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Crate rig_vectorize

Crate rig_vectorize 

Source
Expand description

Cloudflare Vectorize integration for the Rig framework.

This crate provides a vector store implementation using Cloudflare Vectorize, a globally distributed vector database built for AI applications.

§Example

use rig::providers::openai;
use rig_vectorize::VectorizeVectorStore;

let openai = openai::Client::from_env();
let embedding_model = openai.embedding_model(openai::TEXT_EMBEDDING_3_SMALL);

let vector_store = VectorizeVectorStore::new(
    embedding_model,
    "your-account-id",
    "your-index-name",
    std::env::var("CLOUDFLARE_API_TOKEN").unwrap(),
);

Structs§

DeleteByIdsRequest
Request body for the Vectorize delete_by_ids endpoint.
DeleteResult
Result payload from a delete_by_ids request.
ListVectorsResult
Result payload from a list_vectors request.
QueryRequest
Request body for the Vectorize query endpoint.
QueryResult
Result payload from a query request.
UpsertRequest
Request body for the Vectorize upsert endpoint.
UpsertResult
Result payload from an upsert request.
VectorIdEntry
A vector ID entry from the list_vectors response.
VectorInput
A single vector to be inserted or upserted.
VectorMatch
A single matching vector from a query.
VectorizeClient
HTTP client wrapper for Vectorize API operations.
VectorizeFilter
Filter for Vectorize vector search queries.
VectorizeVectorStore
A vector store backed by Cloudflare Vectorize.

Enums§

ReturnMetadata
Options for what metadata to return in query results.
VectorizeError
Errors that can occur when interacting with Cloudflare Vectorize.