context-aware-rag and agentic-rag

context-aware-rag
53
Established
agentic-rag
50
Established
Maintenance 10/25
Adoption 8/25
Maturity 16/25
Community 19/25
Maintenance 2/25
Adoption 10/25
Maturity 15/25
Community 23/25
Stars: 58
Forks: 17
Downloads: —
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 198
Forks: 67
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No Package No Dependents
Stale 6m No Package No Dependents

About context-aware-rag

NVIDIA/context-aware-rag

Context-Aware RAG library for Knowledge Graph ingestion and retrieval functions.

This library helps developers enhance their AI applications by creating sophisticated RAG (Retrieval Augmented Generation) pipelines. It takes various data sources, extracts structured knowledge, and outputs relevant information for natural language queries. Developers, AI engineers, and data scientists use it to build context-aware AI agents or Q&A systems.

AI application development data ingestion knowledge graph extraction natural language processing AI agent development

About agentic-rag

FareedKhan-dev/agentic-rag

Agentic RAG to achieve human like reasoning

This project helps financial analysts and researchers to deeply understand complex financial documents like SEC filings. It takes unstructured documents (10-K, 10-Q, 8-K reports) and processes them to generate structured insights, summaries, and trend analyses, mimicking how a human expert would reason and connect information. The output is a comprehensive, validated understanding of the data, going beyond simple fact retrieval.

financial-analysis market-research regulatory-compliance investment-due-diligence enterprise-search

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