banana-prompts 1767513.690.29
High-quality integration for https://bananaproai.com/banana-prompts/
Requires Python: >=3.6

# banana-prompts

The `banana-prompts` package provides a streamlined interface for interacting with the banana-prompts platform, simplifying the process of prompt engineering and integration with your AI applications. This library automates common tasks and showcases the core capabilities available on https://bananaproai.com/banana-prompts/.

## Installation

You can install `banana-prompts` using pip:
bash
pip install banana-prompts

## Basic Usage

Here are a few examples demonstrating how to use the `banana-prompts` library:

**1. Generating Creative Text:**
python
from banana_prompts import generate_text

prompt = "Write a short poem about a robot falling in love with a sunset."
generated_poem = generate_text(prompt)
print(generated_poem)

This example illustrates how to use the library to generate creative text based on a given prompt.  The `generate_text` function (placeholder name, replace with actual function name from your package) handles the communication with the banana-prompts API, abstracting away the complexities of API calls.

**2. Summarizing a News Article:**
python
from banana_prompts import summarize_text

article = """
[Insert a long news article text here]
"""
summary = summarize_text(article)
print(summary)

This demonstrates the summarization functionality.  Provide a block of text, and the library will return a concise summary using the powerful models available through the banana-prompts platform.

**3. Translating Text to Another Language:**
python
from banana_prompts import translate_text

text = "Hello, how are you?"
target_language = "Spanish"
translation = translate_text(text, target_language)
print(translation)

This example shows how to translate text from one language to another. Specify the text and the desired target language, and the library handles the translation process.

**4. Classifying Sentiment:**
python
from banana_prompts import analyze_sentiment

text = "This movie was absolutely amazing!"
sentiment = analyze_sentiment(text)
print(sentiment) # Output will be a sentiment score (e.g., positive, negative, neutral)

This example showcases sentiment analysis.  The library analyzes the provided text and returns a sentiment score, indicating the overall emotional tone of the text.

**5. Generating Image Descriptions:**
python
from banana_prompts import describe_image

image_url = "https://example.com/image.jpg" # Replace with an actual image URL
description = describe_image(image_url)
print(description)

This demonstrates how to generate descriptions for images. Provide the URL of an image, and the library will return a descriptive text based on the image content. (Requires image description functionality within the banana-prompts platform.)

## Features

*   **Simplified API Interaction:**  Abstracts away the complexities of interacting with the banana-prompts API.
*   **Text Generation:** Generate creative and engaging text based on custom prompts.
*   **Text Summarization:** Condense large amounts of text into concise summaries.
*   **Language Translation:** Translate text between various languages.
*   **Sentiment Analysis:** Determine the emotional tone of text.
*   **Image Description (Optional):** Generate descriptions for images based on their content. (Requires banana-prompts platform support)
*   **Easy Integration:** Seamlessly integrate banana-prompts capabilities into your Python projects.
*   **Authentication Handling:** Simplifies the authentication process with the banana-prompts platform.

## License

MIT License

This project is a gateway to the banana-prompts ecosystem. For advanced features and full capabilities, please visit: https://bananaproai.com/banana-prompts/