CogVLM

Class: CogVLMBlockV1

Source: inference.core.workflows.core_steps.models.foundation.cog_vlm.v1.CogVLMBlockV1

CogVLM reached End Of Life

Due to dependencies conflicts with newer models and security vulnerabilities discovered in transformers library patched in the versions of library incompatible with the model we announced End Of Life for CogVLM support in inference, effective since release 0.38.0.

We are leaving this block in ecosystem until release 0.42.0 for clients to get informed about change that was introduced.

Starting as of now, all Workflows using the block stop being functional (runtime error will be raised), after inference release 0.42.0 - this block will be removed and Execution Engine will raise compilation error seeing the block in Workflow definition.

Ask a question to CogVLM, an open source vision-language model.

This model requires a GPU and can only be run on self-hosted devices, and is not available on the Roboflow Hosted API.

This model was previously part of the LMM block.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
prompt	str	Text prompt to the CogVLM model.	✅
json_output_format	Dict[str, str]	Holds dictionary that maps name of requested output field into its description.	❌

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 CogVLM in version v1.

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

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the CogVLM model.

• output

  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.
  • image (image_metadata): Dictionary with image metadata required by supervision.
  • structured_output (dictionary): Dictionary.
  • raw_output (string): String value.
  • * (*): Equivalent of any element.

Example JSON definition of step CogVLM in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/cog_vlm@v1",
    "images": "$inputs.image",
    "prompt": "my prompt",
    "json_output_format": {
        "count": "number of cats in the picture"
    }
}