API Documentation Generator

API Documentation: PantheraAI Services API

Description: Test run

Topic: AI Technology

Execution Time: 5 min

1. Introduction and Overview

Welcome to the PantheraAI Services API documentation! This API provides a suite of advanced artificial intelligence capabilities, enabling developers to integrate powerful AI models into their applications. Our services currently include state-of-the-art Text Generation, Image Analysis, and Sentiment Analysis.

This documentation will guide you through authenticating with the API, understanding available endpoints, crafting requests, interpreting responses, and handling potential errors.

Key Features:

Text Generation: Generate human-like text based on a given prompt.
Image Analysis: Extract insights from images, such as labels, objects, and facial features.
Sentiment Analysis: Determine the emotional tone (positive, negative, neutral) of text.

Target Audience: Developers, data scientists, and product managers looking to integrate AI functionalities into their platforms.

2. Authentication

All requests to the PantheraAI Services API must be authenticated using an API Key. Your API Key acts as a secure credential that grants access to our services.

2.1. Obtaining Your API Key

Log in to your PantheraHive developer dashboard.
Navigate to the "API Keys" section.
Generate a new API Key if you don't have one, or use an existing one.
Important: Keep your API Key confidential. Do not expose it in client-side code or public repositories.

2.2. Authentication Method

Include your API Key in the Authorization header of every request, using the Bearer scheme.

Header Example:

**Error (HTTP 4xx/5xx):** See [Error Handling](#5-error-handling).

---

### 4.2. Image Analysis

Analyzes an image to extract features like labels, objects, and textual content.

*   **Endpoint:** `/image/analyze`
*   **Method:** `POST`

#### Request

**Headers:**
*   `Content-Type: application/json`
*   `Authorization: Bearer YOUR_API_KEY`

**Body Parameters (JSON):**

| Parameter       | Type     | Required | Description                                                                   | Example                                    |
| :-------------- | :------- | :------- | :---------------------------------------------------------------------------- | :----------------------------------------- |
| `image_url`     | `string` | Yes (or `image_base64`) | Publicly accessible URL of the image to analyze.                              | `"https://example.com/cat.jpg"`            |
| `image_base64`  | `string` | Yes (or `image_url`) | Base64 encoded string of the image. Max size: 5MB.                            | `"data:image/jpeg;base64,/9j/4AAQ..."`     |
| `features`      | `array`  | No       | List of features to extract. Default: `["labels"]`. Available: `["labels", "objects", "text", "faces"]` | `["labels", "objects"]`                    |

**Example Request (Curl with URL):**

Sandboxed live preview

7. Rate Limiting

To ensure fair usage and maintain API stability, requests are subject to rate limits.

Default Limit: 100 requests per minute per API Key.
Headers:

* X-RateLimit-Limit: The total number of requests allowed in the current window.

* X-RateLimit-Remaining: The number of requests remaining in the current window.

* X-RateLimit-Reset: The time (in UTC epoch seconds) when the current window resets.

If you exceed the rate limit, you will receive a 429 Too Many Requests HTTP status code. Implement retry logic with exponential backoff to handle rate limits gracefully.

8. Versioning

The PantheraAI Services API uses URI versioning. The current version is v1. Future breaking changes will be introduced under a new version (e.g., /v2). Non-breaking changes will be deployed to the existing v1 endpoint.

9. Support and Feedback

If you encounter any issues, have questions, or would like to provide feedback, please reach out to our support team:

Support Portal: [https://support.pantherahive.ai](https://support.pantherahive.ai)
Email: support@pantherahive.ai
Developer Forum: [https://community.pantherahive.ai/developers](https://community.pantherahive.ai/developers)

Actionable Details and Recommendations for the User

Start with Authentication: Ensure your API Key is correctly configured as an environment variable or securely managed in your application before making any requests.
Experiment with Endpoints: Use the provided curl examples to quickly test each endpoint and understand its basic functionality.
Implement Error Handling: Always wrap your API calls in try-except blocks (or equivalent) and handle expected HTTP error codes (e.g., 400, 401, 403, 429) to make your application robust.
Consider SDKs: For production applications, leverage official or community-supported SDKs (like the Python example) to abstract away HTTP complexities and improve development speed.
Monitor Usage: Keep an eye on your API usage metrics in the PantheraHive developer dashboard to prevent unexpected billing or rate limit issues.
Provide Contextual Prompts for AI: For text generation and sentiment analysis, the quality of your input (prompts, text) directly impacts the quality of the AI's output. Experiment with different inputs.
Optimize Image Analysis Features: Request only the features you need for image analysis to optimize response time and potentially reduce processing costs.
Stay Updated: Regularly check the PantheraHive developer blog or changelog for updates, new features, and deprecation notices.

This comprehensive documentation should enable developers to quickly and effectively integrate PantheraAI Services into their applications.

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