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import gradio as gr, os, json
from nlp_utils import transcribe_audio, summarize, extract_actions_decisions, make_minutes_md
OUT_DIR = "outputs"
os.makedirs(OUT_DIR, exist_ok=True)
def process(audio_file, transcript_text, meeting_title):
text = ""
if audio_file is not None:
text = transcribe_audio(audio_file)
if transcript_text and transcript_text.strip():
extra = transcript_text.strip()
text = (text + "\n" + extra).strip() if text else extra
if not text or len(text) < 40:
return "Please upload audio OR paste a transcript (≥ 40 characters).", "", [], [], None
resum = summarize(text)
ed = extract_actions_decisions(text)
actions = ed.get("actions", [])
decisions = ed.get("decisions", [])
title = meeting_title or "Meeting"
md = make_minutes_md(title, resum, actions, decisions)
md_path = os.path.join(OUT_DIR, "minutes.md")
with open(md_path, "w", encoding="utf-8") as f:
f.write(md)
actions_ht = [(a, "Action") for a in actions] if actions else []
decisions_ht = [(d, "Decision") for d in decisions] if decisions else []
return "Done ✅", resum, actions_ht, decisions_ht, md_path
with gr.Blocks(title="MeetingNotes AI — Meeting Summarizer") as demo:
gr.Markdown("# MeetingNotes AI — Meeting Summarizer")
gr.Markdown("Upload **audio** or **paste a transcript**, then click **Analyze**. Multilingual audio supported (EN/FR).")
with gr.Row():
with gr.Column():
meeting_title = gr.Textbox(label="Meeting Title", value="Product Launch — Weekly")
audio = gr.Audio(label="Audio (mp3/wav)", sources=["upload"], type="filepath")
transcript = gr.Textbox(label="Transcript (optional if audio)", lines=10, placeholder="Paste here…")
btn = gr.Button("Analyze")
with gr.Column():
status = gr.Textbox(label="Status")
resume = gr.Textbox(label="Summary", lines=8)
actions = gr.HighlightedText(label="Action Items", combine_adjacent=True)
decisions = gr.HighlightedText(label="Decisions", combine_adjacent=True)
files = gr.File(label="Download minutes.md")
btn.click(process, inputs=[audio, transcript, meeting_title], outputs=[status, resume, actions, decisions, files])
if __name__ == "__main__":
demo.launch()
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