v6.4.5
Usage
Docker Image
Multi-arch (linux/amd64, linux/arm64) images for this release are published to GHCR and Docker Hub.
Pull
GitHub Container Registry (GHCR):
docker pull ghcr.io/lcy362/free-short-video:6.4.5Docker Hub:
docker pull lcy362/free-short-video:v6.4.5Run
Data persistence: the app writes all generated videos, uploads and settings into
/app/.working_dirand/app/.agnes_configinside the container. A plaindocker runwithout a volume loses everything when the container is recreated. Mount these paths to your host so outputs survive restarts and can be exported.
Option A — bind mount to a host folder (recommended; files land directly in the folder):
mkdir -p ~/agnes-data/working ~/agnes-data/config
docker run -d -p 8765:8765 \
-e AGNES_API_KEY=<your-key> \
-v ~/agnes-data/working:/app/.working_dir \
-v ~/agnes-data/config:/app/.agnes_config \
ghcr.io/lcy362/free-short-video:6.4.5Your videos will be in ~/agnes-data/working/ on your machine.
Option B — named Docker volume (no host path needed; survives container recreation):
docker volume create agnes-working
docker volume create agnes-config
docker run -d -p 8765:8765 \
-e AGNES_API_KEY=<your-key> \
-v agnes-working:/app/.working_dir \
-v agnes-config:/app/.agnes_config \
ghcr.io/lcy362/free-short-video:6.4.5Export files from a named volume:
docker run --rm -v agnes-working:/data -v "$PWD":/out busybox cp -r /data/. /out/agnes-exportThen open http://localhost:8765.
Notes
- Prefer Docker Hub? Replace the image with
lcy362/free-short-video:v6.4.5. - The image already declares
VOLUMEfor both paths, sodocker run -p 8765:8765 <image>(no-v) keeps data only while you reuse the same container (stop/start); recreating the container starts fresh. AGNES_API_KEYcan also be set later in the Web UI; it is then stored in the mounted config volume.
npm
Use npx for a one-shot run or install globally:
# Quick run (no install):
npx free-short-video
# Global install:
npm install -g free-short-video
free-short-videoRequires Python 3.10+ and ffmpeg on your system.
On first run, a Python virtual environment is auto-created and dependencies are installed.
What's New
Features & Improvements
-
Agnes 3.0 Flash as default text model — all LLM-powered features (AI screenwriting, scene prompt generation, poetry splitting, manuscript segmentation) now use
agnes-3.0-flash, Agnes AI's latest reasoning model. It delivers more stable end-to-end task execution, stronger instruction following in long contexts, and higher-quality structured JSON output compared to the previousagnes-2.5-flash. -
Reasoning capability (transparent) — Agnes 3.0 Flash is a reasoning model that internally performs chain-of-thought before generating output. This happens transparently with no configuration needed; the API response format remains fully backward-compatible (
choices[0].message.content). -
Fallback model list updated — when the
/v1/modelsendpoint is unreachable, the application now falls back to["agnes-3.0-flash", "agnes-2.5-flash"]for text model selection, ensuring graceful degradation.
The agnes-2.5-flash model remains available in the model selector for users who prefer it. No action is required after upgrading.