Update app.py

app.py

@@ -1,49 +1,89 @@
 import gradio as gr
-from transformers import pipeline
 import PyPDF2
 import docx
 import requests
+from bs4 import BeautifulSoup
+from groq import Groq
+from gtts import gTTS
+from pydub import AudioSegment
+import os
+import io
 
-# 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
+# Initialize Groq client
+groq_client = Groq(api_key=os.environ["GROQ_API_KEY"])
+
+def extract_text(file_or_url):
+    if isinstance(file_or_url, str):  # URL
+        response = requests.get(file_or_url)
+        soup = BeautifulSoup(response.text, 'html.parser')
+        return soup.get_text()
+    elif file_or_url is not None:
+        if file_or_url.name.endswith('.pdf'):
+            reader = PyPDF2.PdfReader(file_or_url.file)
+            return ' '.join([page.extract_text() for page in reader.pages])
+        elif file_or_url.name.endswith('.docx'):
+            doc = docx.Document(file_or_url.file)
+            return ' '.join([para.text for para in doc.paragraphs])
     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."
+def generate_podcast_script(text):
+    prompt = f"""Generate a podcast script between a man and a woman discussing the following text:
+    {text}
+    The podcast should be informative and engaging, with a natural conversation flow.
+    Limit the script to approximately 750 words to fit within a 5-minute podcast."""
+
+    response = groq_client.chat.completions.create(
+        messages=[
+            {"role": "system", "content": "You are an AI assistant that generates podcast scripts based on given text."},
+            {"role": "user", "content": prompt}
+        ],
+        model="llama-3.1-70b-versatile",  # Using LLaMa 3.1 70B model
+        max_tokens=1000,
+        temperature=0.7
+    )
+    return response.choices[0].message.content
+
+def text_to_speech(script):
+    lines = script.split('\n')
+    audio_segments = []
+    for line in lines:
+        if line.startswith("Man:"):
+            tts = gTTS(line[4:], lang='en', tld='co.uk')
+        elif line.startswith("Woman:"):
+            tts = gTTS(line[6:], lang='en', tld='com.au')
+        else:
+            continue
+        buffer = io.BytesIO()
+        tts.write_to_fp(buffer)
+        buffer.seek(0)
+        audio_segments.append(AudioSegment.from_mp3(buffer))
     
-    dialogue = f"Man: {input_text}\nWoman: {input_text} (response)"
-    audio = model(dialogue)
-    return audio
+    final_audio = sum(audio_segments)
+    final_audio = final_audio[:300000]  # Trim to 5 minutes (300,000 ms)
+    buffer = io.BytesIO()
+    final_audio.export(buffer, format="mp3")
+    buffer.seek(0)
+    return buffer
+
+def generate_podcast(file_or_url):
+    text = extract_text(file_or_url)
+    if not text:
+        return None, "Failed to extract text. Please check your input."
+    script = generate_podcast_script(text)
+    audio_file = text_to_speech(script)
+    return audio_file, script
 
 iface = gr.Interface(
     fn=generate_podcast,
     inputs=[
-        gr.inputs.File(label="Upload PDF or DOC"),
-        gr.inputs.Textbox(label="Or enter URL"),
+        gr.File(label="Upload PDF/DOC file"),
+        gr.Textbox(label="Or enter URL")
+    ],
+    outputs=[
+        gr.Audio(label="Generated Podcast"),
+        gr.Textbox(label="Podcast Script")
     ],
-    outputs=gr.outputs.Audio(label="Generated Podcast"),
+    title="Custom NotebookLM-type Podcast Generator (LLaMa 3.1 70B)"
 )
 
 iface.launch()