Spaces:
Running
Running
File size: 3,161 Bytes
c494b72 efc0dfb 6ddb846 8647b8a d7d5bfb 00cf38b b0b323a 8647b8a b0b323a d7d5bfb 5d955d6 0987717 5d955d6 6ddb846 5d955d6 6ddb846 8647b8a 5d955d6 d7d5bfb 8647b8a d7d5bfb 8647b8a a9a2aff 8647b8a 6ddb846 8647b8a 6ddb846 d7d5bfb 8647b8a d7d5bfb |
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 |
from transformers import pipeline
import gradio as gr
from pytube import YouTube
import os
import openai
model = pipeline(model="SofiaK/dataset")
openai_api_key = os.getenv("OPENAI_API_KEY")
# Check if the API key is available
if openai_api_key is None:
raise ValueError(
"OpenAI API key is not set. Make sure to set it as a secret variable in Hugging Face Spaces."
)
openai.api_key = openai_api_key
def youtube_to_text(youtube_url):
video = YouTube(youtube_url).streams.filter(only_audio=True).all()
audio = video[0].download()
text = model(audio)["text"]
return text
with gr.Blocks() as demo:
with gr.Row():
gr.HTML(
value="<h1 style='text-align: center;'>Speech-To-Text transcription for Russian Language</h1>"
)
with gr.Row():
with gr.Column():
radio = gr.Radio(
choices=["Audio", "Youtube"],
label="Choose your input type: an audio or a youtube link",
value="Audio",
)
audio_input = gr.Audio(
sources=["upload", "microphone"], type="filepath", visible=True
)
youtube_input = gr.Textbox(
value="https://www.youtube.com/", label="Youtube Link", visible=False
)
btn = gr.Button("Transcript")
with gr.Column():
output = gr.Text(label="Model Output")
chatbot = gr.Chatbot()
msg = gr.Textbox(label="Ask a question!")
def make_visible(val):
audio_visible = val == "Audio"
return {
audio_input: {"visible": audio_visible, "__type__": "update"},
youtube_input: {"visible": not audio_visible, "__type__": "update"},
}
history_gpt = []
def respond(msg, chat_history):
history_gpt.append({"role": "user", "content": msg})
response = openai.chat.completions.create(
model="gpt-3.5-turbo", messages=history_gpt
)
history_gpt.append(
{"role": "assistant", "content": response.choices[0].message.content}
)
chat_history.append((msg, response.choices[0].message.content))
return "", chat_history
radio.change(make_visible, inputs=radio, outputs=[audio_input, youtube_input])
msg.submit(respond, [msg, chatbot], [msg, chatbot])
def transcript(audio_input, youtube_input, radio):
if radio == "Audio":
txt = model(audio_input)["text"]
else:
txt = youtube_to_text(youtube_input)
history_gpt.append(
{
"role": "system",
"content": "Here is a text in Russian that was transcripted from an audio or a video. The user will ask questions about this text such as to translate it to another language, to summarize it, or to get relevant information. By default respond in english, apart if the user tells you otherwise. Here is the text"
+ txt,
}
)
return txt
btn.click(
fn=transcript,
inputs=[audio_input, youtube_input, radio],
outputs=output,
)
demo.launch()
|