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

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"
    ]
}