feat(embedding): make vector dimension configurable - #324

Motivation

Different embedding models produce vectors with different dimensions (e.g., intfloat/multilingual-e5-small uses 384, while intfloat/multilingual-e5-large uses 1024). Currently EverOS hard-codes _DIM = 1024 in LanceDB table schemas and build_embedding_provider, which prevents using smaller/larger embedding models without patching source code.

Changes

• Added dim field to EmbeddingSettings with env binding EVEROS_EMBEDDING__DIM.
• Added dim = 1024 default in default.toml.
• Updated build_embedding_provider to use settings.dim when no explicit dim is passed.
• Updated LanceDB table schemas (agent_case, agent_skill, atomic_fact, episode, foresight, knowledge_topic) to read _DIM from load_settings().embedding.dim instead of hard-coding 1024.

Backward compatibility

The default remains 1024, so existing configurations continue to work without changes.

Testing

• python -m py_compile passes for all modified Python files.
• The changes are minimal and do not alter behavior unless EVEROS_EMBEDDING__DIM or [embedding].dim is explicitly set.