--- title: DeepSeek Harness with AI Gateway product: vercel url: /docs/ai-gateway/coding-agents/deepseek canonical_url: "https://vercel.com/docs/ai-gateway/coding-agents/deepseek" last_updated: 2026-09-13 type: how-to prerequisites: - /docs/ai-gateway/coding-agents - /docs/ai-gateway related: - /docs/cli/ai-gateway - /docs/ai-gateway/observability-and-spend/observability - /docs/ai-gateway/sdks-and-apis/openai-chat-completions - /docs/ai-gateway/observability-and-spend/budgets summary: Connect DeepSeek Harness to AI Gateway with the Vercel CLI or a YAML provider and model shortlist. install_vercel_plugin: npx plugins add vercel/vercel-plugin --- # DeepSeek Harness with AI Gateway [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness) (`dsh`) is DeepSeek's terminal coding agent, built on the pi-ai LLM layer. You can configure it to use AI Gateway for unified model access and spend monitoring, while keeping its native model picker. ## Related pages > **For AI agents:** Follow these links to understand how this page connects to the rest of the Vercel ecosystem. For the full cross-link map (inbound, outbound, prerequisites, and semantic neighbors), see the .graph.md link below. - [Deep Agents CLI with AI Gateway](https://vercel.com/docs/ai-gateway/coding-agents/deepagents?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=related) — Connect Deep Agents CLI to AI Gateway with the Vercel CLI or a TOML provider and model profiles. - [AI Gateway](https://vercel.com/docs/agent-resources/vercel-mcp/tools/ai-gateway?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=related) — Vercel MCP tools for ai gateway. - [OpenHands with AI Gateway](https://vercel.com/docs/ai-gateway/coding-agents/openhands?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=related) — Connect OpenHands to AI Gateway with the Vercel CLI or an OpenAI-compatible LLM configuration. - [Continue CLI with AI Gateway](https://vercel.com/docs/ai-gateway/coding-agents/continue?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=related) — Connect Continue CLI to AI Gateway with the Vercel CLI or a YAML model configuration that reads your API key from the en - [Xcode with AI Gateway](https://vercel.com/docs/ai-gateway/ecosystem/framework-integrations/xcode?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=related) — Connect Xcode's AI chat to AI Gateway through the Chat Completions API. Configure the provider, API key, and models in X Full cross-link map for this page: [/docs/ai-gateway/coding-agents/deepseek.graph.md](/docs/ai-gateway/coding-agents/deepseek.graph.md?from=related&source_path=%2Fdocs%2Fai-gateway%2Fcoding-agents%2Fdeepseek&source_site=vercel-docs&relationship=graph) ## Set up with the Vercel CLI Run the [Vercel CLI setup command](/docs/cli/ai-gateway#setup) for DeepSeek Harness: ```bash filename="terminal" npx vercel ai-gateway setup --agent deepseek ``` The command writes an `llm-pi-ai` section to `$DSH_HOME/settings.yaml` naming `AI_GATEWAY_API_KEY` as the key environment variable, plus a model shortlist that leads with the newest DeepSeek models and follows with the gateway's most-used models. Re-run it to refresh the shortlist. ## Configuring DeepSeek Harness If you can't use the Vercel CLI, configure DeepSeek Harness manually: - ### Create an API key Go to the [**AI Gateway**](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai-gateway\&title=Go+to+AI+Gateway) section in the Vercel dashboard sidebar and click **API keys** to create a new API key. - ### Export the key Export the key in your shell: ```bash filename="Terminal" export AI_GATEWAY_API_KEY="your-ai-gateway-api-key" ``` To persist the key, add the same line to your shell's startup file. - ### Point DeepSeek Harness at the gateway Add the gateway provider to the `llm-pi-ai` section of `$DSH_HOME/settings.yaml` (default `~/.dsh/settings.yaml`): ```yaml filename="~/.dsh/settings.yaml" llm-pi-ai: providers: vercel-ai-gateway: apiKeyEnv: AI_GATEWAY_API_KEY models: - id: deepseek/deepseek-v4-flash name: DeepSeek V4 Flash - id: openai/gpt-6-astra name: GPT-6 Astra agent-default-model: provider: vercel-ai-gateway model: deepseek/deepseek-v4-flash ``` The shortlist under `models` drives the picker. Replace pi-ai's full catalog with the gateway models you want, and add any gateway model ID to it. `agent-default-model` picks the model DeepSeek Harness starts with. - ### Start DeepSeek Harness Open a new terminal so the key is loaded, then run: ```bash filename="Terminal" dsh ``` Headless runs use the gateway route too. Switch models with `/model` in a session. ### Monitor usage and spend View your usage, spend, and request activity in the [**AI Gateway**](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai-gateway\&title=Go+to+AI+Gateway) section in the Vercel dashboard sidebar. See the [observability documentation](/docs/ai-gateway/observability-and-spend/observability) for more details. ## Environment variables | Variable | Description | | -------------------- | ------------------------------------------------- | | `AI_GATEWAY_API_KEY` | Your AI Gateway API key, named by `apiKeyEnv`. Required | | `DSH_HOME` | Overrides the harness home directory. Defaults to `~/.dsh` | > **💡 Note:** DeepSeek Harness calls AI Gateway through the [OpenAI-compatible Chat > Completions API](/docs/ai-gateway/sdks-and-apis/openai-chat-completions), so > any model that supports Chat Completions works. ## Next steps - Browse the [models catalog](/ai-gateway/models) for available models - Configure [spend limits](/docs/ai-gateway/observability-and-spend/budgets) on your API key --- [View full sitemap](/docs/sitemap)