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