embed-db delete-collection command and .delete() method, closes #219

docs/embeddings/cli.md

@@ -167,3 +167,13 @@ Add `-d/--database` to specify a different database file:
 ```bash
 llm embed-db collections -d my-embeddings.db
 ```
+## llm embed-db delete-collection
+
+To delete a collection from the database, run this:
+```bash
+llm embed-db delete-collection collection-name
+```
+Pass `-d` to specify a different database file:
+```bash
+llm embed-db delete-collection collection-name -d my-embeddings.db
+```

docs/embeddings/python-api.md

@@ -104,6 +104,7 @@ A collection instance has the following properties and methods:
 - `similar(query: str, number: int=10)` - returns a list of entries that are most similar to the embedding of the given query string
 - `similar_by_id(id: str, number: int=10)` - returns a list of entries that are most similar to the embedding of the item with the given ID
 - `similar_by_vector(vector: List[float], number: int=10, skip_id: str=None)` - returns a list of entries that are most similar to the given embedding vector, optionally skipping the entry with the given ID
+- `delete()` - deletes the collection and its embeddings from the database
 
 (embeddings-python-similar)=
 ## Retrieving similar items

docs/help.md

@@ -463,8 +463,9 @@ Options:
   --help  Show this message and exit.
 
 Commands:
-  collections  Output the path to the embeddings database
-  path         Output the path to the embeddings database
+  collections        Output the path to the embeddings database
+  delete-collection  Delete the specified collection
+  path               Output the path to the embeddings database
 ```
 #### llm embed-db path --help
 ```
@@ -486,6 +487,20 @@ Options:
   --json               Output as JSON
   --help               Show this message and exit.
 ```
+#### llm embed-db delete-collection --help
+```
+Usage: llm embed-db delete-collection [OPTIONS] COLLECTION
+
+  Delete the specified collection
+
+  Example usage:
+
+      llm embed-db delete-collection my-collection
+
+Options:
+  -d, --database FILE  Path to embeddings database
+  --help               Show this message and exit.
+```
 ### llm openai --help
 ```
 Usage: llm openai [OPTIONS] COMMAND [ARGS]...

llm/cli.py

@@ -1122,6 +1122,33 @@ def embed_db_collections(database, json_):
             )
 
 
+@embed_db.command(name="delete-collection")
+@click.argument("collection")
+@click.option(
+    "-d",
+    "--database",
+    type=click.Path(file_okay=True, allow_dash=False, dir_okay=False, writable=True),
+    envvar="LLM_EMBEDDINGS_DB",
+    help="Path to embeddings database",
+)
+def embed_db_delete_collection(collection, database):
+    """
+    Delete the specified collection
+
+    Example usage:
+
+    \b
+        llm embed-db delete-collection my-collection
+    """
+    database = database or (user_dir() / "embeddings.db")
+    db = sqlite_utils.Database(str(database))
+    try:
+        collection_obj = Collection(collection, db, create=False)
+    except Collection.DoesNotExist:
+        raise click.ClickException("Collection does not exist")
+    collection_obj.delete()
+
+
 def template_dir():
     path = user_dir() / "templates"
     path.mkdir(parents=True, exist_ok=True)

llm/embeddings.py

@@ -282,6 +282,14 @@ def similar(self, text: str, number: int = 10) -> List[Entry]:
         comparison_vector = self.model().embed(text)
         return self.similar_by_vector(comparison_vector, number)
 
+    def delete(self):
+        """
+        Delete the collection and its embeddings from the database
+        """
+        with self.db.conn:
+            self.db.execute("delete from embeddings where collection_id = ?", [self.id])
+            self.db.execute("delete from collections where id = ?", [self.id])
+
     @staticmethod
     def content_hash(text: str) -> bytes:
         "Hash content for deduplication. Override to change hashing behavior."

tests/conftest.py

@@ -94,3 +94,11 @@ def mocked_localai(requests_mock):
         },
         headers={"Content-Type": "application/json"},
     )
+
+
+@pytest.fixture
+def collection():
+    collection = llm.Collection("test", model_id="embed-demo")
+    collection.embed(1, "hello world")
+    collection.embed(2, "goodbye world")
+    return collection

tests/test_embed.py

@@ -6,14 +6,6 @@
 from unittest.mock import ANY
 
 
-@pytest.fixture
-def collection():
-    collection = llm.Collection("test", model_id="embed-demo")
-    collection.embed(1, "hello world")
-    collection.embed(2, "goodbye world")
-    return collection
-
-
 def test_demo_plugin():
     model = llm.get_embedding_model("embed-demo")
     assert model.embed("hello world") == [5, 5] + [0] * 14
@@ -118,3 +110,12 @@ def test_embed_multi(with_metadata):
     else:
         assert len(rows_with_metadata) == 0
         assert len(rows_with_content) == 1000
+
+
+def test_collection_delete(collection):
+    db = collection.db
+    assert db["embeddings"].count == 2
+    assert db["collections"].count == 1
+    collection.delete()
+    assert db["embeddings"].count == 0
+    assert db["collections"].count == 0

tests/test_embed_cli.py

@@ -139,6 +139,25 @@ def test_embed_store(user_path, metadata, metadata_error):
         else:
             assert result2.output == "items: embed-demo\n  1 embedding\n"
 
+    # And test deleting it too
+    result = runner.invoke(cli, ["embed-db", "delete-collection", "items"])
+    assert result.exit_code == 0
+    assert db["collections"].count == 0
+    assert db["embeddings"].count == 0
+
+
+def test_collection_delete_errors(user_path):
+    db = sqlite_utils.Database(str(user_path / "embeddings.db"))
+    collection = Collection("items", db, model_id="embed-demo")
+    collection.embed("1", "hello")
+    assert db["collections"].count == 1
+    assert db["embeddings"].count == 1
+    runner = CliRunner()
+    result = runner.invoke(cli, ["embed-db", "delete-collection", "does-not-exist"])
+    assert result.exit_code == 1
+    assert "Collection does not exist" in result.output
+    assert db["collections"].count == 1
+
 
 @pytest.mark.parametrize(
     "args,expected_error",