Update app.py

app.py

@@ -4,6 +4,7 @@ import time
 from haystack.document_stores import InMemoryDocumentStore
 from haystack.nodes import EmbeddingRetriever
 import pandas as pd
+from deep_translator import GoogleTranslator
 
 
 def load_qa_model():
@@ -40,18 +41,26 @@ def add_file(history, file):
     return history
 
 
-def bot(history):
-    print(history)
-    # response = "**That's cool!**"
-    history[-1][1] = ""
-
+def chatbot_response(chat_history, language):
     global retriever
-    response = get_answers(retriever, history[0][0])
+    global last_answer
+
+    if(len(chat_history) > 0):
+        chat_history[-1][1] = ""
+
 
-    for character in response:
-      history[-1][1] += character
-      time.sleep(0.01)
-      yield history
+        if language == 'pt-br':
+          response = get_answers(retriever, GoogleTranslator(source='pt', target='en').translate(chat_history[0][0]))
+          response = GoogleTranslator(source='en', target='pt').translate(response)
+        else:
+          response = get_answers(retriever, chat_history[0][0])
+       
+        last_answer = response
+    
+        for character in response:
+          chat_history[-1][1] += character
+          time.sleep(0.01)
+          yield history
 
 
 
@@ -79,14 +88,19 @@ retriever = load_qa_model()
 
 
 with gr.Blocks() as demo:
-    chatbot = gr.Chatbot(
+    with gr.Accordion("Settings", open=False):
+      language = gr.Radio(["en-us", "pt-br"], label="Language", info="Choose the language to display the classification result and audio", value='en-us', interactive=True)
+
+
+    with gr.Tab("Help"):
+      chatbot = gr.Chatbot(
         [],
         elem_id="chatbot",
         bubble_full_width=False,
-        # avatar_images=(None, "/content/avatar.png"),
-    )
+        # avatar_images=(None, "content/avatar-socialear.png"),
+      )
 
-    with gr.Row():
+      with gr.Row():
         txt = gr.Textbox(
             scale=4,
             show_label=False,
@@ -94,12 +108,18 @@ with gr.Blocks() as demo:
             container=False,
         )
         inputRecord = gr.Audio(label="Record a question", source="microphone", type="filepath")
-        audioOutput = gr.Audio(label="Listen the answer", interactive=False)
-
-    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-        bot, chatbot, chatbot
-    )
-    txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
+        with gr.Column():
+          btn = gr.Button(value="Listen the answer")
+          audioOutput = gr.Audio(interactive=False)
+
+      txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+          chatbot_response, [chatbot, language], chatbot
+      )
+      txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
+      inputRecord.stop_recording(transcribe_speech, [inputRecord, language], [txt])
+      btn.click(fn=TTS_chatbot, inputs=[language], outputs=audioOutput)
+
+      examples = gr.Examples(examples=examples_chatbot, inputs=[txt])
 
 demo.queue()
 demo.launch()