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import gradio as gr
from transformers import pipeline
import PyPDF2
import docx
import requests
# Load the Llama model from Groq Cloud
model = pipeline("text-to-speech", model="groq/llama-3.1-70b")
def extract_text_from_file(file_path):
if file_path.endswith('.pdf'):
with open(file_path, 'rb') as file:
reader = PyPDF2.PdfReader(file)
text = ""
for page in reader.pages:
text += page.extract_text()
return text
elif file_path.endswith('.docx'):
doc = docx.Document(file_path)
text = "\n".join([para.text for para in doc.paragraphs])
return text
return ""
def fetch_text_from_url(url):
response = requests.get(url)
return response.text if response.status_code == 200 else ""
def generate_podcast(uploaded_file=None, url=None):
if uploaded_file:
input_text = extract_text_from_file(uploaded_file.name)
elif url:
input_text = fetch_text_from_url(url)
else:
return "No input provided."
dialogue = f"Man: {input_text}\nWoman: {input_text} (response)"
audio = model(dialogue)
return audio
iface = gr.Interface(
fn=generate_podcast,
inputs=[
gr.inputs.File(label="Upload PDF or DOC"),
gr.inputs.Textbox(label="Or enter URL"),
],
outputs=gr.outputs.Audio(label="Generated Podcast"),
)
iface.launch() |