JSON Parser

Class: JSONParserBlockV1

Source: inference.core.workflows.core_steps.formatters.json_parser.v1.JSONParserBlockV1

The block expects string input that would be produced by blocks exposing Large Language Models (LLMs) and Visual Language Models (VLMs). Input is parsed to JSON, and its keys are exposed as block outputs.

Accepted formats: - valid JSON strings - JSON documents wrapped with Markdown tags (very common for GPT responses)

{"my": "json"}

Details regarding block behavior:

• error_status is set True whenever at least one of expected_fields cannot be retrieved from input

• in case of multiple markdown blocks with raw JSON content - only first will be parsed and returned, while error_status will remain False

Type identifier

Use the following identifier in step "type" field: roboflow_core/json_parser@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
raw_json	str	The string with raw JSON to parse..	✅
expected_fields	List[str]	List of expected JSON fields. error_status field name is reserved and cannot be used..	❌

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to JSON Parser in version v1.

• inputs: Florence-2 Model, Florence-2 Model, Google Gemini, Llama 3.2 Vision, OpenAI, OpenAI, Anthropic Claude
• outputs: Keypoint Visualization, Google Gemini, Detections Stabilizer, Path Deviation, Gaze Detection, Reference Path Visualization, Stitch Images, Image Blur, Florence-2 Model, Local File Sink, Barcode Detection, Relative Static Crop, Clip Comparison, Cosine Similarity, Icon Visualization, Time in Zone, Dimension Collapse, Polygon Zone Visualization, Identify Outliers, Instance Segmentation Model, Dynamic Zone, Dynamic Crop, Grid Visualization, Property Definition, Detections Consensus, VLM as Classifier, Single-Label Classification Model, Camera Calibration, Perception Encoder Embedding Model, VLM as Classifier, Pixel Color Count, QR Code Generator, SIFT, Camera Focus, Detections Filter, Llama 3.2 Vision, Triangle Visualization, Line Counter Visualization, Multi-Label Classification Model, Email Notification, Roboflow Dataset Upload, Time in Zone, Image Slicer, Byte Tracker, Single-Label Classification Model, OCR Model, Pixelate Visualization, Byte Tracker, Object Detection Model, Dot Visualization, Image Slicer, Roboflow Dataset Upload, OpenAI, Model Monitoring Inference Aggregator, VLM as Detector, Buffer, Trace Visualization, Stability AI Outpainting, Multi-Label Classification Model, Overlap Filter, CogVLM, Corner Visualization, Background Color Visualization, First Non Empty Or Default, Halo Visualization, Ellipse Visualization, OpenAI, Anthropic Claude, Keypoint Detection Model, Image Contours, Circle Visualization, Image Threshold, Absolute Static Crop, Perspective Correction, Color Visualization, QR Code Detection, Instance Segmentation Model, PTZ Tracking (ONVIF).md), Blur Visualization, Keypoint Detection Model, Stability AI Inpainting, SIFT Comparison, Cache Get, Detections Merge, Roboflow Custom Metadata, SmolVLM2, Depth Estimation, Template Matching, Stability AI Image Generation, Crop Visualization, Stitch OCR Detections, Time in Zone, Continue If, Rate Limiter, Segment Anything 2 Model, Dominant Color, Expression, SIFT Comparison, Data Aggregator, Bounding Rectangle, Size Measurement, Detection Offset, Object Detection Model, Twilio SMS Notification, Model Comparison Visualization, CLIP Embedding Model, Clip Comparison, LMM, CSV Formatter, Path Deviation, Detections Transformation, Mask Visualization, Byte Tracker, Qwen2.5-VL, JSON Parser, Webhook Sink, Slack Notification, Velocity, Cache Set, Detections Classes Replacement, YOLO-World Model, Delta Filter, Classification Label Visualization, Polygon Visualization, OpenAI, LMM For Classification, Line Counter, Moondream2, Bounding Box Visualization, Distance Measurement, Image Preprocessing, Image Convert Grayscale, Google Vision OCR, Label Visualization, Line Counter, Detections Stitch, Florence-2 Model, Identify Changes, VLM as Detector

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds JSON Parser in version v1 has.

Bindings

• input

  • raw_json (language_model_output): The string with raw JSON to parse..

• output

  • error_status (boolean): Boolean flag.
  • * (*): Equivalent of any element.

Example JSON definition of step JSON Parser in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/json_parser@v1",
    "raw_json": [
        "$steps.lmm.output"
    ],
    "expected_fields": [
        "field_a",
        "field_b"
    ]
}