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.
94 karma · joined August 8, 2016
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 :)
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.
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)
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.
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.
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?
> 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.
I created this for myself, to automate frequent searches like "XYZ Crunchbase" Or "ABC Angel List". Sharing it here, because I am sure this will be helpful for lot of people on HN.
Link to Chrome Webstore: https://chrome.google.com/webstore/detail/lookup/oamfkboglen...
Source is at https://github.com/dhananjay92/lookup . Feel free to contribute. :)
Cheers!