---
title: "Empower"
description: "```python import os os.environ[\"EMPOWER_API_KEY\"] = \"your-api-key\" ``` ## Example Usage"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/empower
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:24:10.649Z
license: CC-BY-4.0
attribution: "Empower — Claudary (https://claudary.paisolsolutions.com/skills/empower)"
---

# Empower
```python import os os.environ["EMPOWER_API_KEY"] = "your-api-key" ``` ## Example Usage

## Overview

# Empower
LiteLLM supports all models on Empower. 

## API Keys

```python 
import os 
os.environ["EMPOWER_API_KEY"] = "your-api-key"
```
## Example Usage

```python
from litellm import completion 
import os

os.environ["EMPOWER_API_KEY"] = "your-api-key"

messages = [{"role": "user", "content": "Write me a poem about the blue sky"}]

response = completion(model="empower/empower-functions", messages=messages)
print(response)
```

## Example Usage - Streaming
```python
from litellm import completion 
import os

os.environ["EMPOWER_API_KEY"] = "your-api-key"

messages = [{"role": "user", "content": "Write me a poem about the blue sky"}]

response = completion(model="empower/empower-functions", messages=messages, streaming=True)
for chunk in response:
    print(chunk['choices'][0]['delta'])

```

## Example Usage - Automatic Tool Calling

```python
from litellm import completion 
import os

os.environ["EMPOWER_API_KEY"] = "your-api-key"

messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}]
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "Get the current weather in a given location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "The city and state, e.g. San Francisco, CA",
                    },
                    "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
                },
                "required": ["location"],
            },
        },
    }
]

response = completion(
    model="empower/empower-functions-small",
    messages=messages,
    tools=tools,
    tool_choice="auto",  # auto is default, but we'll be explicit
)
print("\\nLLM Response:\\n", response)
```

## Empower Models
liteLLM supports `non-streaming` and `streaming` requests to all models on https://empower.dev/

Example Empower Usage - Note: liteLLM supports all models deployed on Empower


### Empower LLMs - Automatic Tool Using models
| Model Name                        | Function Call                                                          | Required OS Variables           |
|-----------------------------------|------------------------------------------------------------------------|---------------------------------|
| empower/empower-functions  | `completion('empower/empower-functions', messages)`            | `os.environ['TOGETHERAI_API_KEY']` |
| empower/empower-functions-small  | `completion('empower/empower-functions-small', messages)`            | `os.environ['TOGETHERAI_API_KEY']` |

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/empower) · https://claudary.paisolsolutions.com