Update app.py

app.py

@@ -7,6 +7,9 @@ openai.api_key = os.getenv("OPENAI_API_KEY")
 from transformers import pipeline
 p = pipeline("automatic-speech-recognition",model="openai/whisper-tiny")
 
+
+
+
 def transcribe(audio):
     text = p(audio)["text"]
     return text
@@ -28,8 +31,8 @@ messages = [
      "content": "you name is Rebecca and you are a Pepsico call center assistant and your job is to take the order from the customer and also analysis the sentiment of the customer"}
 ]
 
-def chatbot(input):
-    if input:
+def chatbot(input1,input2):
+    if input1:
         input = transcribe(input)
         messages.append({"role": "user", "content": input})
         if sentiment(input) == 'negative':
@@ -47,10 +50,32 @@ def chatbot(input):
     
         messages.append({"role": "assistant", "content": reply})
         return reply
+    elif input2:
+        input =input2
+        messages.append({"role": "user", "content": input})
+        if sentiment(input) == 'negative':
+            reply = "Sorry for any inconvinience. We are tranfering your call."
+        else:
+            chat = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            temperature=0.2,
+            max_tokens=320,
+            top_p=1,
+            frequency_penalty=0,
+            presence_penalty=0)
+            reply = chat.choices[0].message.content        
+    
+        messages.append({"role": "assistant", "content": reply})
+        return reply
 
+        
 ##inputs = gr.inputs.Textbox(lines=7, label="Chat with PepsiCo AI assitant")
 
-inputs= gr.Audio(source="microphone", type="filepath")
+#inputs= gr.Audio(source="microphone", type="filepath")
+        
+inputs= [ gr.Audio(source="microphone", type="filepath"),
+          gr.inputs.Textbox(lines=7)]
 
 
 outputs = gr.outputs.Textbox(label="Reply")