inputs': full_prompt}
-        # Use FLUX.1-schnell - best free model on HuggingFace
-        r = requests.post(
-            'https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell',
-            headers=headers, json=payload, timeout=60
-        )
-        if r.status_code == 200:
-            img = Image.open(io.BytesIO(r.content))
-            return img, 'Image generated successfully!'
-        elif r.status_code == 503:
-            # Model loading - try stable diffusion
-            r2 = requests.post(
-                'https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0',
-                headers=headers, json=payload, timeout=60
-            )
-            if r2.status_code == 200:
-                img = Image.open(io.BytesIO(r2.content))
-                return img, 'Image generated!'
-            return None, 'Model loading, please wait 30 seconds and try again.'
-        else:
-            return None, 'Error: '+str(r.status_code)+' '+r.text[:200]
+        full_prompt = 'Highly detailed scientific biomedical illustration of: ' + prompt + ', professional medical diagram, high quality, detailed'
+        headers = {'Authorization': 'Bearer ' + HF_TOKEN, 'Content-Type': 'application/json'}
+        payload = {'inputs': full_prompt, 'parameters': {'num_inference_steps': 4}}
+        models = [
+            'https://router.huggingface.co/hf-inference/models/black-forest-labs/FLUX.1-schnell',
+            'https://router.huggingface.co/hf-inference/models/stabilityai/stable-diffusion-xl-base-1.0',
+            'https://router.huggingface.co/hf-inference/models/runwayml/stable-diffusion-v1-5',
+        ]
+        for model_url in models:
+            try:
+                r = requests.post(model_url, headers=headers, json=payload, timeout=60)
+                if r.status_code == 200:
+                    img = Image.open(io.BytesIO(r.content))
+                    return img, 'Image generated!'
+            except: continue
+        return None, 'All models busy. Please wait 30 seconds and try again.'
     except Exception as e:
-        return None, 'Error: '+str(e)
+        return None, 'Error: ' + str(e)
 
 def piv_tool(velocity, shear, hr):
     v = 'HIGH - stenosis risk' if float(velocity)>2.0 else 'NORMAL'