API Reference

Alpha

Verify

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Get Verify Job

alpha.verify.get(strjob_id, VerifyGetParams**kwargs) -> VerifyGetResponse

GET/api/alpha/verify/{job_id}

Get a Verify job by ID.

Returns the job status and configuration. Pass expand=result to include the Verify result (overall score, verdict, confidence, composite scores, and suspect regions) when the job is complete.

Raw per-signal detail is available via GET /verify/{job_id}/details.

ParametersExpand Collapse

job_id: str

expand: Optional[Sequence[str]]

Optional fields to include (e.g. result).

organization_id: Optional[str]

project_id: Optional[str]

ReturnsExpand Collapse

class VerifyGetResponse: …

Response for a Verify job.

id: str

Unique identifier

configuration: Configuration

Verify configuration used for this job

target_pages: Optional[str]

Comma-separated page numbers or ranges to analyze (1-based). Omit to analyze all pages. Ignored for non-PDF inputs.

tier: Optional[Literal["agentic", "fast"]]

Verify tier: ‘fast’ runs only the quick deterministic forensic checks (metadata, content integrity, container structure, pixel statistics); ‘agentic’ (default) runs the full pipeline including the learned detectors and the semantic review pass.

One of the following:

"agentic"

"fast"

document_input_type: Literal["file_id", "parse_job_id", "url"]

Type of the document input (FILE)

One of the following:

"file_id"

"parse_job_id"

"url"

file_input: str

ID of the input file

project_id: str

Project this job belongs to

status: Literal["CANCELLED", "COMPLETED", "FAILED", 2 more]

Current job status: PENDING, RUNNING, COMPLETED, FAILED, or CANCELLED

One of the following:

"CANCELLED"

"COMPLETED"

"FAILED"

"PENDING"

"RUNNING"

user_id: str

User who created this job

created_at: Optional[datetime]

Creation datetime

formatdate-time

error_message: Optional[str]

Error message if job failed

result: Optional[Result]

Result of a Verify (doctored-document) analysis.

Raw per-signal detail (evidence list, per-family sub-scores, raw regions, forensic heatmaps) is available separately via the job’s details endpoint.

detector_version: str

Version of the detector that produced the result

overall_score: float

Overall doctoring likelihood (0 to 1)

maximum1

minimum0

verdict: Literal["AUTHENTIC", "DOCTORED", "LIKELY_DOCTORED", 2 more]

Overall verdict for the document

One of the following:

"AUTHENTIC"

"DOCTORED"

"LIKELY_DOCTORED"

"NO_STRONG_SIGNAL"

"SUSPICIOUS"

composite_scores: Optional[ResultCompositeScores]

Composite scores, each answering one question about the document

ai_generated: Optional[ResultCompositeScoresAIGenerated]

Was this content synthesized by a generative model?

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

document_coherence: Optional[ResultCompositeScoresDocumentCoherence]

Does the document’s content agree with itself (checksums, arithmetic, machine-readable zones)?

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

document_metadata: Optional[ResultCompositeScoresDocumentMetadata]

Does the file’s provenance / toolchain history look suspicious? Advisory: individually weak workflow-hygiene signals

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

known_fraud: Optional[ResultCompositeScoresKnownFraud]

Has this asset (or its template) been seen in fraud before?

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

manually_edited: Optional[ResultCompositeScoresManuallyEdited]

Was this document altered after creation (splice, retype, redact, inpaint)?

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

recapture: Optional[ResultCompositeScoresRecapture]

Was the document captured through a channel that destroys forensic evidence (photo of a screen, print-then-rescan)?

applicable: Optional[bool]

Whether the checks feeding this composite ran on this document. When false the document was not checked for this — not cleared of it

score: Optional[float]

Score (0 to 1); null when the composite was not applicable

maximum1

minimum0

confidence: Optional[float]

Confidence in the verdict (0 to 1): how firmly the detected signals support the verdict bucket, independent of the doctoring likelihood itself

maximum1

minimum0

error: Optional[str]

Error detail when the analysis could not complete

page_count: Optional[int]

Number of analysed pages (1 for images/docx)

minimum1

page_dimensions: Optional[List[ResultPageDimension]]

Rendered pixel size per page, so region bboxes can be scaled onto the page

height: int

Rendered page height in pixels

page: int

0-based page index (0 for standalone images)

width: int

Rendered page width in pixels

reasoning: Optional[str]

Explanation of the verdict

suspect_regions: Optional[List[ResultSuspectRegion]]

Regions that led to the suspected fraud, ranked most-suspect first, each with an explanation of what makes it suspect

bbox: List[int]

Region bounding box as [x, y, w, h] in page-render pixels

explanation: str

Human-readable explanation of what makes this region suspect

kind: str

Kind of anomaly detected in this region

page: int

0-based page index (0 for standalone images)

score: float

Suspicion score for this region (0 to 1)

maximum1

minimum0

source: str

Detector that flagged this region

primary: Optional[bool]

Whether this region is part of the small set of decisive evidence behind the verdict — the boxes a reviewer should look at first

review: Optional[str]

Automated reviewer verdict for this region (confirmed, dismissed, unsure, or empty). A dismissed region can still be surfaced when it is the only place to look; this label says how to read it

synthetic_score: Optional[float]

Likelihood (0 to 1) that the document is wholly generated or fabricated rather than a capture of a real document. Null for jobs completed before this score was introduced

maximum1

minimum0

tampering_score: Optional[float]

Likelihood (0 to 1) that a real captured document was locally edited — a genuine capture with regions altered after the fact. Null for jobs completed before this score was introduced

maximum1

minimum0

transaction_id: Optional[str]

Idempotency key

updated_at: Optional[datetime]

Update datetime

formatdate-time

Get Verify Job

Python

HTTP

TypeScript

Python

Go

Java

C#

CLI Tool

import os
from llama_cloud import LlamaCloud

client = LlamaCloud(
    api_key=os.environ.get("LLAMA_CLOUD_API_KEY"),  # This is the default and can be omitted
)
verify = client.alpha.verify.get(
    job_id="job_id",
)
print(verify.id)

200 example

{
  "id": "id",
  "configuration": {
    "target_pages": "1,3,5-7",
    "tier": "agentic"
  },
  "document_input_type": "file_id",
  "file_input": "file_input",
  "project_id": "project_id",
  "status": "CANCELLED",
  "user_id": "user_id",
  "created_at": "2019-12-27T18:11:19.117Z",
  "error_message": "error_message",
  "result": {
    "detector_version": "detector_version",
    "overall_score": 0,
    "verdict": "AUTHENTIC",
    "composite_scores": {
      "ai_generated": {
        "applicable": true,
        "score": 0
      },
      "document_coherence": {
        "applicable": true,
        "score": 0
      },
      "document_metadata": {
        "applicable": true,
        "score": 0
      },
      "known_fraud": {
        "applicable": true,
        "score": 0
      },
      "manually_edited": {
        "applicable": true,
        "score": 0
      },
      "recapture": {
        "applicable": true,
        "score": 0
      }
    },
    "confidence": 0,
    "error": "error",
    "page_count": 1,
    "page_dimensions": [
      {
        "height": 0,
        "page": 0,
        "width": 0
      }
    ],
    "reasoning": "reasoning",
    "suspect_regions": [
      {
        "bbox": [
          0,
          0,
          0,
          0
        ],
        "explanation": "explanation",
        "kind": "kind",
        "page": 0,
        "score": 0,
        "source": "source",
        "primary": true,
        "review": "review"
      }
    ],
    "synthetic_score": 0,
    "tampering_score": 0
  },
  "transaction_id": "transaction_id",
  "updated_at": "2019-12-27T18:11:19.117Z"
}

Returns Examples

200 example

{
  "id": "id",
  "configuration": {
    "target_pages": "1,3,5-7",
    "tier": "agentic"
  },
  "document_input_type": "file_id",
  "file_input": "file_input",
  "project_id": "project_id",
  "status": "CANCELLED",
  "user_id": "user_id",
  "created_at": "2019-12-27T18:11:19.117Z",
  "error_message": "error_message",
  "result": {
    "detector_version": "detector_version",
    "overall_score": 0,
    "verdict": "AUTHENTIC",
    "composite_scores": {
      "ai_generated": {
        "applicable": true,
        "score": 0
      },
      "document_coherence": {
        "applicable": true,
        "score": 0
      },
      "document_metadata": {
        "applicable": true,
        "score": 0
      },
      "known_fraud": {
        "applicable": true,
        "score": 0
      },
      "manually_edited": {
        "applicable": true,
        "score": 0
      },
      "recapture": {
        "applicable": true,
        "score": 0
      }
    },
    "confidence": 0,
    "error": "error",
    "page_count": 1,
    "page_dimensions": [
      {
        "height": 0,
        "page": 0,
        "width": 0
      }
    ],
    "reasoning": "reasoning",
    "suspect_regions": [
      {
        "bbox": [
          0,
          0,
          0,
          0
        ],
        "explanation": "explanation",
        "kind": "kind",
        "page": 0,
        "score": 0,
        "source": "source",
        "primary": true,
        "review": "review"
      }
    ],
    "synthetic_score": 0,
    "tampering_score": 0
  },
  "transaction_id": "transaction_id",
  "updated_at": "2019-12-27T18:11:19.117Z"
}