Create app.py

app.py

@@ -0,0 +1,49 @@
+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()