HippoRAG is an amazing work and it was a source of inspiration for us as noted in the references. There are a couple of differences:
(1) FastGraphRAG allows the user to make the graph construction opinionated and specialized on a given domain and for a given use-case; this allows to clear out all the noise in the data and yields better results;
(2) Unlike HippoRAG, FastGraphRAG initializes PageRank with a mixture of semantic retrieval and entity extractions;
(3) HippoRAG is the outcome of an academic paper, and we saw the need for a more robust and production-ready implementation. Our repo is fully typed, includes tests, handles retries with Instructor, uses structured outputs, and so on.
Moving forward, we see our implementation diverge from HippoRAG more radically as we start to introduce new mechanisms such as weighted edges and negative PageRank to model repulsors.
HippoRAG is an amazing work and it was a source of inspiration for us as noted in the references. There are a couple of differences:
(1) FastGraphRAG allows the user to make the graph construction opinionated and specialized on a given domain and for a given use-case; this allows to clear out all the noise in the data and yields better results; (2) Unlike HippoRAG, FastGraphRAG initializes PageRank with a mixture of semantic retrieval and entity extractions; (3) HippoRAG is the outcome of an academic paper, and we saw the need for a more robust and production-ready implementation. Our repo is fully typed, includes tests, handles retries with Instructor, uses structured outputs, and so on.
Moving forward, we see our implementation diverge from HippoRAG more radically as we start to introduce new mechanisms such as weighted edges and negative PageRank to model repulsors.