Storylinez: A modular library for narrative generation and story manipulation
Project description
Storylinez SDK
Build production-grade AI video workflows in Python.
Storylinez SDK gives you one client that covers:
- Project and media management
- Prompting and generation pipelines
- Storyboard and sequence control
- Rendering, sharing, and automation jobs
- V2 schema-aware workflow modules
Quick Navigation
Install
Install from PyPI:
pip install storylinez
Install from source:
git clone https://github.com/Storylinez-Official/Storylinez_SDK.git
cd Storylinez_SDK
pip install -e .
Authenticate
Create a .env file:
STORYLINEZ_API_KEY=api_your_key_here
STORYLINEZ_API_SECRET=your_secret_here
STORYLINEZ_ORG_ID=your_org_id_here
STORYLINEZ_BASE_URL=https://api.storylinezads.com
Initialize client:
import os
from dotenv import load_dotenv
from storylinez import StorylinezClient
load_dotenv()
client = StorylinezClient(
api_key=os.getenv("STORYLINEZ_API_KEY"),
api_secret=os.getenv("STORYLINEZ_API_SECRET"),
org_id=os.getenv("STORYLINEZ_ORG_ID"),
base_url=os.getenv("STORYLINEZ_BASE_URL", "https://api.storylinezads.com"),
)
5-Minute Quickstart
from storylinez import StorylinezClient
import os
from dotenv import load_dotenv
load_dotenv()
client = StorylinezClient(
api_key=os.getenv("STORYLINEZ_API_KEY"),
api_secret=os.getenv("STORYLINEZ_API_SECRET"),
org_id=os.getenv("STORYLINEZ_ORG_ID"),
)
# 1) Create project
project = client.project.create_project(
name="SDK Quickstart",
orientation="landscape",
purpose="Generate a short launch video"
)
project_id = project["project"]["project_id"]
# 2) Create prompt
client.prompt.create_text_prompt(
project_id=project_id,
main_prompt="Create a 30-second launch teaser for a productivity app",
document_context="Audience: founders and operators",
total_length=30,
)
# 3) Generate storyboard
storyboard = client.storyboard.create_storyboard_and_wait(
project_id=project_id,
deepthink=True,
timeout=300,
)
# 4) Build sequence
client.sequence.create_sequence(
project_id=project_id,
apply_template=True,
apply_grade=True,
)
# 5) Render final output
render = client.render.create_and_wait_for_render(
project_id=project_id,
timeout=1800,
target_width=1920,
target_height=1080,
subtitle_enabled=True,
)
print("Render status:", render.get("status"))
Module Map
All modules are available through StorylinezClient.
Core generation
| Module | What it handles |
|---|---|
project |
Project and folder lifecycle |
prompt |
Text/video prompt creation and updates |
storyboard |
Story generation and scene edits |
voiceover |
AI/custom voiceover management |
sequence |
Sequence timeline generation and refinement |
render |
Final render creation and render history |
Media and discovery
| Module | What it handles |
|---|---|
storage |
Upload, process, analyze, and manage files |
stock |
Stock media search and retrieval |
search |
Semantic and metadata search across media |
Organization and style
| Module | What it handles |
|---|---|
company_details |
Company profile data |
brand |
Brand presets, logos, and styling |
settings |
User defaults and settings |
user |
User info, storage, and usage data |
Utility and advanced workflows
| Module | What it handles |
|---|---|
tools |
AI tools (briefs, plans, trend analysis, scraper) |
utils |
Format metadata, utility jobs, prompt helpers |
v2_project |
V2 project media operations |
v2_context |
V2 docs and references |
v2_effects |
V2 effect catalog |
v2_schema |
V2 sequence/asset schemas |
v2_sequence |
V2 interactive sequence sessions |
v2_render |
V2 render lifecycle |
v2_share |
V2 share links |
pipeline_jobs |
Start and track V1/V2 one-shot pipelines |
data_collection |
YouTube collection and extraction jobs |
voice_library |
Voice catalog and TTS jobs |
Additional helper class:
PipelineClientinsrc/storylinez/pipeline.pyfor combined web scraping + brand extraction helper flow.
Detailed Documentation
New detailed docs are now available in documentation/:
- Documentation Hub
- Getting Started
- V1 End-to-End Workflow
- Module Usage Guide
- Advanced V2 and Automation
- Complete Method Reference (all public methods)
- Production Best Practices
Examples
Working scripts are in examples/:
project_examples.pystorage_examples.pyprompt_examples.pystoryboard_examples.pysequence_examples.pyrender_examples.pytools_examples.pyv2_project_examples.py
Guides
Tutorial-style docs are in guides/, including:
- API key setup and usage
- End-to-end platform workflows
- Organization/team management
- Prompting and editing guidance
- Publishing and support workflows
Platform Links
- Web app: https://app.storylinezads.com
- API docs: https://docs.storylinezads.com
- API endpoint: https://api.storylinezads.com
Requirements
- Python 3.6+
- Dependencies from package metadata (
setup.py)
Support
- Documentation: https://docs.storylinezads.com
- Platform help: https://app.storylinezads.com/help
- Email: support@storylinezads.com
License
MIT License. See LICENSE.rst.
Project details
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