Go to Settings → API Keys and click “Create New Key”. Give it a descriptive name like “Development Key”.
Navigate to Settings → API Keys to create a new key
3
Copy your API key
Copy the API key and store it securely. You’ll need it in the next step.
API keys are only shown once. If you lose it, you’ll need to create a new one.
Store your API key in a secure password manager or environment variable manager like 1Password or Doppler.
Step 2: Install the Arcbeam Connector
Python
pip install arcbeam-connector langchain-openai
Step 3: Create Your First Traced Application
Create a simple LangChain agent that uses Arcbeam tracing:
from langchain.agents import create_agentfrom langchain_openai import ChatOpenAIfrom arcbeam_connector.langchain.connector import ArcbeamLangConnector# Initialize the Arcbeam connectorconnector = ArcbeamLangConnector( base_url="http://platform.arcbeam.ai", # Or your self-hosted URL api_key="your-api-key-here", # Your Arcbeam API key)connector.init()# Create your modelmodel = ChatOpenAI(model="gpt-4o-mini")# Define a simple tooldef get_weather(city: str) -> str: """Get weather for a given city.""" return f"It's always sunny in {city}!"# Create the agent with your toolsagent = create_agent( model=model, tools=[get_weather], system_prompt="You are a helpful assistant",)# Run the agent - this will be automatically traced!result = agent.invoke( {"messages": [{"role": "user", "content": "what is the weather in sf"}]}, config={"callbacks": []})print(result["messages"][-1].content)
Make sure to set your OPENAI_API_KEY environment variable before running this code.
The connector automatically captures all LangChain operations without requiring you to modify your existing code beyond the initialization.
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