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https://github.com/hwchase17/langchain
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2.0 KiB
2.0 KiB
LLMonitor
LLMonitor is an open-source observability platform that provides cost tracking, user tracking and powerful agent tracing.
Setup
Create an account on llmonitor.com, create an App
, and then copy the associated tracking id
.
Once you have it, set it as an environment variable by running:
export LLMONITOR_APP_ID="..."
If you'd prefer not to set an environment variable, you can pass the key directly when initializing the callback handler:
from langchain.callbacks import LLMonitorCallbackHandler
handler = LLMonitorCallbackHandler(app_id="...")
Usage with LLM/Chat models
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.callbacks import LLMonitorCallbackHandler
handler = LLMonitorCallbackHandler(app_id="...")
llm = OpenAI(
callbacks=[handler],
)
chat = ChatOpenAI(
callbacks=[handler],
metadata={"userId": "123"}, # you can assign user ids to models in the metadata
)
Usage with agents
from langchain.agents import load_tools, initialize_agent, AgentType
from langchain.llms import OpenAI
from langchain.callbacks import LLMonitorCallbackHandler
handler = LLMonitorCallbackHandler(app_id="...")
llm = OpenAI(temperature=0)
tools = load_tools(["serpapi", "llm-math"], llm=llm)
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION)
agent.run(
"Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?",
callbacks=[handler],
metadata={
"agentName": "Leo DiCaprio's girlfriend", # you can assign a custom agent in the metadata
},
)
Support
For any question or issue with integration you can reach out to the LLMonitor team on Discord or via email.