Legacy API

These endpoints are part of the legacy neuroflash API and are no longer actively developed. For new integrations, use the modern Content Generation endpoints.

Generate Text

POST/api/word-embedding/generate_text

Request Body

keywordsstringNoThe keywords to base output generation on.

keywords2stringNoThe second keywords to base output generation on.

extra_inputstringNoAn extra input to base output generation on.

extra_input2stringNoAnother extra input to base output generation on.

textstringNoText to generate outputs about.

tonalityarray<string>NoSteer the tonality parameter to be inserted into a suitable prompt.

lengthstringNoSteer the length parameter to be inserted into a suitable prompt.

output_typestringYesWhich output type to generate.

audience_model_idstringYesWhich prompt/success-model to use.

n_timesintegerNoHow often to run the resulting prompts in parallel and accumulate all results

n_text_itemsintegerNoHow many text items to generate. Overrides n_times logic.

qualitystringNoAn enumeration.

personalitystringNoText to describe a personality

personality_idintegerNoIdentifier for the personality (if present)

informationarray<object>NoContext information to base the output generation on.

idintegerYes

contentstringYes

category_namestringNo

brand_voiceobjectNoA dictionary representing the brand voice to be used for text generation.

brand_voice_idstringNoIdentifier for the brand voice (if present)

audienceobjectNoA dictionary representing the audience to be used for text generation.

target_audience_idstringNoID of the audience

Response

outputsarray<object>Generated outputs based on the inputs.

textstring

generation_idinteger

text_item_idstring

n_tokens_inputinteger

n_tokens_usedinteger

n_tokens_showninteger

n_words_inputinteger

n_words_usedinteger

n_words_showninteger

Example

cURL
Python
Node.js
Go

curl -X POST "https://app.neuroflash.com/api/word-embedding/generate_text" \
  -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
      "keywords": "string",
      "keywords2": "string",
      "extra_input": "string",
      "extra_input2": "string",
      "text": "string",
      "tonality": [],
      "length": "string",
      "output_type": "string",
      "audience_model_id": "string",
      "n_times": 0,
      "n_text_items": 0,
      "quality": "string",
      "personality": "string",
      "personality_id": 0,
      "information": [],
      "brand_voice": {},
      "brand_voice_id": "string",
      "audience": {},
      "target_audience_id": "string"
  }'

import requests

response = requests.post(
    f"https://app.neuroflash.com/api/word-embedding/generate_text",
    headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
    json={
        "keywords": "string",
        "keywords2": "string",
        "extra_input": "string",
        "extra_input2": "string",
        "text": "string",
        "tonality": [],
        "length": "string",
        "output_type": "string",
        "audience_model_id": "string",
        "n_times": 0,
        "n_text_items": 0,
        "quality": "string",
        "personality": "string",
        "personality_id": 0,
        "information": [],
        "brand_voice": {},
        "brand_voice_id": "string",
        "audience": {},
        "target_audience_id": "string"
    },
).json()

const response = await fetch(
  `https://app.neuroflash.com/api/word-embedding/generate_text`,
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${token}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
          "keywords": "string",
          "keywords2": "string",
          "extra_input": "string",
          "extra_input2": "string",
          "text": "string",
          "tonality": [],
          "length": "string",
          "output_type": "string",
          "audience_model_id": "string",
          "n_times": 0,
          "n_text_items": 0,
          "quality": "string",
          "personality": "string",
          "personality_id": 0,
          "information": [],
          "brand_voice": {},
          "brand_voice_id": "string",
          "audience": {},
          "target_audience_id": "string"
    }),
  }
).then((r) => r.json());

body, _ := json.Marshal(map[string]any{
		"keywords": "string",
		"keywords2": "string",
		"extra_input": "string",
		"extra_input2": "string",
		"text": "string",
		"tonality": []any{},
		"length": "string",
		"output_type": "string",
		"audience_model_id": "string",
		"n_times": 0,
		"n_text_items": 0,
		"quality": "string",
		"personality": "string",
		"personality_id": 0,
		"information": []any{},
		"brand_voice": map[string]any{},
		"brand_voice_id": "string",
		"audience": map[string]any{},
		"target_audience_id": "string",
	})

req, _ := http.NewRequest("POST", "https://app.neuroflash.com/api/word-embedding/generate_text", bytes.NewReader(body))
req.Header.Set("Authorization", "Bearer "+token)
req.Header.Set("Content-Type", "application/json")

resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()

Response:

{
  "outputs": [
    {
      "text": "This is a very innovative subject line.",
      "generation_id": 12345,
      "text_item_id": "d911f60c-779e-425e-86d2-c8d9f1d5c93b"
    }
  ],
  "n_tokens_input": 0,
  "n_tokens_used": 0,
  "n_tokens_shown": 0,
  "n_words_input": 0,
  "n_words_used": 0,
  "n_words_shown": 0
}

Generate Text Stream

POST/api/word-embedding/generate_text_stream

Request Body

keywordsstringNoThe keywords to base output generation on.

keywords2stringNoThe second keywords to base output generation on.

extra_inputstringNoAn extra input to base output generation on.

extra_input2stringNoAnother extra input to base output generation on.

textstringNoText to generate outputs about.

tonalityarray<string>NoSteer the tonality parameter to be inserted into a suitable prompt.

lengthstringNoSteer the length parameter to be inserted into a suitable prompt.

output_typestringYesWhich output type to generate.

audience_model_idstringYesWhich prompt/success-model to use.

n_timesintegerNoHow often to run the resulting prompts in parallel and accumulate all results

n_text_itemsintegerNoHow many text items to generate. Overrides n_times logic.

qualitystringNoAn enumeration.

personalitystringNoText to describe a personality

personality_idintegerNoIdentifier for the personality (if present)

informationarray<object>NoContext information to base the output generation on.

idintegerYes

contentstringYes

category_namestringNo

brand_voiceobjectNoA dictionary representing the brand voice to be used for text generation.

brand_voice_idstringNoIdentifier for the brand voice (if present)

audienceobjectNoA dictionary representing the audience to be used for text generation.

target_audience_idstringNoID of the audience

Response

outputsarray<object>Generated outputs based on the inputs.

textstring

generation_idinteger

text_item_idstring

n_tokens_inputinteger

n_tokens_usedinteger

n_tokens_showninteger

n_words_inputinteger

n_words_usedinteger

n_words_showninteger

Example

cURL
Python
Node.js
Go

curl -X POST "https://app.neuroflash.com/api/word-embedding/generate_text_stream" \
  -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
      "keywords": "string",
      "keywords2": "string",
      "extra_input": "string",
      "extra_input2": "string",
      "text": "string",
      "tonality": [],
      "length": "string",
      "output_type": "string",
      "audience_model_id": "string",
      "n_times": 0,
      "n_text_items": 0,
      "quality": "string",
      "personality": "string",
      "personality_id": 0,
      "information": [],
      "brand_voice": {},
      "brand_voice_id": "string",
      "audience": {},
      "target_audience_id": "string"
  }'

import requests

response = requests.post(
    f"https://app.neuroflash.com/api/word-embedding/generate_text_stream",
    headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
    json={
        "keywords": "string",
        "keywords2": "string",
        "extra_input": "string",
        "extra_input2": "string",
        "text": "string",
        "tonality": [],
        "length": "string",
        "output_type": "string",
        "audience_model_id": "string",
        "n_times": 0,
        "n_text_items": 0,
        "quality": "string",
        "personality": "string",
        "personality_id": 0,
        "information": [],
        "brand_voice": {},
        "brand_voice_id": "string",
        "audience": {},
        "target_audience_id": "string"
    },
).json()

const response = await fetch(
  `https://app.neuroflash.com/api/word-embedding/generate_text_stream`,
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${token}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
          "keywords": "string",
          "keywords2": "string",
          "extra_input": "string",
          "extra_input2": "string",
          "text": "string",
          "tonality": [],
          "length": "string",
          "output_type": "string",
          "audience_model_id": "string",
          "n_times": 0,
          "n_text_items": 0,
          "quality": "string",
          "personality": "string",
          "personality_id": 0,
          "information": [],
          "brand_voice": {},
          "brand_voice_id": "string",
          "audience": {},
          "target_audience_id": "string"
    }),
  }
).then((r) => r.json());

body, _ := json.Marshal(map[string]any{
		"keywords": "string",
		"keywords2": "string",
		"extra_input": "string",
		"extra_input2": "string",
		"text": "string",
		"tonality": []any{},
		"length": "string",
		"output_type": "string",
		"audience_model_id": "string",
		"n_times": 0,
		"n_text_items": 0,
		"quality": "string",
		"personality": "string",
		"personality_id": 0,
		"information": []any{},
		"brand_voice": map[string]any{},
		"brand_voice_id": "string",
		"audience": map[string]any{},
		"target_audience_id": "string",
	})

req, _ := http.NewRequest("POST", "https://app.neuroflash.com/api/word-embedding/generate_text_stream", bytes.NewReader(body))
req.Header.Set("Authorization", "Bearer "+token)
req.Header.Set("Content-Type", "application/json")

resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()

Response:

{
  "outputs": [
    {
      "text": "This is a very innovative subject line.",
      "generation_id": 12345,
      "text_item_id": "d911f60c-779e-425e-86d2-c8d9f1d5c93b"
    }
  ],
  "n_tokens_input": 0,
  "n_tokens_used": 0,
  "n_tokens_shown": 0,
  "n_words_input": 0,
  "n_words_used": 0,
  "n_words_shown": 0
}

Get Prompts

GET/api/word-embedding/get_prompts

Example

cURL
Python
Node.js
Go

curl "https://app.neuroflash.com/api/word-embedding/get_prompts" \
  -H "Authorization: Bearer YOUR_ACCESS_TOKEN"

import requests

response = requests.get(
    f"https://app.neuroflash.com/api/word-embedding/get_prompts",
    headers={"Authorization": f"Bearer {token}"},
).json()

const response = await fetch(
  `https://app.neuroflash.com/api/word-embedding/get_prompts`,
  { headers: { Authorization: `Bearer ${token}` } }
).then((r) => r.json());

req, _ := http.NewRequest("GET", "https://app.neuroflash.com/api/word-embedding/get_prompts", nil)
req.Header.Set("Authorization", "Bearer "+token)

resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()

Response:

[
  {
    "country": "de",
    "language": "de",
    "output_type": {
      "id": "string",
      "label": "string"
    },
    "output_type_category": {
      "id": "string",
      "label": "string"
    },
    "n_times": 1,
    "n_text_items": 2,
    "display_in_select": false,
    "text": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "keywords": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "keywords2": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "video_id": "string",
    "output_type_description": "string"
  }
]

Get Prompts by Country and Language

GET/api/word-embedding/get_prompts/{country}/{language}

Path Parameters

Parameter	Type	Required	Description
`country`	string	Yes
`language`	string	Yes

Example

cURL
Python
Node.js
Go

curl "https://app.neuroflash.com/api/word-embedding/get_prompts/{country}/{language}" \
  -H "Authorization: Bearer YOUR_ACCESS_TOKEN"

import requests

response = requests.get(
    f"https://app.neuroflash.com/api/word-embedding/get_prompts/{country}/{language}",
    headers={"Authorization": f"Bearer {token}"},
).json()

const response = await fetch(
  `https://app.neuroflash.com/api/word-embedding/get_prompts/${country}/${language}`,
  { headers: { Authorization: `Bearer ${token}` } }
).then((r) => r.json());

req, _ := http.NewRequest("GET", "https://app.neuroflash.com/api/word-embedding/get_prompts/"+country+"/"+language+"", nil)
req.Header.Set("Authorization", "Bearer "+token)

resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()

Response:

[
  {
    "country": "de",
    "language": "de",
    "output_type": {
      "id": "string",
      "label": "string"
    },
    "output_type_category": {
      "id": "string",
      "label": "string"
    },
    "n_times": 1,
    "n_text_items": 2,
    "display_in_select": false,
    "text": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "keywords": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "keywords2": {
      "label": "string",
      "placeholder": "string",
      "prefill_value": "string",
      "character_limit": 600
    },
    "video_id": "string",
    "output_type_description": "string"
  }
]

Generate Text​

Request Body​

Response​

Example​

Generate Text Stream​

Request Body​

Response​

Example​

Get Prompts​

Example​

Get Prompts by Country and Language​

Path Parameters​

Example​

Generate Text

Request Body

Response

Example

Generate Text Stream

Request Body

Response

Example

Get Prompts

Example

Get Prompts by Country and Language

Path Parameters

Example