main
Kye 2 years ago
parent fc507cceb3
commit 56f9aad6b7

@ -1589,7 +1589,7 @@ from langchain.utilities.zapier import ZapierNLAWrapper
zapier = ZapierNLAWrapper() zapier = ZapierNLAWrapper()
toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier) zapier_toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
# agent = initialize_agent( # agent = initialize_agent(
# toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True # toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
# ) # )
@ -1603,7 +1603,7 @@ toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
######################################################## youtube search ######################################################## youtube search
from langchain.tools import YouTubeSearchTool from langchain.tools import YouTubeSearchTool
tool = YouTubeSearchTool() youtube_tool = YouTubeSearchTool()
#tool.run("lex friedman") #tool.run("lex friedman")
@ -1620,7 +1620,7 @@ os.environ["WOLFRAM_ALPHA_APPID"] = ""
from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
wolfram = WolframAlphaAPIWrapper() wolfram_tool = WolframAlphaAPIWrapper()
#wolfram.run("What is 2x+5 = -3x + 7?") #wolfram.run("What is 2x+5 = -3x + 7?")
######################################################## wolfram end ######################################################## wolfram end
@ -1629,7 +1629,7 @@ wolfram = WolframAlphaAPIWrapper()
######################################################## Wikipedia beginning ######################################################## Wikipedia beginning
from langchain.utilities import WikipediaAPIWrapper from langchain.utilities import WikipediaAPIWrapper
wikipedia = WikipediaAPIWrapper() wikipedia_tool = WikipediaAPIWrapper()
#wikipedia.run("HUNTER X HUNTER") #wikipedia.run("HUNTER X HUNTER")
######################################################## Wikipedia beginning ######################################################## Wikipedia beginning
@ -1667,7 +1667,7 @@ requests.get("https://www.google.com")
######################################################## pubmed ######################################################## pubmed
from langchain.tools import PubmedQueryRun from langchain.tools import PubmedQueryRun
pubmed = PubmedQueryRun() pubmed_tool = PubmedQueryRun()
pubmed.run("chatgpt") pubmed.run("chatgpt")
@ -1685,7 +1685,7 @@ import os
key = os.environ["IFTTTKey"] key = os.environ["IFTTTKey"]
url = f"https://maker.ifttt.com/trigger/spotify/json/with/key/{key}" url = f"https://maker.ifttt.com/trigger/spotify/json/with/key/{key}"
IFFT = IFTTTWebhook( IFFT_tool = IFTTTWebhook(
name="Spotify", description="Add a song to spotify playlist", url=url name="Spotify", description="Add a song to spotify playlist", url=url
) )
@ -1740,8 +1740,6 @@ from gradio_tools.tools import (
from langchain.memory import ConversationBufferMemory from langchain.memory import ConversationBufferMemory
llm = OpenAI(temperature=0)
memory = ConversationBufferMemory(memory_key="chat_history")
hf_model_tools = [ hf_model_tools = [
StableDiffusionTool().langchain, StableDiffusionTool().langchain,
ImageCaptioningTool().langchain, ImageCaptioningTool().langchain,
@ -1750,17 +1748,6 @@ hf_model_tools = [
] ]
agent = initialize_agent(
tools, llm, memory=memory, agent="conversational-react-description", verbose=True
)
output = agent.run(
input=(
"Please create a photo of a dog riding a skateboard "
"but improve my prompt prior to using an image generator."
"Please caption the generated image and create a video for it using the improved prompt."
)
)
######################## ######################################################## graphql end ######################## ######################################################## graphql end
@ -1832,15 +1819,8 @@ arxviv_tool = load_tools(
from langchain.utilities import ArxivAPIWrapper from langchain.utilities import ArxivAPIWrapper
arxiv = ArxivAPIWrapper() arxiv_tool = ArxivAPIWrapper()
docs = arxiv.run("1605.08386")
docs
docs = arxiv.run("Caprice Stanley")
docs
docs = arxiv.run("1605.08386WWW")
docs
################################# GMAIL TOOKKIT ################################# GMAIL TOOKKIT
@ -1862,13 +1842,12 @@ credentials = get_gmail_credentials(
api_resource = build_resource_service(credentials=credentials) api_resource = build_resource_service(credentials=credentials)
gmail_toolkit_2 = GmailToolkit(api_resource=api_resource) gmail_toolkit_2 = GmailToolkit(api_resource=api_resource)
tools = toolkit.get_tools() gmail_tools = toolkit.get_tools()
tools
from langchain import OpenAI from langchain import OpenAI
from langchain.agents import initialize_agent, AgentType from langchain.agents import initialize_agent, AgentType
llm = OpenAI(temperature=0)
agent = initialize_agent( agent = initialize_agent(
tools=toolkit.get_tools(), tools=toolkit.get_tools(),
llm=llm, llm=llm,
@ -1877,6 +1856,7 @@ agent = initialize_agent(
################################# GMAIL TOOKKIT JSON AGENT ################################# GMAIL TOOKKIT JSON AGENT
import os import os
import yaml import yaml
@ -1906,8 +1886,7 @@ json_agent_executor.run(
from langchain.agents.agent_toolkits import O365Toolkit from langchain.agents.agent_toolkits import O365Toolkit
toolkit = O365Toolkit() toolkit = O365Toolkit()
tools = toolkit.get_tools() 365_tools = toolkit.get_tools()
tools
from langchain import OpenAI from langchain import OpenAI
@ -1921,11 +1900,6 @@ agent = initialize_agent(
verbose=False, verbose=False,
agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
) )
agent.run("Create an email draft for me to edit of a letter from the perspective of a sentient parrot"
" who is looking to collaborate on some research with her"
" estranged friend, a cat. Under no circumstances may you send the message, however.")
################################# OFFICE 365 TOOLKIT END ################################# OFFICE 365 TOOLKIT END
@ -2113,15 +2087,7 @@ from langchain.chat_models import ChatOpenAI
#test #test
# PythonREPLTool() # PythonREPLTool()
python_repl_tool = PythonREPLTool()
agent_executor = create_python_agent(
llm=OpenAI(temperature=0, max_tokens=1000),
tool=PythonREPLTool(),
verbose=True,
agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
)
############################################ python tool ############################################ python tool
@ -2167,7 +2133,7 @@ vectorstore_info = VectorStoreInfo(
description="the most recent state of the Union adress", description="the most recent state of the Union adress",
vectorstore=state_of_union_store, vectorstore=state_of_union_store,
) )
toolkit = VectorStoreToolkit(vectorstore_info=vectorstore_info) vectorstore_toolkit = VectorStoreToolkit(vectorstore_info=vectorstore_info)
agent_executor = create_vectorstore_agent(llm=llm, toolkit=toolkit, verbose=True) agent_executor = create_vectorstore_agent(llm=llm, toolkit=toolkit, verbose=True)

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