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import gradio as gr
import tempfile, subprocess, requests
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain.chat_models import ChatOpenAI
from gtts import gTTS
from bs4 import BeautifulSoup
from PIL import Image, ImageDraw
# OpenAI LLM (fast + accurate)
llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.3)
summary_prompt = PromptTemplate.from_template("""
Provide a crisp, promotional-style summary (under 50 words) of the following:
{text}
Summary:
""")
summary_chain = LLMChain(llm=llm, prompt=summary_prompt)
# Extract relevant content from article
def extract_main_content(url):
resp = requests.get(url, timeout=10)
soup = BeautifulSoup(resp.content, "html.parser")
for tag in soup(["nav", "header", "footer", "aside", "script", "style", "noscript"]): tag.decompose()
paras = [p.get_text() for p in soup.find_all("p") if len(p.get_text()) > 60]
return "\n".join(paras[:20]) or None
# Gradient background
def create_background(image_path, size=(1280,720)):
img = Image.new("RGB", size)
draw = ImageDraw.Draw(img)
for y in range(size[1]):
color = (10 + y//10, 20 + y//12, 50 + y//15)
draw.line([(0, y), (size[0], y)], fill=color)
img.save(image_path)
# AV generation logic with variable duration
def url_to_av_summary(url, duration):
content = extract_main_content(url)
if not content:
return "Failed to extract article content.", None
summary = summary_chain.run(text=content[:3000]).replace('"','')[:300]
audio_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3").name
gTTS(text=summary).save(audio_path)
bg_path = tempfile.NamedTemporaryFile(delete=False, suffix=".png").name
create_background(bg_path)
video_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4").name
cmd = [
'ffmpeg', '-y',
'-loop', '1', '-i', bg_path, '-i', audio_path,
'-vf', (
"drawtext=fontfile=/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf:text='" + summary +
f"':fontcolor=white:fontsize=48:box=1:[email protected]:boxborderw=5:x=(w-text_w)/2:y=h-(t*(h+text_h)/{duration})"
),
'-t', str(duration),
'-c:v', 'libx264', '-c:a', 'aac', '-pix_fmt', 'yuv420p', '-shortest', video_path
]
subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
return summary, video_path
iface = gr.Interface(
fn=url_to_av_summary,
inputs=[
gr.Textbox(label="Article URL"),
gr.Radio([5, 10], label="Video Duration (sec)", value=5)
],
outputs=[
gr.Textbox(label="Summary"),
gr.Video(label="Generated AV Summary")
],
title="🎞️ AV Summary Generator (OpenAI Powered)",
description="Generate a short AV video (5 or 10 seconds) summarizing any article. Uses OpenAI + gTTS + FFmpeg."
)
if __name__ == '__main__':
iface.launch()
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