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dsh-llm-longcat

LongCat (LongCat-2.0) provider for DeepSeek Harness — 1M context, thinking mode, tool calling

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Language
TypeScript
Created
Aug 20, 2026
Updated
Aug 20, 2026
GitHub repo

Introduction

dsh-llm-longcat

LongCat adapter for the DeepSeek Harness LLM seam.

Adds LongCat-2.0 as a model provider: 1M context, thinking mode, tool calling.

Features

  • Thinking mode — recognizes LongCat's reasoning_content field and translates it into harness ReasoningBlocks
  • Tool calling — full function-calling support, with arguments kept a raw JSON string end to end
  • Multi-turn — replays reasoning_content on tool-call turns, as thinking-mode passback requires
  • Streaming — SSE with the usage-before-finish ordering the harness relies on
  • Credential seam — the key resolves per request from ctx.credentials or the environment; no secret in any config file

Supported models

ModelContextMax outputNotes
LongCat-2.01,048,576131,072text-only; thinking + tool calling

Facts from GET /openai/v1/models/LongCat-2.0, the only documented endpoint that reports supported_parameters. Tool calling is not mentioned on the chat-completions doc page and is only visible there.

Install

dsh plugin --profile default add github:ffyuuu/dsh-llm-longcat
export LONGCAT_API_KEY=...   # create one at https://longcat.chat/platform/api_keys

Installing a bundle lets the package's install scripts run on your machine, outside the sandbox the agent runs under. Pin a commit so a later push cannot change what executes:

dsh plugin --profile default add github:ffyuuu/dsh-llm-longcat#3dcb3b1b5870ba52baab053453bdbb28826e5f13

Then pick LongCat-2.0 in the model selector. The key may also be stored through the Web UI's Models page instead of the environment.

Config

- id: llm-longcat
  name: dsh-llm-longcat
  config:
    apiKeyEnv: LONGCAT_API_KEY   # default; resolved per request, never a literal key
    baseURL: https://api.longcat.chat/openai/v1  # optional; $LONGCAT_BASE_URL then the public API
    thinking: enabled            # optional deployment policy; `disabled` locks every request to off
    reasoningEffort: high        # optional; off | high — LongCat's switch is binary
    maxTokens: 131072            # optional per-request output cap
    defaultContextWindow: 1048576
    streamIdleTimeoutMs: 300000  # optional; five-minute default
    retryPolicy:                 # optional; omission uses bounded normal defaults
      mode: normal
      maxRetries: 3
    models:
      - id: LongCat-2.0
        contextWindow: 1048576

A llm-longcat: section in $DSH_HOME/settings.yaml overrides any field without a restart: base URL, catalog, request defaults, and idle budget all take effect on the next request, while an in-flight stream keeps the facts it started with.

Reasoning is binary, deliberately

LongCat controls thinking with thinking: {type: enabled|disabled} and does not accept OpenAI's top-level reasoning_effort — its supported_parameters lists the former and omits the latter. There is therefore no low/medium/high gradient to map, and this adapter offers exactly two levels rather than advertising controls that would collapse onto the same two request bodies:

Selected effortWire body
high ("Thinking"){"thinking": {"type": "enabled"}}
off{"thinking": {"type": "disabled"}}
(none named)resolves from config; still explicit

off serializes an explicit disabled rather than omitting the field — omitting it would hand the decision to LongCat's server-side default, which is not what selecting Off should mean. Requesting low, medium, or max fails with UNSUPPORTED_REASONING_EFFORT before any network I/O.

Wire-format notes

  • Tool-call deltas repeat id and name as explicit null. LongCat sends them on the opening delta and then null (not omitted) on every continuation, so a naive !== undefined guard blanks the assembled call's name. Verified on live traffic; pinned by a regression test.
  • Streaming only, with stream_options.include_usage always on. Usage may arrive attached to the finish chunk or as a trailing usage-only chunk; both are deferred to [DONE] so usage always precedes finish.
  • The first thinking-mode delta can be an empty string — it must not open a reasoning block.
  • Reasoning passback: on assistant turns that carried tool calls, reasoning_content is serialized back into history; on tool-call-free turns it is dropped (ignored anyway — saves tokens).
  • Assistant content is always a string, never null: the message is durable session history, and a null there would make later turns replay a body the endpoint can reject.
  • Cache accounting: prompt_tokens_details.cached_tokens maps to cacheReadTokens and is subtracted out of inputTokens to keep the harness's disjoint-count convention.

Errors

Non-2xx responses throw LlmError with stable codes. LongCat documents a dedicated 402 for exhausted token quota and puts insufficient_quota on 403, where most OpenAI-compatible providers use 429 — both are classified as QUOTA before the auth and rate-limit buckets, so a depleted balance is never reported as a bad key or retried as a transient rate limit.

ConditionCode
402, or quota detail at any statusQUOTA_EXCEEDED
401 / 403AUTH
429RATE_LIMIT
400 with context-overflow detailCONTEXT_WINDOW_EXCEEDED
other 400INVALID_REQUEST
5xxSERVER
no [DONE] / bad JSONSTREAM_CLOSED / MALFORMED_RESPONSE

A completed stream that opened no content blocks becomes a finish error with EMPTY_RESPONSE, which the shipped retry policy treats as retryable.

Tests

npm run typecheck   # against the published @deepseek-ai/dsh-llm types
npm test            # 30 unit tests over serialize + translate
npm run build       # emits lib/ and lib/types/
npm run test:e2e    # real API, needs LONGCAT_API_KEY, spends a few hundred tokens

test:e2e drives the built adapter's own serialize → SSE → translate pipeline against api.longcat.chat, so it verifies what the plugin actually sends rather than a hand-written approximation. It is what caught the null-name delta bug.

Limitations

  • No image input. LongCat-2.0 reports modality: text->text, so image content is refused before sending, naming the model.
  • No stop sequences. stop is absent from supported_parameters; passing one fails with UNSUPPORTED_OPTION rather than silently running past it.
  • Reasoning is binary — no low/medium/high gradient exists to map.

License

MIT