LMM¶
Deprecated
This block is deprecated and may be removed in a future release.
Class: LMMBlockV1
Source: inference.core.workflows.core_steps.models.foundation.lmm.v1.LMMBlockV1
Ask a question to a Large Multimodal Model (LMM) with an image and text.
You can specify arbitrary text prompts to an LMMBlock.
The LLMBlock supports two LMMs:
- OpenAI's GPT-4 with Vision;
You need to provide your OpenAI API key to use the GPT-4 with Vision model.
If you want to classify an image into one or more categories, we recommend using the dedicated LMMForClassificationBlock.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/lmm@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 |
Holds unconstrained text prompt to LMM mode. | ✅ |
lmm_type |
str |
Type of LMM to be used. | ✅ |
lmm_config |
LMMConfig |
Configuration of LMM. | ❌ |
remote_api_key |
str |
Holds API key required to call LMM model - in current state of development, we require OpenAI key when lmm_type=gpt_4v.. |
✅ |
json_output |
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 LMM in version v1.
- inputs:
S3 Sink,Email Notification,Clip Comparison,Morphological Transformation,VLM As Detector,Qwen-VL,Twilio SMS/MMS Notification,MoonshotAI Kimi,Polygon Zone Visualization,Stitch OCR Detections,OpenAI-Compatible LLM,OpenAI,Heatmap Visualization,Keypoint Visualization,Email Notification,Llama 3.2 Vision,Anthropic Claude,Stability AI Image Generation,Google Vision OCR,Camera Focus,Label Visualization,Instance Segmentation Model,Local File Sink,Google Gemini,Background Color Visualization,Qwen 3.5 API,Google Gemini,Polygon Visualization,SIFT Comparison,Grid Visualization,Florence-2 Model,OCR Model,VLM As Classifier,LMM For Classification,Keypoint Detection Model,Image Preprocessing,SIFT,Roboflow Dataset Upload,Corner Visualization,Stability AI Outpainting,Halo Visualization,Multi-Label Classification Model,Qwen3.5-VL,Blur Visualization,Morphological Transformation,Trace Visualization,Stitch OCR Detections,Reference Path Visualization,Halo Visualization,Model Comparison Visualization,Dot Visualization,Background Subtraction,Text Display,Absolute Static Crop,CSV Formatter,Florence-2 Model,Icon Visualization,Perspective Correction,Stability AI Inpainting,Image Convert Grayscale,QR Code Generator,OpenRouter,Model Monitoring Inference Aggregator,OpenAI,Llama 3.2 Vision,Image Threshold,Anthropic Claude,Dynamic Crop,Contrast Enhancement,Bounding Box Visualization,Depth Estimation,Image Contours,EasyOCR,Relative Static Crop,Polygon Visualization,Google Gemma API,Qwen 3.6 API,Image Blur,Anthropic Claude,Triangle Visualization,Object Detection Model,Roboflow Custom Metadata,OpenAI,Slack Notification,Pixelate Visualization,Stitch Images,Single-Label Classification Model,OpenAI,Image Slicer,Line Counter Visualization,Image Slicer,LMM,Roboflow Dataset Upload,Color Visualization,Google Gemini,Classification Label Visualization,Camera Focus,Camera Calibration,Ellipse Visualization,Mask Visualization,GLM-OCR,Crop Visualization,Circle Visualization,CogVLM,Contrast Equalization,Roboflow Vision Events,Webhook Sink,Twilio SMS Notification,MoonshotAI Kimi,Google Gemma - outputs:
Keypoint Detection Model,VLM As Detector,YOLO-World Model,MoonshotAI Kimi,Polygon Zone Visualization,OpenAI-Compatible LLM,Heatmap Visualization,Email Notification,Llama 3.2 Vision,Anthropic Claude,Label Visualization,Camera Focus,Path Deviation,Qwen3.5,SmolVLM2,Rate Limiter,Byte Tracker,Background Color Visualization,Mask Edge Snap,Moondream2,Velocity,Detection Event Log,Florence-2 Model,Barcode Detection,Single-Label Classification Model,OCR Model,VLM As Classifier,Qwen2.5-VL,Detections Stabilizer,LMM For Classification,SIFT,Roboflow Dataset Upload,Segment Anything 2 Model,Halo Visualization,Multi-Label Classification Model,Qwen3.5-VL,Qwen3-VL,Time in Zone,Stitch OCR Detections,Model Comparison Visualization,QR Code Detection,Detections Combine,Bounding Rectangle,ByteTrack Tracker,Stability AI Inpainting,Image Convert Grayscale,Line Counter,OpenAI,Llama 3.2 Vision,Anthropic Claude,Dynamic Crop,Detections Consensus,Size Measurement,Dominant Color,Continue If,Contrast Enhancement,Bounding Box Visualization,Depth Estimation,CLIP Embedding Model,EasyOCR,Relative Static Crop,Polygon Visualization,Google Gemma API,Qwen 3.6 API,Template Matching,Single-Label Classification Model,Image Blur,Anthropic Claude,Triangle Visualization,Roboflow Custom Metadata,Slack Notification,Image Stack,Pixelate Visualization,Image Slicer,Line Counter Visualization,Image Slicer,Cosine Similarity,Cache Get,Data Aggregator,Expression,Google Gemini,Camera Calibration,Ellipse Visualization,Identify Changes,GLM-OCR,Crop Visualization,Circle Visualization,Dimension Collapse,Webhook Sink,MoonshotAI Kimi,S3 Sink,Email Notification,Clip Comparison,Morphological Transformation,Path Deviation,Qwen-VL,SAM 3,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Stitch OCR Detections,OpenAI,VLM As Detector,Keypoint Visualization,Seg Preview,Stability AI Image Generation,Google Vision OCR,SAM 3,Instance Segmentation Model,Overlap Filter,Local File Sink,Multi-Label Classification Model,Google Gemini,Motion Detection,Instance Segmentation Model,Qwen 3.5 API,Google Gemini,Polygon Visualization,SIFT Comparison,Grid Visualization,Delta Filter,Time in Zone,Detections Filter,Detections Merge,First Non Empty Or Default,Keypoint Detection Model,Image Preprocessing,Dynamic Zone,Corner Visualization,Stability AI Outpainting,Semantic Segmentation Model,Detections List Roll-Up,Blur Visualization,Property Definition,Perception Encoder Embedding Model,Distance Measurement,Morphological Transformation,Trace Visualization,VLM As Classifier,Gaze Detection,Reference Path Visualization,Halo Visualization,Dot Visualization,Pixel Color Count,JSON Parser,Background Subtraction,Text Display,Absolute Static Crop,CSV Formatter,Florence-2 Model,Byte Tracker,Icon Visualization,Identify Outliers,Mask Area Measurement,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Object Detection Model,QR Code Generator,OpenRouter,Model Monitoring Inference Aggregator,Image Threshold,OC-SORT Tracker,Clip Comparison,Cache Set,Detection Offset,Keypoint Detection Model,Image Contours,Multi-Label Classification Model,Per-Class Confidence Filter,Object Detection Model,OpenAI,SIFT Comparison,Single-Label Classification Model,OpenAI,Instance Segmentation Model,Stitch Images,Buffer,Detections Classes Replacement,Semantic Segmentation Model,LMM,Roboflow Dataset Upload,Detections Transformation,Color Visualization,Classification Label Visualization,Camera Focus,Detections Stitch,Byte Tracker,PTZ Tracking (ONVIF),SORT Tracker,Mask Visualization,CogVLM,Inner Workflow,SAM2 Video Tracker,Contrast Equalization,Roboflow Vision Events,Twilio SMS Notification,Google Gemma
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
LMM in version v1 has.
Bindings
-
input
images(image): The image to infer on..prompt(string): Holds unconstrained text prompt to LMM mode.lmm_type(string): Type of LMM to be used.remote_api_key(Union[string,secret]): Holds API key required to call LMM model - in current state of development, we require OpenAI key whenlmm_type=gpt_4v..
-
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 LMM in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/lmm@v1",
"images": "$inputs.image",
"prompt": "my prompt",
"lmm_type": "gpt_4v",
"lmm_config": {
"gpt_image_detail": "low",
"gpt_model_version": "gpt-4o",
"max_tokens": 200
},
"remote_api_key": "xxx-xxx",
"json_output": {
"count": "number of cats in the picture"
}
}