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

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"
    }
}