crewAI/docs/tools/docx-search-tool.mdx

---
title: DOCXSearchTool
description: A tool for semantic search within DOCX documents using RAG capabilities
icon: file-text
---

## DOCXSearchTool

The DOCXSearchTool enables semantic search capabilities for Microsoft Word (DOCX) documents using Retrieval-Augmented Generation (RAG). It supports both fixed and dynamic document selection modes.

## Installation

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

## Usage Example

```python
from crewai import Agent
from crewai_tools import DOCXSearchTool

# Method 1: Fixed document (specified at initialization)
fixed_tool = DOCXSearchTool(
    docx="path/to/document.docx"
)

# Method 2: Dynamic document (specified at runtime)
dynamic_tool = DOCXSearchTool()

# Create an agent with the tool
researcher = Agent(
    role='Document Researcher',
    goal='Search and analyze document contents',
    backstory='Expert at finding relevant information in documents.',
    tools=[fixed_tool],  # or [dynamic_tool]
    verbose=True
)
```

## Input Schema

### Fixed Document Mode
```python
class FixedDOCXSearchToolSchema(BaseModel):
    search_query: str = Field(
        description="Mandatory search query you want to use to search the DOCX's content"
    )
```

### Dynamic Document Mode
```python
class DOCXSearchToolSchema(BaseModel):
    docx: str = Field(
        description="Mandatory docx path you want to search"
    )
    search_query: str = Field(
        description="Mandatory search query you want to use to search the DOCX's content"
    )
```

## Function Signature

```python
def __init__(
    self,
    docx: Optional[str] = None,
    **kwargs
):
    """
    Initialize the DOCX search tool.

    Args:
        docx (Optional[str]): Path to DOCX file (optional for dynamic mode)
        **kwargs: Additional arguments for RAG tool configuration
    """

def _run(
    self,
    search_query: str,
    docx: Optional[str] = None,
    **kwargs: Any
) -> str:
    """
    Execute semantic search on document contents.

    Args:
        search_query (str): Query to search in the document
        docx (Optional[str]): Document path (required for dynamic mode)
        **kwargs: Additional arguments

    Returns:
        str: Relevant content from the document matching the query
    """
```

## Best Practices

1. Document Handling:
   - Use absolute file paths
   - Verify file existence
   - Handle large documents
   - Monitor memory usage

2. Query Optimization:
   - Structure queries clearly
   - Consider document size
   - Handle formatting
   - Monitor performance

3. Error Handling:
   - Check file access
   - Validate file format
   - Handle corrupted files
   - Log issues

4. Mode Selection:
   - Choose fixed mode for static documents
   - Use dynamic mode for runtime selection
   - Consider memory implications
   - Manage document lifecycle

## Integration Example

```python
from crewai import Agent, Task, Crew
from crewai_tools import DOCXSearchTool

# Initialize tool
docx_tool = DOCXSearchTool(
    docx="reports/annual_report_2023.docx"
)

# Create agent
researcher = Agent(
    role='Document Analyst',
    goal='Extract insights from annual report',
    backstory='Expert at analyzing business documents.',
    tools=[docx_tool]
)

# Define task
analysis_task = Task(
    description="""Find all mentions of revenue growth 
    and market expansion.""",
    agent=researcher
)

# Create crew
crew = Crew(
    agents=[researcher],
    tasks=[analysis_task]
)

# Execute
result = crew.kickoff()
```

## Advanced Usage

### Multiple Document Analysis
```python
# Create tools for different documents
report_tool = DOCXSearchTool(
    docx="reports/annual_report.docx"
)

policy_tool = DOCXSearchTool(
    docx="policies/compliance.docx"
)

# Create agent with multiple tools
analyst = Agent(
    role='Document Analyst',
    goal='Cross-reference reports and policies',
    tools=[report_tool, policy_tool]
)
```

### Dynamic Document Loading
```python
# Initialize dynamic tool
dynamic_tool = DOCXSearchTool()

# Use with different documents
result1 = dynamic_tool.run(
    docx="document1.docx",
    search_query="project timeline"
)

result2 = dynamic_tool.run(
    docx="document2.docx",
    search_query="budget allocation"
)
```

### Error Handling Example
```python
try:
    docx_tool = DOCXSearchTool(
        docx="reports/quarterly_report.docx"
    )
    results = docx_tool.run(
        search_query="Q3 performance metrics"
    )
    print(results)
except FileNotFoundError as e:
    print(f"Document not found: {str(e)}")
except Exception as e: 
    print(f"Error processing document: {str(e)}")
```

## Notes

- Inherits from RagTool
- Supports fixed/dynamic modes
- Document path validation
- Memory management
- Performance optimization
- Error handling
- Search capabilities
- Content extraction
- Format handling
- Security features