By setec
Is anyone else having trouble with Knowledgebases and Agents?
I’m using mostly.the DeepSeek R1 Distill Llama 70B model, but changing models definitely didn’t resolve issues.
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Connecting too many knowledge bases to an Agent results in the “reasoning” field being filled up with a bunch of repetitive garbage from the context or chunks of the context. The <think>{reasoning}</think> appears together with the Agent’s normal response. The Agent often has an “out of tokens error”. Detaching all the knowledge bases and reattaching a single knowledge bases fixes the issue, but reattaching multipole knowledge bases causes the same issue again.
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.csv imports will not index. Indexing fails with a “Data sources updated successfully,” message but zero tokens are indexed. I actually want to use Multi QA MPNet Base Dot v1 but I tried all three embedding models, all fail the same way.
Has anyone else had either of these issues and if so have you found a fix?
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Accepted Answer
This seems to have been resolved by increasing memory for the database.
Heya, @setec
I’ve looked into possible solutions, and it seems that attaching only 1 KB per Agent or carefully controlling chunk sizes and retrieval limits (e.g., 2–5 results max). You can fine-tune your agent retrieval configuration to smaller chunk sizes and fewer matches.
As for the CSV imports, all I can think of is to have simple and clean columns like title, text — no weird delimiters or hidden characters.
Hope that this helps!
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