yingfeng

6 ms·

1.
What is Agent context engine(ragflow.io)
1 points by yingfeng 9mo ago|0 comments
2.
Halfway Through 2025: A RAG Progress Report(medium.com)
1 points by yingfeng 1y ago|0 comments
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by yingfeng 2y ago
RAGFlow v0.17.0 now enables Agentic Reasoning for Deep Research, integrating any LLM — no RLM dependency required.
4.
RAGFlow 0.9 is released to support GraphRAG end-to-end(github.com)
3 points by yingfeng 2y ago|0 comments
5.
Multi-way retrieval evaluations based on the Infinity database(medium.com)
1 points by yingfeng 2y ago|0 comments
6.
Show HN: Infinity – Incredibly fast database for RAG with powerful hybrid search(github.com)
2 points by yingfeng 2y ago|0 comments
7.
by yingfeng 2y ago
Because colbert is not an end-to-end solution. As seen for RAGatouille, it has integrated colbertv2 into this repo. However, it's not a database, we implement tensor within infinity, aim to make an end-to-end solution for late interac
8.
by yingfeng 2y ago
paradedb could also deliver three-way hybrid search through pg_vector, pg_sparse and pg_search. Compared with paradedb, infinity has following advantages: 1. Performance The performance of pg_vector is far slower than vector search of Infin
9.
by yingfeng 2y ago
A noticeble work to demostrate the effectiveness of hybrid search is blended rag by IBM research ( https://arxiv.org/abs/2404.07220 ), which has shown that 3-way hybrid search could achieve STOA over multiple evaluation
10.
by yingfeng 2y ago
There are some vector databases that already include both dense vector search and sparse vector search, such as qdrant. A hybrid search of these 2 does not solve many problems well, such as exact queries. Moreover, according to our experime
11.
by yingfeng 2y ago
Hi, I'm one of the creators of infinity, and the article has mentioned about the sparse vector vs bm25. While the sparse vector performs well under some evaluations, it is obtained by training a model, which means that it can't fu
12.
by yingfeng 2y ago
From the viewpoint of RAG 2.0, during the stage of indexing or pre-processing, such approaches as knowledge graph is a MUST to resolve such issues as multi hop question answering, long text question answering as well as semantic gap between
13.
by yingfeng 2y ago
From 0.8, RAGFlow( https://github.com/infiniflow/ragflow ) will provide no code workflow orchestration. This article describes what kind of graph orchestration engine is needed, and how it can be used to implement Agenti
14.
by yingfeng 2y ago
RRF is a simple and effective means of fused ranking for multiple recall. Within our open source RAG product RAGFlow( https://github.com/infiniflow/ragflow ), Elasticsearch is currently used instead of other general vect
15.
by yingfeng 2y ago
I read the paper and there are some similarities between ZenDB and RAGFlow, but also many differences. The goal of RAGFlow is to use computer vision models to recognize the structure of a document, including diagrams and tables, and then to
16.
by yingfeng 2y ago
Actually we've tried almost all lof existing open source models for document processing, and none of them performs well for complex documents, especially those having complicated tables, such as tables cells without borders, cells need
17.
by yingfeng 2y ago
Thanks for your nice suggestion. We train the model using YOLO, but during inference, the model is converted into ONNX and we use ONNXRuntime for the model inference. As a result, YOLO itself is not included in the software package. We wil
18.
by yingfeng 2y ago
We've used YOLOv8 as the object detection model, and use some public datasets, such as PubTable, CDLA, together with some private data to train the model. The model on Huggingface is the one trained using public dataset, and we would o
19.
by yingfeng 2y ago
Hi, buddy, I'm sorry to make you feel like we don't take women's voices into account. We came up with this name because RAG is already a consensus, as an acronym for retrieval augmented generation, RAG is used in many places,
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by yingfeng 3y ago
RAG requires at least both dense retrieval as well as sparse retrieval, vector search is used to serve as the former one.
21.
by yingfeng 3y ago
Congratulations! Vespa is by far the best open source search engine even starts from more than twenty years before. The code base is complicated to support web scale search and right now it could provide both full text search as well as vec
22.
by yingfeng 11y ago
What's the relationship between Fenzo and Titan, and when Titan will be made open source?
23.
by yingfeng 15y ago
I uses boost::atomic to make it usable without c++0x http://www.chaoticmind.net/~hcb/projects/boost.atomic/ #include <boost/atomic.hpp> class AtomicPointer { private: boost::atomic<void > rep_; public: AtomicPointer(
24.
by yingfeng 15y ago
fractal trees should have a faster read performance with leveldb with a comparable updating performance. There does not exist any open source solution for such structure, while we could hope that www.acunu.com might provide an open source s
25.
by yingfeng 15y ago
LevelDB should not be compared with the storage model of TC, because leveldb could be looked on a bigtable that run on single node, which is a model that is optimzied for updating instead of reading. The application situation for leveldb is