FlowiseAI
[BUG] Upserting to Vector Store fails in Document Sore - Request to Ollama server failed
When im upserting two PDFs (655 and 371 chunks; 9105590 and 479470 chars) to a Faiss Vector Store with Ollama Embeddings I get the following error:
I used text splitter with 2000 chunk size and 200 overlap) and updated Flowise and Ollama
Im using Ollama Embedding with nomic-embed-text embedding model
The same process works before with smaller PDFs
Oh snap! The following error occured when loading this page. Status: 500 Error: documentStoreServices.insertIntoVectorStore - Error: documentStoreServices._insertIntoVectorStoreWorkerThread - Error: Request to Ollama server failed: 404 Not Found Please retry after some time. If the issue persists, reach out to us on our Discord server. Alternatively, you can raise an issue on Github.
Also have the same problem when trying to insert from the Chat Flow instead of using Document Store.
Are the Ollama Embeddings the problem? Can I use other embeddings with ollama LLMs as well?
Hi,I was encountering the same things after upsert at Flowise even I was using Ubuntu 24.04 and having /home/myname/vector path" 0 Error: documentStoreServices.insertIntoVectorStore - Error: documentStoreServices._insertIntoVectorStoreWorkerThread - Error: Request to Ollama server failed: 404 Not Found". Banatus Soiraya
having the same issues running on a mac any solution?
Error: documentStoreServices.insertIntoVectorStore - Error: documentStoreServices._insertIntoVectorStoreWorkerThread - Error: Request to Ollama server failed: 404 Not Found
I found that it works with smaller amounts of text. I guess rather Faiss or Ollama hit some capacity limit. Did anyone try a different vector store that is also able to run locally like ChromaDB? Or is the amount of data you can have in a vector store also somehow limited by flowise?
The same issue right here when trying trying to add Ollama model plus Pinecone or Datastack vector database.
I’m using [email protected]
