changes

app.py

@@ -153,7 +153,7 @@ def text2vec(query):
 context_dict = {
     "company; goliath; we" : 
     """
-    Our company builds AI Recommendation Systems for Matching Platforms using the latest technology. Our company is estabilished and operates in Japan. Our company uses the AWS Cloud to manage Servers. Our company can use GPT3 as well. Our company also builds GPT3-based chatbots. Our company can use open-source models, if requested. Our company uses open source models. Our company operates in Japan. Our company has been operating for 1 year, and we are expanding in Hong Kong. Our company offers other services apart from recommendation systems, like GPT3 chatbots. Our company can also build recommendation systems for mobile apps.
+    Our company builds AI Recommendation Systems for Matching Platforms using the latest technology. Our company is estabilished and operates in Japan. Our company uses the AWS Cloud to manage Servers. Our company can use GPT3 as well. Our company also builds GPT3-based chatbots. Our company can use open-source models, if requested. Our company uses open source models. Our company operates in Japan. Our company has been operating for 1 year, and we are expanding in Hong Kong. Our company offers other services apart from recommendation systems, like GPT3 chatbots. Our company can also build recommendation systems for mobile apps. You can contact our company at [email protected] .
     """
     ,
     "price" :
@@ -200,7 +200,8 @@ qa_list = {
     'do you use GPT3 API?' : 'yes, we can',
     'do you use GPT3?' : 'yes, we can',
     'do you use GPT4?' : 'yes, we can',
-    'so you build chatbots' : 'yes, we built state-of-the art chatbots with GPT3 technology'
+    'so you build chatbots' : 'yes, we built state-of-the art chatbots with GPT3 technology',
+    'what do you do?' : 'our company builds AI recommendaion systems'
 }
 df_qa = pd.DataFrame([qa_list]).T.reset_index()
 df_qa.columns = ['question', 'answer']