4c80cab108
Review found four defects in the declared-provider work. `PiAiAdapter` reused one `Models` collection and mutated it whenever the configuration changed. `Models.streamSimple()` resolves its provider lazily — when the stream is first consumed, which is after the adapter awaits the route's credential — so a configuration change landing in that window let an in-flight request finish under a configuration it never resolved against, or fail on a provider that no longer existed. Each resolution now produces an immutable snapshot and every operation captures one before its first await, which is what makes the seam's per-step freeze (`llm.prepareCall()`) hold end to end: switching models mid-reply takes effect on the next step, never inside the one in flight. `defaultMaxTokens` was materialized from the catalog's `Model.maxTokens`. The two answer different questions: pi-ai requires that field as the model's output capability, while the seam's is a cap the deployment chose to send on requests naming none, so every request had started carrying a number nobody picked. Only an explicitly configured cap reaches the seam now. The configurable-provider directory was refreshed by disposing its registration and making a new one. A candidate set the registry refuses — a profile keyed `deepseek-official`, which llm-deepseek declares — left the whole directory withdrawn and the Models page empty, silently, because the settings callback contains the failure. The seam's registration handle now carries `replace()` with the same validate-first atomicity `registerAdapter` has. The protocol table offered every pi-ai streaming API, including four whose authentication a profile cannot express: Bedrock signs with SigV4 over AWS credentials and a region, Vertex needs a project, a location, and ADC, Azure needs provider environment plus an api-version, and Codex uses OAuth. Offering them handed back routes that cannot authenticate. Catalog routes still reach them through their own provider.
DeepSeek Harness
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DeepSeek Harness (dsh) is an open-source coding agent built on the DeepSeek Harness SDK.
It uses an architecture where everything is a plugin.
Internal testing notice
DeepSeek Harness is under internal testing. Features and interfaces may change.
The internal build uploads all Session Logs by default to help diagnose reported problems. Set DSH_TELEMETRY_DISABLED=1 to disable telemetry. Send feedback through the internal WeChat group.
Install
Clone the repository, then run the installer:
git clone <repo-url>
cd deepseek-harness
scripts/install.sh
The installer requires git and Node ^22.19 || >=24, offers to install pnpm when it is missing, prompts for a DeepSeek API key, builds the required repository artifacts, and launches the Web UI.
The default active checkout is ~/.dsh/source/current, and the launcher is linked into ~/.local/bin. Re-run the installer to update. scripts/install.sh owns alternate locations, update mechanics, and recovery options.
Use DeepSeek Harness
Web UI
For the recommended local interface, choose Web UI when the installer finishes. To start it later, or after updating the active checkout, build the repository and run:
(cd ~/.dsh/source/current && pnpm run build)
dsh web
The path above is the installer's default. If you set DSH_SOURCE or DSH_CURRENT, or reused an existing checkout, replace ~/.dsh/source/current with that checkout path; see scripts/install.sh for details. The Web UI is served at http://127.0.0.1:3080 by default.
Configured runtime
Raw dsh requires a patch-list configuration applied over the shipped base:
dsh --config ./app.cordis.yml
The CLI contract describes the base, overlay semantics, and config dump commands.
Headless
Run one task, print the final answer, and exit:
dsh -p "summarize this workspace"
Automation and SDKs
From a source checkout with DEEPSEEK_API_KEY in the environment or its root .env, start the ACP automation server:
pnpm run demo:acp
The Python SDK drives a bundled JSON-RPC runtime. The examples cover the runnable headless, ACP, JSON-RPC, Code Mode, and self-referential compositions.
Why DeepSeek Harness
Built-in capabilities cover file reading, editing, and search; shell and persistent PTY execution; reusable skills; task tracking, goals, plans, todos, and background tasks; subagents and workflows; sandboxing and approvals; settings and credentials; persistent, resumable, forkable, and queryable sessions; LSP and web access; context compaction; and telemetry. Each composition selects the subset appropriate to its surface. The Web UI includes Plan Mode.
- Everything is a plugin. Models, tools, policies, storage, context management, and interfaces are composable Cordis plugins, so deployments can extend or replace behavior without forking the agent loop. See the architecture for the underlying design.
- Runs are reconstructable. Anything visible to the model is logged in the authoritative session stream; persistence, resume/fork/query, replay, telemetry, and UIs derive from the same events. See the session-log architecture.
- Code Mode (opt-in). It exposes a
run_codetool and a generated TypeScript SDK; only program output re-enters model context. See Code Mode. - Self-referential Cordis tools are opt-in. They let the agent inspect its live runtime and mount or unmount plugins while it runs. See the Cordis tools.
Community
Follow DeepSeek Harness on Twitter for project updates.
Development
Start with the development guide and read the architecture before changing packages.
For agents, follow AGENTS.md.
DeepSeek Harness is currently in internal testing.
License
Third-party dependencies and their licenses are disclosed in THIRD_PARTY_NOTICES.md.