d7y
Joined 10 years ago
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94
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18
Member since
Aug 8
Recent submissions
Comment · 2 years ago
Try https://github.com/SecureAI-Tools/SecureAI-Tools -- it's an open-source application layer for Retrieval-Augmented Generation (RAG). It allows you to use any LLM -- you can use OpenAI APIs, or run models locally with Ollama.
Comment · 2 years ago
Hi there!
We just added this in the latest release (v0.0.2). You can now create a document collection and upload as many PDFs into it as needed. The documents are processed in the background and once processing finishes, you can create as many chats with it as needed.
Quick demo: https://youtu.be/PwvfVx8VCoY Installation Instructions: https://github.com/SecureAI-Tools/SecureAI-Tools?tab=readme-...
Please try it out, and let me know how it goes. We're always looking to improve the tool so let us know if you have any feedback for us :)
Comment · 2 years ago
A great question.
We are trying to build a single platform for all the AI tool needs. Chat-with-LLM and chat-with-documents are just a couple of apps or experiences that we have started with, but we have ambitious goals. In future, we would love to provide an SDK that exposes common abstractions and lets everyone build apps/experiences for the long tail of use cases.
Comment · 2 years ago
It is secure because it allows you to fully customize where to process the data (i.e. LLM inference), where to store it, and data-retention policies, etc. You can choose to use a locally running LLM (like it does in my second video) or use a secure third-party service provider like Azure OpenAI.
For example, if you want GDPR compliance, then you can choose Azure OpenAI running in the EU region. For HIPAA compliance, you should choose a service provider that provides the Business Associate Agreement (BAA). You can even run it in air-gapped facilities (like GitLab's offline mode [1]). In all of these cases, you can always run an Ollama-like inference service on your infra and point SecureAI Tools to it)
Comment · 2 years ago
I haven't tried this myself, but I think it should work. It would be worth trying at least, so I highly encourage you to play with it, and file issues if you find any issues with it.
Comment · 2 years ago
I love the idea of allowing anyone to build apps or experiences on top of some of these common elements.
We have briefly discussed an approach where we make some of these common elements available as abstractions and let people build "apps" on top of it. It would operate kind of similar to how Google's app store does in that the head use cases (email, photos, camera, etc) are first-party apps, but then anyone can build and publish a third-party app using the Android SDK.
Comment · 2 years ago
Right now it supports selecting & uploading a _few_ PDFs on chat-creation. Those PDFs get indexed online -- i.e. while the user waits. So it doesn't scale well with the number of PDFs selected in a chat because you'd have to wait that long before the chat responds with your initial question/prompt.
We plan to make this indexing process offline, where you can create a document collection based on either a directory upload or an integrated data source like Google Drive, Notion, Confluence, etc. Then the system would start indexing that collection in the background and notify you once indexing is complete. Once a collection is indexed, users can select it when creating a new chat and query against it.
Let us know if you have any thoughts on this proposed solution.
Comment · 2 years ago
> renaming PDFs
Sorry, I didn't understand. Why do you need ML tool for renaming PDFs? or did you mean rephrasing or rewriting in a different format?
Comment · 2 years ago
Great questions.
> 1. Does chat-with-pdfs function work with scanned PDFs?
Not yet. We don't do OCR or anything to extract text from images yet. But that would be an awesome feature, so we would love to add it in the future.
> 2. In the video example for chat-with-pdfs you show uploading a document interactively. The part of processing is quite slow. Can the tool be fed these documents offline as well?
Not as of right now. But we do have plans to make that an offline/background job so that we can feed a larger corpus of documents into it and query against it later.