openstoryline-install

# OpenStoryline Install

Use this skill when the task is to install or repair a local source checkout of FireRed-OpenStoryline.

Keep the workflow deterministic:

1. Confirm the repo path and read the current README.md and config.toml.
2. Detect local prerequisites before changing anything.
3. Prefer a local `venv` install unless the user explicitly asks for Docker or `conda`.
4. Download resources only after Python dependencies succeed.
5. Validate imports and config loading before claiming success.
6. 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 `.storyline` models and `resource/` assets
- Fill `config.toml` model settings
- Start MCP and web servers
- Explain common installation/documentation gaps

## Preconditions

Check these first:

- `git`
- Python `>= 3.11`
- `ffmpeg`
- `wget`
- `unzip`

Optional:

- `docker`
- `conda`

If `ffmpeg`, `wget`, or `unzip` 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:

1. A system Python `>= 3.11`
2. An already available conda Python `>= 3.11`
3. An already available pyenv Python `>= 3.11`, 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.

## Clone repository

If you don't have a local repository yet, clone the repository first.
```bash
git clone https://github.com/FireRedTeam/FireRed-OpenStoryline.git
cd FireRed-OpenStoryline
```

## 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:

- `download.sh` 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:

- `.venv/` exists
- MCP listens on the configured local port (commonly `127.0.0.1:8001`)
- Web listens on the configured web port (commonly `127.0.0.1:8005`, though `run.sh` defaults may differ)

## Common Problems

### `download.sh` is slow or interrupted

Symptom:

- Large downloads stall or reconnect

Fix:

- Let `wget` continue; it supports resume behavior here
- Verify extracted outputs instead of trusting the progress meter

### Web/MCP server fails to bind

Symptom:

- `operation not permitted` while binding `127.0.0.1` or `0.0.0.0`

Fix:

- In agent sandboxes, request permission to open local listening ports
- Prefer `127.0.0.1` over `0.0.0.0` 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.