vector index usage example table schema is inconsistent

[rhashimoto]

Path: /features/ai-and-embeddings

In the vector index usage example, the schema is declared with a column named full_emb:

turso-docs/features/ai-and-embeddings.mdx

Lines 85 to 93 in 60dba44

	Begin by declaring a column used for storing vectors with the `F32_BLOB` datatype:
	```sql
	CREATE TABLE movies (
	title TEXT,
	year INT,
	full_emb F32_BLOB(4) -- 4-dimensional f32 vector
	);
	```

But subsequently the column is referenced with embedding:

turso-docs/features/ai-and-embeddings.mdx

Lines 101 to 110 in 60dba44

	Once you generate embeddings for your data (via an LLM), you can insert them into your table:
	```sql
	INSERT INTO movies (title, year, embedding)
	VALUES
	('Napoleon', 2023, vector32('[0.800, 0.579, 0.481, 0.229]')),
	('Black Hawk Down', 2001, vector32('[0.406, 0.027, 0.378, 0.056]')),
	('Gladiator', 2000, vector32('[0.698, 0.140, 0.073, 0.125]')),
	('Blade Runner', 1982, vector32('[0.379, 0.637, 0.011, 0.647]'));
	```

turso-docs/features/ai-and-embeddings.mdx

Lines 118 to 128 in 60dba44

	You can now write queries combining vectors and standard SQLite data:
	```sql
	SELECT title,
	vector_extract(embedding),
	vector_distance_cos(embedding, vector32('[0.064, 0.777, 0.661, 0.687]'))
	FROM movies
	ORDER BY
	vector_distance_cos(embedding, vector32('[0.064, 0.777, 0.661, 0.687]'))
	ASC;
	```

[notrab]

Feel free to open a PR to suggest any changes. Thank you 🙏🏻