* add qwen3 vlm example

Author: lxowalle

examples/mllm/vlm/vlm_qwen3.py

@@ -0,0 +1,112 @@
+'''
+     Qwen3 VLM example.
+     Supportted devices: MaixCAM2
+     Not Supported devices: MaixCAM
+     Models:
+        - https://huggingface.co/sipeed/Qwen3-VL-2B-Instruct-GPTQ-Int4-AX630C-P320-CTX448-maixcam2
+'''
+from maix import app, nn, err, image, display, time
+import requests
+import json
+
+model = "/root/models/Qwen3-VL-2B-Instruct-GPTQ-Int4-AX630C-P320-CTX448-maixcam2/model.mud"
+disp = display.Display()
+
+qwen3_vl = nn.Qwen3VL(model)
+
+in_w = qwen3_vl.input_width()
+in_h = qwen3_vl.input_height()
+in_fmt = qwen3_vl.input_format()
+print(f"input size: {in_w}x{in_h}, format: {image.format_name(in_fmt)}")
+
+def on_reply(obj, resp):
+    print(resp.msg_new, end="")
+
+qwen3_vl.set_system_prompt("You are Qwen3VL. You are a helpful vision-to-text assistant.")
+qwen3_vl.set_reply_callback(on_reply)
+
+# load and set image
+img = image.load("/maixapp/share/picture/2024.1.1/ssd_car.jpg", format=in_fmt)
+qwen3_vl.set_image(img, fit=image.Fit.FIT_CONTAIN) # if size not math, will auto resize first
+disp.show(img)
+
+while not app.need_exit():
+    print('wait model is ready')
+    if qwen3_vl.is_ready():
+        break
+    time.sleep(1)
+
+def example1():
+    # set prompt
+    msg = "请描述图中有什么"
+    print(">>", msg)
+    resp = qwen3_vl.send(msg)
+    err.check_raise(resp.err_code)
+
+def example2():
+    msg = "Describe the picture"
+    print(">>", msg)
+    resp = qwen3_vl.send(msg)
+    err.check_raise(resp.err_code)
+
+
+def example3():
+    url = "http://127.0.0.1:12346"
+    headers = {
+        "Content-Type": "application/json",
+    }
+
+    stream = True
+    data = {
+        "model": "AXERA-TECH/Qwen3-VL-2B-Instruct-GPTQ-Int4",
+        "stream":stream,
+        "temperature":0.7,
+        "repetition_penalty":1,
+        "top-p":0.8,
+        "top-k":20,
+        "messages": [{
+                "role":"user",
+                "content": [{
+                        "type":"text",
+                        "text":"告诉我你的名字"
+                    }, {
+                        "type":"image_url",
+                        "image_url":"images/demo.jpg"
+                    }]
+                }]
+    }
+    response = requests.post(url + '/v1/chat/completions', headers=headers, json=data, stream=stream)
+
+    if not stream:
+        print(response.status_code)  # 状态码
+        print(response.text)         # 响应内容
+    else:
+        # 处理流式响应
+        if response.status_code == 200:
+            for line in response.iter_lines():
+                if line:
+                    line = line.decode('utf-8')
+                    if line.startswith('data: '):
+                        data_str = line[6:]  # 移除 "data: " 前缀
+                        if data_str.strip() == '[DONE]':
+                            print("\n流式传输完成")
+                            break
+                        try:
+                            chunk = json.loads(data_str)
+                            # 提取模型输出内容
+                            if 'choices' in chunk and len(chunk['choices']) > 0:
+                                delta = chunk['choices'][0].get('delta', {})
+                                if 'content' in delta:
+                                    print(delta['content'], end='', flush=True)
+                        except json.JSONDecodeError:
+                            continue
+        else:
+            print(f"请求失败: {response.status_code}")
+            print(response.text)
+
+
+example1()
+# example2()
+# example3()
+
+del qwen3_vl        # Must release vlm object