mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-07-22 07:15:10 +00:00
6491f5a663
Some checks failed
Mark stale issues and pull requests / stale (push) Has been cancelled
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Check Documentation Broken Links / Check broken links (push) Has been cancelled
Vulnerability Scan / pip-audit (push) Has been cancelled
Nightly Canary Release / Check for new commits (push) Has been cancelled
Nightly Canary Release / Build nightly packages (push) Has been cancelled
Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled
85 lines
3.1 KiB
Plaintext
85 lines
3.1 KiB
Plaintext
---
|
|
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
|
|
mode: "wide"
|
|
---
|
|
|
|
# `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-generativeai", # or openai, ollama, ...
|
|
config=dict(
|
|
model_name="gemini-embedding-001",
|
|
task_type="RETRIEVAL_DOCUMENT",
|
|
# title="Embeddings",
|
|
),
|
|
),
|
|
)
|
|
)
|
|
``` |