Update app.py

app.py

@@ -12,8 +12,58 @@ if DEVICE == "auto":
 print(f"[SYSTEM] | Using {DEVICE} type compute device.")
 
 # Variables
+DEFAULT_INPUT = "Describe in one paragraph."
+
 repo = AutoModel.from_pretrained("openbmb/MiniCPM-V-2_6", torch_dtype=torch.bfloat16, trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained("openbmb/MiniCPM-V-2_6", trust_remote_code=True)
 
 # Functions
-# Initialize
+@spaces.GPU(duration=60)
+def generate(image, instruction=DEFAULT_INPUT, sampling=False, temperature=0.7, top_p=0.8, top_k=100, repetition_penalty=1.05, max_tokens=512):
+    global model, tokenizer
+    
+    image_rgb = Image.open(image).convert("RGB")
+    print(image_rgb, instruction)
+
+    inputs = [{"role": "user", "content": [image_rgb, instruction]}]
+
+    parameters = {
+        "sampling": sampling,
+        "temperature": temperature,
+        "top_p": top_p,
+        "top_k": top_k,
+        "repetition_penalty": repetition_penalty,
+        "max_new_tokens": max_tokens
+    }
+    
+    output = model.chat(image=None, msgs=inputs, tokenizer=tokenizer, **parameters)
+    
+    return output
+    
+def cloud():
+    print("[CLOUD] | Space maintained.")
+
+# Initialize
+with gr.Blocks(css=css) as main:
+    with gr.Column():
+        gr.Markdown("🪄 Analyze images and caption them.")
+        
+    with gr.Column():
+        input = gr.Image(label="Image")
+        instruction = gr.Textbox(lines=1, value=DEFAULT_INPUT, label="Instruction")
+        sampling = gr.Checkbox(value=False, label="Sampling")
+        temperature = gr.Slider(minimum=0, maximum=2, step=0.01, value=0.7, label="Temperature")
+        top_p = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.8, label="Top P")
+        top_k = gr.Slider(minimum=0, maximum=1000, step=1, value=100, label="Top K")
+        repetition_penalty = gr.Slider(minimum=0, maximum=2, step=0.01, value=1.05, label="Repetition Penalty")
+        max_tokens = gr.Slider(minimum=1, maximum=4096, step=1, value=512, label="Max Tokens")
+        submit = gr.Button("▶")
+        maintain = gr.Button("☁️")
+        
+    with gr.Column():
+        output = gr.Textbox(lines=1, value="", label="Output")
+
+    submit.click(fn=generate, inputs=[input, instruction, sampling, temperature, top_p, top_k, repetition_penalty, max_tokens], outputs=[output], queue=False)
+    maintain.click(cloud, inputs=[], outputs=[], queue=False)
+
+main.launch(show_api=True)