diff --git a/wechat.py b/wechat.py
index b9d81e8..9c4d360 100644
--- a/wechat.py
+++ b/wechat.py
@@ -1,21 +1,17 @@
 from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
-
 import os
-from io import open
-
-import itchat
 import tensorflow as tf
-from itchat.content import TEXT, MAP, CARD, NOTE, SHARING
-
+import itchat
+from itchat.content import *
 import config
 import data_utils
+from model import ChatBotModel
 from chatbot import check_restore_parameters
-from chatbot import construct_response
 from chatbot import find_right_bucket
 from chatbot import run_step
-from model import ChatBotModel
+from chatbot import construct_response
 
 sess = tf.InteractiveSession()
 _, enc_vocab = data_utils.load_vocab(os.path.join(config.DATA_PATH, "vocab.enc"))
@@ -30,17 +26,34 @@
 print("Wechat server started. Say something. Max length is", max_length)
 
 
-@itchat.msg_register([TEXT, MAP, CARD, NOTE, SHARING],
-                     isFriendChat=True, isGroupChat=False, isMpChat=False)
+
+# reply to friends, group or public account
+@itchat.msg_register([TEXT,PICTURE,VIDEO], isFriendChat=True, isGroupChat=False, isMpChat=True)
 def wechat(msg):
-    """
-    Args:
-        msg: can be TEXT, MAP, CARD NOTE and SHARING of wechat.
-    Return:
-        wechat response.
-    """
-    line = msg["Text"]
-    token_ids = data_utils.sentence2id(enc_vocab, line)
+    '''
+    reply according to different types of messages
+    :param msg: msg can be text and picture, for other types of message, reply '爸爸！'
+    :return: response to wechat
+    '''
+    if msg['Type'] == 'Text':
+        response = wechat_text(msg)
+    elif msg['Type'] == 'Picture':
+        response = wechat_pic(msg)
+    else:
+        response = '爸爸！'
+    query = msg['Text']
+    write_wechat_records(query, response)
+    return response
+
+
+def wechat_text(msg):
+    '''
+    get the response to msg
+    :param msg: the type of the msg is 'Text'
+    :return: response to msg by using seq2seq model
+    '''
+    text = msg["Text"]
+    token_ids = data_utils.sentence2id(enc_vocab, text)
     if len(token_ids) > max_length:
         print("Max length I can handle is:", max_length)
         # line = _get_user_input()
@@ -54,13 +67,21 @@ def wechat(msg):
                                    decoder_inputs, decoder_masks,
                                    bucket_id, True)
     response = construct_response(output_logits, inv_dec_vocab)
-    write_wechat_records(line, response)
+
     return response
 
 
+def wechat_pic(msg):
+    '''
+    get the response to msg
+    :param msg: the type of the msg is 'Picture'
+    :return: response to picture
+    '''
+    return '爸爸!'
+
 # write chat records to file
 def write_wechat_records(query, response):
-    output_file = open(os.path.join(config.DATA_PATH, config.WECHAT_OUTPUT),
+    output_file = open(os.path.join(config.DATA_PATH, config.WECHAT_FILE),
                        "a+", encoding="utf-8")
     output_file.write("HUMAN ++++ " + query + "\n")
     output_file.write("BOT ++++ " + response + "\n")