Update app.py

app.py

@@ -7,13 +7,13 @@ import os
 
 # HF token & model
 HF_TOKEN = os.environ.get("HF_CV_ROBOT_TOKEN")
-MODEL = "Qwen/Qwen2.5-VL-7B-Instruct"  # 確認這個模型在 HF 支援列表裡
+MODEL = "Qwen/Qwen2.5-VL-7B-Instruct"  # 確認此模型有支援 VLM (目前有)
 
 if not HF_TOKEN:
     print("ERROR: HF_CV_ROBOT_TOKEN environment variable not set.")
 
 # -------------------------------
-# 主處理函數 (Main Processing Function)
+# 主處理函數
 # -------------------------------
 def process(payload: dict):
     try:
@@ -23,15 +23,17 @@ def process(payload: dict):
         robot_id = payload.get("robot_id", "unknown")
         image_b64 = payload["image_b64"]
 
-        # Base64 -> bytes
+        # ------------------------------------------------
+        # ⭐ 1) Base64 → 圖檔並存成 temp.jpg
+        # ------------------------------------------------
         img_bytes = base64.b64decode(image_b64)
+        temp_path = "temp.jpg"
+        with open(temp_path, "wb") as f:
+            f.write(img_bytes)
 
-        # 將 Base64 bytes 當作 file-like 上傳
-        files = {
-            "file": ("image.jpg", BytesIO(img_bytes), "image/jpeg")
-        }
-
-        # JSON payload 只放文字訊息
+        # ------------------------------------------------
+        # ⭐ 2) JSON 部分（只放文字）
+        # ------------------------------------------------
         data = {
             "model": MODEL,
             "messages": [
@@ -44,32 +46,43 @@ def process(payload: dict):
             ]
         }
 
+        # ------------------------------------------------
+        # ⭐ 3) 用 multipart/form-data 傳送 image + JSON payload
+        # ------------------------------------------------
         resp = requests.post(
             "https://router.huggingface.co/v1/chat/completions",
             headers={"Authorization": f"Bearer {HF_TOKEN}"},
             data={"payload": json.dumps(data)},
-            files=files,
+            files={"file": ("image.jpg", open(temp_path, "rb"), "image/jpeg")},
             timeout=60
         )
 
+        # ------------------------------------------------
+        # ⭐ 4) 處理回應
+        # ------------------------------------------------
         if resp.status_code != 200:
             print(f"VLM API error: {resp.status_code}, {resp.text}")
             return {"error": f"VLM API error: {resp.status_code}, {resp.text}"}
 
-        # 解析返回文字
+        # 正常解析內容
         try:
-            vlm_text = resp.json()["choices"][0]["message"]["content"][0]["text"]
-        except (KeyError, IndexError, json.JSONDecodeError) as e:
+            content = resp.json()["choices"][0]["message"]["content"]
+            # content 是 array，找出 text
+            vlm_text = ""
+            for part in content:
+                if part.get("type") == "text":
+                    vlm_text += part["text"]
+        except Exception as e:
             return {"error": f"Failed to parse VLM response: {e}, Response text: {resp.text}"}
 
         return {
             "received": True,
             "robot_id": robot_id,
-            "vllm_analysis": vlm_text
+            "vllm_analysis": vlm_text.strip()
         }
 
     except Exception as e:
-        print(f"An unexpected error occurred: {e}")
+        print(f"Unexpected error: {e}")
         return {"error": str(e)}
 
 # -------------------------------