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ADITYA0205
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Parent(s):
13065fd
Upload 6 files
Browse files- .env +3 -0
- .env.sample +2 -0
- Voice_Deepgram.zip +3 -0
- app.py +101 -0
- requirements.txt +8 -0
- temp.wav +0 -0
.env
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DEEPGRAM_API_KEY="f5984a104dec71de1e6a2cc10cd3242cedccfe10"
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#OPENAI_API_KEY="sk-proj-DPCl3xqekKXbqesokl5JT3BlbkFJfNvUT163z04Y8AUFd89"
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GROQ_API_KEY="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"
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.env.sample
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DEEPGRAM_API_KEY=""
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GROQ_API_KEY=""
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Voice_Deepgram.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:0cdab898b9816a1729ab14ff156c32d737c08edb08ee6cfd2792a76484935a21
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size 564225
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app.py
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import os
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import asyncio
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import sounddevice as sd
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import numpy as np
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import wave
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import pygame
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import streamlit as st
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from deepgram import Deepgram
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from groq import Groq
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from dotenv import load_dotenv
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from gtts import gTTS
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# Load API keys from .env file
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load_dotenv()
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DEEPGRAM_API_KEY = os.getenv("DEEPGRAM_API_KEY")
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GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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if not DEEPGRAM_API_KEY or not GROQ_API_KEY:
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raise ValueError("API keys for Deepgram and Groq must be set in the .env file")
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# Initialize Deepgram and Groq clients
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dg_client = Deepgram(DEEPGRAM_API_KEY)
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groq_client = Groq(api_key=GROQ_API_KEY)
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# Audio recording parameters
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DURATION = 5 # seconds
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SAMPLERATE = 16000
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FILENAME = "output.wav"
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RESPONSE_AUDIO = "response.mp3"
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async def recognize_audio_deepgram(filename):
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with open(filename, 'rb') as audio:
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source = {'buffer': audio.read(), 'mimetype': 'audio/wav'}
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response = await dg_client.transcription.prerecorded(source, {'punctuate': True, 'language': 'en-US'})
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return response['results']['channels'][0]['alternatives'][0]['transcript']
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def record_audio(filename, duration, samplerate):
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st.write("Recording🔉...")
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audio_data = sd.rec(int(duration * samplerate), samplerate=samplerate, channels=1, dtype=np.int16)
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sd.wait() # Wait until recording is finished
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wavefile = wave.open(filename, 'wb')
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wavefile.setnchannels(1)
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wavefile.setsampwidth(2)
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wavefile.setframerate(samplerate)
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wavefile.writeframes(audio_data.tobytes())
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wavefile.close()
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st.write("Recording finished🔴.")
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def generate_response(prompt):
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response = groq_client.chat.completions.create(
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model="llama3-8b-8192",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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],
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temperature=0.29,
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max_tokens=100,
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top_p=1,
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stream=False,
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stop=None,
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)
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return response.choices[0].message.content.strip()
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def play_response(text):
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tts = gTTS(text=text, lang='en')
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tts.save(RESPONSE_AUDIO)
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pygame.mixer.init()
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pygame.mixer.music.load(RESPONSE_AUDIO)
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pygame.mixer.music.play()
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while pygame.mixer.music.get_busy():
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pygame.time.Clock().tick(10)
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pygame.mixer.quit()
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os.remove(RESPONSE_AUDIO) # Clean up the response audio file
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async def main():
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stop_keywords = {"thank you", "goodbye", "exit"}
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while True:
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record_audio(FILENAME, DURATION, SAMPLERATE)
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user_input = await recognize_audio_deepgram(FILENAME)
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st.write(f"User: {user_input}")
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if any(keyword in user_input.lower() for keyword in stop_keywords):
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st.write("Conversation ended.")
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play_response("Goodbye! Have a great day!")
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break
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response = generate_response(user_input)
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st.write(f"Bot: {response}")
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play_response(response)
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os.remove(FILENAME) # Clean up the audio file
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# Streamlit UI
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def run_streamlit_app():
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st.title("Voice Chatbot🔊")
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if st.button("Start Conversation"):
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asyncio.run(main())
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if __name__ == "__main__":
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run_streamlit_app()
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requirements.txt
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@@ -0,0 +1,8 @@
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1 |
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deepgram
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2 |
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gtts
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groq
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numpy
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pygame
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python-dotenv
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sounddevice
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streamlit
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temp.wav
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Binary file (441 kB). View file
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