mzarnecki/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 combines power of LLMs and access to source documen
This tool helps you get precise answers to your questions by combining the power of advanced AI models with your specific documents. You provide a question, and it gives you a detailed, context-aware answer based on its database of information. It's designed for anyone who needs accurate, contextually relevant information from a large text dataset, like a researcher or an information analyst.
Use this if you need to quickly retrieve accurate, context-specific answers from a large collection of documents, especially when dealing with nuanced topics or named entities that might be ambiguous.
Not ideal if you're looking for a simple chatbot for general knowledge or casual conversation, as its strength lies in leveraging a specific document database for factual retrieval.
Stars
62
Forks
5
Language
PHP
License
MIT
Category
Last pushed
Jan 04, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/mzarnecki/php-rag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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