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POST
/
chat
/
completions
Chat Completions
curl --request POST \
  --url https://modelslab.com/api/v7/llm/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "messages": [
    {
      "content": "<string>"
    }
  ],
  "model": "<string>",
  "max_tokens": 1000,
  "temperature": 1,
  "top_p": 1,
  "stream": false,
  "presence_penalty": 0,
  "frequency_penalty": 0
}
'
{
  "id": "<string>",
  "created": 123,
  "model": "<string>",
  "choices": [
    {
      "index": 123,
      "message": {
        "content": "<string>"
      }
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123
  }
}

Documentation Index

Fetch the complete documentation index at: https://docs.modelslab.com/llms.txt

Use this file to discover all available pages before exploring further.

​
Request

POST https://modelslab.com/api/v7/llm/chat/completions
Pass your API key as a Bearer token in the Authorization header. 
curl -X POST https://modelslab.com/api/v7/llm/chat/completions \
  -H "Authorization: Bearer $MODELSLAB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen2.5-VL-72B-Instruct-together",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "What is the capital of France?"}
    ],
    "max_tokens": 1000,
    "temperature": 0.7
  }'

​
Body

{
  "model": "Qwen/Qwen2.5-VL-72B-Instruct-together",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "What is the capital of France?"}
  ],
  "max_tokens": 1000,
  "temperature": 0.7,
  "top_p": 1,
  "stream": false,
  "presence_penalty": 0,
  "frequency_penalty": 0
}

​
Response

{
  "id": "chat-abc123",
  "object": "chat.completion",
  "created": 1712345678,
  "model": "Qwen/Qwen2.5-VL-72B-Instruct-together",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 8,
    "total_tokens": 33
  }
}

​
Streaming

Set "stream": true to receive Server-Sent Events (SSE) as tokens are generated: 
curl -X POST https://modelslab.com/api/v7/llm/chat/completions \
  -H "Authorization: Bearer $MODELSLAB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen2.5-VL-72B-Instruct-together",
    "messages": [{"role": "user", "content": "Write a haiku"}],
    "stream": true
  }'
Each SSE event contains a chat.completion.chunk object: 
data: {"id":"chat-abc123","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":"Silent"},"finish_reason":null}]}
data: {"id":"chat-abc123","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":" snow"},"finish_reason":null}]}
data: [DONE]

​
OpenAI SDK

This endpoint is fully compatible with the OpenAI SDK. Just change the base_url and api_key: 
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_MODELSLAB_API_KEY",
    base_url="https://modelslab.com/api/v7/llm",
)

# Non-streaming
response = client.chat.completions.create(
    model="Qwen/Qwen2.5-VL-72B-Instruct-together",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain quantum computing in simple terms"},
    ],
    max_tokens=1000,
)
print(response.choices[0].message.content)

# Streaming
stream = client.chat.completions.create(
    model="Qwen/Qwen2.5-VL-72B-Instruct-together",
    messages=[{"role": "user", "content": "Write a story"}],
    stream=True,
)
for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Authorizations

​
Authorization
string
header
required

Bearer token authentication using ModelsLab API key

Body

application/json
​
messages
object[]
required

Array of chat messages

​
model
string

Model ID to use for the completion (e.g. 'Qwen/Qwen2.5-VL-72B-Instruct-together')

​
max_tokens
integer
default:1000

Maximum number of tokens to generate

Required range: x >= 1
​
temperature
number
default:1

Sampling temperature (0-2). Higher values make output more random.

Required range: 0 <= x <= 2
​
top_p
number
default:1

Nucleus sampling parameter

Required range: 0 <= x <= 1
​
stream
boolean
default:false

Whether to stream partial results as Server-Sent Events

​
presence_penalty
number
default:0

Penalize new tokens based on whether they appear in the text so far

Required range: -2 <= x <= 2
​
frequency_penalty
number
default:0

Penalize new tokens based on their frequency in the text so far

Required range: -2 <= x <= 2

Response

Chat completion response

​
id
string

Unique completion ID

​
object
enum<string>
Available options:
chat.completion
​
created
integer

Unix timestamp

​
model
string

Model used

​
choices
object[]
​
usage
object