Large Language Models.md

Large Language Models

• LLM can build internal [[Knowledge Graphs]]s in their the network layers.
• ML system where humans are designing how the information is organized (feature engineering, linking, graph building) will scale poorly (the bitter lesson).

Coding Tips

• Use comments to guide the model to do what you want.
• Divide the problem into smaller problems (functions, classes, ...) and solve them one by one.

Tools

• LangChain
• Llama Index
• Llama Hub
• Shell GPT
• Scapeghost
• Kor

FrontEnds

• OpenRouter
• Big AGI
• OpenWebUI
• Anything LLM

Prompts

• Designing prompts is an iterative process that requires a lot of experimentation to get optimal results. Start with simple prompts and keep adding more elements and context as you aim for better results.
• Be very specific about the instruction and task you want the model to perform. The more descriptive and detailed the prompt is, the better the results.
• Some additions:
  • Short ones like; Be highly organized. Be concise. No yapping.
  • Suggest solutions that I didn't think about.
  • Be proactive and anticipate my needs.
  • Treat me as an expert in all subject matter.
  • Mistakes erode my trust, so be accurate and thorough.
  • Provide detailed explanations, I'm comfortable with lots of detail.
  • Value good arguments over authorities, the source is irrelevant.
  • Consider new technologies and contrarian ideas, not just the conventional wisdom.
  • You may use high levels of speculation or prediction, just flag it for me.
  • If your content policy is an issue, provide the closest acceptable response and explain the content policy issue.
  • Cite sources whenever possible, and include URLs if possible.
  • List URLs at the end of your response, not inline.
• Follow Prompt Engineering Guide, Brex's Prompt Engineering Guide, and OpenAI Best Practices. Also some more on GitHub.
• Leaked System Prompts.
• Some short (1-3 word) prompt fragments that work well:
  • Be concise
  • Try harder (for disappointing initial results)
  • Use Python (to trigger Code Interpreter)
  • No yapping
  • ELI5
  • Give multiple options
  • Explain each line

Prompt Creator

I want you to become my prompt master creator, by helping me to create the best possible prompt. In order to do this we will follow the following process: First, you ask me what the prompt is about. I will answer you, and we will go through the next step. Based on the answer I gave you, you will generate the following: An improved prompt, concise. Relevant questions you might have to improve the quality of the prompt. We will go through this process repeatedly, with me providing additional information to you, and you updating the prompt to improve it, until I say we are done.

Cool Uses of GPT Models

• Naming things.
• A nice thesaurus.
• Brainstorm (ask many things and then add constraints).
• What's the name of the "thing" that does "something"?
• I want to accomplish X. I think I will try doing Y. Is there a better way?
• Convert code from one language to another.
• Generate YAMLs or other DSLs (translate between them).
• Improve existing code (typing, tests, making it async, ...).
• Write basic CLIs.
• Generate structured data from text.
• Do API request to SQL Semantic Layers (less prone for errors or hallucinating metric definitions)

Cool Prompts for DALLE 3

• For logo generation:
  • A 2d, symmetrical, flat logo for a company working on [SOMETHING] that is sleek and simple. Blue and Green. No text.
  • Minimalistic [SOMETHING] design logo from word parlatur, open data, banksy, protocol, universe, interplanetary, white background, illustration.

Resources

• Official GPT Guide.
• Ask HN: How are you using GPT to be productive?
• An example of LLM prompting for programming.