Spaces:
Sleeping
Sleeping
File size: 3,573 Bytes
220e80e dbd7a88 220e80e cdf90fa 220e80e cdf90fa 220e80e cdf90fa 220e80e |
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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
import gradio as gr
import openai
import os
import tempfile
openai.api_key = os.getenv("OPENAI_API_KEY")
def transcribe_audio(audio_file):
with open(audio_file, "rb") as f:
transcript = openai.audio.transcriptions.create(
model="whisper-1",
file=f
)
return transcript.text
def generate_response(conversation_history):
response = openai.chat.completions.create(
model="ft:gpt-4o-2024-08-06:personal::BA52Cq4i",
messages=conversation_history
)
reply = response.choices[0].message.content
return reply
def text_to_speech(text):
response = openai.audio.speech.create(
model="tts-1",
voice="alloy",
input=text,
)
temp_audio_path = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False).name
response.stream_to_file(temp_audio_path)
return temp_audio_path
def process_input(audio, text, conversation_history):
if not conversation_history:
conversation_history = [{"role": "system", "content": "You are a pilot assistant."}]
transcribed_text = ""
if audio:
transcribed_text = transcribe_audio(audio)
else:
transcribed_text = text or ""
if not transcribed_text.strip():
return (
"No text found. Please provide audio or type text.",
"Please provide text or record audio.",
None,
conversation_history
)
conversation_history.append({"role": "user", "content": transcribed_text})
generated_text = generate_response(conversation_history)
conversation_history.append({"role": "assistant", "content": generated_text})
audio_output = None
try:
audio_output = text_to_speech(generated_text)
except Exception:
pass
return transcribed_text, generated_text, audio_output, conversation_history
def update_chat_history(conversation_history):
return "\n".join(
f"{msg['role'].capitalize()}: {msg['content']}" for msg in conversation_history
)
with gr.Blocks() as demo:
gr.Markdown("# OpenAI Multi-turn Voice & Text Chat")
user_name = gr.Textbox(label="Enter your name")
with gr.Row():
audio_input = gr.Audio(
sources="microphone",
type="filepath",
label="Record Audio"
)
text_input = gr.Textbox(
label="Or Type Text",
placeholder="Enter text here..."
)
generate_btn = gr.Button("Generate Response")
conversation_history = gr.State([])
transcribed_textbox = gr.Textbox(
label="Transcribed Speech-to-Text",
interactive=False,
lines=1
)
output_text = gr.Textbox(
label="GPT Response",
interactive=False,
lines=2
)
output_audio = gr.Audio(
label="Generated Audio",
autoplay=True,
interactive=False
)
chat_history_display = gr.Textbox(
label="Conversation History",
interactive=False,
lines=3
)
generate_btn.click(
fn=process_input,
inputs=[audio_input, text_input, conversation_history],
outputs=[transcribed_textbox, output_text, output_audio, conversation_history]
).then(
fn=update_chat_history,
inputs=[conversation_history],
outputs=[chat_history_display]
)
end_conversation = gr.Button("End Conversation")
end_conversation.click(
fn=None,
inputs=[],
outputs=[],
js="() => { window.location.reload() }"
)
demo.launch(share=True)
|