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ai-sdk-provider-dsh

已验证 · 实测可装 krislavten

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2026-08-13最近推送
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功能简介

AI SDK提供者:驱动dsh运行时,兼容v6/v7

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我们的评价
可用 — 实测通过,早期项目

AI SDK提供者:驱动dsh运行时,兼容v6/v7 实测能干净安装、正常启动。早期项目,但功能可用。

「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。

README

ai-sdk-provider-dsh

AI SDK provider that drives a DeepSeek Harness (dsh) runtime as a language model.

dsh is a full agent harness (agent loop, tools, skills, MCP, sessions) from DeepSeek AI. This provider wraps a dsh runtime subprocess behind the AI SDK LanguageModel interface, so you can drive a harness agent from AI SDK generateText / streamText the same way ai-sdk-provider-claude-code drives Claude Code — while keeping the AI SDK as the single orchestration surface.

Version Compatibility

This provider implements the LanguageModelV3 specification (specificationVersion: 'v3'), the interface shared across AI SDK majors. A single build serves both:

AI SDK @ai-sdk/provider Status
ai@^6 @ai-sdk/provider@^3 ✅ supported
ai@^7 @ai-sdk/provider@^4 ✅ supported (V3 models are first-class in v7)
Requirement Value
Node.js >=22.19
Module format ESM only
DeepSeek Harness family pinned exact 0.1.0-rc.6

Upstream status: dsh is in developer preview (0.1.0-rc.x); DeepSeek documents breaking changes as their release policy. This provider pins the harness SDK family to exact versions, so the runtime version is a deliberate platform-side decision — upgrade the pin explicitly, never by range drift.

Install

npm install ai-sdk-provider-dsh

The dsh runtime is bundled: the package ships a default runtime composition (runtime/cordis.yml) plus the dsh-jsonrpc-agent bin (via @deepseek-ai/dsh-sdk-jsonrpc-demo), and all runtime plugins are pinned exact versions in dependencies. A provider instance spawns a working runtime out of the box — no separate install.

Credentials come from the runtime's environment:

export DEEPSEEK_API_KEY=sk-...                                        # required
export DEEPSEEK_BASE_URL=https://api.deepseek.com                     # optional; any OpenAI-compatible gateway works

Quick Start

streamText (AI SDK v7)

import { streamText } from "ai";
import { createDsh } from "ai-sdk-provider-dsh";

const dsh = createDsh({
  runtime: { provider: "deepseek-official", model: "deepseek-v4-flash" },
});

const result = streamText({
  model: dsh.languageModel("deepseek-v4-flash"),
  instructions: "You are a coding agent.",
  prompt: "run the tests",
});

const text = await result.text;
console.log(text);

streamText (AI SDK v6)

import { streamText } from "ai";
import { createDsh } from "ai-sdk-provider-dsh";

const dsh = createDsh({ runtime: { provider: "deepseek-official", model: "deepseek-v4-flash" } });

const result = streamText({
  model: dsh.languageModel("deepseek-v4-flash"),
  system: "You are a coding agent.", // v6 name; v7 uses `instructions`
  prompt: "run the tests",
});

generateText

import { generateText } from "ai";
import { createDsh } from "ai-sdk-provider-dsh";

const dsh = createDsh({ runtime: { provider: "deepseek-official", model: "deepseek-v4-flash" } });
const { text } = await generateText({
  model: dsh.languageModel("deepseek-v4-flash"),
  prompt: "say hello",
});

Provider factory

const dsh = createDsh(options);        // returns the provider
dsh.languageModel("deepseek-v4-flash") // the LanguageModel
dsh("deepseek-v4-flash")               // callable alias (AI SDK provider convention)
await dsh.close();                     // tear down the runtime subprocess (idempotent)

Runtime Options

Option Default Meaning
provider required model provider route passed to the runtime handshake (deepseek-official, or a pi-ai catalog route)
model required model id passed to the runtime handshake
env inherits process.env environment for the runtime subprocess: credentials (DEEPSEEK_API_KEY), DEEPSEEK_BASE_URL, DSH_CWD, DSH_SESSION_ROOT, …
cwd process.cwd() subprocess working directory
configPath bundled runtime/cordis.yml a different cordis.yml composition
binPath bundled dsh-jsonrpc-agent a different runtime bin
command / args node + [bin, config] full custom launch vector (set both together)
maxTokens — positive output-token cap per root-agent request
requestTimeoutMs SDK default per-request timeout for the JSON-RPC transport
disposeEofGraceMs / disposeGraceMs SDK defaults subprocess teardown ladders (EOF → SIGTERM → SIGKILL)
sessionId fresh UUID fixed session id; keep it to continue one harness session across turns

The bundled runtime

The default composition (runtime/cordis.yml) exposes:

  • bash (foreground), read/write/edit (fs), subagent, todo_write — tools execute inside the harness
  • JSONL session persistence with automatic context compaction
  • $DSH_SYSTEM_PROMPT selects the deployment persona

For environments that cannot build node-pty (no Linux prebuild — e.g. minimal containers, WSL without libc6-dev), use the no-pty composition:

runtime: {
  provider: "deepseek-official",
  model: "deepseek-v4-flash",
  configPath: require.resolve("ai-sdk-provider-dsh/runtime/cordis.minimal.yml"),
}

How it works

  • Each provider instance spawns (lazily) one dsh runtime subprocess speaking stdio JSON-RPC (the dsh SDK protocol).
  • doGenerate / doStream translate AI SDK LanguageModelV3CallOptions into a dsh prompt, then map the runtime's session.event stream back into AI SDK stream parts (text-start/delta/end, reasoning-start/delta/end, tool-input-start/delta/end, tool-call, finish).
  • Tools execute inside the harness — the provider is a thin pass-through (like ai-sdk-provider-claude-code): tool calls surface as providerExecuted: true parts and the AI SDK never re-executes them.
  • Multi-turn sessions: one provider instance keeps one runtime subprocess; with a fixed sessionId, follow-up turns continue the same harness session (the runtime persists the session log). Verified end-to-end: turn 1 stores a secret code, turn 2 recalls it.
  • Abort: an aborted call surfaces the original abort reason (never a wrapped transport error); pre-aborted signals throw immediately; the abort listener is removed on completion.

Provider Metadata

Each response exposes dsh metadata under providerMetadata['dsh'] (AI SDK v7: result.finalStep.providerMetadata, or await stream.finalStep for streamText; v6: result.providerMetadata):

Field Type Meaning
sessionId string the harness session id this call ran on
turnId number? last observed turn number
terminalReason string? final turn end kind when not completed (aborted, error, max-tokens, blocked, interrupted)

Error Diagnostics

Errors from the runtime boundary are classified into AI SDK APICallErrors. A sanitized stderr tail is appended to the message so CLI failures are visible in logs:

dsh runtime subprocess failed: runtime exited | stderr (tail): ...; ...
import { generateText } from "ai";
import { createDsh, getErrorMetadata, isAPICallError } from "ai-sdk-provider-dsh";

try {
  await generateText({ model: dsh.languageModel("deepseek-v4-flash"), prompt: "Hello!" });
} catch (error) {
  if (isAPICallError(error)) {
    console.error(getErrorMetadata(error)?.stderr);
    console.error("retryable:", error.isRetryable);
  }
}

Classification map:

Runtime failure AI SDK error Retryable
TransportClosedError (subprocess died / stdio closed) APICallError ✅
RequestTimeoutError APICallError ✅
SdkProtocolError (wire violation) APICallError ❌
JsonRpcResponseError (runtime rejected request) APICallError ❌
Node spawn failure (ENOENT bin, …) APICallError only EAGAIN/EMFILE
Missing/invalid API key LoadAPIKeyError (via createAuthenticationError) —

Limitations

  • Requires Node.js >=22.19; ESM only.
  • No mid-turn cancel on the SDK wire: aborting a turn rejects the current call; the runtime subprocess and session log remain for follow-up turns. dsh.close() tears the subprocess down (EOF → SIGTERM → SIGKILL).
  • Skills use the dsh native mechanism (SKILL.md bundles discovered from .dsh/skills, .agents/skills, $DSH_HOME/skills) — the reskill skills.json/skills.lock convention is not applied by this provider.
  • Tool execution is harness-internal: AI SDK tools / toolChoice are not executed by the AI SDK; configure tools through the runtime composition (cordis.yml) or $DSH_* env.
  • Some AI SDK call options are accepted but not forwarded to the harness: temperature, topP, topK, stopSequences, seed — the harness owns sampling.
  • dsh is in developer preview; DeepSeek documents breaking changes as release policy. Pin the provider version and the harness family (0.1.0-rc.6) deliberately.
  • The bundled default runtime needs node-pty on Linux (compiled at install; no prebuild). Use cordis.minimal.yml (no bash) where that is unavailable.

Development

pnpm install
pnpm run check    # typecheck
pnpm run test     # unit tests (fake runtime) + e2e (real runtime, keyless replay)
pnpm run lint     # biome
pnpm run build    # tsup → dist/

Tests never need a real API key: unit tests drive a fake runtime with synthetic event streams (the ai-sdk-provider-claude-code philosophy), and e2e tests boot the real dsh runtime against recorded session fixtures replayed by @deepseek-ai/dsh-llm-replay.

Recording new fixtures (requires a live key)

DEEPSEEK_API_KEY=sk-... node scripts/record-fixture.mjs   # writes tests/fixtures/*.jsonl

License

MIT

安装

🧩 让 Agent 自动装(推荐)

装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:

dsh plugin add dshbase-catalog

然后对 agent 说「帮我装 ai-sdk-provider-dsh」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。

该插件是 GitHub 源码(未发 npm)——直接从仓库装:

Web profile:

dsh plugin --profile web add github:krislavten/ai-sdk-provider-dsh

Headless(CLI)profile:

dsh plugin --profile headless add github:krislavten/ai-sdk-provider-dsh

实测报告

验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。

使用场景

把一个新模型、provider 或路由策略接入循环,让 dsh 能为任务选对脑子。

适合谁

同时用多个模型或 provider、想让成本/质量/延迟自动平衡的人。

二次开发建议

provider 适配器和路由启发式是缝——加后端、调回退链,或加按任务的模型选择。

安全:尚未扫描——我们的每日静态扫描将很快覆盖它。

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