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

# Stream Chat

> AI SDK compatible chat streaming endpoint

## Request Body

<ParamField body="chatId" type="string" required>
  Chat session identifier
</ParamField>

<ParamField body="messages" type="array" required>
  Array of message objects

  <Expandable title="message properties">
    <ResponseField name="role" type="string" required>
      Message role: `system`, `user`, or `assistant`
    </ResponseField>

    <ResponseField name="content" type="string" required>
      Message content
    </ResponseField>
  </Expandable>
</ParamField>

<ParamField body="model" type="string" default="gpt-4o">
  Model identifier
</ParamField>

<ParamField body="provider" type="string">
  Provider name (e.g., OpenAI, Anthropic, Google)
</ParamField>

<ParamField body="system" type="string">
  System prompt for the conversation
</ParamField>

## Response

The endpoint returns a streaming response compatible with the AI SDK. The response is streamed as Server-Sent Events (SSE).

<RequestExample>
  ```bash cURL theme={null}
  curl --request POST \
    --url https://api.yourapp.com/api/ai/stream-chat \
    --header 'Authorization: Bearer <token>' \
    --header 'Content-Type: application/json' \
    --data '{
      "chatId": "chat_123",
      "messages": [
        {
          "role": "user",
          "content": "Tell me about AI"
        }
      ],
      "model": "gpt-4o",
      "system": "You are a helpful AI assistant."
    }'
  ```

  ```javascript JavaScript theme={null}
  const response = await fetch('https://api.yourapp.com/api/ai/stream-chat', {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      chatId: 'chat_123',
      messages: [
        {
          role: 'user',
          content: 'Tell me about AI'
        }
      ],
      model: 'gpt-4o',
      system: 'You are a helpful AI assistant.'
    })
  });

  // Handle streaming response
  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);
    console.log(chunk);
  }
  ```

  ```python Python theme={null}
  import requests

  url = "https://api.yourapp.com/api/ai/stream-chat"
  headers = {
      "Authorization": "Bearer <token>",
      "Content-Type": "application/json"
  }
  payload = {
      "chatId": "chat_123",
      "messages": [
          {
              "role": "user",
              "content": "Tell me about AI"
          }
      ],
      "model": "gpt-4o",
      "system": "You are a helpful AI assistant."
  }

  response = requests.post(url, json=payload, headers=headers, stream=True)

  # Handle streaming response
  for chunk in response.iter_content(chunk_size=None):
      if chunk:
          print(chunk.decode('utf-8'))
  ```
</RequestExample>

<ResponseExample>
  ```text Streaming Response theme={null}
  0:"AI"
  0:" is"
  0:" a"
  0:" field"
  0:" of"
  0:" computer"
  0:" science"
  ...
  ```

  ```json Error Response theme={null}
  {
    "success": false,
    "message": "Unauthorized"
  }
  ```
</ResponseExample>