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

# Moonshot

> Use Moonshot (Kimi) models for AI generation.

## Setup

```bash theme={null}
export MOONSHOT_API_KEY="sk-..."
```

## Basic Usage

```python theme={null}
from definable.model import MoonshotChat
from definable.model.message import Message

model = MoonshotChat(id="kimi-k2-turbo-preview")
response = model.invoke(
    messages=[Message(role="user", content="Hello!")],
    assistant_message=Message(role="assistant", content=""),
)
print(response.content)
```

## Parameters

<ParamField path="id" type="str" default="kimi-k2-turbo-preview">
  Model identifier.
</ParamField>

<ParamField path="api_key" type="str">
  Moonshot API key. Defaults to the `MOONSHOT_API_KEY` environment variable.
</ParamField>

<ParamField path="base_url" type="str" default="https://api.moonshot.ai/v1">
  Moonshot API base URL.
</ParamField>

<ParamField path="temperature" type="float">
  Sampling temperature.
</ParamField>

<ParamField path="max_tokens" type="int">
  Maximum output tokens.
</ParamField>

## Streaming

```python theme={null}
from definable.model.message import Message

for chunk in model.invoke_stream(
    messages=[Message(role="user", content="Write a haiku about coding.")],
    assistant_message=Message(role="assistant", content=""),
):
    if chunk.content:
        print(chunk.content, end="", flush=True)
```

## Async Usage

```python theme={null}
from definable.model.message import Message

response = await model.ainvoke(
    messages=[Message(role="user", content="Hello!")],
    assistant_message=Message(role="assistant", content=""),
)
```

<Note>
  Moonshot uses an OpenAI-compatible API. All standard parameters like `temperature`, `max_tokens`, `top_p`, and `stop` are supported.
</Note>