DeepSeek Harness creation and deployment

DeepSeek Harness creation mode is an agent creation method in Studio for configuring, previewing, and deploying a containerized agent runtime based on DeepSeek Harness. This mode generates a complete container project including a Dockerfile, configuration files, and a runtime adapter, which can be deployed directly to an AgentKit Runtime or exported as a ZIP for local build and execution.

This feature is currently in Beta; the configuration page displays a Beta badge.

When to use

Scenario	Suitability
Building agents with DeepSeek models	Run agents through the DeepSeek official models or compatible custom model services
Containerized deployment	Generate an independent DeepSeek Harness container project that deploys as an AgentKit Runtime callable via HTTP API
Custom model routing	Add multiple model providers and models, and configure sub-agent model selection policies

Creation entry point

On the Studio “Agents” page, click “Create agent” and select “Quick create” from the creation menu. In the agent type selection dialog, choose “DeepSeek Harness” and click “Continue” to enter the DeepSeek Harness configuration page.

Configuration

The configuration page is organized into sections, each corresponding to a category of native DeepSeek Harness settings. Fields left blank inherit the default values from the deployed image.

Session defaults

The default model, Agent preset, and permissions apply to new sessions. The preset must exist in the deployed Harness.

Setting	Configuration path	Default	Description
Default provider	`agent-default-model.provider`	`deepseek-official`	Default model provider; can be the built-in provider or an added custom provider
Default model	`agent-default-model.model`	`deepseek-flash`	Default inference model; options change with the selected provider
Default reasoning effort	`agent-default-model.reasoningEffort`	—	Reasoning effort level; custom providers’ models that do not declare reasoning levels use the server-side setting
Default Agent preset	`agent-presets.default`	`standard`	Agent preset name; options include `standard`, `minimal`, `ptc`, `cordis`, or a custom value
Default permission preset	`permission.defaultPreset`	`workspace-write`	Permission preset; options are `read-only`, `workspace-write`, `danger-full-access` (full access without approval prompts)

DeepSeek model service

Parameters for the DeepSeek official provider.

Setting	Configuration path	Default	Description
API key environment variable	`llm-deepseek.apiKeyEnv`	`DEEPSEEK_API_KEY`	Name of the environment variable holding the DeepSeek API key; enter only the variable name, the actual secret is supplied by the deployment environment
Base URL	`llm-deepseek.baseURL`	—	DeepSeek model service URL; must be HTTP or HTTPS without credentials in the URL
Thinking mode	`llm-deepseek.thinking`	—	Thinking mode toggle; options are `enabled` or `disabled`
Reasoning effort	`llm-deepseek.reasoningEffort`	`high`	Reasoning effort level; options are `off`, `low`, `high`, `max`
Output limit per request	`llm-deepseek.maxTokens`	`256000`	Maximum output tokens per request
Default context capacity	`llm-deepseek.defaultContextWindow`	`1000000`	Default context window size
Stream idle timeout	`llm-deepseek.streamIdleTimeoutMs`	`300000`	Idle timeout for streaming responses (milliseconds)

Custom model providers

Add custom model services with their endpoints, protocols, and model IDs, including compatible Volcengine and BytePlus services. Each custom provider includes:

Field	Description
Provider ID	Starts with a lowercase letter; may contain lowercase letters, digits, dots, underscores, and hyphens; reserved IDs (`deepseek-official`, `constructor`, `prototype`) are not allowed
Display name	Optional; defaults to the provider ID
Base URL	HTTP or HTTPS URL of the model service
API protocol	API protocol; options are `openai-completions`, `openai-responses`, `anthropic-messages`
API key environment variable	Name of the environment variable holding the provider’s API key

Each provider can configure multiple models with:

Field	Description
Model ID	Server-side model identifier
Display name	Optional model display name
Context capacity	Model context window size
Maximum output capacity	Maximum output tokens for the model

Command execution

Timeout and output limits for shell command execution.

Setting	Configuration path	Default	Description
Default execution timeout	`bash.timeoutMs`	`60000`	Default command execution timeout (milliseconds)
Maximum execution timeout	`bash.maxTimeoutMs`	`600000`	Maximum command execution timeout (milliseconds)
Output limit	`bash.maxOutputBytes`	`64000`	Command output limit (bytes)

Tool calls

Setting	Configuration path	Default	Description
Parallel tool-call limit	`agent-loop.maxParallelToolCalls`	—	Maximum parallel tool calls in a single tool-call loop

Sub-agent model selection

Controls which models sub-agents may select.

Setting	Configuration path	Default	Description
Enable model selection	`subagent-model-selection.enabled`	`false`	When enabled, sub-agents can only select models from the configured `allowedModels` list

When model selection is enabled, at least one provider/model pair must be added as an allowed model.

DeepSeek web search

Parameters for the DeepSeek native web search tool.

Setting	Configuration path	Default	Description
API key environment variable	`web-search-deepseek.apiKeyEnv`	`DEEPSEEK_API_KEY`	Name of the environment variable holding the search service API key
Search base URL	`web-search-deepseek.baseURL`	—	Search service URL
Search model	`web-search-deepseek.model`	`deepseek-v4-flash`	Model used for web search
API version	`web-search-deepseek.apiVersion`	`2023-06-01`	Search API version
Search output limit	`web-search-deepseek.maxTokens`	`4096`	Maximum output tokens for search results
Maximum search uses	`web-search-deepseek.maxUses`	`5`	Maximum number of web searches per task

Preview, export, and deploy

After configuration, the page footer provides three actions:

Action	Description
Preview	View generated project files in the code browser without building or deploying
Export configuration	Download generated project files as a ZIP archive
Deploy	Enter the deployment flow to deploy the project to an AgentKit Runtime

When configuration validation fails, the page highlights fields requiring correction and expands the corresponding sections for immediate fixes.

Deploy to AgentKit

Selecting deploy enters the deployment configuration page. The deployment flow matches custom creation: you can select the deployment region, network mode, and Runtime name. During deployment, Studio builds the container image through CodePipeline, pushes it to the container registry, and creates an AgentKit Runtime.

Deployment creates cloud resources and incurs costs. Verify the region, Runtime name, and required secret environment variables before proceeding.

The following secret environment variables are required during deployment (determined automatically from the configuration):

DEEPSEEK_API_KEY: API key for the DeepSeek official provider (required when using the default provider)
Custom provider secret environment variables: each custom provider has a corresponding secret environment variable that must be supplied at deployment

Secret values are passed through environment variables only at deployment time; they are never written to settings.yaml, the Dockerfile, or build arguments.

Container runtime

The deployed container is built from a Node.js image and installs the DeepSeek Harness npm package as the runtime base layer. The container runs as the node user with /workspace as the working directory. On startup, the exported settings.yaml is copied to the DeepSeek Harness configuration directory, ensuring each start uses the exported configuration to override any existing settings. The DeepSeek Harness native web service runs privately on 127.0.0.1:3080 inside the container. The runtime adapter is loaded as a native plugin and exposes HTTP endpoints on port 8000, which can be overridden via the _FAAS_RUNTIME_PORT or PORT environment variable.

HTTP endpoints

Endpoint	Method	Description
`/ping`	`GET`	Health check; returns `200` when ready, `503` while starting
`/invocations`	`POST`	Invoke the agent and return the response

POST /invocations request body:

Request body

{
  "prompt": "Hello",
  "session_id": "optional-session-id"
}

Success response:

Success response

{
  "response": "...",
  "session_id": "...",
  "agent_preset": "standard"
}

If a session already has an active invocation, 409 is returned. Malformed input returns 400. Agent execution timeout returns 504. If the agent turn does not complete successfully, 502 is returned. The default invocation timeout is 300 seconds, configurable via the DSH_INVOCATION_TIMEOUT_MS environment variable. Client disconnection or timeout cancels the active turn.

Persistence

Session and workspace files depend on mounted persistent storage. Without persistent storage, container replacement loses local sessions. Multi-replica deployments require session routing or shared storage.

Runtime gateway authentication protects the invocation API. When running locally, bind the container port to the loopback address. The adapter itself does not implement an additional authentication layer.

Local build and run

The exported project includes a Dockerfile that can be built directly. In the project directory:

docker build -t deepseek-harness-agent .

When using the default DeepSeek provider, set DEEPSEEK_API_KEY and run:

docker run --rm -p 127.0.0.1:8000:8000 -e DEEPSEEK_API_KEY deepseek-harness-agent

When using custom providers, also pass the corresponding secret environment variables with -e.

Never put secret values in the Dockerfile, settings.yaml, or build arguments. The .env.example file lists environment variable names only and is not loaded automatically.

Configuration scope

The editor covers common native DeepSeek Harness settings, including default model, preset, permissions, DeepSeek model service, custom model providers, command execution, tool calls, sub-agent model selection, and web search. Other native plugin and preset-file settings are outside the editor’s scope. Presets must exist in the deployed Harness; custom presets and extra plugins must be explicitly installed and added to the build context.

Overview

Get started

Core components

Observability

Extensions

Frontend

Security

Deployment

DeepSeek Harness creation and deployment

When to use

Creation entry point

Configuration

Session defaults

DeepSeek model service

Custom model providers

Command execution

Tool calls

Sub-agent model selection

DeepSeek web search

Preview, export, and deploy

Deploy to AgentKit

Container runtime

HTTP endpoints

Persistence

Local build and run

Configuration scope

​When to use

​Creation entry point

​Configuration

​Session defaults

​DeepSeek model service

​Custom model providers

​Command execution

​Tool calls

​Sub-agent model selection

​DeepSeek web search

​Preview, export, and deploy

​Deploy to AgentKit

​Container runtime

​HTTP endpoints

​Persistence

​Local build and run

​Configuration scope

When to use

Creation entry point

Configuration

Session defaults

DeepSeek model service

Custom model providers

Command execution

Tool calls

Sub-agent model selection

DeepSeek web search

Preview, export, and deploy

Deploy to AgentKit

Container runtime

HTTP endpoints

Persistence

Local build and run

Configuration scope