ssocean

ssocean / PPT_Pilot

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【PPT汇报Agent】An AI agent that can present, answer questions, and control slides in real time.

agent agentic-workflow ppt
17
2
100% credibility
Found Mar 30, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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PPT-Pilot is a localized interactive AI agent designed for academic group meeting presentations, integrating slide control, lecture script state machine, local ASR/TTS pipelines, and agent decision-making to automate full presentation workflows with interruption handling.

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AI-Generated Review

What is PPT_Pilot?

PPT_Pilot turns static PPT slides into a live AI presenter that reads speaker notes aloud, controls slides in real time, and fields questions via voice. Upload HTML pages numbered like pilot ppt templates (1.html for pilot plant design ppt, 2.html for pilot plant ppt basics), connect your viewer via WebSocket, and hit start—the agent handles pilot study ppt for nurses or ppt on pilot plant scale up techniques autonomously. It solves awkward solo rehearsals for thesis defenses, sales pitches, or ppt pilot demos by simulating audience Q&A with natural Chinese speech.

Why is it gaining traction?

Unlike basic TTS readers, it syncs voice, slides, and agent smarts: interrupt mid-present, ask about ppt pilotage or ppt pilotentest, and it jumps slides, answers briefly, then resumes. Real-time ASR catches "continue" or "go to page 6," while tools like presentation_jump_for_qa route questions to relevant slides on RTS or NAIDv2 datasets. Devs dig the low-friction setup—run.py fires up servers, web UI manages ASR/tts, no PowerPoint needed.

Who should use this?

PhD candidates practicing thesis defenses with ppt pilot study flows. Engineers demoing pilot plant ppt scale-ups to teams. Nurses or educators prepping interactive pilot ppt templates for training sessions where they need hands-free Q&A on real slides.

Verdict

Worth a spin for interactive PPT practice—neat agent controls and voice loop impress in demos—but 17 stars and 1.0% credibility scream early alpha: sparse docs, no tests, Chinese-only agent. Fork and harden it if you need production polish.

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