LLM Orchestration

RAG-Groq

Integrates multiple data sources with Groq LLM for intelligent Q&A.

Status
Generally available
Last checked
Checked · Oct 10, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

RAG-Groq is a RAG package that integrates various data sources including CSV, databases, Pinecone, and Elasticsearch with Groq's large language models to provide intelligent question-answering capabilities.

RAG-Groq stands out for its flexibility in integrating with a variety of data sources and leveraging Groq's efficient large language models, making it ideal for developers who need to build intelligent Q&A systems without relying on cloud services.

When it fits — and when it doesn’t

A good fit for

  • Developers looking to integrate Groq LLMs with multiple data sources for Q&A systems.

  • Projects requiring a self-hosted solution for intelligent question-answering.

Look elsewhere if

  • Teams needing real-time streaming capabilities (batch-only architecture).

  • Budget-constrained projects that cannot afford the computational resources required by Groq LLMs.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited documentation and examples for advanced use cases

    Official docs lack detailed explanations of complex integrations with Pinecone or Elasticsearch

  2. 02

    Performance issues with large datasets in real-time scenarios

    Query response times significantly increase when dealing with more than 10k records from CSV data sources

What it does well

  • Integration with multiple data sources including CSV, databases, Pinecone, and Elasticsearch.

  • Uses Groq's large language models for generating answers.

  • Open-source under MIT license.

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up RAG-Groq

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
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