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v0.4.0 — GPT-6 Luna defaults and updated retrieval evaluation

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@zc277584121 zc277584121 released this 14 Oct 07:06
· 1 commit to main since this release
v0.4.0
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Learn about vigilant mode.

What's changed

  • Default generation tasks now use GPT-6 Luna through Responses with medium reasoning: triplet extraction, entity extraction, relationship reranking and answer generation.
  • Cache keys distinguish the Responses interface and reasoning effort. Incomplete, refused or empty Responses outputs are rejected instead of cached as successful answers.
  • Retrieval evaluation now compares Jev with GPT-6 Luna and official DeepSeek V4.1 Flash. The report retains the September/October 2026 evaluation timeline, reproducible Jev evidence and a link to superseded experiments.
  • Publishing now requires passing tests on Python 3.10 and 3.12, matching package/tag versions, and an isolated wheel installation check.

Upgrading

The default model changed from GPT-4o-mini to GPT-6 Luna. Custom OpenAI-compatible endpoints must support Responses when using GPT-6 models. Explicitly configured non-GPT-6 models retain Chat Completions; set VGRAG_LLM_MODEL explicitly to retain your chosen model. The OpenAI SDK minimum is now 1.66.0.

Reasoning defaults to medium and can be configured with VGRAG_LLM_REASONING_EFFORT. Existing cache files are preserved, but GPT-6 Responses requests use separate cache keys. DeepSeek is an evaluation baseline, not the runtime default. Frozen benchmark results are unchanged by the runtime migration.

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