Set up a private creative AI agent with OpenClaw and Venice

Start private: an isolated user account

The whole point of this setup is an AI workflow that stays private end to end. Venice is privacy-focused on the model side, but that does not make your local machine private if you hand an agent reckless access to everything or install random plugins.

The first concrete step is to create a brand new user account in your operating system dedicated to OpenClaw. The demo uses macOS. Running the agent under a separate user keeps it walled off from your everyday data, files, and workflows, so nothing personal is exposed to the tools the agent runs.

The four-step plan and choosing your models

The setup follows four moves: connect OpenClaw to Venice with an API key, verify OpenClaw can talk to Venice models directly, add Venice skills so the agent can use media and creative endpoints, then shape it into a real creative agent that turns a rough idea into hooks, scripts, audio, and video.

Venice offers two kinds of models through the same API. Open-source models run privately, and frontier closed-source models like Opus and GPT variants are accessed anonymized. The strategy is to default to the most private models and only widen to closed-source ones when you explicitly choose to.

Get your Venice API key and fund it

Go to Venice.ai, sign up or log in, then open the API section in the left sidebar. Click to generate an API key, give it a name (the demo uses "OpenClaw demo"), and create it. Copy the key immediately and store it somewhere safe, because it is shown only once. You can always generate a new one later.

If this is your first time using the Venice API, top up your account under purchase credits, paying with USD or crypto. You can also fund usage with DIEM, where one DIEM equals one dollar per day of credits, indefinitely. This single key is what gives OpenClaw access to the entire Venice endpoint library.

Install OpenClaw and harden the config

In the Venice API documentation, open the OpenClaw guide in the Guides section and copy the install command. Open a terminal and paste it to launch the installer. On a brand new user, confirm you have the packages and permissions you need first; the demo relies on Homebrew and NPM being available.

The installer asks several configuration questions. Enable the gateway token (it authenticates requests between OpenClaw components and the gateway service). Tighten the OpenClaw directory permissions to 700 so only your user can access it. Because this is an isolated, trusted user, you can also say yes to creating the local session store and the OAuth directory for credentials. Install the gateway service and select the Node runtime.

openclaw onboard

Run the onboarding command, accept the personal-use note, and choose quick start. For the model provider, scroll to Venice AI and paste your saved API key. OpenClaw then discovers the full Venice model catalog automatically.

Pick a default model and skip extra tools

Set your default model to Kimi K2.5, a strong general model with good coding, reasoning, and vision abilities. Other choices appear too, including Opus, Claude Sonnet, DeepSeek, Gemini, GLM, and GPT models. You can change the model for chat or specific tasks at any time, and the multimodal image and video models all run through the same Venice API even though they are not in this list.

During onboarding, do not give the agent access to external tools yet, and skip the channel selection. Venice already has Web Search and Web Scrape built into the API, so no external search provider is needed. If you want something like XSearch, you can get it by using XAI models through Venice. One API key covers all of it.

Understand skills and add media powers

An OpenClaw skill is a structured instruction pack that teaches the agent how to use a capability. At its simplest, a skill is a folder with a skill.md file describing what the skill is called, what it does, which tools or binaries it depends on, and how the agent should use it. You can write your own skills or use ones built by others. Skip skill configuration during onboarding; add them after the agent is connected.

When you launch the bot (the demo uses the web UI), you can ask it to acquire skills directly. Two skills matter here: Venice AI and Venice AI Media, the second adding image and video access. Tell the agent you are building a creative agent and want both, and it will fetch them from the Claw Hub.

Tell me what you can do based on the skills you just acquired.

After acquiring them, the agent reports abilities like text-to-speech, speech-to-text, embeddings for semantic search, image generation, upscaling, editing, image-to-video, and video transformation. You can review installed skills and browse the skill store from the Skills tab in the left sidebar.

Build the creative agent and run a demo

With both skills installed, the agent can reach Venice endpoints for text, image, audio, video, and editing. The demo opens a fresh session with a detailed prompt for chapter one of an alien-invasion story as a full multimedia piece: written text, narrated audio, and short video.

The prompt specifies the models to use for each part. It names the Quintry DTS text-to-speech family for narration, and Veo 3.1 full quality for video because it produces high quality output and can include audio dialogue. If you do not have a specific model in mind, you can simply ask the agent to find one with audio support. The prompt also asks for four to five scene-by-scene video prompts and an ending that leaves people wanting chapter two.

The agent prompts again for the API key, because the creative session does not reuse the key added during general setup. In a fully isolated local environment with no external tools connected, you can safely paste it, since it stays within that local environment. Video and long audio take time to generate, so the run takes a few minutes.

What gets produced from one key

When the run finishes, open the output folder. The agent saves the written chapter as a markdown file, a narrated audio file of that chapter, character and scene images, and videos built from those images, all organized in a static videos folder.

Every output came from one Venice API key hitting multiple endpoints, with no extra providers wired in. The same setup can be extended with more skills and more models as your workflow grows.

Key takeaways

• A dedicated, isolated OS user is what keeps the agent away from your personal data; Venice handles model-side privacy, you handle local exposure.
• One Venice API key gives OpenClaw access to text, image, audio, and video endpoints, including built-in Web Search, so you do not need separate providers.
• Harden the install: enable the gateway token, set directory permissions to 700, and only persist session and credential data on a trusted machine.
• Default to private open-source models, add the Venice AI and Venice AI Media skills, then specify exact models per task in your prompt for full creative output.