I’m working with Google’s Agent Builder and running into a frustrating issue. My setup includes three different datastores and one of them contains website data that works perfectly fine. When I test queries against the website datastore, the agent retrieves information without any problems.
The real headache is with my FAQ datastore. Even when I type in the exact same question that exists in the FAQ documents, I get back empty results. It’s like the system can’t find anything at all. I’ve tried several troubleshooting steps including disconnecting and reconnecting the datastore, clearing out all FAQ content and uploading it again, but nothing seems to help.
What’s really weird is that some FAQ items do get found during searches, but most of them just don’t show up in results. Has anyone else run into this kind of selective searching problem with Agent Builder? I’m looking for any debugging tips or solutions that might help fix this inconsistent behavior.
Been there with Agent Builder FAQ datastores. The selective results thing is usually a chunking issue.
Check your document structure first. If you’ve got one document with multiple Q&As, Agent Builder struggles with chunking boundaries. It’ll cut questions from their answers during indexing.
Split each FAQ pair into separate documents or use clear section breaks. I also put the question text in both the title and body - gives search more chances to match.
Try reducing chunk size to 500-1000 characters in your datastore config. Stops answers from getting buried in larger text blocks.
Also check your search preview in the console. Sometimes content’s indexed but similarity scores are too low. You can see what’s actually matching there and tweak your content.
I encountered a similar issue with the FAQ datastore recently. I discovered that the problem stemmed from the way the FAQs were formatted. The Agent Builder seems to favor more expansive, detailed entries rather than traditional Q&A formats. To rectify this, I revised the content by adding additional context to each answer and incorporating relevant keywords. It’s also essential to verify the parsing settings of your datastore; ensure it is configured to handle structured content appropriately. Additionally, monitoring the document processing status through the console can reveal if certain documents were not indexed properly, which may explain the selective search results you’re experiencing.
sounds like a metadata problem. agent builder needs proper document metadata for faq matching - without it, you’ll get skipped results even with perfect matches. check if your faq docs have title and description fields filled out. i had the same weird issue until i added structured metadata to each document. also try switching from semantic to keyword search temporarily - helps figure out if it’s a similarity scoring issue or an indexing failure.
Had this exact problem last month - drove me crazy until I figured out the indexing delay. Agent Builder doesn’t always refresh the search index right after document updates, even when the console shows it’s done processing. Here’s what worked: I manually triggered a reindex by tweaking the datastore config. Switched the chunk overlap from default to custom, then back to default. Forces a complete index rebuild. Also check your FAQ content for weird characters or formatting that might mess with parsing. I found questions with certain punctuation or quotes weren’t getting indexed properly. The processing logs sometimes show parsing errors you won’t see in the main interface.
This sounds like content overlap between your datastores is messing with search results. Your website datastore works fine, but FAQ doesn’t? Agent Builder’s probably prioritizing the working datastore and treating FAQ matches as duplicates. I’ve seen this tons of times when similar topics span multiple datastores in one agent. Quick test - disable your other datastores temporarily and try FAQ search alone. If it works better, you’ve got overlap issues. Also check your FAQ document length. Agent Builder struggles with short FAQ entries under 100 words. I had to bulk up my brief answers with extra context and examples to get decent retrieval. The search algorithm is clearly built for longer content, not brief FAQ responses.