crewAI/docs/edge/en/tools/file-document/directorysearchtool.mdx

---
title: Directory RAG Search
description: The `DirectorySearchTool` is a powerful RAG (Retrieval-Augmented Generation) tool designed for semantic searches within a directory's content.
icon: address-book
mode: "wide"
---

# `DirectorySearchTool`

<Note>
    **Experimental**: The DirectorySearchTool is under continuous development. Features and functionalities might evolve, and unexpected behavior may occur as we refine the tool.
</Note>

## Description

The DirectorySearchTool enables semantic search within the content of specified directories, leveraging the Retrieval-Augmented Generation (RAG) methodology for efficient navigation through files. Designed for flexibility, it allows users to dynamically specify search directories at runtime or set a fixed directory during initial setup.

## Installation

To use the DirectorySearchTool, begin by installing the crewai_tools package. Execute the following command in your terminal:

```shell
pip install 'crewai[tools]'
```

## Initialization and Usage

Import the DirectorySearchTool from the `crewai_tools` package to start. You can initialize the tool without specifying a directory, enabling the setting of the search directory at runtime. Alternatively, the tool can be initialized with a predefined directory.

```python Code
from crewai_tools import DirectorySearchTool

# For dynamic directory specification at runtime
tool = DirectorySearchTool()

# For fixed directory searches
tool = DirectorySearchTool(directory='/path/to/directory')
```

## Arguments

- `directory`: A string argument that specifies the search directory. This is optional during initialization but required for searches if not set initially.

## Custom Model and Embeddings

The DirectorySearchTool uses OpenAI for embeddings and summarization by default. Customization options for these settings include changing the model provider and configuration, enhancing flexibility for advanced users.

```python Code
from chromadb.config import Settings

tool = DirectorySearchTool(
    config={
        "embedding_model": {
            "provider": "openai",
            "config": {
                "model": "text-embedding-3-small",
                # "api_key": "sk-...",
            },
        },
        "vectordb": {
            "provider": "chromadb",  # or "qdrant"
            "config": {
                # "settings": Settings(persist_directory="/content/chroma", allow_reset=True, is_persistent=True),
                # from qdrant_client.models import VectorParams, Distance
                # "vectors_config": VectorParams(size=384, distance=Distance.COSINE),
            }
        },
    }
)

## Security

### Path Validation

Directory paths provided to this tool are validated against the current working directory. Paths that resolve outside the working directory are rejected with a `ValueError`.

To allow paths outside the working directory (for example, in tests or trusted pipelines), set the environment variable:

```shell
CREWAI_TOOLS_ALLOW_UNSAFE_PATHS=true
```
```