{"data":{"slug":"nirdiamant-prompt-engineering","name":"Prompt_Engineering","tagline":"Hands-on Jupyter Notebook tutorials for prompt engineering with LLMs","github_url":"https://github.com/NirDiamant/Prompt_Engineering","owner":"NirDiamant","repo":"Prompt_Engineering","owner_avatar_url":"https://avatars.githubusercontent.com/u/28316913?v=4","primary_language":"Jupyter Notebook","stars":7859,"forks":1027,"topics":["ai","chain-of-thought","chatgpt","claude","few-shot-learning","genai","generative-ai","gpt","in-context-learning","langchain","llm","llms","machine-learning","openai","prompt-engineering","prompting","python","tutorials"],"archived":false,"github_pushed_at":"2026-09-19T02:18:01+00:00","maintenance_label":"Very active","stars_delta_30d":156,"url":"https://www.graphcanon.com/tools/nirdiamant-prompt-engineering","markdown_url":"https://www.graphcanon.com/tools/nirdiamant-prompt-engineering.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nirdiamant-prompt-engineering","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nirdiamant-prompt-engineering","description":"22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.","homepage_url":"https://diamant-ai.com","license":"Other","open_issues":9,"watchers":88,"ai_summary":"This repository offers practical instructions and examples through Jupyter Notebooks to master various prompt engineering techniques designed for advanced utilization of Language Learning Models.","readme_excerpt":"## Getting Started\n\nTo begin exploring and implementing prompt engineering techniques:\n\n1. Clone this repository:\n   ```\n   git clone https://github.com/NirDiamant/Prompt_Engineering.git\n   ```\n2. Navigate to the technique you're interested in:\n   ```\n   cd all_prompt_engineering_techniques\n   ```\n3. Follow the detailed implementation guide in each technique's notebook.\n\n---\n\n## License\n\nThis project is licensed under a custom non-commercial license - see the [LICENSE](LICENSE) file for details.\n\n---\n\n⭐️ If you find this repository helpful, please consider giving it a star!\n\nKeywords: Prompt Engineering, AI, Machine Learning, Natural Language Processing, LLM, Language Models, NLP, Conversational AI, Zero-Shot Learning, Few-Shot Learning, Chain of Thought","github_created_at":"2024-10-10T08:52:12+00:00","created_at":"2026-07-11T11:56:36.470129+00:00","updated_at":"2026-09-20T06:50:11.110515+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"chain-of-thought","name":"chain-of-thought"},{"slug":"chatgpt","name":"chatgpt"},{"slug":"claude","name":"claude"},{"slug":"few-shot-learning","name":"few-shot-learning"},{"slug":"genai","name":"genai"},{"slug":"generative-ai","name":"generative-ai"},{"slug":"gpt","name":"gpt"}],"trust":{"provenance":{"is_fork":false,"github_id":870554327,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T06:50:09.504Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1,"last_release_at":null,"stars_delta_30d":156,"open_issues_delta_30d":5},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:56:37.610Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T06:50:10.525Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-09-20T06:50:10.525Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-09-20T06:50:10.525Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need practical, step-by-step guidance in Jupyter Notebooks to understand and implement prompt engineering techniques with LLMs.","For developers looking to improve their proficiency specifically with the Chain-of-Thought technique or other nuanced strategies outlined in the detailed tutorials."],"when_not_to_use":["If you prefer interactive tooling over manual notebook work, as the repository is heavily based on self-guided Jupyter Notebook exercises.","This repository may not be suitable if you are focused exclusively on specific LLM frameworks like Hugging Face Transformers or SpaCy that it does not emphasize."],"source":"enrich:decision_facts","observed_at":"2026-07-17T13:30:26.959Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"The Prompt_Engineering repository provides hands-on Jupyter Notebook tutorials that guide users through 22 prompt engineering techniques for advanced use of Language Learning Models."}]}}