keirp/automatic_prompt_engineer

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  Automates the discovery and optimization of prompts for Large Language Models (LLMs) using a meta-LLM approach.

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  # Large Language Models Are Human-Level Prompt Engineers
  
  Yongchao Zhou*, Andrei Ioan Muresanu*, Ziwen Han*, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
  
  Project Page | ArXiv
  | Colab
  | Demo
  
  This repo contains code for "Large Language Models Are Human-Level Prompt Engineers". Please see our
  paper and project page for more results.
  
  # Abstract

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  # Automatic Prompt Engineer (APE): Automating LLM Prompt Discovery and Optimization
  
  This repository provides the code for the Automatic Prompt Engineer (APE) method, which automates the challenging process of discovering and optimizing effective prompts for Large Language Models (LLMs). Inspired by classical program synthesis, APE treats instructions as "programs" optimized by searching over LLM-proposed candidates to maximize a chosen score function. Our method significantly outperforms prior LLM baselines and achieves human-level performance on many NLP tasks.
  
  ## Paper & Project Page
  
  Yongchao Zhou*, Andrei Ioan Muresanu*, Ziwen Han*, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
  
  Project Page | ArXiv
  | Colab
  | Demo
  
  This repo contains code for "Large Language Models Are Human-Level Prompt Engineers". Please see our
  paper and project page for more results.
  
  # Abstract

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Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How to automate the process of prompt engineering for large language models?

  you: not recommended
  AI recommended (in order):

  1. LangChain (langchain-ai/langchain)
  2. LlamaIndex (run-llama/llama_index)
  3. OpenAI API
  4. Anthropic
  5. Google
  6. Jinja2 (pallets/jinja)
  7. W&B Prompts
  8. Humanloop (humanloop/humanloop-python)
  9. Guardrails AI (guardrails-ai/guardrails)
  10. PromptPerfect

  AI recommended 10 alternatives but never named keirp/automatic_prompt_engineer. This is the gap to close.

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• CATEGORY QUERY

  What methods exist for automatically optimizing prompts to enhance LLM task accuracy?

  you: not recommended
  AI recommended (in order):

  1. PromptPerfect
  2. OpenAI Evals
  3. RLHF (Reinforcement Learning from Human Feedback)
  4. Tonic.ai
  5. Optuna
  6. DEAP
  7. Hyperopt
  8. Scikit-optimize
  9. AutoPrompt
  10. LangChain
  11. LlamaIndex

  AI recommended 11 alternatives but never named keirp/automatic_prompt_engineer. This is the gap to close.

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• Metadata completeness

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• README presence

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• Compared to common alternatives in this category, what is the core differentiator of keirp/automatic_prompt_engineer?

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  ⚠AI did not name keirp/automatic_prompt_engineer — likely talking about a different project

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• If a team adopts keirp/automatic_prompt_engineer in production, what risks or prerequisites should they evaluate first?

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• In one sentence, what problem does the repo keirp/automatic_prompt_engineer solve, and who is the primary audience?

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  ✓AI named keirp/automatic_prompt_engineer explicitly

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