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

# Using Prompts in Code

> Fetch deployed prompts from HoneyHive and use them in your application.

After saving and deploying prompts in the [Playground](/v2/prompts/overview), fetch them in your application using the SDK.

## Environments

Each project has three deployment environments:

| Environment | Purpose                   |
| ----------- | ------------------------- |
| `dev`       | Development and testing   |
| `staging`   | Pre-production validation |
| `prod`      | Production deployment     |

Deploy prompts to environments in **Studio > Prompts** by selecting a saved prompt and choosing an environment.

## Fetching and Using Prompts

```python theme={null}
import os
from openai import OpenAI
from honeyhive import HoneyHive

client = HoneyHive(api_key=os.environ["HH_API_KEY"])
openai = OpenAI()

# Fetch all configurations and find the one you want
configs = client.configurations.list()

def get_prompt(name: str, env: str = "prod"):
    for c in configs:
        d = c.model_dump() if hasattr(c, "model_dump") else c
        # env is an array of deployed environments
        if d.get("name") == name and env in d.get("env", []):
            return d
    return None

# Use the prompt
prompt = get_prompt("my-prompt", "prod")
if prompt:
    params = prompt["parameters"]
    response = openai.chat.completions.create(
        model=params["model"],
        messages=params["template"],
        **params.get("hyperparameters", {})
    )
```

<Note>The Python SDK returns all configurations. Filter client-side by `name` and `env` to get specific prompts.</Note>

## Caching for Production

Cache prompts to reduce API calls:

```python theme={null}
from functools import lru_cache

@lru_cache(maxsize=100)
def get_prompt_cached(name: str, env: str = "prod"):
    configs = client.configurations.list()
    for c in configs:
        d = c.model_dump() if hasattr(c, "model_dump") else c
        if d.get("name") == name and env in d.get("env", []):
            return d
    return None

# Clear cache when prompts are updated: get_prompt_cached.cache_clear()
```

<Tip>Set a TTL on your cache to automatically refresh prompts when they're updated.</Tip>

## YAML Export

For static deployments or version control, export prompts as YAML:

```python theme={null}
import os
import yaml
from honeyhive import HoneyHive

client = HoneyHive(api_key=os.environ["HH_API_KEY"])
configs = client.configurations.list()

# Find and export a prompt
for c in configs:
    d = c.model_dump() if hasattr(c, "model_dump") else c
    if d.get("name") == "my-prompt" and "prod" in d.get("env", []):
        with open("prompts/my-prompt.yaml", "w") as f:
            yaml.dump(d, f, default_flow_style=False)
        break
```

Load in your application:

```python theme={null}
import yaml

with open("prompts/my-prompt.yaml") as f:
    config = yaml.safe_load(f)

params = config["parameters"]
template = params["template"]
model = params["model"]
```

## Related

<CardGroup cols={2}>
  <Card title="Prompt Playground" icon="comment-dots" href="/v2/prompts/overview">
    Create and test prompts before deploying.
  </Card>

  <Card title="API Reference" icon="code" href="/v2/api-reference/configurations/retrieve-a-list-of-configurations">
    Full configurations API documentation.
  </Card>
</CardGroup>