Cache Get¶
Class: CacheGetBlockV1
Source: inference.core.workflows.core_steps.cache.cache_get.v1.CacheGetBlockV1
Retrieve a previously stored value from an in-memory cache by key, using the image's video identifier as a namespace to enable data sharing between workflow steps, caching intermediate results, and avoiding redundant computations within the same workflow execution context.
How This Block Works¶
This block retrieves values from an in-memory cache that was previously stored using the Cache Set block. The block:
- Receives image and cache key:
- Takes an input image to determine the cache namespace
- Receives a cache key (string) identifying which value to retrieve
- Determines cache namespace:
- Extracts video identifier from the image's video metadata
- Uses the video identifier as the cache namespace (isolates cache entries per video/stream)
- Falls back to "default" namespace if no video identifier is present
- Looks up cached value:
- Accesses the in-memory cache dictionary for the determined namespace
- Searches for the specified key in the cache
- Returns the cached value if found, or False if the key does not exist
- Returns retrieved value:
- Outputs the cached value (can be any data type: strings, numbers, lists, detections, etc.)
- Returns False if the key was not found in the cache
- The output type matches whatever was originally stored with Cache Set
The cache is namespaced by video identifier, meaning different videos or streams have separate cache storage. This allows workflows processing multiple videos to maintain separate caches for each video. The cache is stored in memory and is cleared when the workflow execution completes or when the block is destroyed. Cache Get must be used in conjunction with Cache Set - values are stored with Cache Set and retrieved with Cache Get using the same key and namespace (determined by the same video identifier).
Common Use Cases¶
- Shared State Between Steps: Store intermediate results in one workflow step and retrieve them in another step (e.g., store detection results for later analysis, cache classification predictions for filtering, share metadata between blocks), enabling state sharing workflows
- Avoid Redundant Computations: Cache expensive computation results and reuse them across multiple workflow steps (e.g., cache model predictions, store processed images, reuse transformation results), enabling computation caching workflows
- Video Frame Context: Maintain context across video frames by storing frame-specific data (e.g., cache previous frame detections, store frame sequence metadata, maintain tracking state), enabling frame context workflows
- Conditional Workflow Logic: Store decision results or flags that control workflow execution in subsequent steps (e.g., cache filtering decisions, store validation results, maintain workflow state), enabling conditional execution workflows
- Data Aggregation: Accumulate data across workflow steps by storing values in cache and retrieving/updating them (e.g., aggregate detection counts, accumulate statistics, build result collections), enabling data aggregation workflows
- Temporary Storage: Use cache as temporary storage for values that need to be accessed by multiple workflow steps without passing through the workflow graph (e.g., store cross-step data, maintain temporary state, share non-linear workflow data), enabling temporary storage workflows
Connecting to Other Blocks¶
This block retrieves cached values and can be used throughout workflows:
- After Cache Set block to retrieve values that were previously stored (e.g., retrieve stored detections, get cached predictions, access stored metadata), enabling cache retrieval workflows
- In workflow branches to access shared cache values from parallel or conditional execution paths (e.g., retrieve shared state, access cached results, get common data), enabling branch coordination workflows
- Before blocks that need cached data to provide cached values as input (e.g., provide cached detections to analysis, use cached predictions for filtering, pass cached metadata to processing), enabling cached input workflows
- In conditional logic workflows to retrieve flags or decisions stored by Cache Set (e.g., get cached validation results, retrieve decision flags, access conditional state), enabling conditional logic workflows
- With video processing workflows to maintain frame-specific or video-specific cache namespaces (e.g., retrieve frame context, access video-specific cache, get stream-specific data), enabling video context workflows
- Before output or sink blocks to include cached data in final results (e.g., include cached aggregations, output cached statistics, return cached results), enabling output workflows
Requirements¶
This block requires an input image (used to determine the cache namespace via video identifier) and a cache key (string) to look up the stored value. The block only works in LOCAL execution mode - it will raise a NotImplementedError if used in other execution modes. Values must be previously stored using the Cache Set block with the same key and namespace (same video identifier). The cache is stored in memory and is automatically cleared when the workflow execution completes. The cache is namespaced by video identifier, so different videos have separate cache storage. If a key is not found in the cache, the block returns False. The cached value can be any data type (strings, numbers, lists, detections, images, etc.) depending on what was originally stored.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/cache_get@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
key |
str |
Cache key (string) identifying which value to retrieve from the cache. The key must match the key used when storing the value with the Cache Set block. If the key does not exist in the cache, the block returns False. Keys are case-sensitive and must be exact matches. Use descriptive keys to identify different cached values (e.g., 'detections', 'classification_result', 'frame_metadata').. | ✅ |
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 Cache Get in version v1.
- inputs:
Clip Comparison,Anthropic Claude,Google Vision OCR,Email Notification,Llama 3.2 Vision,OpenAI,VLM As Classifier,CSV Formatter,LMM For Classification,Object Detection Model,Email Notification,Roboflow Dataset Upload,VLM As Detector,Anthropic Claude,OpenAI,Multi-Label Classification Model,EasyOCR,OCR Model,Instance Segmentation Model,Stitch OCR Detections,Slack Notification,Google Gemini,Florence-2 Model,Local File Sink,Florence-2 Model,Stitch OCR Detections,Google Gemini,Roboflow Custom Metadata,OpenAI,LMM,CogVLM,OpenAI,Webhook Sink,Anthropic Claude,Twilio SMS Notification,Keypoint Detection Model,Model Monitoring Inference Aggregator,Twilio SMS/MMS Notification,Single-Label Classification Model,Roboflow Dataset Upload,Google Gemini - outputs:
Anthropic Claude,Qwen3-VL,Camera Focus,CLIP Embedding Model,Text Display,CSV Formatter,Segment Anything 2 Model,Rate Limiter,Dynamic Crop,Relative Static Crop,Continue If,SAM 3,Qwen2.5-VL,Mask Visualization,Camera Focus,SIFT,VLM As Classifier,Path Deviation,Detections Combine,Background Color Visualization,PTZ Tracking (ONVIF).md),Polygon Visualization,Moondream2,Size Measurement,Stitch OCR Detections,Line Counter,SIFT Comparison,Byte Tracker,Detections List Roll-Up,OpenAI,Identify Outliers,Crop Visualization,Single-Label Classification Model,Keypoint Visualization,Icon Visualization,Multi-Label Classification Model,Llama 3.2 Vision,Gaze Detection,OpenAI,Image Contours,Stitch Images,VLM As Classifier,Anthropic Claude,SmolVLM2,OpenAI,Distance Measurement,Triangle Visualization,Detections Classes Replacement,Expression,Background Subtraction,Reference Path Visualization,EasyOCR,Instance Segmentation Model,Line Counter Visualization,Slack Notification,Time in Zone,Line Counter,Detection Event Log,Google Gemini,JSON Parser,Mask Area Measurement,Image Convert Grayscale,Stability AI Image Generation,Pixel Color Count,Seg Preview,Delta Filter,Time in Zone,OpenAI,Object Detection Model,Stability AI Outpainting,Buffer,Webhook Sink,Image Threshold,Instance Segmentation Model,Anthropic Claude,Detections Merge,Perception Encoder Embedding Model,Perspective Correction,Cache Set,SAM 3,First Non Empty Or Default,Detection Offset,Clip Comparison,Clip Comparison,Halo Visualization,Image Blur,Email Notification,Contrast Equalization,Object Detection Model,Blur Visualization,Detections Stabilizer,VLM As Detector,Roboflow Dataset Upload,Corner Visualization,Classification Label Visualization,Dimension Collapse,Keypoint Detection Model,Trace Visualization,Multi-Label Classification Model,Stitch OCR Detections,YOLO-World Model,Bounding Rectangle,Barcode Detection,Local File Sink,Florence-2 Model,Ellipse Visualization,Pixelate Visualization,Roboflow Custom Metadata,Single-Label Classification Model,Identify Changes,LMM,SAM 3,Dot Visualization,Circle Visualization,Twilio SMS Notification,Byte Tracker,SIFT Comparison,Velocity,Absolute Static Crop,Morphological Transformation,Template Matching,Dominant Color,Overlap Filter,Property Definition,Google Gemini,Dynamic Zone,Polygon Visualization,Google Vision OCR,Color Visualization,LMM For Classification,Email Notification,Cosine Similarity,VLM As Detector,Bounding Box Visualization,Model Comparison Visualization,Grid Visualization,OCR Model,Halo Visualization,Detections Consensus,Data Aggregator,Stability AI Inpainting,Image Slicer,Florence-2 Model,Heatmap Visualization,Polygon Zone Visualization,Image Slicer,Detections Filter,Label Visualization,Google Gemini,Depth Estimation,Image Preprocessing,Cache Get,Detections Stitch,Time in Zone,QR Code Detection,CogVLM,Byte Tracker,Camera Calibration,Path Deviation,Detections Transformation,QR Code Generator,Motion Detection,Keypoint Detection Model,Model Monitoring Inference Aggregator,Twilio SMS/MMS Notification,Roboflow Dataset Upload
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Cache Get in version v1 has.
Bindings
-
input
image(image): Input image used to determine the cache namespace. The block extracts the video identifier from the image's video metadata and uses it as the cache namespace. If no video identifier is present, the block uses 'default' as the namespace. The namespace isolates cache entries so different videos or streams have separate cache storage. Use the same image (with the same video identifier) for both Cache Set and Cache Get blocks to access the same cache namespace..key(string): Cache key (string) identifying which value to retrieve from the cache. The key must match the key used when storing the value with the Cache Set block. If the key does not exist in the cache, the block returns False. Keys are case-sensitive and must be exact matches. Use descriptive keys to identify different cached values (e.g., 'detections', 'classification_result', 'frame_metadata')..
-
output
output(*): Equivalent of any element.
Example JSON definition of step Cache Get in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/cache_get@v1",
"image": "$inputs.image",
"key": "my_cache_key"
}