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import os
import time
import gradio as gr
import openai
from dotenv import load_dotenv, find_dotenv
from simpleaichat import AIChat
from main import weather, search
from utils.tts import TTS, voices
load_dotenv(find_dotenv())
openai.api_key = os.getenv("OPENAI_API_KEY")
def transcribe(audio_file, state=""):
time.sleep(5)
if audio_file is None:
return None
prompt = (
"The author of this tool is Somto Muotoe. "
"Friends: Ire Ireoluwa Adedugbe, Biola Aderiye, Jelson, Raj, Akshay."
"Umm, let me think like, hmm... Okay, here's what I'm, like, "
"thinking. "
)
with open(audio_file, "rb") as f:
response = openai.Audio.transcribe("whisper-1", f, prompt=prompt)
text = response["text"]
state += text
return state, state
def chat_with_gpt(prompt, ai_state, model):
if ai_state is None:
params = {"temperature": 0.0, "max_tokens": 200}
system_prompt = (
"You are a confidante whose response is curt and concise."
"You can use tools to give real-time updates on weather and search the internet. "
"Answer all questions empathetically, and ALWAYS ask follow-up questions."
"Do NOT say Confidante in any response."
"You must TRUST the provided context to inform your response."
)
ai = AIChat(
params=params, model=model, system=system_prompt, save_messages=True
)
else:
ai = ai_state
tools = [weather, search]
response = ai(prompt, tools=tools)
text_response = response["response"]
print(text_response)
return text_response, ai
def tts(text, voice_id):
# Generate audio from the text response
tts_ = TTS(voice_id)
audio_data = tts_.generate(text=text)
return audio_data
def transcribe_and_chat(audio_file, voice, history, ai_state, model):
if audio_file is None:
raise gr.Error("Empty audio file.")
voice_id = voices[voice]
text, text_state = transcribe(audio_file)
gpt_response, ai_state = chat_with_gpt(text, ai_state, model)
audio_data = tts(gpt_response, voice_id)
# Update the history with the new messages
history.append((text, gpt_response))
return history, audio_data, history, ai_state
def clear_chat(history):
# Clear the chat history
history.clear()
# Clear the chat for the AIChat object
chat_with_gpt("", ai_state=None)
return history
with gr.Blocks(title="JARVIS") as demo:
gr.Markdown(
"# Talk with GPT-4! You can get real-time weather updates, and can search Google."
)
audio_input = gr.Audio(source="microphone", type="filepath", visible=True)
gr.ClearButton(audio_input)
gr.Markdown(
"Choose the AI model to use for generating responses. "
"GPT-4 is slower but more accurate, while GPT-3.5-turbo-16k is faster but less accurate."
)
model_select = gr.Radio(
choices=["gpt-4", "gpt-3.5-turbo-16k"],
label="Model",
value="gpt-3.5-turbo-16k",
)
voice_select = gr.Radio(choices=list(voices.keys()), label="Voice", value="Bella")
history = gr.State(label="History", value=[])
ai_state = gr.State(label="AIChat", value=None)
# transcription = gr.Textbox(lines=2, label="Transcription")
chat_box = gr.Chatbot(label="Response")
response_audio = gr.Audio(label="Response Audio", autoplay=True)
gr.ClearButton(chat_box, value="Clear Chat")
# clear_chat_btn.click(clear_chat, inputs=history, outputs=history)
audio_input.stop_recording(
transcribe_and_chat,
inputs=[audio_input, voice_select, history, ai_state, model_select],
outputs=[chat_box, response_audio, history, ai_state],
)
audio_input.clear()
demo.launch()
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