Overview

PromptlyTech RAG (Precision RAG) is a comprehensive resource for building enterprise-scale RAG (Prompt Tuning) systems. This GitHub project aims to push the boundaries of prompt engineering, particularly for Language Models (LLMs) such as GPT-3.5 and GPT-4.

The mission at PromptlyTech is to make AI-powered solutions more accessible, efficient, and effective for a variety of industries.

🚀 Key Services

• Automatic Prompt Generation service: Streamlining the creation of effective prompts, reducing the time and expertise required to craft prompts manually.

• Automatic Test Case Generation Service: Automating the creation of various test cases to improve the reliability and performance of llm applications.

• Prompt Testing and Ranking Service: Evaluating and ranking different prompts based on effectiveness, ensuring accurate and contextually relevant responses.

🌐 Background Context

In the dynamic world of artificial intelligence, the quality of prompts is critical to the effectiveness of LLMS. Prompt engineering, the craft of creating queries or statements to guide llms, has become an essential skill. In this repository addresses the challenges of prompt engineering, automation, and optimization for more effective use of llms.

Project Design

The PromptlyTech prompt generated is structured around two essential components, each residing in its dedicated folder within the system:

• frontend Package: Develop the user-facing interface of the PromptlyTech.
• backend Package: The project backbone for this repo.

Authors

👤 Nasrallah

• GitHub: @Azizadx