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Let the model create its own vectors; batch extraction - #16
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- create tool: {"name": "create", "arguments": {"concept", "more", "less"}}.
The model writes two system prompts for the ends of a direction; Modulo
extracts the vector like the starters (20 questions, response mean, middle
layer, +-10 range) and reports the split-half agreement, warning below 0.5.
Created vectors last for the session: saved under vectors/<slug>/created/
and logged, but never written to registry.yaml (registry session entries),
so a model's wording never reaches another session's prompt. Up to 6 per
session.
- Vector names are normalized for every tool ('Self-Referential' ->
'self_referential', 'optimism!' -> 'optimism'); logs keep what the model
wrote as requested_concept.
- Extraction generates all responses in one left-padded batch: about 3 s per
vector instead of 55-75 s on a 4090, cosine 0.98-0.997 to one-at-a-time
vectors on Qwen2.5, Llama-3.1, OLMo-2 and Mistral v0.3. First-run starter
extraction uses it.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Until now the model could only steer with vectors registered before the session. This PR adds a
createtool, so it can make its own direction mid-session, and makes extraction about 20× faster so that creating one takes seconds.Changes
createtool:{"name": "create", "arguments": {"concept": "new_name", "more": "...", "less": "..."}}.vectors/<slug>/created/and logged with their prompts, file and sha256. They're never written toregistry.yaml(new registry session entries), so a model's wording never reaches another session's prompt.Self-Referentialbecomesself_referential, andoptimism!findsoptimism. Logs keep what the model wrote asrequested_concept.Testing
test_agent_logic,test_cli,test_chat).innovation(0.26) andopenness(0.31).daydreaming(0.76),self(0.71),playfulness(0.87) andunbridled(0.87). It first triedself-referential, which led to the normalisation.novelty(0.67) andexploration(0.62, 0.48).create.🤖 Generated with Claude Code