Update app.py

app.py

@@ -1,68 +1,108 @@
+# app.py
+
 import streamlit as st
+import hmac
+import os
+from helpers import text_to_speech, autoplay_audio, speech_to_text, get_api_key
+from generate_answer import base_model_chatbot, with_pdf_chatbot
 from audio_recorder_streamlit import audio_recorder
-import openai
-
-# Prompt the user to input their OpenAI API key
-API_KEY = st.text_input("Enter your OpenAI API Key", type="password")
-
-# Check if the API key is provided
-if API_KEY:
-    openai.api_key = API_KEY  # Set the API key
-
-    def transcribe_text_to_voice(audio_location):
-        # Transcribe audio to text using Whisper API
-        with open(audio_location, "rb") as audio_file:
-            transcript = openai.Audio.transcribe(
-                model="whisper-1", file=audio_file
-            )
-        return transcript['text']
-
-    def chat_completion_call(text):
-        # Send the text to GPT-3.5 for chat completion
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo-1106", 
-            messages=[{"role": "user", "content": text}]
-        )
-        return response['choices'][0]['message']['content']
-
-    def text_to_speech_ai(speech_file_path, api_response):
-        # Convert the text to speech using OpenAI's TTS API
-        response = openai.Audio.speech.create(
-            model="text-to-speech-1",  # TTS model name may differ
-            voice="nova",  # Specify a voice (choose one that is available)
-            input=api_response
-        )
-        # Save the speech response to a file
-        with open(speech_file_path, "wb") as f:
-            f.write(response['audio'])
-
-    # Streamlit interface for voice assistant
-    st.title("🧑‍💻 Skolo Online 💬 Talking Assistant")
-    """
-    Hi🤖 just click on the voice recorder and let me know how I can help you today?
-    """
-
-    audio_bytes = audio_recorder()
-    if audio_bytes:
-        # Save the Recorded Audio File
-        audio_location = "audio_file.wav"
-        with open(audio_location, "wb") as f:
-            f.write(audio_bytes)
+from streamlit_float import *
+
+def main(answer_mode: str):
+    # Float feature initialization
+    float_init()
+
+    # Prompt for API key
+    api_key = get_api_key()
+    if not api_key:
+        st.error("You must provide a valid OpenAI API Key to proceed.")
+        st.stop()
+
+    def check_password():
+        """Returns `True` if the user had a correct password."""
+        def login_form():
+            """Form with widgets to collect user information"""
+            with st.form("Credentials"):
+                st.text_input("Username", key="username")
+                st.text_input("Password", type="password", key="password")
+                st.form_submit_button("Log in", on_click=password_entered)
+
+        def password_entered():
+            """Checks whether a password entered by the user is correct."""
+            if st.session_state["username"] in st.secrets[
+                "passwords"
+            ] and hmac.compare_digest(
+                st.session_state["password"],
+                st.secrets.passwords[st.session_state["username"]], 
+            ):
+                st.session_state["password_correct"] = True
+                del st.session_state["password"]  
+                del st.session_state["username"]
+            else:
+                st.session_state["password_correct"] = False
+
+        # Return True if the username + password is validated.
+        if st.session_state.get("password_correct", False):
+            return True
+
+        # Show inputs for username + password.
+        login_form()
+        if "password_correct" in st.session_state:
+            st.error("😕 User not known or password incorrect")
+        return False
 
-        # Transcribe the saved file to text
-        text = transcribe_text_to_voice(audio_location)
-        st.write("You said:", text)
+    if not check_password():
+        st.stop()
+
+    def initialize_session_state():
+        if "messages" not in st.session_state:
+            st.session_state.messages = [
+                {"role": "assistant", "content": "Hi! How may I assist you today?"}
+            ]
+
+    initialize_session_state()
+
+    st.title("OpenAI Conversational Chatbot 🤖")
+
+    # Create footer container for the microphone
+    footer_container = st.container()
+    with footer_container:
+        audio_bytes = audio_recorder()
+
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.write(message["content"])
+
+    if audio_bytes:
+        # Write the audio bytes to a file
+        with st.spinner("Transcribing..."):
+            webm_file_path = "temp_audio.mp3"
+            with open(webm_file_path, "wb") as f:
+                f.write(audio_bytes)
 
-        # Get AI response from GPT-3.5
-        api_response = chat_completion_call(text)
-        st.write("AI says:", api_response)
+            transcript = speech_to_text(webm_file_path)
+            if transcript:
+                st.session_state.messages.append({"role": "user", "content": transcript})
+                with st.chat_message("user"):
+                    st.write(transcript)
+                os.remove(webm_file_path)
 
-        # Convert the response to speech and save it as a file
-        speech_file_path = 'audio_response.mp3'
-        text_to_speech_ai(speech_file_path, api_response)
+    if st.session_state.messages[-1]["role"] != "assistant":
+        with st.chat_message("assistant"):
+            with st.spinner("Thinking🤔..."):
+                if answer_mode == 'base_model':
+                    final_response = base_model_chatbot(st.session_state.messages)
+                elif answer_mode == 'pdf_chat':
+                    final_response = with_pdf_chatbot(st.session_state.messages)
+            with st.spinner("Generating audio response..."):
+                audio_file = text_to_speech(final_response)
+                autoplay_audio(audio_file)
+            st.write(final_response)
+            st.session_state.messages.append({"role": "assistant", "content": final_response})
+            os.remove(audio_file)
 
-        # Play the audio response in the app
-        st.audio(speech_file_path)
+    # Float the footer container and provide CSS to target it with
+    footer_container.float("bottom: 0rem;")
 
-else:
-    st.warning("Please enter your OpenAI API key to continue.")
+if __name__ == "__main__":
+    main(answer_mode='base_model')  # Or: answer_mode='base_model'