KG_RAG VS TaskingAI

Compare KG_RAG vs TaskingAI and see what are their differences.

KG_RAG

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks (by BaranziniLab)
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KG_RAG TaskingAI
5 1
357 4,837
36.1% 26.7%
9.7 9.4
27 days ago 4 days ago
Jupyter Notebook Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

TaskingAI

Posts with mentions or reviews of TaskingAI. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing KG_RAG and TaskingAI you can also consider the following projects:

LangChain-SynData-RAG-Eval - LangChain, Llama2-Chat, and zero- and few-shot prompting are used to generate synthetic datasets for IR and RAG system evaluation

leaptable - Reframe - The fastest way to build, deploy, and manage LLM-powered agents on tabular data (dataframes, SQL tables and Spreadsheets). [Moved to: https://github.com/peterwnjenga/reframe]

open-assistant-api - The Open Assistant API is a ready-to-use, open-source, self-hosted agent/gpts orchestration creation framework, supporting customized extensions for LLM, RAG, function call, and tools capabilities. It also supports seamless integration with the openai/langchain sdk.

evadb - Database system for AI-powered apps

raptor - The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval