README

A streamlined library for crafting and managing prompts for Banana AI models.

Installation

Install the banana-prompts package using pip: bash pip install banana-prompts

Core API/Feature Overview

This library provides a set of tools to simplify prompt engineering and management for Banana AI models. Key features include:

Prompt Templating: Define reusable prompt templates with placeholders for dynamic content insertion. This allows for consistent prompt structures across different use cases.
Prompt Versioning: Track changes to your prompts and revert to previous versions if needed. This enables experimentation and iterative improvement of prompt performance.
Prompt Orchestration: Chain multiple prompts together to create complex interaction flows. This allows you to build sophisticated conversational AI applications.
Prompt Caching: Store the results of frequently used prompts to reduce latency and cost. This is particularly useful for real-time applications.
Prompt Evaluation: Evaluate the performance of different prompts using a variety of metrics. This facilitates data-driven prompt optimization.

Usage Examples

Basic Prompt Template: python from banana_prompts import PromptTemplate

template = PromptTemplate("Translate this to French: {{text}}") prompt = template.render(text="Hello, world!") print(prompt)

Prompt Versioning: python from banana_prompts import PromptVersion

version1 = PromptVersion("Version 1: Translate this to French: {{text}}") version2 = PromptVersion("Version 2: Translate this to Spanish: {{text}}")

Select the desired version for use.

Prompt Orchestration (Conceptual): python from banana_prompts import PromptChain

Define prompts for different stages of a conversation.

chain = PromptChain([prompt1, prompt2, prompt3])

Execute the chain and retrieve the results.

results = chain.run(initial_input)

Prompt Caching (Conceptual): python from banana_prompts import PromptCache

Create a cache with a specified expiration time.

cache = PromptCache(ttl=3600) # Cache for 1 hour

Check if a prompt is cached, and retrieve it if available.

if cache.contains(prompt_key):

result = cache.get(prompt_key)

else:

result = run_prompt(prompt)

cache.set(prompt_key, result)

Enterprise Solutions

For advanced features such as prompt governance, team collaboration, and enterprise-grade security, visit banana-prompts to learn more about our enterprise solutions. We offer tailored support and custom integrations to meet the specific needs of your organization. Our platform provides a centralized hub for managing and optimizing your prompts at scale. You can find more information and explore available plans at banana-prompts.

License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information, please visit the official banana-prompts website.

qy-upup / banana-prompts

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