Chat Completion API

API Overview

This API is used to create chat completions, process provided messages, and generate responses. The API supports streaming responses and is compatible with OpenAI format.

Prerequisites

Before using this API, you need to:

Register: Execute the register operation to create your instance
Status Check: Wait until your instance status becomes "online"
Get Instance ID: Obtain your unique {instance_id} from the registration response
API Access: Use the instance ID to construct the API endpoint: https://app.secondme.io/api/chat/{instance_id}

API Endpoints

POST /api/chat/{instance_id}
POST /api/chat/{instance_id}/chat/completions

Path Parameters

Parameter	Type	Required	Description
`instance_id`	string	Yes	Unique identifier for the model instance, obtained during registration

Request Body

Field	Type	Required	Default	Description
`messages`	array	Yes	-	List of messages in the conversation
`metadata`	object	No	null	Additional metadata for the request
`temperature`	float	No	0.7	Controls randomness of the response, value between 0 and 1
`max_tokens`	integer	No	2000	Maximum number of tokens to generate
`stream`	boolean	No	true	Whether to stream the response

messages Field

Each message should contain the following fields:

Field	Type	Required	Description
`role`	string	Yes	Role of the message sender. Can be 'system', 'user', or 'assistant'
`content`	string	Yes	Content of the message

metadata Field

Field	Type	Required	Description
`enable_l0_retrieval`	boolean	No	Whether to enable L0 level retrieval
`role_id`	string	No	Role ID to use for this chat

Response

Server-Sent Events (SSE) stream in OpenAI-compatible format
Each event contains a fragment of the generated response
The last event is marked as [DONE]

Response Format Example

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"lpm-registry-model","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"lpm-registry-model","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" world!"},"finish_reason":null}]}

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"lpm-registry-model","system_fingerprint":null,"choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]

Request Examples

cURL

bash

curl -X POST "https://app.secondme.io/api/chat/{instance_id}" \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello, please introduce yourself."}
    ],
    "metadata": {
      "enable_l0_retrieval": false,
      "role_id": "default_role"
    },
    "temperature": 0.7,
    "max_tokens": 2000,
    "stream": true
  }'

Python

python

import http.client
import json

url = "app.secondme.io"
path = "/api/chat/{instance_id}"           

headers = {"Content-Type": "application/json"}
data = {
    "messages": [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello, please introduce yourself."}
    ],
    "metadata": {
        "enable_l0_retrieval": False,
        "role_id": "default_role"
    },
    "temperature": 0.7,
    "max_tokens": 2000,
    "stream": True
}

# Prepare the connection
conn = http.client.HTTPSConnection(url)

# Send the POST request
conn.request("POST", path, body=json.dumps(data), headers=headers)

# Get the response
response = conn.getresponse()


# Read the body line by line
for line in response:
    if line:
        decoded_line = line.decode('utf-8').strip()
        if decoded_line == 'data: [DONE]':
            break
        if decoded_line.startswith('data: '):
            try:
                json_str = decoded_line[6:]
                chunk = json.loads(json_str)
                content = chunk['choices'][0]['delta'].get('content', '')
                if content:
                    print(content, end='', flush=True)
            except json.JSONDecodeError:
                pass

# Close the connection when done
conn.close()

Error Codes

Status Code	Description
404	Instance not found
422	Invalid request parameters
503	Instance not connected or unavailable

Notes

Before using this API, ensure that the instance is registered and connected to the server (status: "online")
The instance ID is unique and required for all API calls
For streaming responses, the client should be able to handle data in SSE format
Roles in the message list should follow the conversation order, typically starting with 'system' or 'user'