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BrainGPT — Hugging Face Space (Gradio) build.
Web UI wrapper around pipeline_core. Runs on GPU automatically (A10G).
API keys come from Space Secrets, so end users don't need their own.
"""
import os, queue, threading, tempfile
import gradio as gr
import pipeline_core as pc
# Keys live as Space Secrets (Settings → Variables and secrets)
KEYS = {
"ANTHROPIC_API_KEY": os.getenv("ANTHROPIC_API_KEY", ""),
"MINIMAX_API_KEY": os.getenv("MINIMAX_API_KEY", ""),
"MINIMAX_GROUP_ID": os.getenv("MINIMAX_GROUP_ID", ""),
}
DEFAULT_VOICE = os.getenv("MINIMAX_VOICE_ID", "")
def _format_report(rep: dict) -> str:
lines = [
f"**Segments found:** {rep.get('total_segments', 0)}",
f"**Corrected by AI:** {rep.get('corrected_ok', 0)}",
f"**Voiced:** {rep.get('voiced_segments', 0)}",
]
st = rep.get("stages", {})
if st:
lines.append(f"**Transcribe:** {st.get('transcribe', 0)}s · "
f"**Render:** {st.get('render', 0)}s")
skipped = rep.get("skipped", [])
if skipped:
lines.append("\n**Skipped / notes:**")
lines += [f"- {s}" for s in skipped]
else:
lines.append("\n_Nothing skipped — full run ✓_")
return "\n".join(lines)
def process(video_path, voice_id, whisper_model, speed):
if not video_path:
raise gr.Error("Please upload a video first.")
missing = [k for k, v in KEYS.items() if not v]
if missing:
raise gr.Error("Server is missing API keys: " + ", ".join(missing) +
". (Owner: add them in Settings → Secrets.)")
if not voice_id.strip():
raise gr.Error("Enter a MiniMax voice ID.")
voice = {"voice_id": voice_id.strip(), "model": "speech-02-hd", "speed": float(speed)}
settings = {"whisper_model": whisper_model}
out_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4").name
q: queue.Queue = queue.Queue()
result = {}
def run():
try:
rep = pc.process_video(video_path, out_path, KEYS, voice, settings,
progress=lambda s, d: q.put(("p", s, d)),
logfile=None)
result["report"] = rep
q.put(("done", None, None))
except Exception as e:
result["error"] = str(e)
q.put(("err", str(e), None))
threading.Thread(target=run, daemon=True).start()
yield None, "⏳ Starting…"
while True:
kind, a, b = q.get()
if kind == "p":
yield None, f"⏳ {a}: {b}"
elif kind == "done":
yield out_path, "✅ Done!\n\n" + _format_report(result["report"])
return
elif kind == "err":
raise gr.Error(a)
with gr.Blocks(title="BrainGPT", theme=gr.themes.Soft(primary_hue="violet")) as demo:
gr.Markdown("# 🎙 BrainGPT\nReplace your screen-recording voice with a clean AI voice, "
"synced to your video.")
with gr.Row():
with gr.Column(scale=1):
video_in = gr.Video(label="Screen recording", sources=["upload"])
voice_in = gr.Textbox(label="MiniMax Voice ID", value=DEFAULT_VOICE,
placeholder="your-voice-id")
model_in = gr.Dropdown(label="Transcription model",
choices=["base", "small", "large-v3-turbo"],
value="large-v3-turbo")
speed_in = gr.Slider(label="Voice speed", minimum=0.5, maximum=2.0,
value=1.0, step=0.05)
go = gr.Button("Generate", variant="primary")
with gr.Column(scale=1):
status = gr.Markdown("Upload a video and click Generate.")
video_out = gr.Video(label="Result (with AI voice)")
go.click(process, [video_in, voice_in, model_in, speed_in],
[video_out, status])
if __name__ == "__main__":
demo.queue().launch()
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