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import os | |
import openai | |
from dotenv import load_dotenv | |
load_dotenv() | |
openai.api_key=os.environ["OPENAI_API_KEY"] | |
import gradio as gr | |
from langchain.llms import OpenAI | |
from interface import AudioInterface | |
interface = AudioInterface() | |
def process(filepath): | |
print(filepath) | |
audio = open(filepath,"rb") | |
transcript = openai.Audio.transcribe("whisper-1",audio) | |
llm = OpenAI(temperature=1) | |
#print(llm(transcript["text"])) | |
interface.speak(llm(transcript["text"])) | |
return llm(transcript["text"]) | |
demo = gr.Interface( | |
fn=process, | |
inputs=gr.Audio(source="microphone",type="filepath"), | |
outputs="text") | |
demo.launch() | |
""" | |
from dotenv import load_dotenv | |
load_dotenv() | |
from interface import AudioInterface | |
from agents import SmartChatAgent | |
interface = AudioInterface() | |
agent = SmartChatAgent() | |
while True: | |
text = interface.listen() | |
response = agent.run(text) | |
interface.speak(response) | |
""" |