Spaces:
Sleeping
Sleeping
File size: 2,236 Bytes
2e0ffd8 2071de1 a2f2a2c 2071de1 2e0ffd8 2071de1 a2f2a2c 2e0ffd8 2071de1 2e0ffd8 2071de1 2e0ffd8 2071de1 2e0ffd8 2071de1 2e0ffd8 2071de1 2e0ffd8 2071de1 a2f2a2c 556a36e 2071de1 556a36e 2e0ffd8 a2f2a2c 2e0ffd8 2071de1 2e0ffd8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
import gradio as gr
from huggingface_hub import InferenceClient
import soundfile as sf
from transformers import pipeline
import torch
# Initialize the client for the text generation model
client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
# Initialize the TTS pipeline from Huggingface
synthesizer = pipeline("text-to-speech", "Futuresony/output")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
# Prepare the messages for the chatbot
messages = [{"role": "system", "content": system_message}]
# Add history of previous conversation
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
# Generate the response from the model
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
# Convert the generated text to speech
speech = synthesizer(response)
# Save the generated speech to a file
sf.write("generated_speech.wav", speech["audio"], samplerate=speech["sampling_rate"])
# Return both the text and the audio for playback
return response, "generated_speech.wav"
# Create the Gradio interface with a textbox for the user to input a message
demo = gr.Interface(
fn=respond,
inputs=[
gr.Textbox(label="Type your message here", placeholder="Enter message...", lines=2),
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
],
outputs=[gr.Textbox(), gr.Audio()],
)
if __name__ == "__main__":
demo.launch()
|