---
title: Chat Completions
description: OpenAI-compatible chat completions API with streaming support for elizaOS Cloud.
---
# Chat Completions
OpenAI-compatible chat completions endpoint for conversational AI.
## Create Chat Completion
POST
/api/v1/chat/completions
Generate a chat completion response from the model.
### Request
```bash
curl -X POST "https://elizacloud.ai/api/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-oss-120b",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
],
"temperature": 0.7
}'
```
```javascript
const response = await fetch('https://elizacloud.ai/api/v1/chat/completions', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'gpt-oss-120b',
messages: [
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Hello!' }
],
temperature: 0.7,
}),
});
const data = await response.json();
console.log(data.choices[0].message.content);
```
```python
import requests
response = requests.post(
'https://elizacloud.ai/api/v1/chat/completions',
headers={
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'gpt-oss-120b',
'messages': [
{'role': 'system', 'content': 'You are a helpful assistant.'},
{'role': 'user', 'content': 'Hello!'}
],
'temperature': 0.7,
}
)
data = response.json()
print(data['choices'][0]['message']['content'])
```
### Parameters
| Parameter | Type | Required | Description |
| ------------------- | ------------ | -------- | -------------------------------------- |
| `model` | string | ✓ | Model ID or agent ID |
| `messages` | array | ✓ | Array of message objects |
| `temperature` | number | | Sampling temperature (0-2). Default: 1 |
| `max_tokens` | integer | | Maximum tokens to generate |
| `stream` | boolean | | Stream response chunks. Default: false |
| `top_p` | number | | Nucleus sampling parameter (0-1) |
| `frequency_penalty` | number | | Frequency penalty (-2 to 2) |
| `presence_penalty` | number | | Presence penalty (-2 to 2) |
| `stop` | string/array | | Stop sequences |
| `user` | string | | Unique user identifier |
### Message Object
| Field | Type | Required | Description |
| --------- | ------ | -------- | ---------------------------------------- |
| `role` | string | ✓ | `system`, `user`, `assistant`, or `tool` |
| `content` | string | ✓ | Message content |
| `name` | string | | Optional name for the participant |
### Response
```json
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1705312800,
"model": "gpt-oss-120b",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help you today?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 20,
"completion_tokens": 10,
"total_tokens": 30
}
}
```
---
## Streaming
Enable streaming for real-time responses by setting `stream: true`.
### Streaming Request
```javascript
const response = await fetch("https://elizacloud.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gpt-oss-120b",
messages: [{ role: "user", content: "Tell me a story" }],
stream: true,
}),
});
const reader = response.body.getReader();
const decoder = new TextDecoder();
while (true) {
const { done, value } = await reader.read();
if (done) break;
const chunk = decoder.decode(value);
const lines = chunk.split("\n").filter((line) => line.startsWith("data: "));
for (const line of lines) {
const data = line.slice(6);
if (data === "[DONE]") continue;
const parsed = JSON.parse(data);
process.stdout.write(parsed.choices[0]?.delta?.content || "");
}
}
```
---
## Using with Agents
You can use an agent ID as the model to chat with your custom AI agents:
```json
{
"model": "agent_abc123",
"messages": [{ "role": "user", "content": "Hello!" }]
}
```
The agent's personality, system prompt, and configured model will be used
automatically.
---
## Available Models
Model availability changes as provider catalogs and account configuration
change. See the [Models API](/cloud/api/models) or API Explorer for the current
catalog and defaults.