embedchain/docs/integration/langsmith.mdx
Embedchain now supports integration with LangSmith.
To use LangSmith, you need to do the following steps.
Let's cover each step in detail.
First make sure that you have created a LangSmith account and have all the necessary variables handy. LangSmith has a good documentation on how to get started with their service.
Once you have setup the account, we will need the following environment variables
# Setting environment variable for LangChain Tracing V2 integration.
export LANGCHAIN_TRACING_V2=true
# Setting the API endpoint for LangChain.
export LANGCHAIN_ENDPOINT=https://api.smith.langchain.com
# Replace '<your-api-key>' with your LangChain API key.
export LANGCHAIN_API_KEY=<your-api-key>
# Replace '<your-project>' with your LangChain project name, or it defaults to "default".
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
If you are using Python, you can use the following code to set environment variables
import os
# Setting environment variable for LangChain Tracing V2 integration.
os.environ['LANGCHAIN_TRACING_V2'] = 'true'
# Setting the API endpoint for LangChain.
os.environ['LANGCHAIN_ENDPOINT'] = 'https://api.smith.langchain.com'
# Replace '<your-api-key>' with your LangChain API key.
os.environ['LANGCHAIN_API_KEY'] = '<your-api-key>'
# Replace '<your-project>' with your LangChain project name.
os.environ['LANGCHAIN_PROJECT'] = '<your-project>'
from embedchain import App
# Initialize EmbedChain application.
app = App()
# Add data to your app
app.add("https://en.wikipedia.org/wiki/Elon_Musk")
# Query your app
app.query("How many companies did Elon found?")