Debug, Test, and Monitor LLM Apps
What is LangSmith?
LangSmith is a developer tool by LangChain that helps you:
- Debug
- Test
- Monitor
- Evaluate LLM-powered applications (chains, agents, tools, etc.).
Key Features:
1. Traces
- Automatically captures detailed execution traces of your LangChain apps.
- View inputs, outputs, intermediate steps, errors, and more.
- Helps debug complex chains and agents.
2. Dataset Management
- Upload or create custom datasets (input prompts).
- Useful for running batch tests on chains or agents.
3. Evaluation Framework
- Run manual or automated evaluations on model outputs.
- Use built-in evaluators (e.g., correctness, relevance) or custom ones.
- Compare performance across versions.
4. Version Tracking
- Track versions of your LLM chains and compare outputs/metrics.
- Helpful in A/B testing and debugging regressions.
5. Monitoring in Production
- Log real-world usage.
- Analyze failure rates, latency, and other performance metrics.
Typical Use Cases
- Debugging why your agent made a bad decision.
- Evaluating a summarization chain across multiple inputs.
- Monitoring LLM app usage in real time.
- Comparing outputs between two LLM providers.
How to Use
- Sign up at: https://smith.langchain.com
- Set up an API key.
- Instrument your LangChain app:
from langsmith import traceable
@traceable
def my_chain(input):
# your chain logic
Or configure LangChain’s LangSmithTracer.
Integrated With:
- LangChain
- OpenAI, Anthropic, Google GenAI
- Python SDK and CLI
Summary:
LangSmith = The Postman + Debugger + Monitor for your LangChain + LLM apps.