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docs/tools/codedocssearchtool.mdx

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+---
+title: Code Docs RAG Search
+description: The `CodeDocsSearchTool` is a powerful RAG (Retrieval-Augmented Generation) tool designed for semantic searches within code documentation.
+icon: code
+---
+
+# `CodeDocsSearchTool`
+
+<Note>
+    **Experimental**: We are still working on improving tools, so there might be unexpected behavior or changes in the future.
+</Note>
+
+## Description
+
+The CodeDocsSearchTool is a powerful RAG (Retrieval-Augmented Generation) tool designed for semantic searches within code documentation. 
+It enables users to efficiently find specific information or topics within code documentation. By providing a `docs_url` during initialization, 
+the tool narrows down the search to that particular documentation site. Alternatively, without a specific `docs_url`, 
+it searches across a wide array of code documentation known or discovered throughout its execution, making it versatile for various documentation search needs.
+
+## Installation
+
+To start using the CodeDocsSearchTool, first, install the crewai_tools package via pip:
+
+```shell
+pip install 'crewai[tools]'
+```
+
+## Example
+
+Utilize the CodeDocsSearchTool as follows to conduct searches within code documentation:
+
+```python Code
+from crewai_tools import CodeDocsSearchTool
+
+# To search any code documentation content 
+# if the URL is known or discovered during its execution:
+tool = CodeDocsSearchTool()
+
+# OR
+
+# To specifically focus your search on a given documentation site 
+# by providing its URL:
+tool = CodeDocsSearchTool(docs_url='https://docs.example.com/reference')
+```
+<Note>  
+    Substitute 'https://docs.example.com/reference' with your target documentation URL 
+    and 'How to use search tool' with the search query relevant to your needs.
+</Note>
+
+## Arguments
+
+The following parameters can be used to customize the `CodeDocsSearchTool`'s behavior:
+
+| Argument       | Type     | Description                                                                                                                         |
+|:---------------|:---------|:-------------------------------------------------------------------------------------------------------------------------------------|
+| **docs_url**    | `string` | _Optional_. Specifies the URL of the code documentation to be searched.                                                | 
+
+## 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 = CodeDocsSearchTool(
+    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",
+            ),
+        ),
+    )
+)
+```