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

# Vector Stores

> Create vector stores to provide context and knowledge to your agents using RAG (Retrieval-Augmented Generation)

## What is a Vector Store?

Vector Stores allow you to upload documents, PDFs, and text files that provide context and knowledge to your agents. When agents need information, they can retrieve relevant content from your vector store using RAG (Retrieval-Augmented Generation), enabling them to answer questions and make decisions based on your uploaded knowledge base.

<Info>
  Vector Stores use semantic search to find the most relevant information from
  your uploaded files based on the agent's query. This allows agents to access
  specific knowledge without needing to process entire documents.
</Info>

## How It Works

Upload files to a vector store and provide a clear description of what information it contains. When you connect a vector store to an agent, the agent can automatically retrieve relevant content from your files to answer questions, make informed decisions, and provide accurate responses based on your knowledge base.

<CardGroup cols={3}>
  <Card title="Add Files" icon="upload">
    Add documents, PDFs, and text files to build your knowledge base
  </Card>

  <Card title="Semantic Search" icon="magnifying-glass">
    Agents automatically find relevant content using semantic search
  </Card>

  <Card title="Provide Context" icon="book">
    Give agents access to specific knowledge domains and information
  </Card>
</CardGroup>

## Creating a Vector Store

<Steps>
  <Step title="Open Agent Studio">
    Navigate to **Agent Studio** and click the **Create** button to open the "Create new item" modal.
  </Step>

  <Step title="Select Vector Store">
    Choose the **Vector Store** option from the creation modal.
  </Step>

  <Step title="Add a Description">
    In the vector store editor, provide a clear description of what information
    this vector store contains. This description helps the agent understand when
    to retrieve information from this vector store.

    <Warning>
      The description field is required. You must provide a description before you
      can use your vector store with an agent.
    </Warning>

    <Tip>
      Write descriptions that clearly explain the domain, topic, or type of
      information stored. For example: "This vector store includes company
      policies and employee handbooks."
    </Tip>
  </Step>

  <Step title="Rename Your Vector Store">
    Change the default name to something specific that describes what the vector
    store contains. This makes it easier to identify and manage multiple vector
    stores.

    <Tip>
      Use descriptive names like "Research Papers", "Company Policies", or
      "Product Documentation".
    </Tip>
  </Step>

  <Step title="Add Files">
    Click the **Add files** button to add documents to your vector store.

    <Note>
      Supported file types include documents, PDFs, and text files. The files will be processed and indexed for semantic search.
    </Note>
  </Step>
</Steps>

## Using Vector Stores in Agents

Add vector stores to agent steps to give agents access to your knowledge base. You can use managed vector stores that you create in Narada, or connect to external vector stores using Amazon Bedrock.

<Steps>
  <Step title="Open the Add Vector Store Modal">
    In any agent step, find the **Vector Stores** section and click to open the "Add vector store" modal.
  </Step>

  <Step title="Create New or Add Existing">
    Choose **Create new** to create a new vector store, or **Add existing** to select
    from your existing vector stores.
  </Step>

  <Step title="Select Vector Store Type">
    Choose the type of vector store you want to add:

    * **Managed**: Select from your existing vector stores created in Narada. These are vector stores you've created and uploaded files to.
    * **Amazon Bedrock**: Connect by providing the required connection information and credentials.

    <Info>
      When selecting an external vector store type, you'll need to provide the connection details specific to that service, such as API keys, region information, and other configuration required to connect to the external vector store.
    </Info>
  </Step>

  <Step title="Complete the Form">
    Fill in the required information based on your vector store type and selection, then click **Add vector store** or **Create vector store** to complete the process.

    <Warning>
      Vector stores without descriptions cannot be used with agents until a description is added.
    </Warning>
  </Step>
</Steps>

<Note>
  You can add multiple vector stores to a single agent step, giving your agent
  access to different knowledge domains simultaneously.
</Note>

## Best Practices

<CardGroup cols={2}>
  <Card title="Clear Descriptions" icon="message">
    Write detailed descriptions that explain what information is stored. The agent uses this to determine when to retrieve from the vector store.
  </Card>

  <Card title="Organized Files" icon="folder">
    Upload related files to the same vector store. Group documents by topic or
    domain for better organization.
  </Card>

  <Card title="Descriptive Names" icon="tag">
    Use specific, descriptive names for your vector stores to make them easy to
    identify and manage.
  </Card>

  <Card title="Quality Content" icon="star">
    Upload well-structured documents with clear, relevant information. Better source material leads to better agent responses.
  </Card>
</CardGroup>

## Common Use Cases

<Tabs>
  <Tab title="Research & Documentation">
    Store research papers, technical documentation, or reference materials that agents can consult when answering questions or performing research tasks.

    **Example:** A vector store containing research papers about machine learning that agents can reference when discussing ML concepts.
  </Tab>

  <Tab title="Company Knowledge">
    Upload company policies, employee handbooks, or internal documentation to give agents access to organizational knowledge.

    **Example:** A vector store with HR policies and employee guidelines that agents can reference when answering HR-related questions.
  </Tab>

  <Tab title="Product Information">
    Store product documentation, specifications, or FAQs that agents can use to provide accurate product information.

    **Example:** A vector store containing product manuals and specifications that support agents in customer service scenarios.
  </Tab>
</Tabs>