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import gradio as gr
import numpy as np
import io
from pydub import AudioSegment
import tempfile
import os
import base64
import openai
from dataclasses import dataclass, field
from threading import Lock
@dataclass
class AppState:
conversation: list = field(default_factory=list)
lock: Lock = field(default_factory=Lock)
client: openai.OpenAI = None
def create_client(api_key):
return openai.OpenAI(
base_url="https://llama3-1-8b.lepton.run/api/v1/",
api_key=api_key
)
def transcribe_audio(audio):
# This is a placeholder function. In a real-world scenario, you'd use a
# speech-to-text service here. For now, we'll just return a dummy transcript.
return "This is a dummy transcript. Please implement actual speech-to-text functionality."
def generate_response_and_audio(message, state):
if state.client is None:
raise gr.Error("Please enter a valid API key first.")
with state.lock:
state.conversation.append({"role": "user", "content": message})
try:
completion = state.client.chat.completions.create(
model="llama3-1-8b",
messages=state.conversation,
max_tokens=128,
stream=True,
extra_body={
"require_audio": "true",
"tts_preset_id": "jessica",
}
)
full_response = ""
audio_chunks = []
for chunk in completion:
if not chunk.choices:
continue
content = chunk.choices[0].delta.content
audio = getattr(chunk.choices[0], 'audio', [])
if content:
full_response += content
yield full_response, None, state
if audio:
audio_chunks.extend(audio)
audio_data = b''.join([base64.b64decode(a) for a in audio_chunks])
yield full_response, audio_data, state
state.conversation.append({"role": "assistant", "content": full_response})
except Exception as e:
raise gr.Error(f"Error generating response: {str(e)}")
def chat(message, state):
if not message:
return "", None, state
return generate_response_and_audio(message, state)
def process_audio(audio, state):
if audio is None:
return "", state
# Convert numpy array to wav
audio_segment = AudioSegment(
audio[1].tobytes(),
frame_rate=audio[0],
sample_width=audio[1].dtype.itemsize,
channels=1 if len(audio[1].shape) == 1 else audio[1].shape[1]
)
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio:
audio_segment.export(temp_audio.name, format="wav")
transcript = transcribe_audio(temp_audio.name)
os.unlink(temp_audio.name)
return transcript, state
def set_api_key(api_key, state):
if not api_key:
raise gr.Error("Please enter a valid API key.")
state.client = create_client(api_key)
return "API key set successfully!", state
with gr.Blocks() as demo:
state = gr.State(AppState())
with gr.Row():
api_key_input = gr.Textbox(type="password", label="Enter your Lepton API Key")
set_key_button = gr.Button("Set API Key")
api_key_status = gr.Textbox(label="API Key Status", interactive=False)
with gr.Row():
with gr.Column(scale=1):
audio_input = gr.Audio(source="microphone", type="numpy")
with gr.Column(scale=2):
chatbot = gr.Chatbot()
text_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
with gr.Column(scale=1):
audio_output = gr.Audio(label="Generated Audio")
set_key_button.click(set_api_key, inputs=[api_key_input, state], outputs=[api_key_status, state])
audio_input.change(process_audio, inputs=[audio_input, state], outputs=[text_input, state])
text_input.submit(chat, inputs=[text_input, state], outputs=[chatbot, audio_output, state])
demo.launch() |