OpenStoryline Install
Use this skill when the task is to install or repair a local source checkout of FireRed-OpenStoryline.
Keep the workflow deterministic:
- Confirm the repo path and read the current README.md and config.toml.
- Detect local prerequisites before changing anything.
- Prefer a local install unless the user explicitly asks for Docker or .
- Download resources only after Python dependencies succeed.
- Validate imports and config loading before claiming success.
- This skill assumes macOS, Linux, or WSL with a POSIX shell.
What This Skill Covers
- Clone the GitHub repo if needed
- Create a Python environment
- Install Python dependencies
- Download models and assets
- Fill model settings
- Start MCP and web servers
- Explain common installation/documentation gaps
Preconditions
Check these first:
Optional:
If
,
, or
are missing, install them through the OS package manager before continuing.
Examples:
-
macOS with Homebrew:
bash
brew install ffmpeg wget unzip
-
Debian/Ubuntu:
bash
sudo apt-get update
sudo apt-get install -y ffmpeg wget unzip
If no supported package manager or permission is available, stop and report the missing system dependency clearly.
Interpreter selection
First prefer any interpreter that already exists and passes version checks:
- A system Python
- An already available conda Python
- An already available pyenv Python , but only if basic stdlib modules work
Validate candidate interpreters before using them:
bash
/path/to/python -c "import ssl, sqlite3, venv; print('stdlib_ok')"
If no supported interpreter already exists, peferr conda fallback:
bash
conda create -y -n openstoryline-py311 python=3.11
conda run -n openstoryline-py311 python --version
conda run -n openstoryline-py311 python -m venv .venv
After a supported interpreter is found, always create a repo-local .venv and continue using .venv/bin/python for install, config validation, and service startup.
Do not duplicate the rest of the workflow for pyenv or conda unless the user explicitly asks to stay inside a conda environment.
Preferred Install Path
From the repo root:
bash
/path/to/python -m venv .venv
.venv/bin/python -m pip install --upgrade pip
.venv/bin/python -m pip install -r requirements.txt
bash download.sh
Notes:
- pulls both model weights and a large resource archive. It can take a long time and may resume after network drops.
- The resource download is required for a full local run, not just the Python package install.
Configuration
Before starting the app, update config.toml.
You can use scripts/update_config.py.
At minimum, fill:
bash
.venv/bin/python scripts/update_config.py --config ./config.toml --set llm.model=REPLACE_WITH_REAL_MODEL
.venv/bin/python scripts/update_config.py --config ./config.toml --set llm.base_url=REPLACE_WITH_REAL_URL
.venv/bin/python scripts/update_config.py --config ./config.toml --set llm.api_key=sk-REPLACE_WITH_REAL_KEY
.venv/bin/python scripts/update_config.py --config ./config.toml --set vlm.model=REPLACE_WITH_REAL_MODEL
.venv/bin/python scripts/update_config.py --config ./config.toml --set vlm.base_url=REPLACE_WITH_REAL_URL
.venv/bin/python scripts/update_config.py --config ./config.toml --set vlm.api_key=sk-REPLACE_WITH_REAL_KEY
Optional but common:
search_media.pexels_api_key
for searching media
- TTS provider keys under
generate_voiceover.providers.*
(choose one provider)
Verification
Run these checks before saying installation is complete:
bash
.venv/bin/pip check
PYTHONPATH=src .venv/bin/python -c "from open_storyline.config import load_settings; load_settings('config.toml'); print('config_ok')"
Also confirm key resources exist:
bash
test -f .storyline/models/transnetv2-pytorch-weights.pth
test -d resource/bgms
Start Services
There are two common paths. These are long-running processes. Do not wait for them to exit normally. Treat successful startup log lines or confirmed listening ports as success, and keep the services running in separate shells/sessions as needed.
Manual start:
bash
PYTHONPATH=src .venv/bin/python -m open_storyline.mcp.server
In a second shell:
bash
PYTHONPATH=src .venv/bin/python -m uvicorn agent_fastapi:app --host 127.0.0.1 --port 8005
Expected Outputs
After a successful install:
- exists
- MCP listens on the configured local port (commonly )
- Web listens on the configured web port (commonly , though defaults may differ)
Common Problems
is slow or interrupted
Symptom:
- Large downloads stall or reconnect
Fix:
- Let continue; it supports resume behavior here
- Verify extracted outputs instead of trusting the progress meter
Web/MCP server fails to bind
Symptom:
Fix:
- In agent sandboxes, request permission to open local listening ports
- Prefer over unless external access is required
Response Pattern
When reporting status to the user, separate:
- what is installed
- what is still downloading
- what config is still missing
- what address the service is listening on
Do not say "installation complete" if only the Python packages are installed but the resource bundle is still missing.