pi-ai resolves a request's apiKey override only through a provider that
declares an api-key method: resolveProviderAuth short-circuits to that
method when the override is present, and otherwise falls through to the
credential store and then to ambient discovery. A provider with no
api-key method at all therefore resolves to nothing, and the request
fails with "Provider is not configured" before any network I/O.
Two routes hit that. openai-codex ships OAuth alone, so moving off the
/compat dispatch broke a profile that names a key for it — the old path
handed the token straight to the provider. And a catalog route naming an
api was being rebuilt with the harness's own auth, so `openai: {api:
openai-completions}` stopped reading OPENAI_API_KEY, contradicting the
documented promise that omitting a credential keeps provider-native
discovery.
Auth is now one decision for both constructions. A catalog route keeps
its installed provider's auth, through an api override too: which
environment a provider reads belongs to the provider, not to the wire
format its models speak. A catalog provider with no api-key method gets
the harness method beside its own, but only when the profile names a
credential — a keyless codex profile keeps the honest refusal, since
this adapter holds no OAuth store to resolve through.
Materialization now spreads the installed entry instead of enumerating
the result, so a Model field this package does not model survives a
pi-ai upgrade; headers went missing from an nvidia route exactly that
way once already. providerInfo reports the configured displayName, which
also joins the registration facts so a rename re-registers rather than
leaving the old label in every selector. A refused registration swap
gets its own diagnostic naming the route, matching the directory swap
beside it.
The README documented endpoint interrogation this layer does not
implement, and still described unknown providers as kept-last-good after
they became legal declarations refused at the write point. The Agent
Note claimed per-model reasoning configurability the schema never had,
required capacities the route now defaults, and stated an apiKey
override that short-circuits unconditionally.
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.