Turn long videos into editor-ready cut plans.
This CLI wraps the Twelve Labs API and adds workflow commands for video upload, indexing waits, structured briefs, embeddings, and local clip cutting. Agents can go from a long source video to JSON or Markdown editing guidance without manually watching the whole file.
Quick Start
1. Install
See Install above.
2. Set Up Credentials
Get your API key from your API provider's developer portal. The key typically looks like a long alphanumeric string.
export TWELVELABS_X_API_KEY="<paste-your-key>"
You can also persist this in your config file at ~/.config/twelvelabs-video-understanding-pp-cli/config.toml.
3. Verify Setup
twelvelabs-pp-cli doctor
This checks your configuration and credentials.
4. Try Your First Command
twelvelabs-pp-cli assets list
5. Create an Editor Brief
Upload or register a video, wait for indexing, then produce an editor-ready plan:
twelvelabs-pp-cli upload-video --index-id IDX --file ./long-video.mp4 --wait --json
twelvelabs-pp-cli video-brief --video-id VIDEO_ID --format json --out edit-plan.json
twelvelabs-pp-cli video-brief --video-id VIDEO_ID --format markdown --out edit-plan.md
Use clips to cut local files from recommended_cuts when you have the source video:
twelvelabs-pp-cli clips --input ./long-video.mp4 --plan edit-plan.json --out ./clips
Unique Features
These capabilities aren't available in any other tool for this API.
Editor workflows
-
upload-video — Upload a local video file or register a public URL, then poll Twelve Labs until indexing reaches a terminal status.
Use this before analysis when you need the CLI to wait until the video is usable.
twelvelabs-pp-cli upload-video --index-id IDX --file ./long-video.mp4 --wait --json --dry-run
-
video-brief — Generate a deterministic JSON or Markdown editing plan with title, topics, hashtags, chapters, highlights, and recommended cuts.
Use this when you want to avoid manually watching a long video just to find the strongest moments.
twelvelabs-pp-cli video-brief --video-id VID --format json --json --dry-run
-
embed — Create a video embedding task from a local file or public URL and optionally wait for ready results.
Use this when you need embeddings for deeper search, matching, or semantic workflows.
twelvelabs-pp-cli embed --video-file ./long-video.mp4 --model marengo3.0 --wait --json --dry-run
-
clips — Cut local clip files with ffmpeg from a video-brief JSON plan without inventing timestamps.
Use this after video-brief when you have the source video locally and want clip files immediately.
twelvelabs-pp-cli clips --dry-run --json
Usage
Run twelvelabs-pp-cli --help for the full command reference and flag list.
Commands
analyze
Manage analyze
twelvelabs-pp-cli analyze - This endpoint analyzes your videos and creates fully customizable text based on your prompts, including but not limited to tables of content, action items, memos, and detailed analyses.
editor workflows
Higher-level commands for turning long videos into editing plans:
twelvelabs-pp-cli upload-video - Upload a local file or register a public URL with POST /tasks, then optionally wait until indexing reaches a terminal status.twelvelabs-pp-cli video-brief - Generate a deterministic JSON or Markdown plan with title, topics, hashtags, chapters, highlights, and recommended cuts. Uses /analyze when deprecated summary/gist endpoints are unavailable.twelvelabs-pp-cli embed - Create a video embedding task from a local file or URL and optionally wait for ready results.twelvelabs-pp-cli clips - Use local ffmpeg to cut files from a video-brief JSON plan without inventing timestamps.
assets
Manage assets
twelvelabs-pp-cli assets create - This method creates an asset by uploading a file to the platform. Assets are media files that you can use in downstream workflows, including indexing, analyzing video content, and creating entities.
Supported content: Video, audio, and images.
Upload methods:
- Local file: Set the
method parameter to direct and use the file parameter to specify the file.
- Publicly accessible URL: Set the
method parameter to url and use the url parameter to specify the URL of your file.
File size: 200MB maximum for local file uploads, 4GB maximum for URL uploads.
Additional requirements depend on your workflow:
Supported content: Video and audio
File size: 4GB maximum.
Additional requirements depend on your workflow:
- Search: Marengo requirements
- Video analysis: Pegasus requirements
- Create embeddings: Marengo requirements
twelvelabs-pp-cli assets delete - This method deletes the specified asset. This action cannot be undone.twelvelabs-pp-cli assets get-upload-status - This method provides information about an upload session, including its current status, chunk-level progress, and completion state.
Use this method to:
- Verify upload completion (
status = completed)
- Identify any failed chunks that require a retry
- Monitor the upload progress by comparing
uploaded_size with total_size
- Determine if the session has expired
- Retrieve the status information for each chunk
You must call this method after reporting chunk completion to confirm the upload has transitioned to the completed status before using the asset.
twelvelabs-pp-cli assets list - This method returns a list of assets in your account.
The platform returns your assets sorted by creation date, with the newest at the top of the list.
twelvelabs-pp-cli assets list-incomplete-uploads - This method returns a list of all incomplete multipart upload sessions in your account.twelvelabs-pp-cli assets report-chunk-batch - This method reports successfully uploaded chunks to the platform. The platform finalizes the upload after you report all chunks.
For optimal performance, report chunks in batches and in any order.
twelvelabs-pp-cli assets request-additional-presigned-urls - This method generates new presigned URLs for specific chunks that require uploading. Use this endpoint in the following situations:- Your initial URLs have expired (URLs expire after one hour).
- The initial set of presigned URLs does not include URLs for all chunks.
- You need to retry failed chunk uploads with new URLs.
To specify which chunks need URLs, use the
start and count parameters. For example, to generate URLs for chunks 21 to 30, use start=21 and count=10.
The response will provide new URLs, each with a fresh expiration time of one hour.
twelvelabs-pp-cli assets retrieve - This method retrieves details about the specified asset.
embed
Manage embed
twelvelabs-pp-cli embed create-text-image-audio-embedding -
This endpoint will be deprecated in a future version. Migrate to the Embed API v2 for continued support and access to new features.
This method creates embeddings for text, image, and audio content.
Ensure your media files meet the following requirements:
Parameters for embeddings:
- Common parameters:
model_name: The video understanding model you want to use. Example: "marengo3.0".
- Text embeddings:
text: Text for which to create an embedding.
- Image embeddings:
Provide one of the following:
image_url: Publicly accessible URL of your image file.image_file: Local image file.
- Audio embeddings:
Provide one of the following:
audio_url: Publicly accessible URL of your audio file.audio_file: Local audio file.
This method creates a new video embedding task that uploads a video to the platform and creates one or multiple video embeddings.
Upload options:
- Local file: Use the
video_file parameter
- Publicly accessible URL: Use the
video_url parameter.
Specify at least one option. If both are provided, video_url takes precedence.
Your video files must meet the requirements.
This endpoint allows you to upload files up to 2 GB in size. To upload larger files, use the Multipart Upload API
A task can have one of the following statuses:
processing: The platform is creating the embeddings.ready: Processing is complete. Retrieve the embeddings by invoking the GET method of the /embed/tasks/{task_id} endpoint.failed: The task could not be completed, and the embeddings haven't been created.
embed-v2
Manage embed v2
twelvelabs-pp-cli embed-v2 create-async-embedding-task - This endpoint creates embeddings for audio and video content asynchronously.
When to use this endpoint:
- Process audio or video files longer than 10 minutes
- Process files up to 4 hours in duration
Audio:
- Minimum duration: 4 seconds
- Maximum duration: 4 hours
- Maximum file size: 2 GB
- Formats: WAV (uncompressed), MP3 (lossy), FLAC (lossless)
Creating embeddings asynchronously requires three steps:
- Create a task using this endpoint. The platform returns a task ID.
- Poll for the status of the task using the
GET method of the /embed-v2/tasks/{task_id} endpoint. Wait until the status is ready.
- Retrieve the embeddings from the response when the status is
ready using the GET method of the /embed-v2/tasks/{task_id} endpoint.
When to use this endpoint:
- Create embeddings for text, images, audio, or video content
- Get immediate results without waiting for background processing
- Process audio or video content up to 10 minutes in duration
Do not use this endpoint for:
- Audio or video content longer than 10 minutes. Use the
POST method of the /embed-v2/tasks endpoint instead.
Images:
- Formats: JPEG, PNG
- Minimum size: 128x128 pixels
- Maximum file size: 5 MB
Audio and video:
- Maximum duration: 10 minutes
- Maximum file size for base64 encoded strings: 36 MB
- Audio formats: WAV (uncompressed), MP3 (lossy), FLAC (lossless)
- Video formats: FFmpeg supported formats
- Video resolution: 360x360 to 5184x2160 pixels
- Aspect ratio: Between 1:1 and 1:2.4, or between 2.4:1 and 1:1
Task statuses:
processing: The platform is creating the embeddings.ready: Processing is complete. Embeddings are available in the response.failed: The task failed. Embeddings were not created.
Invoke this method repeatedly until the status field is ready. When status is ready, use the embeddings from the response.
entity-collections
Manage entity collections
twelvelabs-pp-cli entity-collections create - This method creates an entity collection.twelvelabs-pp-cli entity-collections delete - This method deletes the specified entity collection. This action cannot be undone.twelvelabs-pp-cli entity-collections list - This method returns a list of the entity collections in your account.twelvelabs-pp-cli entity-collections retrieve - This method retrieves details about the specified entity collection.twelvelabs-pp-cli entity-collections update - This method updates the specified entity collection.
gist
Manage gist
twelvelabs-pp-cli gist -
This endpoint will be sunset and removed on February 15, 2026. Instead, use the POST method of the /analyze endpoint, passing the response_format parameter to specify the format of the response as structured JSON. For migration instructions, see the Release notes page.
This method analyzes videos and generates titles, topics, and hashtags.
indexes
Manage indexes
twelvelabs-pp-cli indexes create-index - This method creates an index.twelvelabs-pp-cli indexes delete-index - This method deletes the specified index and all the videos within it. This action cannot be undone.twelvelabs-pp-cli indexes list - This method returns a list of the indexes in your account. The platform returns indexes sorted by creation date, with the oldest indexes at the top of the list.twelvelabs-pp-cli indexes retrieve-index - This method retrieves details about the specified index.twelvelabs-pp-cli indexes update-index - This method updates the name of the specified index.
summarize
Manage summarize
twelvelabs-pp-cli summarize -
This endpoint will be sunset and removed. Use the POST method of the /analyze endpoint. Pass the response_format parameter to specify the format of the response as structured JSON. For migration instructions, see the Release notes page.
This endpoint analyzes videos and generates summaries, chapters, or highlights. Optionally, you can provide a prompt to customize the output.
tasks
Manage tasks
twelvelabs-pp-cli tasks create-video-indexing - This method creates a video indexing task that uploads and indexes a video in a single operation.
This separation provides better control, reusability of assets, and improved error handling. New implementations should use the new workflow.
Upload options:
- Local file: Use the
video_file parameter.
- Publicly accessible URL: Use the
video_url parameter.
Your video files must meet requirements based on your workflow:
video_search
Manage video search
twelvelabs-pp-cli video-search any-to - Use this endpoint to search for relevant matches in an index using text, media, or a combination of both as your query.
Text queries:
- Use the
query_text parameter to specify your query.
Media queries:
- Set the
query_media_type parameter to the corresponding media type (example: image).
- Specify either one of the following parameters:
query_media_url: Publicly accessible URL of your media file.query_media_file: Local media file.
If both query_media_url and query_media_file are specified in the same request, query_media_url takes precedence.
Composed text and media queries (Marengo 3.0 only):
-
Use the query_text parameter for your text query.
-
Set query_media_type to image.
-
Specify the image using either the query_media_url or the query_media_file parameter.
Example: Provide an image of a car and include "red color" in your query to find red instances of that car model.
Entity search (Marengo 3.0 only and in beta):
- To find a specific person in your videos, enclose the unique identifier of the entity you want to find in the
query_text parameter.
Output Formats
# Human-readable table (default in terminal, JSON when piped)
twelvelabs-pp-cli assets list
# JSON for scripting and agents
twelvelabs-pp-cli assets list --json
# Filter to specific fields
twelvelabs-pp-cli assets list --json --select id,name,status
# Dry run — show the request without sending
twelvelabs-pp-cli assets list --dry-run
# Agent mode — JSON + compact + no prompts in one flag
twelvelabs-pp-cli assets list --agent
Agent Usage
This CLI is designed for AI agent consumption:
- Non-interactive - never prompts, every input is a flag
- Pipeable -
--json output to stdout, errors to stderr
- Filterable -
--select id,name returns only fields you need
- Previewable -
--dry-run shows the request without sending
- Explicit retries - add
--idempotent to create retries and --ignore-missing to delete retries when a no-op success is acceptable
- Confirmable -
--yes for explicit confirmation of destructive actions
- Piped input - write commands can accept structured input when their help lists
--stdin
- Offline-friendly - sync/search commands can use the local SQLite store when available
- Agent-safe by default - no colors or formatting unless
--human-friendly is set
Exit codes: 0 success, 2 usage error, 3 not found, 4 auth error, 5 API error, 7 rate limited, 10 config error.
Health Check
twelvelabs-pp-cli doctor
Verifies configuration, credentials, and connectivity to the API.
Configuration
Config file: ~/.config/twelvelabs-video-understanding-pp-cli/config.toml
Static request headers can be configured under headers; per-command header overrides take precedence.
Environment variables:
| Name | Kind | Required | Description |
|---|
TWELVELABS_X_API_KEY | per_call | Yes | Set to your API credential. |
agentcookie (optional)
If you use agentcookie to sync secrets across machines, this CLI auto-adopts agentcookie-managed credentials with no extra setup. When the daemon writes to this CLI's config, twelvelabs-pp-cli doctor reports agentcookie: detected and auth-status labels the source as agentcookie. Skip this section if you don't use agentcookie - the CLI works the same as any other.
Troubleshooting
Authentication errors (exit code 4)
- Run
twelvelabs-pp-cli doctor to check credentials
- Verify the environment variable is set:
echo $TWELVELABS_X_API_KEY
Not found errors (exit code 3)
- Check the resource ID is correct
- Run the
list command to see available items
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