dgx-spark-playbooks/community/cbag/README.md

Corporate Bullshit Agentic Generator (CBAG)

Generate a lip-synced talking-head video of someone delivering AI-written corporate buzzword nonsense — 100% locally on your DGX Spark. It's a remake of the old known project with an AI skew and demostrate voice cloning and fake video also for cybersecurity purposes.

Table of Contents

• Overview
• Instructions
• Troubleshooting

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Overview

Basic idea

CBAG is a fully local, GPU-native demo that turns a topic and a persona into a short video of a "person" delivering confident corporate nonsense. It chains four model families on a single DGX Spark:

1. Buzzword grammar — a deterministic generator seeds the nonsense (no GPU).
2. LLM refine — a local Ollama model (default qwen2.5:3b) rewrites it into an on-persona monologue (visionary CEO, McKinsey consultant, startup founder, thought leader).
3. Voice — Kokoro default voices, or your own cloned voice from a ~10 s sample (Qwen3-TTS).
4. Talking-head video — ComfyUI + Sonic + Stable Video Diffusion animate a portrait (a default face, or your uploaded photo) to lip-sync the speech.

Everything runs in one docker compose stack, exposed as a small web app. No cloud, no API tokens — a fun, honest stress-test of the Spark's unified memory (a 20B-class LLM, two speech models, and a video diffusion stack, warm at once).

What you'll accomplish

You'll install CBAG on your DGX Spark and generate a talking-head video from a topic + persona in your browser, optionally in your own cloned voice.

What to know before starting

• Basic command line and git usage
• Familiarity with Docker / Docker Compose and GPU containers
• That model weights are downloaded from their official sources on first install

Prerequisites

Hardware Requirements:

• NVIDIA Grace Blackwell GB10 Superchip system (DGX Spark / Dell GB10), 128 GB unified memory
• At least ~50 GB available storage (container images + model weights)

Software Requirements:

• DGX OS / Ubuntu 24.04 with CUDA 13
• Docker + Docker Compose v2 + NVIDIA Container Toolkit: docker compose version
• Git: git --version
• A web browser with access to https://<SPARK_IP>:8443

Ancillary files

All assets live in the CBAG repository (Apache-2.0): https://github.com/vitorallo/CBAG

Model weights are not bundled — scripts/fetch-models.sh downloads each from its official source at install time and verifies it by SHA-256. See the repo's MODELS.md for every model, its source, and its license.

Licensing note: the talking-head video models (Stable Video Diffusion and Sonic) are licensed for non-commercial use only, so the talking-head feature of this demo is non-commercial. The text and voice stages use permissive (Apache-2.0/MIT) models. See MODELS.md.

Time & risk

• Estimated time: 30–45 minutes (first build + model downloads)
• Risk level: Medium
  • Model downloads are large (~15–20 GB total) and may fail on flaky networks — build.sh is idempotent, just re-run it.
  • Port 443 is often taken by the pre-installed Dell demo, so CBAG serves HTTPS on 8443.
• Rollback: ./scripts/down.sh stops the stack; ./scripts/down.sh --purge also removes the model volumes.
• Last Updated: 06/21/2026
  • Initial release.

Instructions

Step 1. Verify system prerequisites

Confirm your DGX Spark meets the requirements.

uname -m                  # aarch64
docker compose version    # Compose v2
nvidia-smi                # GPU detected
df -h .                   # ~50 GB free

Step 2. Clone CBAG

git clone https://github.com/vitorallo/CBAG.git
cd CBAG

Step 3. Build (preflight + auto-configure + images + weights)

./scripts/build.sh

This auto-detects your box's LAN/Tailscale IPs and writes .env, generates a self-signed TLS cert for those addresses, builds the container images, and downloads all model weights from their official sources (each verified by SHA-256). No Hugging Face token is required for the default sources.

Step 4. Start the stack

./scripts/run.sh

It waits for the services to become healthy and prints the URL, e.g. https://<your-spark-ip>:8443.

Step 5. Generate

Open the printed https:// URL. On first visit, accept the self-signed certificate once (Advanced → Proceed) — HTTPS is required so the in-browser microphone (for voice cloning) works.

Pick a topic and a persona, then Generate. The text appears first, then the audio, then the talking-head video. Optionally upload a portrait (≥512 px) or record/upload a voice sample to clone your own voice.

Stop the stack any time with ./scripts/down.sh.

Troubleshooting

• Port 443 already in use — expected on a Spark (the pre-installed Dell demo owns it); CBAG serves HTTPS on 8443.
• Microphone is blocked — you must use the https://…:8443 URL (a secure context), not http://…:8000.
• First voice-clone is slow — the Qwen3-TTS model (~4 GB) downloads once on first use; the default Kokoro voices are instant.
• A weight download failed — re-run ./scripts/build.sh (it skips what's already present and verifies SHA-256).
• Render takes a while — talking-head render time scales with audio length; choose a short length for a snappy demo.