mba-ia-prompt-engineering
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파일 탐색기
최종 버전 다운로드 (.zip)- .env.example
- 0-Role-prompting.py
- 1-zero-shot.py
- 2-one-few-shot.py
- 3-CoT.py
- 3.1-CoT-Self-consistency.py
- 4-ToT.py
- 5-SoT.py
- 6-ReAct.py
- 7-Prompt-channing.py
- 8-Least-to-most.py
- AGENTS.md
- requirements.txt
- utils.py
- architectural-analyzer.md
- component-deep-analyzer.md
- dependency-auditor.md
- orchestrator.md
- run-project-state-full-report.md
- AGENTS.md
- prompt.tests.yaml
- prompt.yaml
- README.md
- prompt.tests.yaml
- prompt.yaml
- prompt.tests.yaml
- prompt.yaml
- README.md
- registry.yaml
- __init__.py
- agent_code_reviewer.py
- agent_pull_request.py
- langsmith_client.py
- langsmith_push.py
- prompt_registry.py
- test_prompts.py
- .env.example
- AGENTS.md
- README.md
- requirements.txt
- .env.example
- .gitignore
- 0-No-expansion.py
- 1-ITER_RETGEN.py
- 2-query-enrichment.py
- AGENTS.md
- requirements.txt
- additional_criteria.yaml
- bad_hallucination.yaml
- bad_not_helpful.yaml
- bad_text_before.yaml
- bad_verbose.yaml
- correctness_eval.yaml
- criteria_eval.yaml
- embedding_distance_eval.yaml
- format_eval.yaml
- 1-format-eval.py
- 10-bad-not-helpful.py
- 2-criteria-binary-eval.py
- 3-criteria-score-eval.py
- 4-correctness-eval.py
- 5-additional-criteria.py
- 6-embedding-distance-eval.py
- 7-bad-text-before.py
- 8-bad-verbose.py
- 9-bad-hallucination.py
- dataset.jsonl
- README.md
- requirements.txt
- reset.py
- upload_dataset.py
- aggressive.yaml
- balanced.yaml
- conservative.yaml
- 1-conservative-high-precision.py
- 2-aggressive-high-recall.py
- 3-balanced-best-f1.py
- dataset.jsonl
- metrics.py
- README.md
- reset.py
- upload_dataset.py
- pairwise_judge.yaml
- performance_expert.yaml
- security_expert_v1.yaml
- security_expert_v2.yaml
- create_prompts.py
- dataset.jsonl
- pairwise_helpers.py
- README.md
- reset.py
- run.py
- update_prompt_v2.py
- upload_dataset.py
- llm_judge_pairwise.yaml
- prompt_doc_a.yaml
- prompt_doc_b.yaml
- create_prompt.py
- dataset.jsonl
- doc_evaluators.py
- pairwise_helpers.py
- README.md
- reset.py
- run.py
- upload_dataset.py
- 0-only-traces.yaml
- 1-correctness-langfuse.yaml
- llm_judge_pairwise.yaml
- prompt_doc_a.yaml
- prompt_doc_b.yaml
- 0-only-traces.py
- 1-correctness-langfuse.py
- create_prompts.py
- dataset.jsonl
- dataset2.jsonl
- langfuse_helpers.py
- load_prompts.py
- README.md
- requirements.txt
- run.py
- upload_dataset.py
- __init__.py
- clients.py
- datasets.py
- evaluators.py
- parsers.py
- prompts.py
- .env.example
- AGENTS.md
- README.md
- requirements.txt
- .gitignore
- AGENTS.md
- README.md
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/devfullcycle/mba-ia-prompt-engineering
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd mba-ia-prompt-engineering
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Python
쉬움 추천사전 준비물
python -m venv venv
파이썬 스크립트(또는 모듈)를 실행합니다.
pip install -r requirements.txt
requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
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