REST API Quickstart - Pangram Labs

Set your API key

All requests require your API key in the x-api-key header.

export PANGRAM_API_KEY=<your API key>

Discover available models

Retrieve the model selectors enabled for your API key.

curl -X GET https://text.external-api.pangram.com/models \
  -H "x-api-key: $PANGRAM_API_KEY"

The response is entitlement- and availability-aware:

{
  "models": ["default", "pangram-4"]
}

Submit an AI detection task

Pangram AI detection uses an async task API. Submit text to create a task.

curl -X POST https://text.external-api.pangram.com/task \
  -H "Content-Type: application/json" \
  -H "x-api-key: $PANGRAM_API_KEY" \
  -d '{
    "text": "The text to analyze",
    "model": "pangram-4",
    "public_dashboard_link": false
  }'

Example Response

{
  "task_id": "123e4567-e89b-12d3-a456-426614174000"
}

Poll for the completed result

Poll the task endpoint until stage is STAGE_SUCCESS or STAGE_FAILED.

curl -X GET https://text.external-api.pangram.com/task/123e4567-e89b-12d3-a456-426614174000 \
  -H "x-api-key: $PANGRAM_API_KEY"

Example Success Response

{
  "stage": "STAGE_SUCCESS",
  "text": "The text to analyze",
  "version": "4.0",
  "headline": "Human Written",
  "prediction": "We believe that this entire text is human-written.",
  "prediction_short": "Human",
  "fraction_ai": 0.0,
  "fraction_ai_assisted": 0.0,
  "fraction_human": 1.0,
  "num_ai_segments": 0,
  "num_ai_assisted_segments": 0,
  "num_human_segments": 1,
  "windows": [
    {
      "text": "The text to analyze",
      "label": "Human Written",
      "ai_assistance_score": 0.02,
      "confidence": "High",
      "start_index": 0,
      "end_index": 19,
      "word_count": 4,
      "token_length": 5,
      "is_humanized": false,
      "humanizer_score": 0.0
    }
  ]
}

Key response fields:

stage — terminal task stage for completed results
fraction_ai / fraction_ai_assisted / fraction_human — breakdown of text by authorship
windows — segment-level classifications with confidence scores
headline — summary classification, such as "AI Detected" or "Human Written"
is_humanized / humanizer_score — Pangram 4 humanizer-head output on every window

Request a dashboard link

Pass public_dashboard_link: true when submitting the task to get a shareable link in the completed result.

curl -X POST https://text.external-api.pangram.com/task \
  -H "Content-Type: application/json" \
  -H "x-api-key: $PANGRAM_API_KEY" \
  -d '{
    "text": "The text to analyze",
    "model": "pangram-4",
    "public_dashboard_link": true
  }'

Submit a Bulk API job

Use POST /bulk for asynchronous AI detection across many inputs.

curl -X POST https://text.external-api.pangram.com/bulk \
  -H "Content-Type: application/json" \
  -H "x-api-key: $PANGRAM_API_KEY" \
  -d '{
    "items": [
      {"id": "row-001", "text": "First text to analyze"},
      {"id": "row-002", "text": "Second text to analyze"}
    ],
    "model": "pangram-4"
  }'

Example Response

{
  "bulk_id": "blk_123",
  "status": "queued",
  "total_items": 2,
  "accepted_items": [
    {"index": 0, "id": "row-001", "task_id": "123e4567-e89b-12d3-a456-426614174000"},
    {"index": 1, "id": "row-002", "task_id": "223e4567-e89b-12d3-a456-426614174000"}
  ],
  "failed_items": []
}

Poll and fetch bulk results

Poll the bulk job until status is succeeded, failed, or partial.

curl -X GET https://text.external-api.pangram.com/bulk/blk_123 \
  -H "x-api-key: $PANGRAM_API_KEY"

Then page through results.

curl -X GET "https://text.external-api.pangram.com/bulk/blk_123/results?offset=0&limit=100" \
  -H "x-api-key: $PANGRAM_API_KEY"

Upload a file

Send documents as multipart form data to create file-based AI detection results.

curl -s -X POST https://file-external.api.pangram.com \
  -H "x-api-key: $PANGRAM_API_KEY" \
  -F "files=@modeling/deployments/test/test_document.docx" \
  -F "public_dashboard_link=true" \
  | jq -r '.[0].public_dashboard_link'

Check for plagiarism

Check text against a database of online content. Note the different base URL.

curl -X POST https://plagiarism.api.pangram.com \
  -H "Content-Type: application/json" \
  -H "x-api-key: $PANGRAM_API_KEY" \
  -d '{
    "text": "Text to check for plagiarism"
  }'

Example Response

{
  "text": "Text to check for plagiarism",
  "plagiarism_detected": true,
  "plagiarized_content": [
    {
      "source_url": "https://example.com/source",
      "matched_text": "Text to check for plagiarism",
      "similarity_score": 0.95
    }
  ],
  "total_sentences": 1,
  "plagiarized_sentences": 1,
  "percent_plagiarized": 100.0
}

The text and bulk APIs temporarily accept an omitted model for backward compatibility and resolve it to "default". New integrations should always send a selector returned by GET /models. A bulk selector applies to every item in the job.

Error Handling

Status Code	Description
`400 Bad Request`	The request body is not properly formatted.
`401 Unauthorized`	The `x-api-key` is missing or invalid.
`402 Payment Required`	The account has insufficient credits.
`403 Forbidden`	The requested model is not enabled for the API key, or the API key does not own the requested task or bulk job.
`404 Not Found`	The requested task or bulk job does not exist.
`413 Payload Too Large`	The bulk request exceeds the maximum billable units.
`422 Unprocessable Entity`	The input text or model selector is invalid.
`429 Too Many Requests`	The API key exceeds its configured rate limit.
`500 Internal Server Error`	There was an error processing the request.
`503 Service Unavailable`	The requested model is temporarily unavailable.

If you are running into errors, please reach out at support@pangram.com.

​Error Handling

Error Handling