Create app.py

app.py

@@ -0,0 +1,79 @@
+import os
+import gradio as gr
+import openai
+from gtts import gTTS
+
+
+openai.api_key = os.environ["OPEN_AI_KEY"]
+
+
+
+#messages = gr.State([
+#       {"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."}
+#])
+messages = [{"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."}]
+
+
+def transcribe(audio):
+
+    audio_file = open(audio, "rb")    
+    # Call the transcribe method with the file-like object
+    transcript = openai.Audio.transcribe("whisper-1", audio_file)
+
+
+    #msg_contents.append({"role": "user", "content": transcript["text"]})
+
+    #chat_transcript = ""
+    #for message in msg_contents:
+    #    if (message["role"] != "system"):
+    #        chat_transcript += message["role"] + ": " + message["content"] + "\n\n"
+
+    return transcript
+
+def botResponse(chat_log, msg_contents):    
+    response = openai.ChatCompletion.create(
+      model="gpt-3.5-turbo",
+      messages=msg_contents)
+  
+    system_message = response["choices"][0]["message"]["content"]
+    msg_contents.append({"role": "assistant", "content": system_message})
+
+    chat_transcript = chat_log
+    for message in msg_contents:
+        if (message["role"] != "system"):
+            chat_transcript += message["role"] + ": " + message["content"] + "\n\n"
+
+    return system_message
+
+
+def giveVoice(bot_message):
+    myobj = gTTS(text=bot_message)
+    myobj.save("temp.mp3")
+
+    dir = os.getcwd()
+    new_path = os.path.join(dir, "temp.mp3")
+
+    return new_path
+
+
+
+
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            user_audio = gr.Audio(source="microphone", type="filepath", label="Input Phrase")
+            submit_btn = gr.Button(value="Transcribe") 
+            submit2_btn = gr.Button(value="Bot Response")
+            submit3_btn = gr.Button(value="Give Voice")
+        with gr.Column():
+            #gpt_response = gr.Audio(label="Voice Response")
+            gpt_transcript = gr.Text(label="Generate Transcript")
+            gpt_transcript2 = gr.Text(label="Bot Response")
+            gpt_response = gr.Audio(label="Voice Response")
+    submit_btn.click(transcribe, inputs=user_audio, outputs=gpt_transcript)
+    
+    
+
+demo.launch(share=True)