Embed documents or text and ask questions with a single API.
In minutes, you can build an internal tool for searching documents, or a customer-facing app for answering questions.
What is RAG? When you ask an LLM a question, you're hoping that it has seen the answer somewhere in its training data, or has enough context to generate a reasonable answer. But what if the data it needs is private, like some internal company documentation? Do you train a model from scratch on your data? Do you create a whole training set to fine-tune your model?
There's a simpler way to feed the data into your model. You can add your documents to a database, and for each query, retrieve the most relevant chunks of text from your database and give them to your model, along with your question. This is called retrieval-augmented generation. You're just giving the LLM the context it needs.
But what if I'm just building an internal tool and don't want to spin up a whole database and deal with document parsing, chunking, and vector embeddings?
This is where RagHost can help! We provide a simple API that allows you to upload your documents and query them. We do all the work for you, so you can focus on building your app.