Hi everyone,
We developing an AI-powered game with a Gemini 1.5 agent acting as the game master. We’re very interested in using grounding to integrate domain-specific data for more accurate and relevant responses.
While the Vertex AI Studio interface appears to offer grounding functionality, my attempts to use it with Gemini 1.5 have been unsuccessful. I’ve encountered various errors and inconsistencies (one of such example attached). After further research, I discovered that grounding is currently only available for Gemini 1.0, which unfortunately doesn’t meet our quality standards for a production environment.
To move forward, we’re currently building a custom RAG pipeline using Langchain. However, this approach adds unnecessary complexity to our infrastructure and isn’t as cost-effective. We haven’t yet achieved optimal retrieval, and the need to extract large amounts of context from source documents is driving up token usage and costs.
We were hopeful after Google I/O 24 that native grounding support for Gemini 1.5 within Vertex AI Studio was imminent. Is there any update on the timeline for this feature?
Specifically, we’d love to know:
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When can we expect robust, built-in grounding support for Gemini 1.5 in Vertex AI Studio?
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Are there any best practices or recommendations for implementing RAG pipelines with Gemini 1.5 in the meantime?
Any insights from the Google team or the community would be greatly appreciated!
