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ruvnet / deepseek-chat

One-shot chat completion against DeepSeek's `deepseek-chat` model via the OpenAI-compatible /v1/chat/completions endpoint. Reads DEEPSEEK_API_KEY from the environment; degrades gracefully (exit 0 with a JSON status:degraded envelope) when the key is missing or the API is unreachable. Use for non-reasoning tasks — summarization, extraction, quick classification — where deepseek-reasoner would be overkill.

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Wraps DeepSeek's chat/completions endpoint in the same subprocess-invocation
shape as the other ruflo-*-harness skills (see ruflo-metaharness's
harness-score for the reference). No library import on ruflo's boot path.

When to use

  • You want a cheap, fast completion from a non-reasoning model.
  • The task fits in a single request/response — no multi-turn context.
  • You want the raw content back as JSON so downstream tooling can consume it.

  • For reasoning-heavy tasks (proofs, multi-step planning, hard debugging),
    use deepseek-reason instead — same plugin, different model.

Data handling

The prompt and any --system text are sent over the network to api.deepseek.com, a third party. Do not put secrets, credentials, personal data or proprietary code you are not allowed to share into them. The API key is read from DEEPSEEK_API_KEY in your shell only; never paste it into a prompt, a file or a command line.

Algorithm

Implementation: [`scripts/chat.mjs`](../../scripts/chat.mjs).

  1. Read DEEPSEEK_API_KEY from env. If missing, emit
    { status: 'degraded', reason: 'DEEPSEEK_API_KEY is not set', ... }
    and exit 0 (ADR-150-style graceful degradation).

  2. POST to https://api.deepseek.com/v1/chat/completions with
    { model, messages, temperature?, max_tokens? }. 60s hard timeout.

  3. Extract choices[0].message.content and usage counters.

  4. --format table prints only the content (for piping); --format json
    (default) returns the full envelope.

  5. --alert-on-error exits 1 on any degraded/error status (CI-friendly).

Example

node plugins/ruflo-deepseek-harness/scripts/chat.mjs \
  --prompt "In one sentence: what is HNSW?" \
  --temperature 0.2

Sample output:

{
  "status": "ok",
  "model": "deepseek-chat",
  "content": "HNSW is a graph-based approximate nearest neighbor …",
  "finishReason": "stop",
  "usage": { "promptTokens": 12, "completionTokens": 34, "totalTokens": 46 }
}