# Ell — Prompt Engineering as Code in Python

> Treat prompts as versioned Python functions with automatic tracking, visualization, and A/B testing. Like Git for your AI prompts with a beautiful studio UI.

## Install

Paste the prompt below into your AI tool:

## Quick Use

```bash
pip install ell-ai
```

```python
import ell

@ell.simple(model="claude-sonnet-4-20250514")
def summarize(text: str) -> str:
    "You are a concise summarizer."
    return f"Summarize this: {text}"

result = summarize("Long article text here...")
print(result)
```

## What is Ell?

Ell treats prompts as versioned, typed Python functions instead of opaque strings. Every prompt call is automatically tracked with inputs, outputs, and metadata — viewable in Ell Studio, a local visualization tool. It brings software engineering practices (versioning, testing, monitoring) to prompt engineering.

**Answer-Ready**: Ell is a Python library that treats AI prompts as versioned functions with automatic tracking, visualization in Ell Studio, and A/B testing. It brings software engineering practices to prompt engineering. 6k+ GitHub stars.

**Best for**: Teams iterating on prompts who need versioning and analytics. **Works with**: OpenAI, Anthropic, any OpenAI-compatible API. **Setup time**: Under 2 minutes.

## Core Features

### 1. Prompts as Functions

```python
import ell

@ell.simple(model="claude-sonnet-4-20250514")
def write_poem(topic: str) -> str:
    "You are a creative poet."
    return f"Write a short poem about {topic}"

# Every call is tracked automatically
poem = write_poem("sunset")
```

### 2. Complex Prompts (Multi-Message)

```python
@ell.complex(model="claude-sonnet-4-20250514")
def chat(history: list[ell.Message]) -> list[ell.Message]:
    return [
        ell.system("You are a helpful assistant."),
        *history,
    ]
```

### 3. Ell Studio — Visual Dashboard

```bash
ell-studio --storage ./ell_logs
# Opens http://localhost:8000
```

Studio shows:
- Version history of each prompt function
- Input/output pairs for every call
- Latency and token usage metrics
- Diff view between prompt versions

### 4. Automatic Versioning
Ell detects when you change a prompt function and creates a new version:

```python
# Version 1
@ell.simple(model="claude-sonnet-4-20250514")
def greet(name: str):
    "You are friendly."
    return f"Say hi to {name}"

# Version 2 (auto-detected)
@ell.simple(model="claude-sonnet-4-20250514")
def greet(name: str):
    "You are friendly and enthusiastic."
    return f"Enthusiastically greet {name}"
```

### 5. Multimodal Support

```python
from PIL import Image

@ell.simple(model="gpt-4o")
def describe_image(image: Image.Image):
    return [
        ell.system("Describe this image in detail."),
        ell.user(["What do you see?", image]),
    ]
```

## Why Use Ell?

| Without Ell | With Ell |
|-------------|----------|
| Prompts as strings in code | Prompts as typed functions |
| Manual copy-paste to track changes | Automatic version control |
| No visibility into prompt performance | Studio dashboard with metrics |
| Hard to compare prompt variants | Built-in A/B comparison |

## FAQ

**Q: How does it compare to LangChain?**
A: Ell is focused purely on prompt engineering — versioning, tracking, and iteration. LangChain is a broader framework for chains and agents.

**Q: Does it work with Claude?**
A: Yes, Anthropic Claude is fully supported.

**Q: Where is the data stored?**
A: Locally in SQLite (default: `./ell_logs/`). No data sent externally.

## Source & Thanks

> Created by [William Guss](https://github.com/MadcowD). Licensed under MIT.
>
> [MadcowD/ell](https://github.com/MadcowD/ell) — 6k+ stars

<!-- ZH -->

## 快速使用

```bash
pip install ell-ai
```

用 Python 装饰器定义 prompt，自动跟踪版本和调用。

## 什么是 Ell？

Ell 将 AI 提示词视为带版本的 Python 函数。每次调用自动追踪输入输出，可在 Ell Studio 可视化面板中查看。

**一句话总结**：Ell 是 Python 库，将提示词作为版本化函数管理，提供自动追踪、可视化和 A/B 测试，6k+ GitHub stars。

**适合人群**：需要提示词版本管理和分析的团队。**支持**：OpenAI、Anthropic、兼容 API。

## 核心功能

### 1. 提示词即函数
用 `@ell.simple` 装饰器定义，自动追踪。

### 2. Ell Studio 可视化
本地仪表盘查看版本历史、调用记录、性能指标。

### 3. 自动版本控制
修改提示词函数自动创建新版本。

### 4. 多模态支持
支持图片、文本混合输入。

## 常见问题

**Q: 和 LangChain 比较？**
A: Ell 专注提示词工程（版本、追踪、迭代），LangChain 是更广的框架。

**Q: 数据存在哪？**
A: 本地 SQLite，不发送外部。

## 来源与致谢

> [MadcowD/ell](https://github.com/MadcowD/ell) — 6k+ stars, MIT

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Author: Script Depot