erag — Agent Tool by EduardTalianu

Last updated: 2025-06-17 · Indexed by AgentSkillsHub · Auto-synced every 8h

About erag

an AI interaction tool with RAG hybrid search, conversation context, web content processing and structured data analysis with LLM / GPT

Quick Facts

Stars	212
Forks	27
Language	Python
Category	Agent Tool
Quality Score	27.75/100
Last Updated	2025-06-17
Created	2024-04-25
Platforms	browser, python
Est. Tokens	~473k

Compatible Skills

These tools work well together with erag for enhanced workflows:

datagouv-mcp — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
flexible-graphrag — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (55%)
dbt-llm-agent — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (55%)
data-analysis-llm-agent — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (54%)

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Frequently Asked Questions

What is erag?

erag is an AI interaction tool with RAG hybrid search, conversation context, web content processing and structured data analysis with LLM / GPT. It is categorized as a Agent Tool with 212 GitHub stars.

What programming language is erag written in?

erag is primarily written in Python.

How do I install or use erag?

You can find installation instructions and usage details in the erag GitHub repository at github.com/EduardTalianu/erag. The project has 212 stars and 27 forks, indicating an active community.

View on GitHub → Browse Agent Tool tools