AdaptiqAI for DeepSeek Harness
Use your AdaptiqAI workspace in DeepSeek Harness: every model your workspace has lanes on, with native memory that keeps the whole conversation — up to 5 million tokens — and your Knowledge collections in any conversation. You sign in once, or create your account, in the browser; then pick a model and start, all from inside the harness. There are no keys to copy.
Welcome
Install
Needs DeepSeek Harness 0.2.0-rc.2 or a later 0.2 release.
- Open Plugins in the sidebar and choose Add plugin.
- Enter the package —
@adaptiqai/deepseek-harness, or the full path to a downloaded adaptiqai-deepseek-harness-<version>.tgz — and install it.
- A welcome card asks you to Connect AdaptiqAI. Your browser opens; you sign in (or create an account with GitHub, Google or email) and approve, and the harness picks it up by itself.
- A new account has no model yet: the same card shows the models on offer, with price, speed and memory. Choose one and how many lanes (conversations at once), then Get access and confirm in the browser. The model appears in the picker as soon as it is active.
In the DeepSeek Harness desktop app, use the Plugins page; it keeps its own profile, which the dsh command can't change. If you run dsh web from a terminal, the same install is:
dsh plugin --profile web add @adaptiqai/deepseek-harness
What you get
Your models, set up correctly. The model picker gets an AdaptiqAI group with exactly the models your workspace has lanes on. Each one comes with its real context window, its output limit and its own thinking levels, all read from the server — nothing in the plugin names a model.
Model picker Thinking levels
Memory you can see. A small pill next to the send button shows how much of the conversation AdaptiqAI holds (NCM · 25k of 5M). After each answer it shows how much came straight from memory (24.6k from memory). Click it to switch the conversation between Remember and Private, see the last reply's split, and add or remove knowledge.
Composer Memory popover
Settings → AdaptiqAI. Your workspace, the models and lanes with live running/waiting counts, memory use split into conversations and knowledge, whether new conversations are saved, and links to the console.
Settings
Knowledge. The Knowledge panel in the sidebar lists your collections. Use one in the open conversation with one click, or drop files to create a new collection; it is attached automatically when it is ready.
Knowledge New collection
One model per memory. AdaptiqAI builds a conversation's memory and each collection for one model, and they only work with that model. The Knowledge panel lists the collections that work with the model you are using first. Collections built for other models appear below, greyed out, each with Make available for . A collection can never be added to a conversation on the wrong model. If you switch the model in a conversation whose memory is on another model, a short note above the composer offers Switch back or Start fresh on .
Other models' collections Model notice
Notices that say what to do. If every lane is busy, the harness waits and retries by itself and tells you so. If the workspace has no lanes on a model, you get a Get access button. If memory is nearly full, you are told before it fills, with a way to clean up or continue privately. Where AdaptiqAI puts idle conversations to sleep to make room, one quiet line says so instead: nothing is deleted, and they wake when you use them. Then you are only told when nothing idle could sleep or your library is full, with a button to the console. If your sign-in expires, you are asked to sign in again.
Notices
Updates in one click. When a new AdaptiqAI release is out, a notice offers Update: the plugin installs it through the Plugins page's own installer and switches to it, without a restart where the harness allows. pnpm normally waits a day before it installs a new version; so that the update installs at once, the plugin first lists exactly that version of @adaptiqai/deepseek-harness under minimumReleaseAgeExclude in the profile's pnpm-workspace.yaml, replacing the version it listed before. Other packages keep pnpm's wait. If that file is laid out in a way the plugin can't edit safely, it is left alone and the update is offered a day after release, as before.
/adaptiq in the composer: status, signin, private, remember, knowledge, open, diagnostics, signout.
Get a model without leaving the harness. Settings → AdaptiqAI → Get a model (or Get access on any "no lanes" notice) lists what is on offer. You confirm, and pay when payment is by card, in the browser; the plugin follows the request and shows the model when it is ready.
Get a model Ready
Conversations as knowledge. Type @ in a message and pick another conversation: if it is on the same model, it is added to this conversation from memory (the model does not read it again as text), and it stays added for later messages. The memory pill says what was added. Or open the memory pill and choose Add: two tabs, Knowledge (your collections, newest first, the ones made in the last days marked New, the ones made for another model greyed with Make available here) and Conversations (recent ones on this model, named as in the sidebar); everything shows without typing, one click adds or removes. What a conversation uses shows as chips above the message box, × to stop using one, also before the first message. A private conversation adds nothing; a conversation you mention there is read as text.
Conversations
Agent tools. Agents can find and attach knowledge (adaptiq_knowledge), check shared memory and offer clean-up options (adaptiq_memory), and save what they learned as a new collection (adaptiq_create_knowledge). After reading a sizeable set of files, or when you say remember, save, collection or NCM, the agent searches your knowledge and offers to save the material as a collection; on your yes it creates it and confirms in one sentence, in your language. Its chip shows a quiet progress line while it compiles and a short notice says when it is ready. The agent never shows ids or technical status. If it saved something with a mistake, saving again corrects the same collection instead of making a second one, and it can take back a collection it made in this conversation in the last 15 minutes; it never deletes anything else. The whole journey, with what still needs the server, is in docs/CONTEXT_MANAGEMENT.md.
How it works
- Requests go to the AdaptiqAI OpenAI-compatible API. Each request carries the harness conversation id (
X-Adaptiq-Session-Id), so the server keeps one memory per conversation. Title requests carry no id, so they never fork a saved conversation.
- Subagents and teammates also name the conversation that started them (
X-Adaptiq-Parent-Session-Id), so the console shows them under it. A subagent is a helper of its parent; an Agent Teams teammate is a track, a line of work of its own (X-Adaptiq-Session-Role). A conversation you fork yourself names no parent.
- No compaction. AdaptiqAI keeps the full conversation, so the plugin reports the model's true context window and declines the harness's compaction requests — in Remember and in Private — with a plain explanation, said once rather than at every step. Nothing is ever summarised away, and nothing is sent to the server for it.
- Thinking levels come from each model's capability card (
adaptiq-model-capabilities-v1): the levels, the value that turns thinking off, the default and the request field. Models without a card fall back to Low/High/Extra high/Max only when their id names a reasoning model.
- Usage is reported the harness's way: tokens read from memory count as cache reads, so the harness's own counters (cost, cache hit) are right.
- Busy and preparing answers are retried by the harness, honouring the server's
Retry-After.
Privacy and security
- Sign-in uses the device flow: the plugin shows a short code, you approve in the browser, and the plugin receives a workspace credential. It is stored in the harness credential store (
$DSH_HOME/.credentials.yaml, readable only by you) and renews itself. Tokens never reach the browser page.
- The connection appears in the AdaptiqAI console under API keys as "DeepSeek Harness on "; revoking it there disconnects this computer only.
- Private conversations can still read memory and knowledge, but nothing new is saved.
/adaptiq diagnostics produces a report without any secrets that you can send to support.
Headless and CI
Without a browser, store an API key from the console under the credential reference ADAPTIQAI_API_KEY (for example as an environment variable). The plugin uses it whenever no one is signed in.
Configuration
Everything has a production default. To change something, add a row to your profile's cordis.patch.yml:
- id: adaptiq
name: '@adaptiqai/deepseek-harness'
config:
route: adaptiqai # provider id in the model picker
apiBase: https://api.adaptiqai.com
consoleUrl: https://memory.adaptiqai.com/memory
apiKeyEnv: ADAPTIQAI_API_KEY # headless credential reference
tools: true # agent tools
progressEvents: true # streamed "preparing" progress
streamIdleTimeoutSeconds: 900
Troubleshooting
- "AdaptiqAI models are hidden — another provider already uses the route". An older hand-made
adaptiqai provider exists in your profile (usually an llm-pi-ai entry in cordis.patch.yml). Remove that entry and restart the harness.
- Models missing. Open Settings → AdaptiqAI and press refresh; the list shows exactly what the workspace has lanes on.
- Anything else: run
/adaptiq diagnostics and send the report to support.
Development
pnpm install
npm install -g @deepseek-ai/dsh@0.2.0-rc.2 # the harness release the plugin targets (as CI does)
npm run link-dsh # link the installed DeepSeek Harness packages for types and tests
npm run build # lib/index.js (Host), lib/client.js (browser), Typert artifacts
npm test # unit tests
ADAPTIQ_LIVE=1 ADAPTIQAI_API_KEY=ak_live_… npx vitest run test/live.test.ts # one short live request
npm run pack:local # dist/adaptiqai-deepseek-harness-<version>.tgz
Layout: src/host (adapter, sign-in, workspace service, Remote controller, command, tools), src/client (React UI in the AdaptiqAI design), scripts/remote-spec.mjs (the Remote namespace; scripts/gen-typert.mjs turns it into the Typert artifacts the harness loads).
The UI uses PP Frama when it is installed on the computer. The package does not ship PP Frama (its licence does not allow it); otherwise it falls back to Manrope, an SIL Open Font License grotesk embedded in the browser bundle (licence in assets/fonts/Manrope-OFL.txt).
