# 📓 Text to Text Quickstart

In this quickstart you will create a simple text to text application and learn how to log it and get feedback.

## Setup

### Add API keys

For this quickstart you will need an OpenAI Key.

```python
# !pip install trulens trulens-providers-openai openai
```

```python
import os

if "OPENAI_API_KEY" not in os.environ:
    os.environ["OPENAI_API_KEY"] = "sk-proj-..."
```

### Import from TruLens

```python
# Create openai client
from openai import OpenAI

# Imports main tools:
from trulens.core import Metric
from trulens.core import Selector
from trulens.core import TruSession
from trulens.providers.openai import OpenAI as fOpenAI

client = OpenAI()
session = TruSession()
session.reset_database()
```

### Create Simple Text to Text Application

This example uses a bare bones OpenAI LLM, and a non-LLM just for demonstration purposes.

```python
def llm_standalone(prompt):
    return (
        client.chat.completions.create(
            model="gpt-4.1-mini",
            messages=[
                {
                    "role": "system",
                    "content": "You are a question and answer bot, and you answer super upbeat.",
                },
                {"role": "user", "content": prompt},
            ],
        )
        .choices[0]
        .message.content
    )
```

### Send your first request

```python
prompt_input = "How good is language AI?"
prompt_output = llm_standalone(prompt_input)
prompt_output
```

## Initialize Feedback Function(s)

```python
# Initialize OpenAI-based feedback function collection class:
fopenai = fOpenAI()

# Define a relevance function from openai
f_answer_relevance = Metric(
    implementation=fopenai.relevance,
    selectors={
        "prompt": Selector.select_record_input(),
        "response": Selector.select_record_output(),
    },
)
```

## Instrument the callable for logging with TruLens

```python
from trulens.apps.basic import TruBasicApp

tru_llm_standalone_recorder = TruBasicApp(
    llm_standalone, app_name="Happy Bot", feedbacks=[f_answer_relevance]
)
```

```python
with tru_llm_standalone_recorder as recording:
    tru_llm_standalone_recorder.app(prompt_input)
```

## Explore in a Dashboard

```python
from trulens.dashboard import run_dashboard

run_dashboard(session)  # open a local streamlit app to explore

# stop_dashboard(session) # stop if needed
```

## Or view results directly in your notebook

```python
session.get_records_and_feedback()[0]
```