Generate Completions

curl --request POST \
  --url https://api.nugen.in/api/v3/inference/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "max_tokens": 400,
  "model": "nugen-flash-instruct",
  "prompt": "The sky is",
  "stream": false,
  "temperature": 1
}
'

import requests

url = "https://api.nugen.in/api/v3/inference/completions"

payload = {
    "max_tokens": 400,
    "model": "nugen-flash-instruct",
    "prompt": "The sky is",
    "stream": False,
    "temperature": 1
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    max_tokens: 400,
    model: 'nugen-flash-instruct',
    prompt: 'The sky is',
    stream: false,
    temperature: 1
  })
};

fetch('https://api.nugen.in/api/v3/inference/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.nugen.in/api/v3/inference/completions",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'max_tokens' => 400,
    'model' => 'nugen-flash-instruct',
    'prompt' => 'The sky is',
    'stream' => false,
    'temperature' => 1
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.nugen.in/api/v3/inference/completions"

	payload := strings.NewReader("{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.nugen.in/api/v3/inference/completions")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.nugen.in/api/v3/inference/completions")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}"

response = http.request(request)
puts response.read_body

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

Inference

Generate Completions

Generate text completions with streaming support.

This endpoint generates text completions using specified language models. Supports both streaming (real-time response chunks) and non-streaming modes. Ideal for text generation, continuation, and completion tasks.

Request Body:

model: Model ID (required). Use your aligned model id (e.g. aligned-model-01kmqm4nrn9fw6r); base text models (e.g. nugen-flash-instruct) also work if you have not aligned a model yet
prompt: Input to complete (required) - Can be:
- Single string
- List of strings
- Array of integers (tokenized prompt)
- Array of integer arrays (batch of tokenized prompts)
max_tokens (optional): Maximum tokens to generate (default: 16, minimum: 0)
temperature (optional): Sampling temperature between 0 and 2 (default: 1). Higher values like 0.8 make output more random, lower values like 0.2 make it more focused and deterministic
stream (optional): Enable streaming responses (default: false)

Optional Headers:

X-Session-ID: Session identifier for conversation tracking

Returns:

Non-streaming mode -

id: Unique identifier for the response
object: Object type (always text_completion)
created: Unix timestamp when response was generated
model: Model ID used for completion
choices: List of completion choices, each containing:
- text: Generated completion text
- index: Index of this choice
- finish_reason: Reason model stopped (stop for natural stop point, length if max tokens reached)
usage: Token usage statistics:
- prompt_tokens: Number of tokens in the prompt
- completion_tokens: Number of tokens generated
- total_tokens: Total tokens used (prompt + completion)
confidence_score (optional): Confidence score from Domain-Aligned AI models

Streaming mode - Server-sent events (SSE) stream with StreamingCompletionResponsev2 chunks containing:

id: Response identifier
object: Always text_completion
created: Timestamp
model: Model ID
choices: Completion chunks
usage (optional): Only in final chunk
confidence_score (optional): Only in final chunk

Example Request (Non-streaming):

POST /api/v3/inference/completions
Headers: {"Authorization": "Bearer <api_key>"}

{
  "model": "aligned-model-01kmqm4nrn9fw6r",
  "prompt": "Write a haiku about programming:",
  "max_tokens": 100,
  "temperature": 0.7
}

Example Response (Non-streaming):

{
  "id": "nugen-abc123",
  "object": "text_completion",
  "created": 1704123600.0,
  "model": "aligned-model-01kmqm4nrn9fw6r",
  "choices": [
    {
      "text": "Code flows like water,
Bugs emerge, then disappear,
Debug and refine.",
      "index": 0,
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 7,
    "completion_tokens": 18,
    "total_tokens": 25
  },
  "confidence_score": 86.5221
}

Example Request (Streaming):

POST /api/v3/inference/completions
Headers: {"Authorization": "Bearer <api_key>"}

{
  "model": "aligned-model-01kmqm4nrn9fw6r",
  "prompt": "Write a haiku about programming:",
  "max_tokens": 100,
  "temperature": 0.7,
  "stream": true
}

Example Response (Streaming):

data: {"id":"nugen-aligned-model-01kmqm4nrn9fw6r-abc123","object":"text_completion","created":1704123600.0,"model":"nugen-flash-instruct","choices":[{"text":"Code","index":0,"finish_reason":null}]}

data: {"id":"nugen-aligned-model-01kmqm4nrn9fw6r-abc123","object":"text_completion","created":1704123600.0,"model":"nugen-flash-instruct","choices":[{"text":" flows","index":0,"finish_reason":null}]}

data: {"id":"nugen-aligned-model-01kmqm4nrn9fw6r-abc123","object":"text_completion","created":1704123600.0,"model":"nugen-flash-instruct","choices":[{"text":" like water","index":0,"finish_reason":"stop"}],"usage":{"prompt_tokens":7,"completion_tokens":18,"total_tokens":25},"confidence_score":86.5221}

data: [DONE]

Example Request (Tokenized Prompt):

POST /api/v3/inference/completions
Headers: {"Authorization": "Bearer <api_key>"}

{
  "model": "aligned-model-01kmqm4nrn9fw6r",
  "prompt": [1014, 6766, 318],
  "max_tokens": 50,
  "temperature": 1
}

Notes:

Using Domain-Aligned Models: Pass the model_id from your completed alignment project as the model parameter. Get your aligned model IDs from GET /api/v3/alignment-project/status/{id} or GET /api/v3/models/aligned
Streaming provides real-time response generation for better user experience
The prompt parameter accepts pre-tokenized inputs for advanced use cases
Default max_tokens is 16 - adjust based on your needs
Temperature controls randomness: 0 = deterministic, 2 = very random
confidence_score (0-100) comes from inference-time alignment: uncertainty is quantified across the generation trajectory, flagging any drift from your domain. Available on aligned models
Include X-Session-ID header for multi-turn conversation tracking
Token usage is tracked and billed per request

POST

api

inference

completions

Generate Completions

curl --request POST \
  --url https://api.nugen.in/api/v3/inference/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "max_tokens": 400,
  "model": "nugen-flash-instruct",
  "prompt": "The sky is",
  "stream": false,
  "temperature": 1
}
'

import requests

url = "https://api.nugen.in/api/v3/inference/completions"

payload = {
    "max_tokens": 400,
    "model": "nugen-flash-instruct",
    "prompt": "The sky is",
    "stream": False,
    "temperature": 1
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    max_tokens: 400,
    model: 'nugen-flash-instruct',
    prompt: 'The sky is',
    stream: false,
    temperature: 1
  })
};

fetch('https://api.nugen.in/api/v3/inference/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.nugen.in/api/v3/inference/completions",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'max_tokens' => 400,
    'model' => 'nugen-flash-instruct',
    'prompt' => 'The sky is',
    'stream' => false,
    'temperature' => 1
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.nugen.in/api/v3/inference/completions"

	payload := strings.NewReader("{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.nugen.in/api/v3/inference/completions")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.nugen.in/api/v3/inference/completions")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"max_tokens\": 400,\n  \"model\": \"nugen-flash-instruct\",\n  \"prompt\": \"The sky is\",\n  \"stream\": false,\n  \"temperature\": 1\n}"

response = http.request(request)
puts response.read_body

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Headers

X-Session-ID

string | null

Body

application/json

model

string

required

Use your aligned model id (e.g. aligned-model-01kmqm4nrn9fw6r). The same aligned id serves chat completions, completions, embeddings and reranking. Base text models (e.g. nugen-flash-instruct) also work if you have not aligned a model yet.

Examples:

"aligned-model-01kmqm4nrn9fw6r"

"nugen-flash-instruct"

prompt

required

The prompt to generate completions for. It can be a single string or a list of strings. It can also be an array of integers or an array of integer arrays, which allows to pass already tokenized prompt.

Example:

"The sky is"

max_tokens

integer | null

default:16

The maximum number of tokens to generate in the completion.

Required range: x >= 0

Example:

400

temperature

number | null

default:1

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

Required range: 0 <= x <= 2

Example:

1

stream

boolean | null

default:false

Whether to stream back partial progress as server-sent events.

stream_options

Stream Options · object | null

Options for streaming responses, e.g., {'include_usage': true}

Response

Streaming text completion responses or complete response depending on stream parameter

Alignment Projects

Models

Documents

Benchmarks

Evaluations

Inference

Generate Completions

Authorizations

Headers

Body

Response