Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models
Nadir is a Python package designed to dynamically choose the best llm for your prompt by balancing complexity and cost and response time.
Visualize LLM outputs against datasets, manually annotate results, and run automated evaluations to algorithmically optimize prompts.
📝 Discover and use powerful prompts for LLMs to enhance your AI interactions and boost productivity in coding and creative tasks.
LLM-optimized MCP server for Datadog APM, logs, and metrics. Delivers structured, token-efficient trace and log insights designed specifically for AI-driven debugging—not just raw Datadog data.
Fit any LLM under a memory budget — an optimizer/planner that picks per-layer quantization, KV-cache precision, context length and GPU/CPU/disk offload to run large language models locally, then emits ready-to-run llama.cpp / HuggingFace / Ollama commands.
Python tool to convert Markdown files into a compact, LLM-friendly format. It reduces token usage by simplifying Markdown syntax, converting tables to JSON, and removing unnecessary formatting.
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