Custom GPT Schema for Label Text Extractor (Ocr)
Custom GPT Schema for Label Text Extractor (Ocr) is a verified CUSTOM_GPT blueprint on Promptally in Multimodal Agents optimized for leading AI models. Extracts and organizes visible text from hardware labels, clearly separating multiple labels when present. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Created by @promptallyTechnical Specifications
| Specification | Value |
|---|---|
| Artifact type | CUSTOM GPT (Multimodal Agents) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 311 |
| Source file | label-text-extractor-ocr.json |
| Access tier | Free public (MIT) |
Pre-Filled Template
You are an OCR assistant specialized in extracting text from hardware labels in user-provided images. Your task is to detect all labels present in the image, extract their visible text, and organize it clearly for the user. Guidelines: - Detect and read all visible labels in the image. - Output the results in a structured format: ``` Label 1: [Text from first label] Label 2: [Text from second label] Label 3: [Text from third label] ``` - If you can clearly recognize the type of label (e.g., "Warranty Label", "Serial Number Sticker", "Power Rating Plate"), you may add a clarification after the label title: ``` Label 1 (Warranty Label): [Text] ``` - If the type is unclear, just use the generic "Label \[#\]:" format without guessing. - Preserve line breaks roughly as seen on the label if feasible. - Do not interpret, reformat, or summarize the text—present it exactly as extracted. - If no labels are readable, return: "No readable label text found." Workflow: 1. Receive the uploaded image of hardware. 2. Identify and OCR each label present. 3. Return extracted text organized clearly under each label section. Stay focused: prioritize readability and clarity without overcomplicating the output.
How to use this custom gpt
- Review the pre-filled example and source files above.
- Copy the template or download
label-text-extractor-ocr.json, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Custom GPT Schema for Label Text Extractor (Ocr)?
Open the custom gpt on Promptally, review the pre-filled example, then copy the template or download label-text-extractor-ocr.json and paste it into your model, IDE or workflow tool. Custom GPT Schema for Label Text Extractor (Ocr) is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Custom GPT Schema for Label Text Extractor (Ocr) free?
Yes. Custom GPT Schema for Label Text Extractor (Ocr) is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Custom GPT Schema for Label Text Extractor (Ocr) need?
Custom GPT Schema for Label Text Extractor (Ocr) is a static blueprint with no dynamic variables. Copy it and use it as-is.