{"id":23272444,"url":"https://github.com/tghurair/agentic-prompting","last_synced_at":"2026-02-04T10:12:23.179Z","repository":{"id":258723673,"uuid":"847337320","full_name":"tghurair/agentic-prompting","owner":"tghurair","description":"Leverage large language models (LLMs) and LLM Agents to craft impactful and effective prompts","archived":false,"fork":false,"pushed_at":"2024-10-11T16:35:11.000Z","size":77,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-08T03:51:07.259Z","etag":null,"topics":["agents","crewai","llms","openai","streamlit"],"latest_commit_sha":null,"homepage":"https://agentic-prompting.streamlit.app/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tghurair.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-08-25T14:41:08.000Z","updated_at":"2024-10-11T16:45:39.000Z","dependencies_parsed_at":"2024-10-20T10:31:15.471Z","dependency_job_id":"8c293c45-06b3-497b-be49-257598f97473","html_url":"https://github.com/tghurair/agentic-prompting","commit_stats":null,"previous_names":["tghurair/agentic-prompting"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/tghurair/agentic-prompting","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tghurair%2Fagentic-prompting","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tghurair%2Fagentic-prompting/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tghurair%2Fagentic-prompting/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tghurair%2Fagentic-prompting/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tghurair","download_url":"https://codeload.github.com/tghurair/agentic-prompting/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tghurair%2Fagentic-prompting/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271425114,"owners_count":24757413,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-21T02:00:08.990Z","response_time":74,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agents","crewai","llms","openai","streamlit"],"created_at":"2024-12-19T19:17:33.117Z","updated_at":"2026-02-04T10:12:18.144Z","avatar_url":"https://github.com/tghurair.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Agentic Prompting: AI Prompt Engineering Assistant\n\nA comprehensive tool designed to help you explore and master various prompt engineering techniques. This project leverages LLMs (Large Language Models) or a LLM agent to optimize and enhance your prompt crafting skills, making it easier to generate effective and context-aware prompts for a wide range of applications.\n\n## Table of Contents\n1. [Features](#features)\n2. [How to Use](#how-to-use)\n3. [Installation](#installation)\n4. [Usage](#usage)\n5. [Tools Used](#tools-used)\n6. [Contributing](#contributing)\n\n## Features\n### 1. Agentic Prompting\nThe Agentic Prompting feature is a sophisticated tool that enhances your prompts through a two-step process:\n\n#### 1. Deep Analysis\nThe AI agent thoroughly analyzes your prompt idea by:\n- Examining the context and intent of your input\n- Assessing the complexity of the task\n- Identifying key elements and requirements\n- Determining the most suitable prompt engineering technique\n\n#### 2. Intelligent Generation\nBased on the analysis, the agent crafts an optimized prompt by:\n- Applying the chosen prompt engineering technique\n- Restructuring and refining the original input\n- Enhancing clarity and specificity\n- Ensuring alignment with the intended goal\n- Providing a detailed explanation of the optimization process\n\nWe utilized CrewAI for agent implementation and orchestration, which was instrumental in the Agentic Prompting feature.\n\n### 2. Prompt Engineering Techniques\nExplore a variety of prompt engineering techniques, including:\n- **General Prompting**: Suitable for open-ended questions and creative tasks.\n- **Zero-Shot Prompting**: Ideal for straightforward tasks without examples.\n- **Few-Shot Prompting**: Provides examples to guide the model for complex tasks.\n- **Include-Exclude Prompting**: Specifies elements to include or exclude in responses.\n- **Chain of Thought (CoT)**: Breaks down complex problems into sequential reasoning steps.\n- **Chain of Thought Reflection**: Incorporates a reflection step for self-correction.\n- **ReAct Prompting**: Combines reasoning and action steps for dynamic interactions.\n\n### 3. Playground\nThe Playground tab allows you to experiment with different prompts and see how AI models respond in real-time. It provides a sandbox environment to test and refine your prompts, enhancing your understanding of AI behavior and response patterns.\n\n## How to Use\n\n1. **Start with the Prompt Engineering Tab**: Learn about different techniques and practice crafting prompts.\n2. **Experiment in the Playground**: Test your prompts with various AI models and refine your skills.\n3. **Leverage Agentic Prompting**: Use this feature for advanced optimization of your prompts.\n4. **Iterate and Refine**: Continuously improve your prompt crafting skills across all tabs.\n\n## Installation\n\nTo get started, clone the repository and install the required dependencies:\n\n```bash\ngit clone https://github.com/your-repo/agentic-prompting.git\ncd agentic-prompting\npip install -r requirements.txt\n```\n\n## Usage\nYou can explore the AI Prompt Engineering Assistant live at [agentic-prompting.streamlit.app](https://agentic-prompting.streamlit.app).\n\nRun the application using locally using Streamlit:\n\nstreamlit run app.py\n\n## Tools Used\n- Streamlit\n- CrewAI\n- OpenAI\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a pull request or open an issue for any bugs or feature requests. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftghurair%2Fagentic-prompting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftghurair%2Fagentic-prompting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftghurair%2Fagentic-prompting/lists"}