Adityav369
Often, the blocker becomes high quality eval sets (which I guess always is the blocker).
I'd be happy to report back after some testing, we are looking to optimize more of this soon, as speed is somewhat of a missing piece at the moment.
Creating graphs and entity resolution are both tunable with overrides, you can specify domain specific prompts and overrides (will add a pharma example!) (https://docs.morphik.ai/python-sdk/create_graph#parameters). I tried to add code, but was formatting badly, sorry for the redirect.
If you're using txts, then plain RAG built on top of any vector database can suffice depending on your queries (if they directly reference the text, or can be made to, then similarity search is good enough). If they are cross document, setting a high number of chunks with plain RAG to retrieve might also do a good job.
If you have tables, images, etc. then using a better extraction mechanism (maybe unstructured, or other document processors) and then creating the embeddings can also work well.
I'd say if docs are simple, then just building your own pipeline on top of a vector db is good!
For the metadata extraction, we save these as Column(JSONB) for each documents which allows it to be changed on the fly.
Although, I keep wondering if it would have been better to use something like mongodb for this part, just because it's more natural.
Please let me know if you have questions and how it works out for you.
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Have you personally faced this issue/ know of anyone who has been looking for a solution to fill this market hole? Would love to know more.
Hey HN! My brother and I are building BrandSync AI to address a problem we identified while talking with businesses: Businesses have existing brand assets like catalogs, PDFs, images, etc, but struggle to translate these into effective social media content. BrandSync AI leverages these assets, along with platform-specific best practices, to generate social media posts.
We'd love to get your feedback on the product and would love to connect if this can help solve any of y'alls problems. Let us know what you think!
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