Chat Completions

Generate chat completions with conversation context

Chat Completions

The chat completions endpoint is the recommended way to generate text. It supports multi-turn conversations with system, user, and assistant messages.

This endpoint is OpenAI-compatible. If you’re migrating from OpenAI, most code will work with minimal changes.

Create Chat Completion

POST /v1/chat/completions

Generate a chat completion for the given messages.

Request Body

Parameter	Type	Required	Default	Description
model	string	Yes	—	Model ID (e.g., llama-3.1-8b)
messages	array	Yes	—	Array of message objects
max_tokens	integer	No	150	Maximum tokens to generate (1-4096)
temperature	number	No	0.7	Sampling temperature (0.0-2.0)
top_p	number	No	0.9	Nucleus sampling (0.0-1.0)
top_k	integer	No	—	Top-k sampling
frequency_penalty	number	No	0.0	Frequency penalty (-2.0 to 2.0)
presence_penalty	number	No	0.0	Presence penalty (-2.0 to 2.0)
stop	array	No	—	Up to 4 stop sequences
stream	boolean	No	false	Enable streaming
user	string	No	—	End-user identifier

Message Format

{
  "role": "system" | "user" | "assistant",
  "content": "message text"
}

Example Request

cURL

curl -X POST https://api.ymq-01.edge.polargrid.ai:55111/v1/chat/completions \
  -H "Authorization: Bearer pg_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.1-8b",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "What is the capital of France?"}
    ],
    "max_tokens": 100,
    "temperature": 0.7
  }'

Response

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1234567890,
  "model": "llama-3.1-8b",
  "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

For real-time responses, enable streaming:

JavaScript

for await (const chunk of client.chatCompletionStream({
  model: 'llama-3.1-8b',
  messages: [{ role: 'user', content: 'Tell me a story' }],
})) {
  const content = chunk.choices[0]?.delta?.content;
  if (content) {
    process.stdout.write(content);
  }
}

Stream Response Format

Each chunk is a Server-Sent Event:

data: {"id":"chatcmpl-abc","object":"chat.completion.chunk","choices":[{"delta":{"content":"The"}}]}

data: {"id":"chatcmpl-abc","object":"chat.completion.chunk","choices":[{"delta":{"content":" capital"}}]}

data: {"id":"chatcmpl-abc","object":"chat.completion.chunk","choices":[{"delta":{},"finish_reason":"stop"}]}

data: [DONE]

Finish Reasons

Reason	Description
stop	Natural completion or stop sequence hit
length	Max tokens reached
content_filter	Content filtered