> ## Documentation Index
> Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChain With & Without Streaming

> Learn how to integrate Maxim observability with LangChain OpenAI calls.

[LangChain](https://www.langchain.com/) is a popular framework for developing applications powered by language models. It provides a standard interface for chains, integrations with other tools, and end-to-end chains for common applications.

This guide demonstrates how to integrate Maxim's observability capabilities with LangChain applications, allowing you to:

1. **Track LLM interactions** - Monitor all calls to language models
2. **Analyze performance** - Measure latency, token usage, and costs
3. **Debug chains** - Visualize the flow of information through your LangChain applications
4. **Evaluate outputs** - Assess the quality of responses from your LLM chains

The integration is simple and requires minimal changes to your existing LangChain code.

## Requirements

```
maxim-py
langchain-openai>=0.0.1
langchain
python-dotenv
```

## Env variables

```
MAXIM_LOG_REPO_ID=
OPENAI_API_KEY=
```

## Initialize logger

```python theme={null}
from maxim import Maxim, Config, LoggerConfig

# Instantiate Maxim and create a logger
logger = Maxim(Config()).logger(
    LoggerConfig(id=MAXIM_LOG_REPO_ID)
)
```

## Initialize MaximLangchainTracer

```python {4} theme={null}
from maxim.logger.langchain import MaximLangchainTracer

# Create the LangChain-specific tracer
langchain_tracer = MaximLangchainTracer(logger)
```

## Make LLM calls using MaximLangchainTracer

```python theme={null}
from langchain_openai import ChatOpenAI

MODEL_NAME = "gpt-4o"
llm = ChatOpenAI(model=MODEL_NAME, api_key=OPENAI_API_KEY)

messages = [
  ("system", "You are a helpful assistant."),
  ("human", "Describe big bang theory")
]

response = llm.invoke(
  messages,
  config={"callbacks": [langchain_tracer]}
)
print(response.content)
```

![Langchain Gif](https://github.com/maximhq/maxim-docs/blob/main/images/docs/sdk/python/langchain/langchain.gif?raw=true)

## Streaming example

```python theme={null}
# Enable streaming
llm_stream = ChatOpenAI(
  model=MODEL_NAME,
  api_key=OPENAI_API_KEY,
  streaming=True
)

response_text = ""
for chunk in llm_stream.stream(
  messages,
  config={"callbacks": [langchain_tracer]}
):
  response_text += chunk.content

print("\nFull response:", response_text)
```

***