LangChain With & Without Streaming

LangChain 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:

Track LLM interactions - Monitor all calls to language models
Analyze performance - Measure latency, token usage, and costs
Debug chains - Visualize the flow of information through your LangChain applications
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

from maxim import Maxim, Config, LoggerConfig

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

Initialize MaximLangchainTracer

from maxim.logger.langchain import MaximLangchainTracer

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

Make LLM calls using MaximLangchainTracer

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)

Streaming example

# 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)

Overview

Python

Typescript

LangChain With & Without Streaming

Requirements

Env variables

Initialize logger

Initialize MaximLangchainTracer

Make LLM calls using MaximLangchainTracer

Streaming example

​Requirements

​Env variables

​Initialize logger

​Initialize MaximLangchainTracer

​Make LLM calls using MaximLangchainTracer

​Streaming example

Requirements

Env variables

Initialize logger

Initialize MaximLangchainTracer

Make LLM calls using MaximLangchainTracer

Streaming example