---
title: Apertis
 | Developer Documentation
---

Apertis provides a unified API gateway to access multiple LLM providers including OpenAI, Anthropic, Google, and more through an OpenAI-compatible interface. You can find out more on their [documentation](https://docs.stima.tech).

**Supported Endpoints:**

- `/v1/chat/completions` - OpenAI Chat Completions format (default)
- `/v1/responses` - OpenAI Responses format compatible
- `/v1/messages` - Anthropic format compatible

If you’re opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.

```
%pip install llama-index-llms-apertis
```

```
!pip install llama-index
```

```
from llama_index.llms.apertis import Apertis
from llama_index.core.llms import ChatMessage
```

## Call `chat` with ChatMessage List

You need to either set env var `APERTIS_API_KEY` or set api\_key in the class constructor

```
# import os
# os.environ['APERTIS_API_KEY'] = '<your-api-key>'


llm = Apertis(
    api_key="<your-api-key>",
    max_tokens=256,
    context_window=4096,
    model="gpt-5.2",
)
```

```
message = ChatMessage(role="user", content="Tell me a joke")
resp = llm.chat([message])
print(resp)
```

### Streaming

```
message = ChatMessage(role="user", content="Tell me a story in 250 words")
resp = llm.stream_chat([message])
for r in resp:
    print(r.delta, end="")
```

## Call `complete` with Prompt

```
resp = llm.complete("Tell me a joke")
print(resp)
```

```
resp = llm.stream_complete("Tell me a story in 250 words")
for r in resp:
    print(r.delta, end="")
```

## Model Configuration

Apertis supports models from multiple providers:

| Provider  | Example Models                     |
| --------- | ---------------------------------- |
| OpenAI    | `gpt-5.2`, `gpt-5-mini-2025-08-07` |
| Anthropic | `claude-sonnet-4.5`                |
| Google    | `gemini-3-flash-preview`           |

```
# Using Claude
llm = Apertis(model="claude-sonnet-4.5")
```

```
resp = llm.complete("Write a story about a dragon who can code in Rust")
print(resp)
```

```
# Using Gemini
llm = Apertis(model="gemini-3-flash-preview")
```

```
resp = llm.complete("Explain quantum computing in simple terms")
print(resp)
```