I've been trying out the vector similarity search but for some reason it returns this error:
Error parsing vector similarity query: query vector blob size (788) does not match index's expected size (3072).
The vector "dim" in the schema/index I set it to 768 since thats the length of the vectors I am creating. The vector I try to search with is 768 in length, I am not sure why it says its 788, and the expected size is 3072. Did I miss anything?
Here is a snippet of my implementation:
\\\\\\\\\\\\\\\\\\\\\\\\ USER SCHEMA \\\\\\\\\\\\\\\\\\\\\\\\\\\
const userSchema = client.schema({
firstName: "string",
lastName: "string",
age: "number",
verified: "boolean",
location: "point",
skills: "array",
personalStatement: { type: "text", phonetic: "dm:es" },
vectorEmbedding: {
type: "vector",
index: true,
algorithm: "HNSW",
dim: 768,
distance: "COSINE",
vecType: "FLOAT32",
},
});
// Create the interface
const User = client.model("User", userSchema);
\\\\\\\\\\\\\\\\\\\\\\\\\\ SEARCH VECTORS \\\\\\\\\\\\\\\\\\\\\
export const searchVectors = async (req, res) => {
// vectors is the text entered by the user converted to a 768 vector
const user = await User.search()
.where("vectorEmbedding")
.eq((vector) => vector.knn().from(vectors).return(8))
.returnAll();
res.send(user);
I've been trying out the vector similarity search but for some reason it returns this error:
The vector "dim" in the schema/index I set it to 768 since thats the length of the vectors I am creating. The vector I try to search with is 768 in length, I am not sure why it says its 788, and the expected size is 3072. Did I miss anything?
Here is a snippet of my implementation: