> ## Documentation Index
> Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Context Sources

> Learn how to create, use, and evaluate context sources for your AI applications. Context sources in Maxim allow you to connect your RAG pipeline via a simple API endpoint and link it as a variable in your prompts or endpoints for evaluation.

export const MaximPlayer = ({url}) => {
  return <iframe className="border-background-highlight-secondary h-full w-full rounded-md border-2 aspect-video" src={url} allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowFullScreen></iframe>;
};

<MaximPlayer url="https://www.youtube.com/embed/VXdRMXyKfYw?si=l48qYvKCV04M5IR5" />

## Connecting Your RAG Pipeline to Maxim

Context sources in Maxim allow you to expose your RAG pipeline via a simple endpoint irrespective of the complex steps within it. This context source can then be linked as a variable in your prompt or endpoints and selected for evaluation.

## How to Connect Your RAG Pipeline to Maxim

Connect your existing RAG system to Maxim by exposing it via an API endpoint.

<MaximPlayer url="https://www.youtube.com/embed/VXdRMXyKfYw" />

<Steps>
  <Step title="Create a new context source">
    You can create a new context source by clicking on the left navigation and then the plus icon.
  </Step>

  <Step title="Name your context source">
    Provide a name for the context source.
  </Step>

  <Step title="Configure API endpoint">
    Enter the API endpoint. When we pass a query to this endpoint, it should return the retrieved context for that query as would be the real world scenario.
  </Step>

  <Step title="Set up request configuration">
    Add necessary headers and parameters to your request and save the context source
  </Step>

  <Step title="Implement in prompts and endpoints">
    You can now use this in prompts and endpoints.
  </Step>
</Steps>

<MaximPlayer url="https://drive.google.com/file/d/10K4-9SmTLUxv4ORD4qtbsxu_sOc2YqSM/preview" />

## Ingest Files as Context Source

Maxim allows you to upload various document formats and automatically creates embeddings for use as context in your applications.

<Steps>
  <Step title="Navigate to Context Sources">
    Navigate to the Context Sources section in your workspace and click on the Plus icon.
  </Step>

  <Step title="Select Files source type">
    Select "Files" as your context source type.
  </Step>

  <Step title="Upload your documents">
    Drag and drop your files or click "Browse files" and select files from your system.
    Supported formats:

    * PDF documents (.pdf)
    * Word documents (.docx)
    * CSV files (.csv)
    * Text files (.txt)
    * Markdown files (.md)
  </Step>

  <Step title="Wait for processing">
    Wait for the files to upload and for embeddings to be generated. The status indicator will show progress.
  </Step>

  <Step title="Use your context source">
    Once processing is complete, your files are ready to be used as context. You can now reference this context source in agent simulation.
  </Step>
</Steps>

## Evaluate Your Context

Context sources in Maxim allow you to expose your RAG pipeline via a simple endpoint irrespective of the complex steps within it. This context source can then be linked as a variable in your prompt or workflow and selected for evaluation [here](/prompt-engineering/retrieval).

<Note>[Schedule a demo](https://getmaxim.ai/demo) to learn more about how to connect your RAG pipeline to Maxim</Note>