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app.py

@@ -13,10 +13,8 @@ current_model_id = None
 model = None
 processor = None
 
-# SAFELY LOADING TOKEN FROM SPACE SECRETS (No hardcoding)
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
-# --- MODEL LOADER ---
 def load_selected_model(repo_id):
     global model, processor, current_model_id
     if repo_id == current_model_id and model is not None:
@@ -43,7 +41,6 @@ def load_selected_model(repo_id):
     except Exception as e:
         return f"❌ Error loading {repo_id}: {str(e)}"
 
-# --- PARSER ---
 def extract_tag(tag, text):
     match = re.search(f"<(?:{tag})?>(.*?)</(?:{tag})?", text, re.IGNORECASE)
     if not match:
@@ -86,18 +83,11 @@ def run_qwen(image, prompt_text, max_tokens=150):
     except Exception as e:
          return f"Extraction Failed: {str(e)}"
 
-# --- TAB FUNCTIONS ---
 def ocr_extraction(front_img):
     prompt = "Extract details inside these XML tags ONLY:\n<ID></ID>\n<NAME></NAME>\n<DOB></DOB>\n<NAT></NAT>"
     raw_output = run_qwen(front_img, prompt, max_tokens=150)
     return build_enterprise_json(raw_output)
 
-def chat_with_doc(image, user_message, chat_history):
-    ai_response = run_qwen(image, user_message, max_tokens=200)
-    chat_history.append((user_message, ai_response))
-    return "", chat_history
-
-# --- GRADIO UI ---
 with gr.Blocks() as demo:
     gr.Markdown("# 🪪 CSM Universal Model Testing Playground")
     
@@ -132,17 +122,16 @@ with gr.Blocks() as demo:
                 with gr.Column(scale=1):
                     chat_img_input = gr.Image(type="pil", label="Document Attachment")
                 with gr.Column(scale=2):
-                    chatbot = gr.Chatbot(label="Chat Interface", height=400, type="messages")
+                    # REMOVED: type="messages" to make it compatible with all Gradio versions
+                    chatbot = gr.Chatbot(label="Chat Interface", height=400)
                     with gr.Row():
                         chat_input = gr.Textbox(placeholder="Ask anything...", show_label=False)
                         send_btn = gr.Button("Send")
             
+            # REVERTED back to standard list of tuples format
             def chat_wrapper(image, user_message, chat_history):
-                if not chat_history:
-                    chat_history = []
                 ai_response = run_qwen(image, user_message, max_tokens=200)
-                chat_history.append({"role": "user", "content": user_message})
-                chat_history.append({"role": "assistant", "content": ai_response})
+                chat_history.append((user_message, ai_response))
                 return "", chat_history
                 
             send_btn.click(chat_wrapper, inputs=[chat_img_input, chat_input, chatbot], outputs=[chat_input, chatbot])