Yes. Opensolr is a native LlamaIndex vector store:
pip install llama-index-opensolr
You get OpensolrVectorStore (under the standard llama_index.vector_stores.opensolr namespace) and OpensolrEmbedding. Embeddings are computed server-side on our GPUs, VectorStoreQueryMode.HYBRID fuses BM25 + kNN per document with a tunable alpha, and standard MetadataFilters (EQ, NE, IN, NIN, ranges) map straight to Solr filters. Your VectorStoreIndex, retriever, and query engine work unchanged.
Try it right now, without an account. There is a public demo account: email mcp@opensolr.com, API key 420b8b23e7b12dc8ab838932145a5065. The index mcp_demo_d1__dense is preloaded with 300 news articles, so search and grounded answers work the moment you connect, and you can create your own indexes on the account.
Anything you create there is deleted after 3 days. The account is shared with everyone — other people can change or delete your index, and you can do the same to theirs, so never put anything real in it. The limits are per index and deliberately small: 200 MB of bandwidth and 50 MB of disk. For an index that is private and stays put, start a free 15-day trial — no card — and swap in your own two values.
Learn more: LlamaIndex integration page · PyPI package · Source on GitHub