Data & Research · GitHub ·65 ★

php-rag

This application uses LLMs like DeepSeek, GPT-5, Claude, Gemini or Llama, Mixtral (locally) in order to generate text based on the user input. The user input is used to retrieve relevant information from the database and then the retrieved information is used to generate the text. This approach com

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Details

Author
mzarnecki
Category
Data & Research
Platform
GitHub
Framework
custom
Language
php
Stars
65
First indexed
2026-05-15
Last active
2026-01-04
Directory sync
2026-05-15
@mzarnecki

Overview

This application uses LLMs like DeepSeek, GPT-5, Claude, Gemini or Llama, Mixtral (locally) in order to generate text based on the user input. The user input is used to retrieve relevant information from the database and then the retrieved information is used to generate the text. This approach com

Quick start

git

git clone https://github.com/mzarnecki/php-rag

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What php-rag can do

ragllmembeddingdata
  • Rag — Retrieves grounded context before answering.
  • Llm — llm task automation.
  • Embedding — Computes vector embeddings for semantic search.
  • Data — Reads, transforms, and analyses structured data.

Frequently asked questions

What is php-rag?
This application uses LLMs like DeepSeek, GPT-5, Claude, Gemini or Llama, Mixtral (locally) in order to generate text based on the user input. The user input is used to retrieve relevant information from the database and then the retrieved information is used to generate the text. This approach com
How do I install php-rag?
Use git: `git clone https://github.com/mzarnecki/php-rag`. Full setup details on the source page linked above.
Is php-rag open source?
php-rag is published on GitHub.
What are alternatives to php-rag?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for php-rag is sourced from GitHub, published by mzarnecki.

Last scraped: · First indexed:

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