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The chat completions endpoint provides OpenAI-compatible API access to AgentOS agents. This allows you to integrate AgentOS with any tool that supports the OpenAI API format.

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Endpoint

POST /v1/chat/completions

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Request

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model
string
default:"claude-sonnet-4-6"
The model to use for completion. Supports all 25 LLM providers and 47 models available in AgentOS.
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messages
array
required
Array of message objects in OpenAI format.
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temperature
number
Sampling temperature (0-2). Higher values make output more random.
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max_tokens
number
Maximum number of tokens to generate.
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stream
boolean
default:false
Whether to stream responses. Currently processes through the default agent.

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Response

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id
string
Unique identifier for the chat completion (format: chatcmpl-xxxxxxxx).
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object
string
Always "chat.completion".
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created
number
Unix timestamp of when the completion was created.
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model
string
The model used for the completion.
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choices
array
Array of completion choices.
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usage
object
Token usage information.

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Examples

curl -X POST http://localhost:3111/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "messages": [
      {
        "role": "user",
        "content": "What can you help me with?"
      }
    ]
  }'

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Response Example

{
  "id": "chatcmpl-a3f2b1c4",
  "object": "chat.completion",
  "created": 1709856000,
  "model": "claude-sonnet-4-6",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "I can help you with a wide range of tasks including:\n\n- Answering questions and providing information\n- Writing and editing code\n- Analyzing data and files\n- Searching the web\n- Managing workflows\n- And much more!\n\nWhat would you like assistance with?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 15,
    "completion_tokens": 87,
    "total_tokens": 102
  }
}

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Implementation Details

The endpoint:
  1. Extracts the last message from the messages array
  2. Routes it to the default agent via agent::chat function
  3. Creates a unique session ID with format api:{timestamp}
  4. Returns the response in OpenAI-compatible format
The actual agent processing includes:
  • Security capability checks
  • Memory recall and storage
  • LLM routing based on model selection
  • Tool execution (60+ tools available)
  • Loop guard protection
  • Session replay recording

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Rate Limiting

Chat completions are limited to 60 requests per hour per IP address.

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Supported Models

AgentOS supports 47 models across 25 providers. Some examples:
  • Anthropic: claude-opus-4, claude-sonnet-4-6, claude-haiku-4
  • OpenAI: gpt-4o, gpt-4o-mini, o1, o3-mini
  • Google: gemini-2.0-flash, gemini-2.0-pro
  • DeepSeek: deepseek-v3, deepseek-r1
  • And many more…
See the full list with agentos models list.

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