Update app.py

app.py

@@ -8,38 +8,36 @@ import requests
 HF_VLM_API = "https://api-inference.huggingface.co/models/Qwen/Qwen2-VL-7B-Instruct"
 HF_TOKEN = "HF_CV_ROBOT_TOKEN"  # HF Token
 
-def call_vlm_api(img: Image):
-    # encode image to bytes
-    buf = io.BytesIO()
-    img.save(buf, format="JPEG")
-    img_bytes = buf.getvalue()
-
+def call_vlm_api(payload: dict):
     headers = {"Authorization": f"Bearer {HF_TOKEN}"}
-    payload = {"inputs": [{"image": img_bytes, "text": "Describe the image in detail."}]}
-    
-    resp = requests.post(HF_VLM_API, headers=headers, json=payload, timeout=60)
+    data = {
+        "inputs": [
+            {
+                "image": {"b64": payload["image_b64"]},
+                "text": "Describe the image in detail."
+            }
+        ]
+    }
+    resp = requests.post(HF_VLM_API, headers=headers, json=data, timeout=60)
     if resp.status_code == 200:
         return resp.json()[0].get("generated_text", "")
     else:
-        return f"VLM API error: {resp.status_code}"
+        return f"VLM API error: {resp.status_code}, {resp.text}"
 
 def process(payload: dict):
     try:
-        img_bytes = base64.b64decode(payload["image_b64"])
-        img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
-
-        vlm_text = call_vlm_api(img)
+        vlm_text = call_vlm_api(payload)
 
         reply = {
             "received": True,
             "robot_id": payload.get("robot_id", "unknown"),
-            "size": img.size,
             "vllm_analysis": vlm_text
         }
         return reply
     except Exception as e:
         return {"error": str(e)}
 
+
 demo = gr.Interface(
     fn=process,
     inputs=gr.JSON(label="Input Payload (Dict format)"),