curl --request POST \
  --url https://api.flashdocs.ai/v3/generate/deck/task \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data @- <<EOF
{
  "prompt": "In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.",
  "source_document_id": "abc-def-ghi-jkl",
  "number_slides": 5,
  "audience_domain": "slack.com",
  "presentation_name": "Renewable Energy Innovations 2025",
  "outline": [
    {
      "content_instruction": "Introduce the topic of renewable energy and its importance.",
      "layout_instruction": "Title slide with a background image.",
      "markdown": "# Parallel Inference on GPUs for LLMs\n## **Data Parallelism**\n- Distributes batches of input data across GPUs.\n- **Benefits:** Increased throughput via simultaneous processing.\n## **Model Parallelism**\n- Splits the model's layers or components among GPUs.\n## **Pipeline Parallelism**\n- Overlaps different stages of inference, reducing idle time.\n- **Advantage:** Maximizes resource utilization.\n    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).",
      "text_placeholder_manual_insertions": [
        {
          "placeholder": "[title]",
          "value": "Renewable Energy Innovations 2027"
        },
        {
          "placeholder": "[content]",
          "value": "Introduce the topic of renewable energy and its importance."
        }
      ],
      "image_placeholder_manual_insertions": [
        {
          "alt_text": "[top right]",
          "slide_index": 0,
          "url": "https://example.com/image.jpg"
        },
        {
          "alt_text": "[bottom left]",
          "slide_index": 1,
          "url": "https://example.com/image2.jpg"
        }
      ],
      "slide_id": "slide_123"
    }
  ],
  "export_options": {
    "google_slides_permission_options": {
      "anyone_edit_with_link": false,
      "anyone_view_with_link": false,
      "google_document_editors": [
        "bob@acme.com",
        "joe@acme.com"
      ]
    },
    "output_format": "google_slides_direct_link"
  }
}
EOF

import requests

url = "https://api.flashdocs.ai/v3/generate/deck/task"

payload = {
    "prompt": "In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.",
    "source_document_id": "abc-def-ghi-jkl",
    "number_slides": 5,
    "audience_domain": "slack.com",
    "presentation_name": "Renewable Energy Innovations 2025",
    "outline": [
        {
            "content_instruction": "Introduce the topic of renewable energy and its importance.",
            "layout_instruction": "Title slide with a background image.",
            "markdown": "# Parallel Inference on GPUs for LLMs
## **Data Parallelism**
- Distributes batches of input data across GPUs.
- **Benefits:** Increased throughput via simultaneous processing.
## **Model Parallelism**
- Splits the model's layers or components among GPUs.
## **Pipeline Parallelism**
- Overlaps different stages of inference, reducing idle time.
- **Advantage:** Maximizes resource utilization.
    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).",
            "text_placeholder_manual_insertions": [
                {
                    "placeholder": "[title]",
                    "value": "Renewable Energy Innovations 2027"
                },
                {
                    "placeholder": "[content]",
                    "value": "Introduce the topic of renewable energy and its importance."
                }
            ],
            "image_placeholder_manual_insertions": [
                {
                    "alt_text": "[top right]",
                    "slide_index": 0,
                    "url": "https://example.com/image.jpg"
                },
                {
                    "alt_text": "[bottom left]",
                    "slide_index": 1,
                    "url": "https://example.com/image2.jpg"
                }
            ],
            "slide_id": "slide_123"
        }
    ],
    "export_options": {
        "google_slides_permission_options": {
            "anyone_edit_with_link": False,
            "anyone_view_with_link": False,
            "google_document_editors": ["bob@acme.com", "joe@acme.com"]
        },
        "output_format": "google_slides_direct_link"
    }
}
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({
    prompt: 'In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.',
    source_document_id: 'abc-def-ghi-jkl',
    number_slides: 5,
    audience_domain: 'slack.com',
    presentation_name: 'Renewable Energy Innovations 2025',
    outline: [
      {
        content_instruction: 'Introduce the topic of renewable energy and its importance.',
        layout_instruction: 'Title slide with a background image.',
        markdown: '# Parallel Inference on GPUs for LLMs\n## **Data Parallelism**\n- Distributes batches of input data across GPUs.\n- **Benefits:** Increased throughput via simultaneous processing.\n## **Model Parallelism**\n- Splits the model\'s layers or components among GPUs.\n## **Pipeline Parallelism**\n- Overlaps different stages of inference, reducing idle time.\n- **Advantage:** Maximizes resource utilization.\n    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).',
        text_placeholder_manual_insertions: [
          {placeholder: '[title]', value: 'Renewable Energy Innovations 2027'},
          {
            placeholder: '[content]',
            value: 'Introduce the topic of renewable energy and its importance.'
          }
        ],
        image_placeholder_manual_insertions: [
          {alt_text: '[top right]', slide_index: 0, url: 'https://example.com/image.jpg'},
          {
            alt_text: '[bottom left]',
            slide_index: 1,
            url: 'https://example.com/image2.jpg'
          }
        ],
        slide_id: 'slide_123'
      }
    ],
    export_options: {
      google_slides_permission_options: {
        anyone_edit_with_link: false,
        anyone_view_with_link: false,
        google_document_editors: ['bob@acme.com', 'joe@acme.com']
      },
      output_format: 'google_slides_direct_link'
    }
  })
};

fetch('https://api.flashdocs.ai/v3/generate/deck/task', 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.flashdocs.ai/v3/generate/deck/task",
  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([
    'prompt' => 'In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.',
    'source_document_id' => 'abc-def-ghi-jkl',
    'number_slides' => 5,
    'audience_domain' => 'slack.com',
    'presentation_name' => 'Renewable Energy Innovations 2025',
    'outline' => [
        [
                'content_instruction' => 'Introduce the topic of renewable energy and its importance.',
                'layout_instruction' => 'Title slide with a background image.',
                'markdown' => '# Parallel Inference on GPUs for LLMs
## **Data Parallelism**
- Distributes batches of input data across GPUs.
- **Benefits:** Increased throughput via simultaneous processing.
## **Model Parallelism**
- Splits the model\'s layers or components among GPUs.
## **Pipeline Parallelism**
- Overlaps different stages of inference, reducing idle time.
- **Advantage:** Maximizes resource utilization.
    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).',
                'text_placeholder_manual_insertions' => [
                                [
                                                                'placeholder' => '[title]',
                                                                'value' => 'Renewable Energy Innovations 2027'
                                ],
                                [
                                                                'placeholder' => '[content]',
                                                                'value' => 'Introduce the topic of renewable energy and its importance.'
                                ]
                ],
                'image_placeholder_manual_insertions' => [
                                [
                                                                'alt_text' => '[top right]',
                                                                'slide_index' => 0,
                                                                'url' => 'https://example.com/image.jpg'
                                ],
                                [
                                                                'alt_text' => '[bottom left]',
                                                                'slide_index' => 1,
                                                                'url' => 'https://example.com/image2.jpg'
                                ]
                ],
                'slide_id' => 'slide_123'
        ]
    ],
    'export_options' => [
        'google_slides_permission_options' => [
                'anyone_edit_with_link' => false,
                'anyone_view_with_link' => false,
                'google_document_editors' => [
                                'bob@acme.com',
                                'joe@acme.com'
                ]
        ],
        'output_format' => 'google_slides_direct_link'
    ]
  ]),
  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.flashdocs.ai/v3/generate/deck/task"

	payload := strings.NewReader("{\n  \"prompt\": \"In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.\",\n  \"source_document_id\": \"abc-def-ghi-jkl\",\n  \"number_slides\": 5,\n  \"audience_domain\": \"slack.com\",\n  \"presentation_name\": \"Renewable Energy Innovations 2025\",\n  \"outline\": [\n    {\n      \"content_instruction\": \"Introduce the topic of renewable energy and its importance.\",\n      \"layout_instruction\": \"Title slide with a background image.\",\n      \"markdown\": \"# Parallel Inference on GPUs for LLMs\\n## **Data Parallelism**\\n- Distributes batches of input data across GPUs.\\n- **Benefits:** Increased throughput via simultaneous processing.\\n## **Model Parallelism**\\n- Splits the model's layers or components among GPUs.\\n## **Pipeline Parallelism**\\n- Overlaps different stages of inference, reducing idle time.\\n- **Advantage:** Maximizes resource utilization.\\n    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).\",\n      \"text_placeholder_manual_insertions\": [\n        {\n          \"placeholder\": \"[title]\",\n          \"value\": \"Renewable Energy Innovations 2027\"\n        },\n        {\n          \"placeholder\": \"[content]\",\n          \"value\": \"Introduce the topic of renewable energy and its importance.\"\n        }\n      ],\n      \"image_placeholder_manual_insertions\": [\n        {\n          \"alt_text\": \"[top right]\",\n          \"slide_index\": 0,\n          \"url\": \"https://example.com/image.jpg\"\n        },\n        {\n          \"alt_text\": \"[bottom left]\",\n          \"slide_index\": 1,\n          \"url\": \"https://example.com/image2.jpg\"\n        }\n      ],\n      \"slide_id\": \"slide_123\"\n    }\n  ],\n  \"export_options\": {\n    \"google_slides_permission_options\": {\n      \"anyone_edit_with_link\": false,\n      \"anyone_view_with_link\": false,\n      \"google_document_editors\": [\n        \"bob@acme.com\",\n        \"joe@acme.com\"\n      ]\n    },\n    \"output_format\": \"google_slides_direct_link\"\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.flashdocs.ai/v3/generate/deck/task")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"prompt\": \"In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.\",\n  \"source_document_id\": \"abc-def-ghi-jkl\",\n  \"number_slides\": 5,\n  \"audience_domain\": \"slack.com\",\n  \"presentation_name\": \"Renewable Energy Innovations 2025\",\n  \"outline\": [\n    {\n      \"content_instruction\": \"Introduce the topic of renewable energy and its importance.\",\n      \"layout_instruction\": \"Title slide with a background image.\",\n      \"markdown\": \"# Parallel Inference on GPUs for LLMs\\n## **Data Parallelism**\\n- Distributes batches of input data across GPUs.\\n- **Benefits:** Increased throughput via simultaneous processing.\\n## **Model Parallelism**\\n- Splits the model's layers or components among GPUs.\\n## **Pipeline Parallelism**\\n- Overlaps different stages of inference, reducing idle time.\\n- **Advantage:** Maximizes resource utilization.\\n    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).\",\n      \"text_placeholder_manual_insertions\": [\n        {\n          \"placeholder\": \"[title]\",\n          \"value\": \"Renewable Energy Innovations 2027\"\n        },\n        {\n          \"placeholder\": \"[content]\",\n          \"value\": \"Introduce the topic of renewable energy and its importance.\"\n        }\n      ],\n      \"image_placeholder_manual_insertions\": [\n        {\n          \"alt_text\": \"[top right]\",\n          \"slide_index\": 0,\n          \"url\": \"https://example.com/image.jpg\"\n        },\n        {\n          \"alt_text\": \"[bottom left]\",\n          \"slide_index\": 1,\n          \"url\": \"https://example.com/image2.jpg\"\n        }\n      ],\n      \"slide_id\": \"slide_123\"\n    }\n  ],\n  \"export_options\": {\n    \"google_slides_permission_options\": {\n      \"anyone_edit_with_link\": false,\n      \"anyone_view_with_link\": false,\n      \"google_document_editors\": [\n        \"bob@acme.com\",\n        \"joe@acme.com\"\n      ]\n    },\n    \"output_format\": \"google_slides_direct_link\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.flashdocs.ai/v3/generate/deck/task")

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  \"prompt\": \"In a few slides, describe the recent Innovations in Renewable Energy. Discuss the foundational problems and key papers. Include specific examples.\",\n  \"source_document_id\": \"abc-def-ghi-jkl\",\n  \"number_slides\": 5,\n  \"audience_domain\": \"slack.com\",\n  \"presentation_name\": \"Renewable Energy Innovations 2025\",\n  \"outline\": [\n    {\n      \"content_instruction\": \"Introduce the topic of renewable energy and its importance.\",\n      \"layout_instruction\": \"Title slide with a background image.\",\n      \"markdown\": \"# Parallel Inference on GPUs for LLMs\\n## **Data Parallelism**\\n- Distributes batches of input data across GPUs.\\n- **Benefits:** Increased throughput via simultaneous processing.\\n## **Model Parallelism**\\n- Splits the model's layers or components among GPUs.\\n## **Pipeline Parallelism**\\n- Overlaps different stages of inference, reducing idle time.\\n- **Advantage:** Maximizes resource utilization.\\n    - Use various layers of DNN see [here](https://developer.nvidia.com/blog).\",\n      \"text_placeholder_manual_insertions\": [\n        {\n          \"placeholder\": \"[title]\",\n          \"value\": \"Renewable Energy Innovations 2027\"\n        },\n        {\n          \"placeholder\": \"[content]\",\n          \"value\": \"Introduce the topic of renewable energy and its importance.\"\n        }\n      ],\n      \"image_placeholder_manual_insertions\": [\n        {\n          \"alt_text\": \"[top right]\",\n          \"slide_index\": 0,\n          \"url\": \"https://example.com/image.jpg\"\n        },\n        {\n          \"alt_text\": \"[bottom left]\",\n          \"slide_index\": 1,\n          \"url\": \"https://example.com/image2.jpg\"\n        }\n      ],\n      \"slide_id\": \"slide_123\"\n    }\n  ],\n  \"export_options\": {\n    \"google_slides_permission_options\": {\n      \"anyone_edit_with_link\": false,\n      \"anyone_view_with_link\": false,\n      \"google_document_editors\": [\n        \"bob@acme.com\",\n        \"joe@acme.com\"\n      ]\n    },\n    \"output_format\": \"google_slides_direct_link\"\n  }\n}"

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

{
  "task_id": "task_67890",
  "created_at": "<string>"
}

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