Update app.py

app.py

@@ -5,35 +5,36 @@ import re
 import gradio as gr
 import google.generativeai as genai
 
-# API Keys
+# In ra version để debug
+print("Google Generative AI SDK version:", genai.__version__)
+
+# ==== API KEY ROTATION ====
 API_KEYS = [
     "AIzaSyAtHYSw1iWJYyGLt_hC5mKO3627wkHtN-s",
-    "AIzaSyBfJeK_IAkfLpmnBsMNe6xwjcielrloSFY", 
+    "AIzaSyBfJeK_IAkfLpmnBsMNe6xwjcielrloSFY",
     "AIzaSyCprm_rLChQ7Rv7YkHKI_6tcbS213PiPto",
     "AIzaSyAPFCgH8uSjANmPRF9iHYIYcneTOod8Qi0",
     "AIzaSyBbK-1P3JD6HPyE3QLhkOps6_-Xo3wUFbs"
 ]
 
 key_index = 0
-
 def get_next_key():
     global key_index
     key = API_KEYS[key_index % len(API_KEYS)]
     key_index += 1
     return key
 
+# ==== JSON EXTRACTION ====
 def extract_json(text):
-    # Tìm JSON trong ```json blocks
     match = re.search(r"```json\s*(.*?)\s*```", text, re.IGNORECASE | re.DOTALL)
     if match:
         json_text = match.group(1).strip()
     else:
         json_text = text.strip()
-    
+
     try:
         return json.loads(json_text)
     except:
-        # Tìm {...} ngoài cùng
         first = json_text.find("{")
         last = json_text.rfind("}")
         if first != -1 and last != -1 and last > first:
@@ -43,68 +44,70 @@ def extract_json(text):
                 pass
         return {"raw_response": text}
 
+# ==== MAIN PROCESS ====
 def process_image(image, prompt):
     try:
         print(f"Received image: {type(image)}")
         print(f"Received prompt: {prompt}")
-        
+
         # Lấy API key
         api_key = get_next_key()
         genai.configure(api_key=api_key)
-        
-        # Tạo model
+
+        # Tạo model Gemini
         model = genai.GenerativeModel("gemini-2.5-flash")
-        
-        # Upload ảnh
+
+        # Tạo file tạm
         temp_file = None
         uploaded_file = None
-        
-        try:
-            # Tạo file tạm
-            with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as tmp:
-                if hasattr(image, 'save'):
-                    # PIL Image object
-                    image.save(tmp.name)
-                elif isinstance(image, str):
-                    # File path
-                    with open(image, 'rb') as f:
-                        tmp.write(f.read())
-                else:
-                    raise ValueError(f"Unsupported image type: {type(image)}")
-                temp_file = tmp.name
-            
-            print(f"Created temp file: {temp_file}")
-            
-            # Upload lên Gemini
-            #uploaded_file = genai.upload_file(temp_file)
-            genai.upload_file(temp_file, rag_store_name="my_rag_store")
-
-            print(f"Uploaded to Gemini: {uploaded_file.name}")
-            
-            # Gọi API
-            response = model.generate_content([prompt, uploaded_file])
-            print(f"Got response: {response.text[:100]}...")
-            
-            # Extract JSON
-            result = extract_json(response.text)
-            return result
-            
-        finally:
-            # Cleanup
-            if temp_file and os.path.exists(temp_file):
-                os.remove(temp_file)
-                print(f"Cleaned temp file: {temp_file}")
-            if uploaded_file:
-                genai.delete_file(uploaded_file.name)
-                print(f"Deleted from Gemini: {uploaded_file.name}")
-                
+
+        with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as tmp:
+            if hasattr(image, 'save'):
+                image.save(tmp.name)
+            elif isinstance(image, str):
+                with open(image, 'rb') as f:
+                    tmp.write(f.read())
+            else:
+                raise ValueError(f"Unsupported image type: {type(image)}")
+            temp_file = tmp.name
+
+        print(f"Created temp file: {temp_file}")
+
+        # === Upload ảnh lên Gemini ===
+        uploaded_file = genai.upload_file(
+            path=temp_file,
+            display_name=os.path.basename(temp_file),
+            mime_type="image/png",
+            rag_store_name="default_rag_store"
+        )
+        print(f"Uploaded to Gemini: {uploaded_file.name}")
+
+        # === Gọi model ===
+        response = model.generate_content([prompt, uploaded_file])
+        print(f"Got response: {response.text[:200]}...")
+
+        result = extract_json(response.text)
+        return result
+
     except Exception as e:
         print(f"Error: {e}")
         import traceback
         traceback.print_exc()
         return {"error": str(e)}
 
-# Gradio Interface
+    finally:
+        # Cleanup
+        if temp_file and os.path.exists(temp_file):
+            os.remove(temp_file)
+            print(f"Cleaned temp file: {temp_file}")
+        if uploaded_file:
+            try:
+                genai.delete_file(uploaded_file.name)
+                print(f"Deleted from Gemini: {uploaded_file.name}")
+            except Exception as del_err:
+                print(f"Warning: Could not delete file: {del_err}")
+
+# ==== GRADIO UI ====
 demo = gr.Interface(
     fn=process_image,
     inputs=[
@@ -112,8 +115,8 @@ demo = gr.Interface(
         gr.Textbox(lines=5, placeholder="Enter your prompt here...", label="Prompt"),
     ],
     outputs=gr.JSON(label="Response"),
-    title="OCR API- Sample",
-    description="Upload image + prompt to get JSON response",
+    title="Gemini OCR & Analyzer",
+    description="Upload an image + prompt, returns structured JSON extracted via Gemini 2.5 Flash",
     flagging_mode="never",
 )
 
@@ -125,6 +128,4 @@ if __name__ == "__main__":
         server_port=int(os.getenv("PORT", "7860")),
         show_error=True,
         debug=True,
-        # share=True,        
-        # inbrowser=True,    
-    )
+    )