A high-performance Python-based interface for running machine learning models and managing predictions via the Replicate API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install replicate
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install replicate using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Replicate Skill?
The Replicate skill provides a robust bridge between your AI agents and the Replicate cloud platform. Designed specifically for Openclaw Skills users, it allows for seamless model discovery and execution without external dependencies. By leveraging this tool, developers can integrate state-of-the-art ML models into their workflows, handling everything from text generation to image processing with minimal configuration.
This skill is part of the broader ecosystem of Openclaw Skills, ensuring that your agents can interact with external compute resources efficiently. It focuses on providing a clean, standard-library-only implementation that remains compatible with modern Python environments while delivering the full power of the Replicate inference engine.
Replicate Skill Use Cases
- Discover and search for machine learning models within the Openclaw Skills ecosystem.
- Trigger and monitor long-running AI predictions directly from your terminal or agent scripts.
- Browse curated collections of AI models to find the best fit for specific creative tasks.
- Retrieve hardware availability to optimize compute-heavy AI tasks based on available GPUs.
How Replicate Skill Works
- Authenticate with the Replicate platform using the required environment variable.
- Query the Replicate API to find specific model versions or curated collections.
- Submit prediction requests with JSON-formatted inputs to start the inference process.
- Track the status of active predictions and retrieve the final output once the processing is complete.
Replicate Skill Setup
To get started with this skill in your Openclaw Skills environment, ensure you have your API token ready:
# Set your API token as an environment variable
export REPLICATE_API_TOKEN='your_token_here'
# Run a search to verify the installation
python3 scripts/replicate.py search "text to image"
# Start a prediction for a specific model
python3 scripts/replicate.py run <version_id> '{"prompt":"a futuristic city"}'
Replicate Skill Data Schema & Taxonomy
The skill manages model data and prediction states using a structured approach consistent with Openclaw Skills requirements:
| Property | Description | Format |
|---|---|---|
| REPLICATE_API_TOKEN | Primary authentication key | Environment Variable |
| Model Version | The unique identifier for a specific ML model | String |
| Input Payload | Arguments required by the model (e.g., prompt, steps) | JSON Object |
| Prediction Status | Lifecycle state such as starting, processing, or succeeded | String |
Replicate Skill Advanced Features
- Zero-dependency architecture utilizing only Python 3.10 standard libraries.
- Real-time hardware status monitoring to check for available GPU resources on the Replicate platform.
- Full support for prediction lifecycle management including cancellation of stuck tasks.
- Deep integration with other Openclaw Skills for automated multi-model pipelines.
SKILL.md
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