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 :)
Danswer
https://github.com/danswer-ai/danswer
Khoj
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)
I've had a workflow digitizing my incoming paper documents, running OCR, and tagging them, all locally, and it would be great to have an easy front-end to talk to them.
I have been building some stuff on top of the OpenAi interface (to use their store) but find myself wanting to implement some simple UI elements (like a date selected or a simple dashboard).
So I feel like these types of apps have a few re occurring elements:
1. A chat interface „frontend“ (with threads, interfaces to popular APIs or local models) nice Ui ideally extensibility to some custom UI elements authentication etc.
2. API calls. (E.g. like OpenAI actions) Simplest case just reading and writing to a db (simple crud).
3. Local data + RAG. With a custom retrieval/search logic could be embeddings or simpler search methods.
Do you know open source software for all three elements? Of course you can piece it together and maybe this is the best approach. But maybe you could build something integrated.
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.