> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llumo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Connect Your App to LLUMO AI in Minutes

Get started with our SDK and ensure reliability for your app with intelligent observability and evaluation. Follow this quick guide to plug LLUMO AI into your workflow—fast, simple, and built for AI product teams.

***

## 1. Install the LLUMO AI SDK

Please ensure that you have the **LLUMO AI SDK** installed before running evaluation.

```python theme={null}
!pip install llumo
```

## 2. Set your API key

You will find your LLUMO AI API key on the top navbar next to your profile icon.

```python theme={null}
LLUMO_AI_API_KEY = "key_NzE4NmU4*****************00d0cd"
```

## 3. Select your framework

Simply select your framework. For different frameworks, we have different callback handlers or wrappers. If you just want to evaluate the final log, select evaluate

<AccordionGroup>
  <Accordion title="Langchain">
    ```python theme={null}
    !pip install langchain_community
    !pip install langchain-openai
    ```

    ```python theme={null}
    from langchain_openai import ChatOpenAI
    from langchain.agents import initialize_agent, Tool, AgentType
    from llumo import LlumoLogger
    ```

    ```python theme={null}
    logger = LlumoLogger(apiKey=llumoKey, playground="playground-agent-logs")
    ```

    ```python theme={null}
    sessionContext = LlumoSessionContext(logger=logger)
    sessionContext.start()

    sessionContext.startLlumoRun(runName="QUERY_EXECUTION")
    callbackHandler = LlumoCallbackHandler(session=sessionContext)

    try:
        # Execute query
        result = agent.run(q, callbacks=[callbackHandler])
    except Exception as e:
        print(f"❌ Error: {str(e)}")

    # End Run
    sessionContext.endLlumoRun()

    # End Session
    sessionContext.end()
    ```
  </Accordion>

  <Accordion title="OpenAI">
    ```python theme={null}
    from llumo.openai import OpenAI
    from llumo.llumoLogger import LlumoLogger
    from llumo.llumoSessionContext import LlumoSessionContext

    logger = LlumoLogger(apiKey=llumoKey, playground="playground-openai-raw")

    # Initialize and start the Llumo Session
    session = LlumoSessionContext(logger = logger)

    ```

    ```python theme={null}
    client = OpenAI(
        api_key="openaiKey",
        session=session,
    )

    # Start Session
    session.start()
    session.startLlumoRun(runName="QUERY_EXECUTION")

    messages = [{"role": "user", "content": query}]

    # Output Generation
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=messages,
        createExperiment=True,
    )

    aiOutput = response.choices[0].message.content
    results.append({"query": query, "output": aiOutput})

    # End Run
    session.endLlumoRun()

    # End Session
    session.end()


    ```
  </Accordion>

  <Accordion title="Evaluate">
    ```python theme={null}
    from llumo import LlumoLogger, LlumoSessionContext

    # Initialize logger
    logger = LlumoLogger(
        apiKey=llumoKey,
        playground="playground-batch-eval"
    )

    # Initialize Llumo session
    session = LlumoSessionContext(logger=logger)

    # Run multiple evaluations
    resData = session.evaluateMultiple(
        data,
        evals=[
            "Response Correctness",
            "Hallucination",
            "Response Completeness",
            "Input Bias",
        ],
        createExperiment=True,  # Creates a named experiment in your dashboard
    )

    # Print results
    print(resData)

    ```
  </Accordion>
</AccordionGroup>

## 4. View Results on the LLUMO AI Dashboard

Once you have integrated the SDK, we will handle all the heavy lifting, from logging, evaluating, creating run-reports, analysis issues across different runs and creating flow graph and insights for you. You can check out the whole debug reports on
[app.llumo.ai/debugger](https://app.llumo.ai/debugger)