Spaces:
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Sleeping
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import re
import tempfile
import time
import traceback
import gradio as gr
import httpx
import yt_dlp
try:
import spaces
except ImportError:
class spaces:
@staticmethod
def GPU(duration=60):
def decorator(fn):
return fn
return decorator
PROXY_BASE = os.environ.get("PROXY_BASE", "").rstrip("/")
PROXY_TOKEN = os.environ.get("PROXY_TOKEN", "")
from transcribe import transcribe_audio, unload_model as unload_whisper
from lecture_processor import summarize_lecture, generate_quiz
# LANGUAGES = {
# "Auto-detect": None,
# "English": "en",
# "Korean": "ko",
# "Japanese": "ja",
# "Chinese": "zh",
# "Spanish": "es",
# "French": "fr",
# "German": "de",
# "Italian": "it",
# "Portuguese": "pt",
# "Russian": "ru",
# "Arabic": "ar",
# "Hindi": "hi",
# }
def get_youtube_video_id(url: str) -> str | None:
"""Extract video ID from various YouTube URL formats."""
patterns = [
r"(?:youtube\.com/watch\?v=|youtu\.be/|youtube\.com/embed/)([a-zA-Z0-9_-]{11})",
]
for pattern in patterns:
match = re.search(pattern, url)
if match:
return match.group(1)
return None
def make_embed_html(video_id: str) -> str:
return f'<iframe width="100%" height="400" src="https://www.youtube.com/embed/{video_id}" frameborder="0" allowfullscreen></iframe>'
def download_youtube_audio(url: str) -> str:
"""Download audio from YouTube URL, returns path to wav file."""
tmp_dir = tempfile.mkdtemp()
output_path = f"{tmp_dir}/audio.wav"
ydl_opts = {
"format": "bestaudio/best",
"postprocessors": [{
"key": "FFmpegExtractAudio",
"preferredcodec": "wav",
}],
"outtmpl": f"{tmp_dir}/audio",
"quiet": True,
"no_warnings": True,
}
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
return output_path
LANGUAGES = {
"English": "en",
}
def make_status_html(step: int = 0, timing: str = "", error: str = "") -> str:
"""Step progress indicator. Steps: 0=idle, 1=download, 2=transcribe, 3=summarize, 4=quiz, 5=done."""
if error:
return f'<div class="status-bar error">{error}</div>'
if step == 0:
return ""
labels = ["Download", "Transcribe", "Summarize", "Quiz"]
items = []
for i, label in enumerate(labels):
s = i + 1
if s < step or step == 5:
cls, icon = "done", "✓"
elif s == step:
cls, icon = "active", "↻"
else:
cls, icon = "pending", str(s)
items.append(
f'<div class="step {cls}"><span class="num">{icon}</span>{label}</div>'
)
connector = '<div class="conn"></div>'
steps_html = connector.join(items)
timing_html = f'<div class="timing">{timing}</div>' if timing else ""
return f'<div class="status-bar"><div class="steps">{steps_html}</div>{timing_html}</div>'
@spaces.GPU(duration=120)
def _run_pipeline(audio_path: str, language: str):
"""Pipeline that yields (transcript, summary, quiz, step, timing) progressively."""
lang_code = LANGUAGES.get(language)
timings = {}
gr.Info("Transcribing audio with WhisperX...")
try:
t0 = time.time()
raw_text = transcribe_audio(audio_path, language=lang_code)
timings["Transcription"] = time.time() - t0
except Exception as e:
yield f"[Transcription error] {e}", "", "", 0, ""
return
if not raw_text:
yield "(no speech detected)", "", "", 0, ""
return
timing_str = " | ".join(f"{k}: {v:.1f}s" for k, v in timings.items())
yield raw_text, "", "", 3, timing_str
unload_whisper()
gr.Info("Generating summary with Gemma...")
try:
t0 = time.time()
summary = summarize_lecture(raw_text)
timings["Summarization"] = time.time() - t0
except Exception as e:
print(f"[ERROR] Summarization failed: {e}")
traceback.print_exc()
summary = f"[Summarization error] {e}"
timing_str = " | ".join(f"{k}: {v:.1f}s" for k, v in timings.items())
yield raw_text, summary, "", 4, timing_str
gr.Info("Generating quiz with Gemma...")
try:
t0 = time.time()
quiz = generate_quiz(raw_text)
timings["Quiz Generation"] = time.time() - t0
except Exception as e:
print(f"[ERROR] Quiz generation failed: {e}")
traceback.print_exc()
quiz = f"[Quiz generation error] {e}"
timing_str = " | ".join(f"{k}: {v:.1f}s" for k, v in timings.items())
total = sum(timings.values())
timing_str += f" | Total: {total:.1f}s"
yield raw_text, summary, quiz, 5, timing_str
def fetch_audio_from_proxy(url: str) -> str:
"""Request audio extraction from proxy, save to tmp file, return path."""
headers = {"x-proxy-token": PROXY_TOKEN} if PROXY_TOKEN else {}
with httpx.stream(
"POST",
f"{PROXY_BASE}/extract",
json={"url": url, "audio_format": "best"},
headers=headers,
timeout=600,
) as resp:
resp.raise_for_status()
tmp_dir = tempfile.mkdtemp()
audio_path = f"{tmp_dir}/audio.wav"
with open(audio_path, "wb") as f:
for chunk in resp.iter_bytes(chunk_size=8192):
f.write(chunk)
return audio_path
def process_youtube(url: str, language: str):
"""Yields (embed, transcript, summary, quiz, status_html) progressively."""
if not url or not url.strip():
yield "", "", "", "", ""
return
url = url.strip()
video_id = get_youtube_video_id(url)
if not video_id:
yield "", "", "", "", make_status_html(error="Please enter a valid YouTube URL")
return
embed_html = make_embed_html(video_id)
yield embed_html, "", "", "", make_status_html(1)
try:
t0 = time.time()
if PROXY_BASE:
audio_path = fetch_audio_from_proxy(url)
else:
gr.Info("Downloading audio from YouTube...")
audio_path = download_youtube_audio(url)
dl_time = time.time() - t0
except Exception as e:
yield embed_html, "", "", "", make_status_html(error=f"Download failed: {e}")
return
yield embed_html, "", "", "", make_status_html(2, f"Download: {dl_time:.1f}s")
for raw_text, summary, quiz, step, timing_str in _run_pipeline(audio_path, language):
full_timing = f"Download: {dl_time:.1f}s | {timing_str}" if timing_str else ""
yield embed_html, raw_text, summary, quiz, make_status_html(step, full_timing)
EXAMPLES = {
"MIT OpenCourseWare": "https://www.youtube.com/watch?v=7Pq-S557XQU",
"Stanford CS229": "https://www.youtube.com/watch?v=jGwO_UgTS7I",
}
# ---------------------------------------------------------------------------
# ICL Gradio Theme
# ---------------------------------------------------------------------------
_icl_blue = gr.themes.Color(
c50="#F0F7FC",
c100="#D4EFFC",
c200="#A8DFFA",
c300="#5CC4F0",
c400="#00ACD7",
c500="#0091D4",
c600="#003E74",
c700="#002147",
c800="#001A38",
c900="#001029",
c950="#000A1A",
name="icl-blue",
)
_icl_tangerine = gr.themes.Color(
c50="#FFF5EB",
c100="#FFE6CC",
c200="#FFCC99",
c300="#FFB366",
c400="#FF9933",
c500="#EC7300",
c600="#CC6300",
c700="#A35000",
c800="#7A3C00",
c900="#522800",
c950="#331900",
name="icl-tangerine",
)
_icl_grey = gr.themes.Color(
c50="#F7F8F8",
c100="#EBEEEE",
c200="#D5D9D9",
c300="#B8BCBC",
c400="#9D9D9D",
c500="#7A7A7A",
c600="#5C5C5C",
c700="#4A4A4A",
c800="#373A36",
c900="#2A2D2A",
c950="#1A1C1A",
name="icl-grey",
)
ICL_THEME = gr.themes.Base(
primary_hue=_icl_blue,
secondary_hue=_icl_tangerine,
neutral_hue=_icl_grey,
font=[gr.themes.GoogleFont("Source Sans Pro"), "Arial", "sans-serif"],
font_mono=[gr.themes.GoogleFont("Source Code Pro"), "monospace"],
).set(
# Primary buttons β Navy background
button_primary_background_fill="#002147",
button_primary_background_fill_dark="#003E74",
button_primary_background_fill_hover="#003E74",
button_primary_background_fill_hover_dark="#0091D4",
button_primary_border_color="#002147",
button_primary_border_color_dark="#003E74",
button_primary_border_color_hover="#003E74",
button_primary_text_color="white",
button_primary_text_color_dark="white",
# Secondary buttons β white bg, blue border/text
button_secondary_background_fill="white",
button_secondary_background_fill_dark="#1A1C1A",
button_secondary_background_fill_hover="#D4EFFC",
button_secondary_background_fill_hover_dark="#001A38",
button_secondary_border_color="#003E74",
button_secondary_border_color_dark="#0091D4",
button_secondary_border_color_hover="#002147",
button_secondary_text_color="#003E74",
button_secondary_text_color_dark="#D4EFFC",
button_secondary_text_color_hover="#002147",
# Focus & loader
input_border_color_focus="#00ACD7",
input_border_color_focus_dark="#00ACD7",
loader_color="#003E74",
loader_color_dark="#0091D4",
)
# ---------------------------------------------------------------------------
# CSS β custom properties + minimal overrides
# ---------------------------------------------------------------------------
CSS = """
:root {
--icl-navy: #002147;
--icl-blue: #003E74;
--icl-process-blue: #0091D4;
--icl-pool: #00ACD7;
--icl-light-blue: #D4EFFC;
--icl-tangerine: #EC7300;
--icl-violet: #653098;
--icl-green: #02893B;
--icl-lime: #BBCE00;
--icl-red: #B22234;
--icl-grey: #EBEEEE;
--icl-cool-grey: #9D9D9D;
--icl-dark-grey: #373A36;
--sp-1: 4px; --sp-2: 8px; --sp-3: 12px; --sp-4: 16px;
--sp-5: 24px; --sp-6: 32px; --sp-7: 48px; --sp-8: 64px;
}
/* Header brand bar */
.icl-header {
text-align: center;
padding: var(--sp-5) var(--sp-4);
border-bottom: 3px solid var(--icl-navy);
margin-bottom: var(--sp-5);
}
.icl-header img { height: 60px; margin-bottom: var(--sp-2); }
.dark .icl-header { border-bottom-color: var(--icl-pool); }
/* Title & subtitle */
.main-title { text-align: center; color: var(--icl-navy); margin-bottom: 0 !important; }
.subtitle { text-align: center; color: var(--icl-blue); margin-top: 0 !important; }
.dark .main-title { color: var(--icl-light-blue); }
.dark .subtitle { color: var(--icl-pool); }
/* Tab selected override (Gradio tabs need !important) */
.tabs .tab-nav button.selected {
border-color: var(--icl-navy) !important;
color: var(--icl-navy) !important;
}
.dark .tabs .tab-nav button.selected {
border-color: var(--icl-pool) !important;
color: var(--icl-pool) !important;
}
/* Focus & active states */
button:focus-visible, input:focus-visible, textarea:focus-visible, select:focus-visible {
outline: 3px solid var(--icl-pool);
outline-offset: 2px;
}
button:active { transform: scale(0.97); }
/* Example buttons β compact inside bordered card */
.examples-row {
justify-content: center !important;
gap: var(--sp-2);
border: 1px solid var(--icl-light-blue);
border-radius: 8px;
padding: var(--sp-3) var(--sp-4);
background: var(--icl-grey);
}
.examples-row > * { flex: 0 0 auto !important; max-width: fit-content !important; }
.dark .examples-row { background: #1f2937; border-color: var(--icl-blue); }
/* Step progress indicator */
.status-bar {
padding: var(--sp-3) var(--sp-4);
border-radius: 8px;
background: var(--icl-grey);
border: 1px solid var(--icl-light-blue);
}
.status-bar.error {
background: #f8d7da;
border-color: #f5c6cb;
color: #721c24;
text-align: center;
font-weight: 500;
}
.status-bar .steps {
display: flex;
align-items: center;
justify-content: center;
gap: 0;
}
.status-bar .step {
display: flex;
align-items: center;
gap: 6px;
padding: 6px 14px;
border-radius: 20px;
font-size: 14px;
font-weight: 500;
background: var(--icl-light-blue);
color: var(--icl-blue);
white-space: nowrap;
transition: all 0.3s ease;
}
.status-bar .step.active {
background: var(--icl-blue);
color: white;
animation: pulse 1.5s ease-in-out infinite;
}
.status-bar .step.done {
background: var(--icl-navy);
color: white;
}
.status-bar .step .num {
font-weight: 700;
min-width: 18px;
text-align: center;
}
.status-bar .conn {
width: 24px;
height: 2px;
background: var(--icl-light-blue);
flex-shrink: 0;
}
.status-bar .timing {
text-align: center;
margin-top: var(--sp-2);
font-size: 13px;
color: var(--icl-blue);
}
@keyframes pulse {
0%, 100% { opacity: 1; }
50% { opacity: 0.6; }
}
/* Dark mode β status bar */
.dark .status-bar { background: #1f2937; border-color: var(--icl-blue); }
.dark .status-bar.error { background: #7f1d1d; border-color: #991b1b; color: #fca5a5; }
.dark .status-bar .step { background: var(--icl-blue); color: var(--icl-light-blue); }
.dark .status-bar .step.active { background: var(--icl-tangerine); color: white; }
.dark .status-bar .step.done { background: var(--icl-navy); color: var(--icl-light-blue); }
.dark .status-bar .conn { background: var(--icl-blue); }
.dark .status-bar .timing { color: var(--icl-light-blue); }
/* Footer */
.footer {
text-align: center;
color: var(--icl-dark-grey);
font-size: 0.85em;
margin-top: var(--sp-4);
}
.dark .footer { color: var(--icl-cool-grey); }
/* Reduced motion */
@media (prefers-reduced-motion: reduce) {
*, *::before, *::after {
animation-duration: 0.01ms !important;
animation-iteration-count: 1 !important;
transition-duration: 0.01ms !important;
}
}
/* Responsive */
@media (max-width: 768px) {
.icl-header img { height: 40px; }
.status-bar .step { padding: 4px 10px; font-size: 12px; }
.status-bar .conn { width: 12px; }
}
@media (max-width: 480px) {
.icl-header img { height: 32px; }
.icl-header { padding: var(--sp-3) var(--sp-2); }
}
"""
with gr.Blocks(
title="Lecture Processor",
css=CSS,
theme=ICL_THEME,
) as demo:
gr.HTML("""
<div class="icl-header">
<img src="https://upload.wikimedia.org/wikipedia/commons/5/51/Imperial_College_London_crest.svg"
alt="ICL Crest"
onerror="this.style.display='none';">
</div>
""")
gr.Markdown("# Lecture Processor", elem_classes="main-title")
gr.Markdown(
"Transcribe, summarize, and generate quizzes from lectures",
elem_classes="subtitle",
)
with gr.Row():
youtube_input = gr.Textbox(
label="π YouTube URL",
placeholder="https://www.youtube.com/watch?v=...",
scale=3,
)
language_dropdown = gr.Dropdown(
choices=list(LANGUAGES.keys()),
value="English",
label="Language",
scale=1,
)
youtube_btn = gr.Button("βΆ Process Lecture", variant="primary", size="lg")
gr.Markdown("**Examples:**")
with gr.Row(elem_classes="examples-row"):
for name, url in EXAMPLES.items():
gr.Button(name, variant="secondary", size="sm", min_width=160).click(
fn=lambda u=url: u, outputs=[youtube_input]
)
status_output = gr.HTML()
video_embed = gr.HTML()
with gr.Tabs():
with gr.TabItem("Transcript"):
raw_output = gr.Textbox(
label="Raw Transcription", lines=12
)
with gr.TabItem("Summary"):
summary_output = gr.Textbox(label="Lecture Summary", lines=12)
with gr.TabItem("Quiz"):
quiz_output = gr.Textbox(label="Quiz Questions", lines=12)
gr.Markdown(
"Powered by **WhisperX** & **Gemma 3 4B** | Fine-tuned LoRA adapter",
elem_classes="footer",
)
outputs = [video_embed, raw_output, summary_output, quiz_output, status_output]
youtube_btn.click(
fn=process_youtube,
inputs=[youtube_input, language_dropdown],
outputs=outputs,
)
youtube_input.submit(
fn=process_youtube,
inputs=[youtube_input, language_dropdown],
outputs=outputs,
)
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", share=True)
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