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Update using langchain tools docs (#1664)

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* Update example of how to use LangChain tools with correct syntax

* Use .env

* Add  Code back

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
This commit is contained in:
Ola Hungerford
2024-12-03 08:13:06 -08:00
committed by GitHub
parent 1ca68aff08
commit 79cfa87341
1 changed files with 33 additions and 20 deletions
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53
docs/concepts/langchain-tools.mdx
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@@ -7,32 +7,45 @@ icon: link
## Using LangChain Tools ## Using LangChain Tools
<Info> <Info>
CrewAI seamlessly integrates with LangChain’s comprehensive [list of tools](https://python.langchain.com/docs/integrations/tools/), all of which can be used with CrewAI. CrewAI seamlessly integrates with LangChain's comprehensive [list of tools](https://python.langchain.com/docs/integrations/tools/), all of which can be used with CrewAI.
</Info> </Info>
```python Code ```python Code
import os import os
from crewai import Agent from dotenv import load_dotenv
from langchain.agents import Tool from crewai import Agent, Task, Crew
from langchain.utilities import GoogleSerperAPIWrapper from crewai.tools import BaseTool
from pydantic import Field
from langchain_community.utilities import GoogleSerperAPIWrapper
# Setup API keys # Set up your SERPER_API_KEY key in an .env file, eg:
os.environ["SERPER_API_KEY"] = "Your Key" # SERPER_API_KEY=<your api key>
load_dotenv()
search = GoogleSerperAPIWrapper() search = GoogleSerperAPIWrapper()
# Create and assign the search tool to an agent class SearchTool(BaseTool):
serper_tool = Tool( name: str = "Search"
name="Intermediate Answer", description: str = "Useful for search-based queries. Use this to find current information about markets, companies, and trends."
func=search.run, search: GoogleSerperAPIWrapper = Field(default_factory=GoogleSerperAPIWrapper)
description="Useful for search-based queries",
)
agent = Agent( def _run(self, query: str) -> str:
role='Research Analyst', """Execute the search query and return results"""
goal='Provide up-to-date market analysis', try:
backstory='An expert analyst with a keen eye for market trends.', return self.search.run(query)
tools=[serper_tool] except Exception as e:
return f"Error performing search: {str(e)}"
# Create Agents
researcher = Agent(
role='Research Analyst',
goal='Gather current market data and trends',
backstory="""You are an expert research analyst with years of experience in
gathering market intelligence. You're known for your ability to find
relevant and up-to-date market information and present it in a clear,
actionable format.""",
tools=[SearchTool()],
verbose=True
) )
# rest of the code ... # rest of the code ...
@@ -40,6 +53,6 @@ agent = Agent(
## Conclusion ## Conclusion
Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively. Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively.
When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, caching mechanisms, When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, caching mechanisms,
and the flexibility of tool arguments to optimize your agents' performance and capabilities. and the flexibility of tool arguments to optimize your agents' performance and capabilities.