# Observability with LangSmith

This example uses `LangSmith` to trace a small LangChain pipeline. The trace shows the context selection step, the prompt, and the final answer in one run.

## Requirements

This project requires [Python](https://www.python.org/) 3.9+ and the libraries listed in `requirements.txt`. You will also need an OpenAI API key and a LangSmith account.

## Steps for running this example

1. Install dependencies:
```bash
python -m venv .venv

# macOS/Linux:
source .venv/bin/activate

# Windows Command Prompt:
.venv\Scripts\activate.bat

# Windows PowerShell:
.venv\Scripts\Activate.ps1

pip install -r requirements.txt
```

2. Configure your credentials:
* Create a `.env` file in this directory.
* Add your OpenAI and LangSmith credentials:
```
OPENAI_API_KEY="YOUR_OPENAI_API_KEY"
LANGSMITH_TRACING=true
LANGCHAIN_PROJECT="Your LangChain Project Name"
LANGCHAIN_API_KEY="YOUR_LANGSMITH_API_KEY"
LANGSMITH_ENDPOINT=https://api.smith.langchain.com
```

3. Run the script:
```bash
python langsmith_observability.py
```

## Output

The script prints the selected context and the final answer. The full run appears in your LangSmith dashboard as a trace with metadata and tags.

```
--- LangSmith traced run ---
Question: I was charged twice for order #12345. What should I do?
Selected context: Billing policy: duplicate charges must be verified by billing before any refund is promised.
Answer: Please contact our billing department to verify the duplicate charges for order #12345 before any refund can be processed. They will assist you in resolving the issue.
Trace available in LangSmith when LANGSMITH_TRACING=true, LANGCHAIN_PROJECT, and LANGCHAIN_API_KEY are set.
```

Example LangSmith dashboard:

![LangSmith dashboard](/docs/img/langsmith-dashboard.png)