4d2786935a
Co-authored-by: Eric Gustin <eric@arcade-ai.com> Co-authored-by: Nate Barbettini <nathanaelb@gmail.com> Co-authored-by: Nate Barbettini <nate@arcade-ai.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
import os
|
|
|
|
from langchain import hub
|
|
from langchain.agents import AgentExecutor, create_openai_functions_agent
|
|
from langchain_arcade import ArcadeToolManager
|
|
from langchain_openai import ChatOpenAI
|
|
|
|
arcade_api_key = os.environ["ARCADE_API_KEY"]
|
|
openai_api_key = os.environ["OPENAI_API_KEY"]
|
|
|
|
# Pull relevant agent model.
|
|
prompt = hub.pull("hwchase17/openai-functions-agent")
|
|
|
|
# Get all the tools available in Arcade
|
|
manager = ArcadeToolManager(api_key=arcade_api_key)
|
|
|
|
# Tool names follow the format "ToolkitName.ToolName"
|
|
tools = manager.get_tools(tools=["Web.ScrapeUrl"])
|
|
print(manager.tools)
|
|
|
|
# clear and init new tools from a toolkit
|
|
manager.init_tools(toolkits=["Search"])
|
|
print(manager.tools)
|
|
# get more tools
|
|
tools = manager.get_tools(toolkits=["Math"])
|
|
print(manager.tools)
|
|
|
|
# init the LLM
|
|
llm = ChatOpenAI(api_key=openai_api_key)
|
|
|
|
# Define agent
|
|
agent = create_openai_functions_agent(llm, tools, prompt)
|
|
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
|
|
|
|
# Try a few examples
|
|
agent_executor.invoke({"input": "Lookup Seymour Cray on Google"})
|
|
agent_executor.invoke({"input": "What is 1234567890 * 9876543210?"})
|