LLM Prompt Engineering & Optimization
10 repos
Tools and frameworks for engineering, testing, and optimizing prompts for large language models. This cluster covers prompt composition, evaluation, structured output generation (JSON/regex), and systematic prompt tuning across different LLM providers. The repositories range from prompt testing platforms and parameter optimization frameworks to domain-specific applications like insurance underwriting, reflecting a shared focus on making LLM outputs more reliable and controllable.
Python · 5
Jupyter Notebook · 3
C++ · 1
generative-ai ·50,824
prompt-engineering ·50,019
llms ·48,187
symbolic-ai ·47,340
structured-generation ·47,340
cfg ·47,340
json ·47,340
regex ·47,340
llm ·3,335
fine-tuning ·2,946
