> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentops.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# LangChain
> AgentOps provides first class support for LangChain applications
AgentOps works seamlessly with applications built using LangChain.
## Adding AgentOps to LangChain applications
```bash pip theme={null}
pip install agentops
pip install agentops[langchain]
```
```bash poetry theme={null}
poetry add agentops
poetry add agentops[langchain]
```
[Give us a star](https://github.com/AgentOps-AI/agentops) on GitHub while you're at it (you may be our 3,000th 😊)
Import the following LangChain and AgentOps dependencies
```python python theme={null}
import os
from langchain.chat_models import ChatOpenAI
from langchain.agents import initialize_agent, AgentType
from agentops.integration.callbacks.langchain import LangchainCallbackHandler
```
Note that you don't need to set up a separate agentops.init() call, as the LangChain callback handler will automatically initialize the AgentOps client for you.
Set up your LangChain agent with the AgentOps callback handler, and AgentOps will automatically record your LangChain sessions.
```python python theme={null}
handler = LangchainCallbackHandler(api_key=AGENTOPS_API_KEY, tags=['LangChain Example'])
llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY,
callbacks=[handler],
model='gpt-3.5-turbo')
agent = initialize_agent(tools,
llm,
agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
verbose=True,
callbacks=[handler], # You must pass in a callback handler to record your agent
handle_parsing_errors=True)
```
Set your API key as an `.env` variable for easy access.
```python .env theme={null}
AGENTOPS_API_KEY=
```
Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your LangChain Agent! 🕵️
After your run, AgentOps prints a clickable URL to the console linking directly to your session in the Dashboard
## Full Examples
```python python theme={null}
import os
from langchain.chat_models import ChatOpenAI
from langchain.agents import initialize_agent, AgentType
from agentops.integration.callbacks.langchain import LangchainCallbackHandler
handler = LangchainCallbackHandler(api_key=AGENTOPS_API_KEY, tags=['LangChain Example'])
llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY,
callbacks=[handler],
model='gpt-3.5-turbo')
agent = initialize_agent(tools,
llm,
agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
verbose=True,
callbacks=[handler], # You must pass in a callback handler to record your agent
handle_parsing_errors=True)
```