- Add EmbeddingProvider ABC for pluggable embedding generation
- Implement SimpleWordEmbeddingProvider for lightweight semantic similarity
- Implement MockEmbeddingProvider for testing
- Add cosine_similarity utility function for vector comparison
- Create comprehensive Behave BDD tests for semantic context search
- Support configurable embedding providers (local/API)
- Enable relevance-based file selection using embeddings
- Full type annotations with no suppression
- Coverage >= 97% for all new code

Closes #5254

@@ -0,0 +167,4 @@
+        )
+        context.fragments.append(frag)
+
+

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+        """
+        self._embedding_dim = embedding_dim
+
+    def embed(self, text: str) -> Sequence[float]:

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+
+@given("I have two text embeddings")
+def step_have_two_embeddings(context):
+    """Create two text embeddings."""

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+    # Score fragments by similarity
+    scored = []
+    for frag in context.fragments:
+        frag_embedding = context.embedding_provider.embed(frag.content)

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+strategies. Supports both local models and API-based providers.
+
+Based on `docs/specification.md` ~line 25207-25216.
+"""

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+
+        Raises:
+            ValueError: If the text cannot be embedded.
+        """

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+"""Plugin management commands stub."""
+from __future__ import annotations
+
+import typer

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+        """
+        self._embedding_dim = embedding_dim
+
+    def embed(self, text: str) -> Sequence[float]:

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+    @property
+    def embedding_dimension(self) -> int:
+        """Return the dimension of the embedding vectors."""
+        return self._embedding_dim

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+        f"Similarity {context.similarity} out of range"
+    )
+
+

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+    """Initialize embedding provider configuration."""
+    context.config = {
+        "provider_type": "simple_word",
+        "vocab_size": 100,

@@ -0,0 +3,4 @@
+
+import typer
+
+app = typer.Typer(help="Manage plugins (install, enable, disable).")