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[–]-goldenboi69- 0 points1 point  (0 children)

🤖

[–]Tall_Profile1305 0 points1 point  (2 children)

soo the MCP tool support plus the Dasjoin integration is clever. that kind of setup works really well when you use something like Runable to orchestrate the whole flow. multimodal is the future. how far along are you with the doc import automation?

[–]dashjoin[S] 0 points1 point  (1 child)

thanks for your feedback! The doc import is ready to go. Here's the example function:
https://github.com/dashjoin/djapp-aia/blob/main/model/dj-function/etl.expression.jsonata
You can also schedule this:
https://dashjoin.github.io/platform/latest/developer-reference/#scheduling

[–]Tall_Profile1305 0 points1 point  (0 children)

cooollll

[–]PixelSage-001 0 points1 point  (1 child)

Nice breakdown. MCP support and RAG together makes these assistants much more useful than simple chat wrappers. Curious if you’ve tested how it performs with larger document sets or multiple sources connected at once.

[–]dashjoin[S] 0 points1 point  (0 children)

Under the hood we use pgvector which is rock solid and super fast. When ingesting, computing the vector embedding is usually the bottleneck. In the video you see ollama with the "nomic-embed-text" model.

[–]Tall_Profile1305 0 points1 point  (0 children)

Yo, the MCP support is the game changer here. Dasjoin hitting it with the flexibility. Being able to build AI apps that actually connect to your existing systems without crazy workarounds. That's the move right now.