Dabarqus

Add PDF chat to your LLM app in less than 9 lines of code

37 followers

Add PDF chat to your LLM app in less than 9 lines of code

37 followers

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AI Chatbots

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Command line tools

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AI Infrastructure Tools

Dabarqus gives you a practical way to add retrieval-augmented generation (RAG) to your app in less than 9 lines of code. Chat with your PDFs, summarize emails and messaging, and digest a vast range of facts, figures, and reports. A dash of genius for your LLM.

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Launch tags:Developer Tools•Artificial Intelligence•GitHub

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AssemblyAI — Build voice AI apps with a single API

Build voice AI apps with a single API

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Dabarqus

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Hey everyone, If you're a developer, building a basic RAG solution is pretty straightforward. There are tons of tutorials and how-tos, as well as Python code to reuse. But, if you're deploying your RAG solution within a company, or on end-user PCs, you will also have to figure out some potentially tricky deployment and maintenance issues. That also means deploying Python, a vector database, the right embedding AI model, and possibly dealing with licensing challenges. Dabarqus was created to address these issues with a stand-alone, all-in-one solution with no runtime dependencies. It's written in C++ and has built-in vector search, an industry-standard embedding model, and a REST API for easy development integration. I made an example python chatbot that uses Dabarqus with Ollama, and put it in the Github repo. I'd love your feedback – is anything missing? What would make Dabarqus more useful? Thanks for checking this out. Looking forward to your thoughts.

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1yr ago