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docs/tools/txtsearchtool.mdx

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+---
+title: TXT RAG Search
+description: The `TXTSearchTool` is designed to perform a RAG (Retrieval-Augmented Generation) search within the content of a text file.
+icon: file-lines
+---
+
+# `TXTSearchTool`
+
+<Note>
+    We are still working on improving tools, so there might be unexpected behavior or changes in the future.
+</Note>
+
+## Description
+
+This tool is used to perform a RAG (Retrieval-Augmented Generation) search within the content of a text file. 
+It allows for semantic searching of a query within a specified text file's content, 
+making it an invaluable resource for quickly extracting information or finding specific sections of text based on the query provided.
+
+## Installation
+
+To use the `TXTSearchTool`, you first need to install the `crewai_tools` package. 
+This can be done using pip, a package manager for Python. 
+Open your terminal or command prompt and enter the following command:
+
+```shell
+pip install 'crewai[tools]'
+```
+
+This command will download and install the TXTSearchTool along with any necessary dependencies.
+
+## Example
+
+The following example demonstrates how to use the TXTSearchTool to search within a text file. 
+This example shows both the initialization of the tool with a specific text file and the subsequent search within that file's content.
+
+```python Code
+from crewai_tools import TXTSearchTool
+
+# Initialize the tool to search within any text file's content 
+# the agent learns about during its execution
+tool = TXTSearchTool()
+
+# OR
+
+# Initialize the tool with a specific text file, 
+# so the agent can search within the given text file's content
+tool = TXTSearchTool(txt='path/to/text/file.txt')
+```
+
+## Arguments
+- `txt` (str): **Optional**. The path to the text file you want to search. 
+This argument is only required if the tool was not initialized with a specific text file; 
+otherwise, the search will be conducted within the initially provided text file.
+
+## Custom model and embeddings
+
+By default, the tool uses OpenAI for both embeddings and summarization. 
+To customize the model, you can use a config dictionary as follows:
+
+```python Code
+tool = TXTSearchTool(
+    config=dict(
+        llm=dict(
+            provider="ollama", # or google, openai, anthropic, llama2, ...
+            config=dict(
+                model="llama2",
+                # temperature=0.5,
+                # top_p=1,
+                # stream=true,
+            ),
+        ),
+        embedder=dict(
+            provider="google", # or openai, ollama, ...
+            config=dict(
+                model="models/embedding-001",
+                task_type="retrieval_document",
+                # title="Embeddings",
+            ),
+        ),
+    )
+)
+```