> ## Documentation Index > Fetch the complete documentation index at: https://docs.aiornot.com/llms.txt > Use this file to discover all available pages before exploring further. # Text > Analyze **text** to determine if it was generated by AI. This endpoint analyzes text content and returns confidence scores for AI detection. **Text Processing Limits:** - **Minimum Text Length:** 250 characters - **Maximum Text Length:** 500,000 characters (500KB) - **Minimum Words**: Approximately 64 words ## OpenAPI ````yaml api-reference/openapi.yaml post /v2/text/sync openapi: 3.1.0 info: title: AIORNOT API summary: |2- Welcome to AI or Not`s documentation, the developer guide to discerning digital authenticity! termsOfService: https://aiornot.com/terms-of-service contact: name: AIORNOT url: https://aiornot.com/ email: support@aiornot.com version: 5.0.2 servers: - url: https://api.aiornot.com description: Production environment security: [] paths: /v2/text/sync: post: tags: - Reports by Modality summary: Text description: >- Analyze **text** to determine if it was generated by AI. This endpoint analyzes text content and returns confidence scores for AI detection. **Text Processing Limits:** - **Minimum Text Length:** 250 characters - **Maximum Text Length:** 500,000 characters (500KB) - **Minimum Words**: Approximately 64 words operationId: get_text_report_text_sync_post parameters: - name: external_id in: query description: An optional external identifier for tracking this text analysis required: false schema: type: string nullable: true - name: include_annotations in: query description: Include block-level AI detection annotations in the response required: false schema: type: boolean default: false requestBody: content: application/x-www-form-urlencoded: schema: type: object properties: text: type: string title: Text description: >- The text content to analyze for AI generation (minimum 250 characters, maximum 500,000 characters) minLength: 250 maxLength: 500000 required: - text required: true responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/TextReportResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - HTTPBearer: [] x-codeSamples: - lang: python label: Python source: | import os, requests # Set API key ENV variable or replace with your own API key API_KEY = os.getenv("AIORNOT_API_KEY") TEXT_ENDPOINT = "https://api.aiornot.com/v2/text/sync" data = { "text": "Your text content to analyze goes here..." } resp = requests.post( TEXT_ENDPOINT, headers={"Authorization": f"Bearer {API_KEY}"}, data=data, params={ "include_annotations": True, # Optional: Include block-level annotations "external_id": "my-tracking-id" # Optional: External tracking ID } ) resp.raise_for_status() print(resp.json()) - lang: curl label: cURL source: | curl --request POST \ --url 'https://api.aiornot.com/v2/text/sync?include_annotations=true&external_id=my-tracking-id' \ --header 'Authorization: Bearer $AIORNOT_API_KEY' \ --header 'Content-Type: application/x-www-form-urlencoded' \ --data 'text=Your text content to analyze goes here...' - lang: javascript label: JavaScript source: | const fetch = require('node-fetch'); const querystring = require('querystring'); const API_KEY = process.env.AIORNOT_API_KEY; const TEXT_ENDPOINT = 'https://api.aiornot.com/v2/text/sync'; const data = querystring.stringify({ text: 'Your text content to analyze goes here...' }); const params = new URLSearchParams({ include_annotations: 'true', // Optional: Include block-level annotations external_id: 'my-tracking-id' // Optional: External tracking ID }); fetch(`${TEXT_ENDPOINT}?${params}`, { method: 'POST', headers: { 'Authorization': `Bearer ${API_KEY}`, 'Content-Type': 'application/x-www-form-urlencoded' }, body: data }) .then(response => { if (!response.ok) { throw new Error(`Failed to analyze text: ${response.status} ${response.statusText}`); } return response.json(); }) .then(data => console.log(data)) .catch(error => console.error('Error:', error)); - lang: php label: PHP source: | 'Your text content to analyze goes here...' ]; $query_params = http_build_query([ 'include_annotations' => 'true', // Optional: Include block-level annotations 'external_id' => 'my-tracking-id' // Optional: External tracking ID ]); curl_setopt_array($curl, [ CURLOPT_URL => $TEXT_ENDPOINT . '?' . $query_params, CURLOPT_RETURNTRANSFER => true, CURLOPT_POST => true, CURLOPT_POSTFIELDS => http_build_query($data), CURLOPT_HTTPHEADER => [ "Authorization: Bearer $API_KEY", "Content-Type: application/x-www-form-urlencoded" ], ]); $response = curl_exec($curl); $httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE); $err = curl_error($curl); curl_close($curl); if ($err) { echo "cURL Error #:" . $err; } elseif ($httpCode !== 200) { echo "Failed to analyze text: HTTP $httpCode - $response"; } else { $data = json_decode($response, true); print_r($data); } - lang: go label: Go source: | package main import ( "fmt" "io/ioutil" "net/http" "net/url" "os" "strings" ) func main() { APIKey := os.Getenv("AIORNOT_API_KEY") textEndpoint := "https://api.aiornot.com/v2/text/sync" data := url.Values{} data.Set("text", "Your text content to analyze goes here...") params := url.Values{} params.Set("include_annotations", "true") // Optional: Include block-level annotations params.Set("external_id", "my-tracking-id") // Optional: External tracking ID fullURL := textEndpoint + "?" + params.Encode() req, err := http.NewRequest("POST", fullURL, strings.NewReader(data.Encode())) if err != nil { panic(err) } req.Header.Set("Authorization", "Bearer "+APIKey) req.Header.Set("Content-Type", "application/x-www-form-urlencoded") client := &http.Client{} resp, err := client.Do(req) if err != nil { panic(err) } defer resp.Body.Close() body, err := ioutil.ReadAll(resp.Body) if err != nil { panic(err) } if resp.StatusCode != 200 { fmt.Printf("Failed to analyze text: %d %s\n", resp.StatusCode, string(body)) return } fmt.Println(string(body)) } - lang: java label: Java source: | import java.io.IOException; import okhttp3.*; public class TextAnalysis { public static void main(String[] args) { String apiKey = System.getenv("AIORNOT_API_KEY"); String textEndpoint = "https://api.aiornot.com/v2/text/sync"; OkHttpClient client = new OkHttpClient(); RequestBody formBody = new FormBody.Builder() .add("text", "Your text content to analyze goes here...") .build(); HttpUrl url = HttpUrl.parse(textEndpoint).newBuilder() .addQueryParameter("include_annotations", "true") // Optional: Include block-level annotations .addQueryParameter("external_id", "my-tracking-id") // Optional: External tracking ID .build(); Request request = new Request.Builder() .url(url) .header("Authorization", "Bearer " + apiKey) .post(formBody) .build(); try { Response response = client.newCall(request).execute(); if (!response.isSuccessful()) { System.err.println("Failed to analyze text: " + response.code() + " " + response.body().string()); } else { System.out.println(response.body().string()); } } catch (IOException e) { e.printStackTrace(); } } } components: schemas: TextReportResponse: properties: id: type: string format: uuid title: Id description: Unique identifier associated with the request created_at: type: string format: date-time title: Created At description: Date and time of request processing report: type: object properties: ai_text: $ref: '#/components/schemas/AITextReportScheme' required: - ai_text metadata: $ref: '#/components/schemas/TextMetadata' external_id: type: string nullable: true title: External Id description: The external identifier provided in the request, if any type: object required: - id - report - metadata title: TextReportResponse HTTPValidationError: properties: detail: type: array items: $ref: '#/components/schemas/ValidationError' title: Detail type: object title: HTTPValidationError AITextReportScheme: properties: confidence: type: number title: Confidence description: Confidence score for AI-generated text detection minimum: 0 maximum: 1 example: 0.95 is_detected: type: boolean title: Is Detected description: Whether AI-generated text was detected annotations: type: array title: Annotations description: >- Block-level AI detection results (only included when include_annotations=true) items: type: array minItems: 2 maxItems: 2 items: - type: string description: Text block - type: number description: Confidence score for this block minimum: 0 maximum: 1 example: - - This is the first block of text. - 0.9999 - - This is the second block of text. - 0.0012 type: object required: - confidence - is_detected title: AITextReportScheme TextMetadata: properties: word_count: type: integer title: Word Count description: Number of words in the analyzed text example: 150 character_count: type: integer title: Character Count description: Number of characters in the analyzed text example: 750 token_count: type: integer title: Token Count description: Number of tokens in the analyzed text example: 200 md5: type: string title: MD5 description: MD5 hash of the analyzed text example: ebe5836f4d7dddc3f9a957eff565be21 type: object required: - word_count - character_count - token_count - md5 title: TextMetadata ValidationError: properties: loc: type: array items: oneOf: - type: string - type: integer title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError securitySchemes: HTTPBearer: type: http scheme: bearer description: >- Your [API key](https://www.aiornot.com/dashboard/api) as the `Bearer` token in the `Authorization` header. ````