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I tried to learn more but this link from readme gives me 404 https://databridge.gitbook.io/databridge-docs/architecture/overview https://databridge.gitbook.io/d

by eamag 2y ago

I tried to learn more but this link from readme gives me 404 https://databridge.gitbook.io/databridge-docs/architecture/overview https://databridge.gitbook.io/databridge-docs/architecture/o... Can you tell what is it and how it works?

ArnavAgrawal03 2y ago
Yes of course! DataBridge is a multi-modal database with the belief that retrieval over unstructured data - such as videos, pdfs, and other documents should work with the same reliability, speed, and consistency as regular database data structures (and at a similar level of abstraction). Right now, we're focusing on helping simplify RAG pipelines for users. You can find more about getting started and installation instructions here: https://databridge.mintlify.app/getting-started https://databridge.mintlify.app/getting-started And you can find our API reference here: https://databridge.mintlify.app/api-reference/ https://databridge.mintlify.app/api-reference/ Is there anything specific you're looking for?
- eamag 2y ago
  what does it mean "multi-modal database"? Do you have any details somewhere?
  - ArnavAgrawal03 2y ago
    multi-modal database means that we treat multi-modal data, such as images, audio, and video as first-class citizens and provide natural language search over them. That is, you can ingest multi-modal content into DataBridge the same way you'd ingest structured data into a database. You can perform updates over this information, extract metadata, or define custom parsing/processing rules (eg. redact any PII). Your search queries would go through a planner which - depending on the kind of data we're retrieving - will call the correct tools to extract information from the data and respond to your query. For instance, this could be function calling over object-tracking data if your query relates to object movements over a video. This could also be a call to ColQwen in case we're looking for particular features within a diagram-heavy PDF. It could also be a simple semantic search if thats what the planner deems most useful. The idea is that traditional databases work the same way - query planning systems figure out the best path to execute the user query, and pass that to the query execution engine. We think a lot of this complexity can be abstracted away from the user - as long as we can provide them strong retrieval guarantees (the same ways Databases have SLAs). Let me know if something is unclear here!

by eamag 2y ago

ArnavAgrawal03 2y ago

Yes of course! DataBridge is a multi-modal database with the belief that retrieval over unstructured data - such as videos, pdfs, and other documents should work with the same reliability, speed, and consistency as regular database data structures (and at a similar level of abstraction). Right now, we're focusing on helping simplify RAG pipelines for users. You can find more about getting started and installation instructions here: https://databridge.mintlify.app/getting-started https://databridge.mintlify.app/getting-started And you can find our API reference here: https://databridge.mintlify.app/api-reference/ https://databridge.mintlify.app/api-reference/ Is there anything specific you're looking for?

eamag 2y ago
what does it mean "multi-modal database"? Do you have any details somewhere?
- ArnavAgrawal03 2y ago
  multi-modal database means that we treat multi-modal data, such as images, audio, and video as first-class citizens and provide natural language search over them. That is, you can ingest multi-modal content into DataBridge the same way you'd ingest structured data into a database. You can perform updates over this information, extract metadata, or define custom parsing/processing rules (eg. redact any PII). Your search queries would go through a planner which - depending on the kind of data we're retrieving - will call the correct tools to extract information from the data and respond to your query. For instance, this could be function calling over object-tracking data if your query relates to object movements over a video. This could also be a call to ColQwen in case we're looking for particular features within a diagram-heavy PDF. It could also be a simple semantic search if thats what the planner deems most useful. The idea is that traditional databases work the same way - query planning systems figure out the best path to execute the user query, and pass that to the query execution engine. We think a lot of this complexity can be abstracted away from the user - as long as we can provide them strong retrieval guarantees (the same ways Databases have SLAs). Let me know if something is unclear here!