OpenAI Chat Format

Create chat completion

curl --request POST \
  --url https://api.dgrid.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "openai/gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
}
'

import requests

url = "https://api.dgrid.ai/v1/chat/completions"

payload = {
    "model": "openai/gpt-4o",
    "messages": [
        {
            "role": "user",
            "content": "What is the meaning of life?"
        }
    ]
}
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({
    model: 'openai/gpt-4o',
    messages: [{role: 'user', content: 'What is the meaning of life?'}]
  })
};

fetch('https://api.dgrid.ai/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

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

func main() {

	url := "https://api.dgrid.ai/v1/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"openai/gpt-4o\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What is the meaning of life?\"\n    }\n  ]\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.dgrid.ai/v1/chat/completions")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"openai/gpt-4o\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What is the meaning of life?\"\n    }\n  ]\n}")
  .asString();

{
  "id": "<string>",
  "object": "<string>",
  "created": 123,
  "model": "<string>",
  "choices": [
    {
      "index": 123,
      "message": {
        "role": "<string>",
        "content": "<string>",
        "reasoning_content": "<string>",
        "tool_calls": [
          {}
        ]
      },
      "finish_reason": "<string>"
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "prompt_tokens_details": {
      "cached_tokens": 123,
      "text_tokens": 123,
      "audio_tokens": 123,
      "image_tokens": 123
    },
    "completion_tokens_details": {
      "text_tokens": 123,
      "audio_tokens": 123,
      "reasoning_tokens": 123
    }
  },
  "system_fingerprint": "<string>"
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

POST

chat

completions

Create chat completion

curl --request POST \
  --url https://api.dgrid.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "openai/gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
}
'

import requests

url = "https://api.dgrid.ai/v1/chat/completions"

payload = {
    "model": "openai/gpt-4o",
    "messages": [
        {
            "role": "user",
            "content": "What is the meaning of life?"
        }
    ]
}
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({
    model: 'openai/gpt-4o',
    messages: [{role: 'user', content: 'What is the meaning of life?'}]
  })
};

fetch('https://api.dgrid.ai/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

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

func main() {

	url := "https://api.dgrid.ai/v1/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"openai/gpt-4o\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What is the meaning of life?\"\n    }\n  ]\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.dgrid.ai/v1/chat/completions")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"openai/gpt-4o\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What is the meaning of life?\"\n    }\n  ]\n}")
  .asString();

{
  "id": "<string>",
  "object": "<string>",
  "created": 123,
  "model": "<string>",
  "choices": [
    {
      "index": 123,
      "message": {
        "role": "<string>",
        "content": "<string>",
        "reasoning_content": "<string>",
        "tool_calls": [
          {}
        ]
      },
      "finish_reason": "<string>"
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "prompt_tokens_details": {
      "cached_tokens": 123,
      "text_tokens": 123,
      "audio_tokens": 123,
      "image_tokens": 123
    },
    "completion_tokens_details": {
      "text_tokens": 123,
      "audio_tokens": 123,
      "reasoning_tokens": 123
    }
  },
  "system_fingerprint": "<string>"
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

This page uses the same chat/completions operation as Create chat completion, with the playground above pre-filled for the generic chat schema. The notes below describe how to use this endpoint to request Gemini-backed image generation from an OpenAI-compatible client.

Include an image-generation model in model (such as gemini-2.0-flash-preview-image-generation), set stream as needed, and supply your prompt through messages. Optionally include contents for additional Gemini-style multimodal context alongside messages.

Provider-specific notes

Field	Type	Required	Description
`model`	string	Yes	Image-generation model identifier, e.g. `gemini-2.0-flash-preview-image-generation`.
`messages[].content`	string	Yes	Prompt text describing the desired image.
`contents`	array	No	Optional Gemini-style content array for additional multimodal context, not part of the standard OpenAI chat schema.

The contents field is a DGrid extension layered on top of the standard chat completions schema — it lets you pass Gemini-native parts (such as inlineData) alongside the OpenAI-style messages array when the target model supports it.

Example: requesting an image

{
  "model": "gemini-2.0-flash-preview-image-generation",
  "stream": false,
  "messages": [
    {
      "role": "user",
      "content": "Generate an image of a futuristic city skyline at sunset."
    }
  ]
}

Response fields

The response follows the standard chat completions shape. The generated image is embedded directly in the assistant message content:

array

Returned choice entries.

Show choice properties

integer

Choice index.

object

Assistant message object.

Show message properties

string

Message role, typically assistant.

string

Message content. For image-output models, this is a markdown image reference embedding the generated image as a base64 data URI, e.g. ![generated image](data:image/png;base64,...).

string

Finish reason, e.g. stop.

object

Token usage summary.

Example response

200

{
  "id": "chatcmpl-abc123",
  "model": "gemini-2.0-flash-preview-image-generation",
  "object": "chat.completion",
  "created": 1719859200,
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "![generated image](data:image/png;base64,<base64-encoded-image-bytes>)"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 0,
    "total_tokens": 12
  }
}

Authorizations

Authorization

string

header

required

Your DGrid API key. All endpoints use Authorization: Bearer <DGRID_API_KEY>.

Body

application/json

model

string

required

Target model ID in provider/model-name format.

Example:

"openai/gpt-4o"

messages

object[]

required

Conversation message list.

Show child attributes

temperature

number

default:1

Sampling temperature.

top_p

number

default:1

Nucleus sampling value.

integer

default:1

Number of choices to generate.

stream

boolean

default:false

Enable SSE streaming.

max_tokens

integer

Maximum token count.

max_completion_tokens

integer

Max completion-only tokens.

presence_penalty

number

default:0

Presence penalty.

frequency_penalty

number

default:0

Frequency penalty.

logit_bias

object

Token bias configuration.

stop

Stop sequence string or array.

tools

object[]

Tool definitions.

tool_choice

Tool selection behavior. Defaults to auto.

response_format

object

Response schema or JSON mode config.

seed

integer

Deterministic seed.

user

string

End-user identifier.

Response

Chat completion result.

string

Completion identifier.

object

string

Always chat.completion.

created

integer

Creation timestamp.

model

string

Model that served the request.

choices

object[]

Returned choices.

Show child attributes

usage

object

Token usage breakdown.

Show child attributes

system_fingerprint

string

Gemini Native Format

Create image

GETTING STARTED

MODEL API

MANAGEMENT API KEYS

X402 API

Provider-specific notes

Example: requesting an image

Response fields

Example response

Authorizations

Body

Response

​Provider-specific notes

​Example: requesting an image

​Response fields

​Example response

Authorizations

Body

Response

Provider-specific notes

Example: requesting an image

Response fields

Example response