chore: initialize EverOS 1.0.0

md-first memory extraction framework for AI agents.

Markdown is the single source of truth; SQLite holds state and LanceDB
provides the rebuildable vector + BM25 + scalar index. The codebase follows
a single-direction DDD layering (entrypoints -> service -> memory -> infra,
with component / core / config cross-cutting) enforced by import-linter.

Engineering surface:
- Coding conventions in .claude/rules/ (path-scoped) and workflows in
  .claude/skills/ (/commit, /new-branch, /pr).
- GitHub Actions CI runs make lint + test + integration; pre-commit mirrors
  the gates locally (ruff, hygiene hooks, gitlint commit-msg).
- Commit messages follow Conventional Commits, enforced by gitlint.
- make lint also enforces datetime two-zone discipline and OpenAPI drift.

tests/unit/test_component/test_embedding/test_factory.py

@@ -0,0 +1,46 @@
+"""``build_embedding_provider`` — settings validation + provider build."""
+
+from __future__ import annotations
+
+import pytest
+from pydantic import SecretStr
+
+from everos.component.embedding import (
+    OpenAIEmbeddingProvider,
+    build_embedding_provider,
+)
+from everos.config.settings import EmbeddingSettings
+
+
+def test_raises_when_model_missing() -> None:
+    s = EmbeddingSettings(model=None, api_key=SecretStr("k"), base_url="https://x")
+    with pytest.raises(ValueError, match="EVEROS_EMBEDDING__MODEL"):
+        build_embedding_provider(s)
+
+
+def test_raises_when_api_key_missing() -> None:
+    s = EmbeddingSettings(model="m", api_key=None, base_url="https://x")
+    with pytest.raises(ValueError, match="EVEROS_EMBEDDING__API_KEY"):
+        build_embedding_provider(s)
+
+
+def test_raises_when_base_url_missing() -> None:
+    s = EmbeddingSettings(model="m", api_key=SecretStr("k"), base_url=None)
+    with pytest.raises(ValueError, match="EVEROS_EMBEDDING__BASE_URL"):
+        build_embedding_provider(s)
+
+
+def test_builds_openai_embedding_provider_with_default_dim() -> None:
+    s = EmbeddingSettings(model="m", api_key=SecretStr("k"), base_url="https://x")
+    p = build_embedding_provider(s)
+    assert isinstance(p, OpenAIEmbeddingProvider)
+
+
+def test_custom_dim_passes_through() -> None:
+    s = EmbeddingSettings(model="m", api_key=SecretStr("k"), base_url="https://x")
+    p = build_embedding_provider(s, dim=512)
+    assert isinstance(p, OpenAIEmbeddingProvider)
+    # Provider stores dim on a private attr; assert via the public output shape
+    # only if straightforward. Skip introspection if attr name differs.
+    if hasattr(p, "_dim"):
+        assert p._dim == 512