Prompt_Engineering_using_Precision_RAG and Prompt-Engineering-GPT-Assistants-API-using-RAG

Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 12/25
Maintenance 0/25
Adoption 4/25
Maturity 8/25
Community 13/25
Stars: 3
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 5
Forks: 2
Downloads:
Commits (30d): 0
Language: Python
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About Prompt_Engineering_using_Precision_RAG

GetachewAbebe/Prompt_Engineering_using_Precision_RAG

This project aims to develop an enterprise-grade Retrieval-Augmented Generation (RAG) system by automating the prompt engineering process. The goal is to create a comprehensive solution that simplifies the task of crafting effective prompts for Language Models (LLMs), enabling businesses to leverage advanced AI capabilities more efficiently.

About Prompt-Engineering-GPT-Assistants-API-using-RAG

GvHemanth/Prompt-Engineering-GPT-Assistants-API-using-RAG

This project showcases the implementation of a prompt engineering using the OpenAI Assistant API, specifically leveraging the Retrieval-Augmented Generation (RAG) system. By integrating cutting-edge language models, the system demonstrates advanced natural language understanding and generation capabilities.

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