# ChatGPT
## Overview
The ChatGPT Plugin enables seamless integration of OpenAI’s language and multimodal models into your annotation workflows on Ango Hub. This plugin is designed to support a wide range of use cases, including text processing, image understanding, named entity recognition (NER), and audio processing.
## Plugin Functionality
The ChatGPT Plugin processes assets and generates outputs based on the selected mode, model, and prompt configuration.
* **Text Processing:** Generate summaries, classifications, structured outputs, or rewritten content from text inputs.
* **Image Understanding:** Analyze visual content and generate descriptions, extract text (OCR-style), or answer questions about images.
* **Named Entity Recognition (NER):** Identify and extract structured entities such as names, organizations, locations, and dates from text.
* **Audio Processing:** Transcribe, summarize, or analyze audio content using prompt-based instructions.
#### Prompt Construction
The plugin dynamically constructs the final prompt using:
```
[prompt_prefix] + [input content] + [prompt_suffix]
```
* **prompt\_prefix** defines the task or instruction
* **Input content** comes from the asset or annotation
* **prompt\_suffix** refines output format or constraints
This flexible structure allows you to standardize instructions across all assets.
### Supported Modes
#### Workflow-1: Text Processing (Asset)
{
"mode": "text-prompt",
"model_name": "gpt-4.1-nano",
"openai_api_key": "<YOUR_OPENAI_API_KEY>",
"prompt_prefix": "What is the capital of ",
"prompt_suffix": "? Provide only the city name."
}
```json
{
"mode": "ner",
"model_name": "gpt-4.1-nano",
"openai_api_key": "",
"prompt_prefix": "",
"prompt_suffix": ""
}
```
{% hint style="info" %}
In the "ner" mode, class mapping is not required. The plugin automatically assigns entity labels based on the project's category schema, so no manual mapping configuration is needed.
{% endhint %}
Category Schema
```json
{
"tools": [
{
"schemaId": "796d1292cfbf6229e793571",
"tool": "ner",
"title": "Adjective",
"required": false,
"classifications": [],
"multiple": false,
"color": "#f44336",
"shortcutKey": "1"
},
{
"schemaId": "fd74cf3157e7805f080f405",
"tool": "ner",
"title": "Verb",
"required": false,
"classifications": [],
"multiple": false,
"color": "#03a9f4",
"shortcutKey": "2"
},
{
"schemaId": "c956228f2b8e2effebac917",
"tool": "ner",
"title": "Noun",
"required": false,
"classifications": [],
"multiple": false,
"color": "#9c27b0",
"shortcutKey": "3"
}
],
"classifications": [],
"relations": []
}
```
#### Workflow-5: Speech-to-Text
```json
{
"mode": "audio-prompt",
"model_name": "whisper-1",
"openai_api_key": "",
"prompt_prefix": "",
"prompt_suffix": ""
}
```
Category Schema
```json
{
"tools": [
{
"schemaId": "8280042f0f98b800b6cc860",
"tool": "ner",
"title": "Transcription Entity",
"required": false,
"classifications": [
{
"schemaId": "f9a4e85dc1d215022e31013",
"tool": "text",
"title": "Transcription Text",
"required": false,
"classifications": [],
"multiple": false,
"options": [],
"parentToolType": "ner",
"parentToolId": "8280042f0f98b800b6cc860",
"shortcutKey": "3",
"frameSpecific": false,
"richText": false,
"katex": false,
"katexBottom": true,
"regex": ""
}
],
"multiple": false,
"color": "#f44336",
"shortcutKey": "1"
}
],
"classifications": [
{
"schemaId": "0912500394b493f68cdd406",
"tool": "text",
"title": "Full Transcription Text",
"required": false,
"classifications": [],
"multiple": false,
"options": [],
"shortcutKey": "2",
"frameSpecific": false,
"richText": false,
"katex": false,
"katexBottom": true,
"regex": ""
}
],
"relations": []
}
```
### Supported Data Types
* Audio (*audio-prompt*)
* Image (*image-prompt*)
* Text (*NER, text-prompt+asset source*)
* Any Data Type (*text-prompt+text annotation source*)
### Supported Annotation Tools
* Text
* Entity
* Radio
* Checkbox
* Single-Select Dropdown
* Multi-Select Dropdown
## Plugin Configuration
The **Overwrite** setting in model plugins controls whether existing annotations are replaced or kept. When enabled, the plugin replaces all existing annotations with new model predictions; when disabled, it simply adds the new results without deleting what’s already there.
In the **class mapping**, the ChatGPT plugin uses two fields: “Prompt Body” and “Reply Text”.
* **Prompt Body** refers to the text tool from which the main content of the prompt is retrieved.
* **Reply Text** refers to the text tool where the ChatGPT response will be written.
ChatGPT plugin integration to the workflow
You may vary a number of settings related to the model plugin from the **Config JSON** field. Each option is detailed below:
```json
{
"mode": "text-prompt",
"model_name": "gpt-4.1-nano",
"openai_api_key": "",
"prompt_prefix": "",
"prompt_suffix": ""
}
```
* **"mode":** Defines the operating mode of the plugin. The selected mode determines the type of input the plugin processes and the kind of task it performs.
* Options:
* "text-prompt"
* "image-prompt"
* "ner"
* "audio-prompt"
* Example:
* "mode": "text-prompt"
* **"model\_name":** Specifies the OpenAI model that the plugin will use for inference. See the OpenAI [models](https://developers.openai.com/api/docs/models) and [pricing](https://developers.openai.com/api/docs/pricing) pages for available options and details.
* Options:
* "gpt-5.4"
* "gpt-5.4-mini"
* "gpt-5.4-nano"
* "gpt-5.4-pro"
* ...
* Example:
* "model\_name": "gpt-4.1-nano"
* **"openai\_api\_key":** Specifies the OpenAI API key used to authenticate requests sent by the plugin. You can generate and manage your API keys from the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys).
* Example:
* "openai\_api\_key": "\"
* **"prompt\_prefix":** A text string added before the main input content when constructing the prompt sent to the model.
* Example:
* "prompt\_prefix": "Extract all company names from the following text:"
* **"prompt\_suffix":** A text string added after the main input content when constructing the prompt sent to the model.
* Example:
* "prompt\_suffix": "Return the result as a JSON array."
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.imerit.net/plugins/first-party-ango-plugins/chatgpt.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
