Adding chat clear button

app.py

@@ -48,9 +48,6 @@ def chat_application(llm_service,key,temperature=0.1,max_tokens=1024):
         llm = get_openai_chat_model(API_key=key)
     return llm 
 
-def summarize_contents():
-    question = "Generate a summary of the contents. Do not return the response in json format"
-    return qa.run(question)
 
 def document_loader(file_path,api_key,doc_type='pdf',llm='Huggingface',temperature=0.1,max_tokens=4096):
     document = None
@@ -104,6 +101,10 @@ def process_pdf_document(document_file):
     document = loader.load()
     return document
 
+
+def clear_chat():
+    return []
+
 def infer(question, history):
     # res = []
     # # for human, ai in history[:-1]:
@@ -155,13 +156,13 @@ with gr.Blocks(css=css) as demo:
     with gr.Row():
         question = gr.Textbox(label="Type your question?",lines=1).style(full_width=False)
         submit_btn = gr.Button(value="Send message", variant="primary", scale = 1)
+        clean_chat = gr.Button(Value = "Clear chat", variant="primary", scale = 1)
 
     with gr.Column():
         with gr.Box():
             LLM_option = gr.Dropdown(['HuggingFace','OpenAI'],label='Large Language Model Selection',info='LLM Service')
             API_key = gr.Textbox(label="Add API key", type="password")
-                
-                
+                 
         with gr.Column():
             with gr.Box():
                 file_extension = gr.Dropdown(FILE_EXT, label="File Extensions", info="Select type of file to upload !")
@@ -189,11 +190,13 @@ with gr.Blocks(css=css) as demo:
         # question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter")
         # submit_button = gr.Button("Send Message")
 
-    load_pdf.click(loading_file, None, langchain_status, queue=False)    
-    load_pdf.click(document_loader, inputs=[pdf_doc,API_key,file_extension,LLM_option,temperature,max_new_tokens], outputs=[langchain_status], queue=False)
-        
-    
+    if pdf_doc:
+        load_pdf.click(loading_file, None, langchain_status, queue=False)    
+        load_pdf.click(document_loader, inputs=[pdf_doc,API_key,file_extension,LLM_option,temperature,max_new_tokens], outputs=[langchain_status], queue=False)
+
     question.submit(add_text, [chatbot, question], [chatbot, question]).then(bot, chatbot, chatbot)
     submit_btn.click(add_text, [chatbot, question], [chatbot, question]).then(bot, chatbot, chatbot)
+    clean_chat.click(clear_chat, [], chatbot)
+
 
 demo.launch()