Update app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+
+from transformers import pipeline
+
+import wikipedia
+
+
+talk = 0
+su = ''
+nlp_qa = pipeline('question-answering')
+
+def chat(message):
+    history = gr.get_state() or []
+
+
+    global talk
+    global su
+
+    if talk == 0:
+      response = 'tell me a subject you wanted to talk about'
+      talk = 1
+    
+    elif talk == 1:
+      results = wikipedia.search(message)
+      summary = wikipedia.summary(results)
+      su = summary
+      response = 'ask me a question about this topic'
+      talk = 2
+    
+    else:
+      a = nlp_qa(context=su, question=message)
+      response = list(a.values())[3]
+      talk = 0
+
+
+
+    history.append((message, response))
+    gr.set_state(history)
+    html = "<div class='chatbot'>"
+    for user_msg, resp_msg in history:
+        html += f"<div class='user_msg'>{user_msg}</div>"
+        html += f"<div class='resp_msg'>{resp_msg}</div>"
+    html += "</div>"
+    return html
+
+iface = gr.Interface(chat, "text", "html", css="""
+    .chatbox {display:flex;flex-direction:column}
+    .user_msg, .resp_msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%}
+    .user_msg {background-color:cornflowerblue;color:white;align-self:start}
+    .resp_msg {background-color:lightgray;align-self:self-end}
+""", allow_screenshot=False, allow_flagging=False)
+if __name__ == "__main__":
+    iface.launch(debug=True)