MRAG Documentation
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Welcome to the official documentation of MRAG, a no-code platform to build RAG pipelines.

The contents in the sidebar should let you easily access the documentation for your topic of interest. You can also use the search function in the top-left corner.


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   <span>Visit the product website at <a href="https://mragapp.github.io/" target="_blank">mragapp.github.io</a></span>


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What is MRAG?
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MRAG is a no-code platform to build RAG pipelines and chat with your documents which uses GenAI technology to answer your queries about your documents.


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Why use MRAG?
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Creating RAG pipelines to chat with your documents requires technical knowledge. MRAG enables users with minimal technical knowledge to build RAG pipelines with ease. 
MRAG has a drag-and-drop user interface that enables a user to build indexing pipelines without writing a single line of code. MRAG is loaded 
with multiple settings enabling a user to even handle complex documents.


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Can MRAG handle every case?
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No application can satisfy all the requirements of a user, same goes with MRAG as well. While, MRAG can help a user build RAG pipelines for simple and complex use cases, 
there might be situations where a user needs to build more complex RAG pipelines to satisfy their requirements.


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Who developed MRAG?
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**MRAG** is developed and maintained by KSV Muralidhar.

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   <span>Know more about KSV Muralidhar at <a href="https://ksvmuralidhar.in" target="_blank">ksvmuralidhar.in</a></span>


.. toctree::
   :maxdepth: 2
   :caption: Contents
   :hidden:
   
   Features <features>
   Getting Started <getting_started>
   Building Indexing Pipelines <indexing>
   Q&A Chatbot <qa_chatbot>
   How-To Guide <how_to>
   Technologies Used <technologies>