mirror of
https://github.com/gpt-omni/mini-omni
synced 2024-11-16 05:03:47 +00:00
258 lines
8.1 KiB
Python
258 lines
8.1 KiB
Python
import streamlit as st
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import wave
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# from ASR import recognize
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import requests
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import pyaudio
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import numpy as np
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import base64
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import io
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import os
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import time
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import tempfile
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import librosa
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import traceback
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from pydub import AudioSegment
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from utils.vad import get_speech_timestamps, collect_chunks, VadOptions
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API_URL = os.getenv("API_URL", "http://127.0.0.1:60808/chat")
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# recording parameters
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IN_FORMAT = pyaudio.paInt16
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IN_CHANNELS = 1
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IN_RATE = 24000
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IN_CHUNK = 1024
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IN_SAMPLE_WIDTH = 2
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VAD_STRIDE = 0.5
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# playing parameters
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OUT_FORMAT = pyaudio.paInt16
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OUT_CHANNELS = 1
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OUT_RATE = 24000
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OUT_SAMPLE_WIDTH = 2
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OUT_CHUNK = 5760
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# Initialize chat history
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if "messages" not in st.session_state:
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st.session_state.messages = []
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def run_vad(ori_audio, sr):
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_st = time.time()
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try:
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audio = np.frombuffer(ori_audio, dtype=np.int16)
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audio = audio.astype(np.float32) / 32768.0
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sampling_rate = 16000
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if sr != sampling_rate:
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audio = librosa.resample(audio, orig_sr=sr, target_sr=sampling_rate)
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vad_parameters = {}
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vad_parameters = VadOptions(**vad_parameters)
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speech_chunks = get_speech_timestamps(audio, vad_parameters)
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audio = collect_chunks(audio, speech_chunks)
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duration_after_vad = audio.shape[0] / sampling_rate
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if sr != sampling_rate:
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# resample to original sampling rate
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vad_audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=sr)
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else:
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vad_audio = audio
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vad_audio = np.round(vad_audio * 32768.0).astype(np.int16)
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vad_audio_bytes = vad_audio.tobytes()
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return duration_after_vad, vad_audio_bytes, round(time.time() - _st, 4)
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except Exception as e:
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msg = f"[asr vad error] audio_len: {len(ori_audio)/(sr*2):.3f} s, trace: {traceback.format_exc()}"
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print(msg)
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return -1, ori_audio, round(time.time() - _st, 4)
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def warm_up():
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frames = b"\x00\x00" * 1024 * 2 # 1024 frames of 2 bytes each
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dur, frames, tcost = run_vad(frames, 16000)
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print(f"warm up done, time_cost: {tcost:.3f} s")
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def save_tmp_audio(audio_bytes):
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmpfile:
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file_name = tmpfile.name
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audio = AudioSegment(
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data=audio_bytes,
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sample_width=OUT_SAMPLE_WIDTH,
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frame_rate=OUT_RATE,
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channels=OUT_CHANNELS,
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)
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audio.export(file_name, format="wav")
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return file_name
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def speaking(status):
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# Initialize PyAudio
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p = pyaudio.PyAudio()
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# Open PyAudio stream
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stream = p.open(
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format=OUT_FORMAT, channels=OUT_CHANNELS, rate=OUT_RATE, output=True
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)
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audio_buffer = io.BytesIO()
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wf = wave.open(audio_buffer, "wb")
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wf.setnchannels(IN_CHANNELS)
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wf.setsampwidth(IN_SAMPLE_WIDTH)
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wf.setframerate(IN_RATE)
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total_frames = b"".join(st.session_state.frames)
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dur = len(total_frames) / (IN_RATE * IN_CHANNELS * IN_SAMPLE_WIDTH)
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status.warning(f"Speaking... recorded audio duration: {dur:.3f} s")
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wf.writeframes(total_frames)
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmpfile:
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with open(tmpfile.name, "wb") as f:
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f.write(audio_buffer.getvalue())
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file_name = tmpfile.name
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with st.chat_message("user"):
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st.audio(file_name, format="audio/wav", loop=False, autoplay=False)
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st.session_state.messages.append(
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{"role": "assistant", "content": file_name, "type": "audio"}
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)
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st.session_state.frames = []
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audio_bytes = audio_buffer.getvalue()
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base64_encoded = str(base64.b64encode(audio_bytes), encoding="utf-8")
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files = {"audio": base64_encoded}
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output_audio_bytes = b""
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with requests.post(API_URL, json=files, stream=True) as response:
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try:
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for chunk in response.iter_content(chunk_size=OUT_CHUNK):
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if chunk:
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# Convert chunk to numpy array
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output_audio_bytes += chunk
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audio_data = np.frombuffer(chunk, dtype=np.int8)
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# Play audio
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stream.write(audio_data)
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except Exception as e:
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st.error(f"Error during audio streaming: {e}")
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out_file = save_tmp_audio(output_audio_bytes)
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with st.chat_message("assistant"):
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st.audio(out_file, format="audio/wav", loop=False, autoplay=False)
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st.session_state.messages.append(
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{"role": "assistant", "content": out_file, "type": "audio"}
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)
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wf.close()
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# Close PyAudio stream and terminate PyAudio
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stream.stop_stream()
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stream.close()
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p.terminate()
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st.session_state.speaking = False
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st.session_state.recording = True
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def recording(status):
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audio = pyaudio.PyAudio()
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stream = audio.open(
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format=IN_FORMAT,
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channels=IN_CHANNELS,
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rate=IN_RATE,
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input=True,
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frames_per_buffer=IN_CHUNK,
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)
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temp_audio = b""
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vad_audio = b""
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start_talking = False
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last_temp_audio = None
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st.session_state.frames = []
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while st.session_state.recording:
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status.success("Listening...")
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audio_bytes = stream.read(IN_CHUNK)
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temp_audio += audio_bytes
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if len(temp_audio) > IN_SAMPLE_WIDTH * IN_RATE * IN_CHANNELS * VAD_STRIDE:
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dur_vad, vad_audio_bytes, time_vad = run_vad(temp_audio, IN_RATE)
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print(f"duration_after_vad: {dur_vad:.3f} s, time_vad: {time_vad:.3f} s")
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if dur_vad > 0.2 and not start_talking:
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if last_temp_audio is not None:
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st.session_state.frames.append(last_temp_audio)
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start_talking = True
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if start_talking:
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st.session_state.frames.append(temp_audio)
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if dur_vad < 0.1 and start_talking:
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st.session_state.recording = False
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print(f"speech end detected. excit")
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last_temp_audio = temp_audio
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temp_audio = b""
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stream.stop_stream()
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stream.close()
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audio.terminate()
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def main():
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st.title("Chat Mini-Omni Demo")
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status = st.empty()
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if "warm_up" not in st.session_state:
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warm_up()
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st.session_state.warm_up = True
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if "start" not in st.session_state:
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st.session_state.start = False
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if "recording" not in st.session_state:
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st.session_state.recording = False
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if "speaking" not in st.session_state:
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st.session_state.speaking = False
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if "frames" not in st.session_state:
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st.session_state.frames = []
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if not st.session_state.start:
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status.warning("Click Start to chat")
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start_col, stop_col, _ = st.columns([0.2, 0.2, 0.6])
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start_button = start_col.button("Start", key="start_button")
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# stop_button = stop_col.button("Stop", key="stop_button")
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if start_button:
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time.sleep(1)
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st.session_state.recording = True
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st.session_state.start = True
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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if message["type"] == "msg":
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st.markdown(message["content"])
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elif message["type"] == "img":
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st.image(message["content"], width=300)
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elif message["type"] == "audio":
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st.audio(
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message["content"], format="audio/wav", loop=False, autoplay=False
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)
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while st.session_state.start:
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if st.session_state.recording:
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recording(status)
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if not st.session_state.recording and st.session_state.start:
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st.session_state.speaking = True
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speaking(status)
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# if stop_button:
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# status.warning("Stopped, click Start to chat")
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# st.session_state.start = False
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# st.session_state.recording = False
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# st.session_state.frames = []
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# break
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if __name__ == "__main__":
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main()
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