superuely
superuely
> Unfortunately enabling the Cloud Resource Manager API didn't solve it for me. I am using the latest image. Same.
Recreate the Qdrant collection (or change the collection name) so its Size is 1024, or purge LightRAG’s working_dir if using NanoVectorDB, then reinsert the document.
# tried to declutter and make it readable: ## [Bug]: Embedding not happening - constant errors **Issue #2257** - Opened by @ndrewpj ## Description ### Do you need to file...
somehow managed to run into the same despite having read this. 2365624 entities, server, 64GB RAM, redis, qdrant, neo4j, down in 2 minutes after starting "migration".
"There are two key parameters that control pipeline concurrency: the maximum number of files processed in parallel (MAX_PARALLEL_INSERT) and the maximum number of concurrent LLM requests (MAX_ASYNC). The workflow is...
1. Embedding Dimension Mismatch You correctly changed the embedding dimension from 1024 to 768 to match nomic-embed-text, which outputs 768-dimensional vectors. However, you must also clear your old vector database...