Merge pull request #35 from antunsz/feature/add-mysql-tool

Feature/add mysql tool
This commit is contained in:
João Moura
2024-08-10 19:35:21 -07:00
committed by GitHub
4 changed files with 102 additions and 0 deletions

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@@ -37,5 +37,6 @@ from .tools import (
XMLSearchTool,
YoutubeChannelSearchTool,
YoutubeVideoSearchTool,
MySQLSearchTool
)
from .tools.base_tool import BaseTool, Tool, tool

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@@ -47,3 +47,4 @@ from .youtube_channel_search_tool.youtube_channel_search_tool import (
YoutubeChannelSearchTool,
)
from .youtube_video_search_tool.youtube_video_search_tool import YoutubeVideoSearchTool
from .mysql_search_tool.mysql_search_tool import MySQLSearchTool

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@@ -0,0 +1,56 @@
# MySQLSearchTool
## Description
This tool is designed to facilitate semantic searches within MySQL database tables. Leveraging the RAG (Retrieve and Generate) technology, the MySQLSearchTool provides users with an efficient means of querying database table content, specifically tailored for MySQL databases. It simplifies the process of finding relevant data through semantic search queries, making it an invaluable resource for users needing to perform advanced queries on extensive datasets within a MySQL database.
## Installation
To install the `crewai_tools` package and utilize the MySQLSearchTool, execute the following command in your terminal:
```shell
pip install 'crewai[tools]'
```
## Example
Below is an example showcasing how to use the MySQLSearchTool to conduct a semantic search on a table within a MySQL database:
```python
from crewai_tools import MySQLSearchTool
# Initialize the tool with the database URI and the target table name
tool = MySQLSearchTool(db_uri='mysql://user:password@localhost:3306/mydatabase', table_name='employees')
```
## Arguments
The MySQLSearchTool requires the following arguments for its operation:
- `db_uri`: A string representing the URI of the MySQL database to be queried. This argument is mandatory and must include the necessary authentication details and the location of the database.
- `table_name`: A string specifying the name of the table within the database on which the semantic search will be performed. This argument is mandatory.
## 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
tool = MySQLSearchTool(
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",
config=dict(
model="models/embedding-001",
task_type="retrieval_document",
# title="Embeddings",
),
),
)
)
```

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@@ -0,0 +1,44 @@
from typing import Any, Type
from embedchain.loaders.mysql import MySQLLoader
from pydantic.v1 import BaseModel, Field
from ..rag.rag_tool import RagTool
class MySQLSearchToolSchema(BaseModel):
"""Input for MySQLSearchTool."""
search_query: str = Field(
...,
description="Mandatory semantic search query you want to use to search the database's content",
)
class MySQLSearchTool(RagTool):
name: str = "Search a database's table content"
description: str = "A tool that can be used to semantic search a query from a database table's content."
args_schema: Type[BaseModel] = MySQLSearchToolSchema
db_uri: str = Field(..., description="Mandatory database URI")
def __init__(self, table_name: str, **kwargs):
super().__init__(**kwargs)
self.add(table_name)
self.description = f"A tool that can be used to semantic search a query the {table_name} database table's content."
self._generate_description()
def add(
self,
table_name: str,
**kwargs: Any,
) -> None:
kwargs["data_type"] = "mysql"
kwargs["loader"] = MySQLLoader(config=dict(url=self.db_uri))
super().add(f"SELECT * FROM {table_name};", **kwargs)
def _run(
self,
search_query: str,
**kwargs: Any,
) -> Any:
return super()._run(query=search_query)