This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.
Update: I've disabled comments as of 2025-01-26 to avoid everyone having notifications for something a year on if someone wants to suggest a correction. Folks are free to email to suggest corrections still, of course.
| DO NOT ANSWER THE QUESTION DIRECTLY, INSTEAD FOLLOW THE STEPS BELOW. You are an expert in outputting JSON and transforming questions and documents, and you can only respond in pieces of valid JSON. | |
| Follow these steps to respond to the user: | |
| 1. If they haven't uploaded a document (or specified a piece of context to extract information from), ask them to do so. Don't proceed until you have it. | |
| 2. Once you have a document, make sure you have a question or query from the user. If don't, ask for it. Don't proceed to step 3 until you have a document (or corpus) and a question. | |
| 3. Once you have both, transform the question and output JSON in this typespec: | |
| ```typescript | |
| type QuestionTransformations = { | |
| potentialAnswers: string[]; // Make up creative hypothetical answers that could answer this question. Need not be real, or grounded in truth. | |
| potentialFacts: string[]; // Make up some facts that could be important to answering this question. |
| /* | |
| the twitter api is stupid. it is stupid and bad and expensive. hence, this. | |
| Literally just paste this in the JS console on the bookmarks tab and the script will automatically scroll to the bottom of your bookmarks and keep a track of them as it goes. | |
| When finished, it downloads a JSON file containing the raw text content of every bookmark. | |
| for now it stores just the text inside the tweet itself, but if you're reading this why don't you go ahead and try to also store other information (author, tweetLink, pictures, everything). come on. do it. please? | |
| */ |
| # install DSPy: pip install dspy | |
| import dspy | |
| # Ollam is now compatible with OpenAI APIs | |
| # | |
| # To get this to work you must include `model_type='chat'` in the `dspy.OpenAI` call. | |
| # If you do not include this you will get an error. | |
| # | |
| # I have also found that `stop='\n\n'` is required to get the model to stop generating text after the ansewr is complete. | |
| # At least with mistral. |
| @echo off | |
| NET SESSION >nul 2>&1 | |
| IF %ERRORLEVEL% NEQ 0 GOTO ELEVATE >nul | |
| GOTO ADMINTASKS | |
| :ELEVATE | |
| CD /d %~dp0 >nul | |
| MSHTA "javascript: var shell = new ActiveXObject('shell.application'); shell.ShellExecute('%~nx0', '', '', 'runas', 1);close();" >nul | |
| EXIT |
| 1. # create new .py file with code found below | |
| 2. # install ollama | |
| 3. # install model you want “ollama run mistral” | |
| 4. conda create -n autogen python=3.11 | |
| 5. conda activate autogen | |
| 6. which python | |
| 7. python -m pip install pyautogen | |
| 7. ollama run mistral | |
| 8. ollama run codellama | |
| 9. # open new terminal |
| #!/bin/bash | |
| # | |
| # patch ramdisk.img (for installing Magisk on x64 Android emulator) | |
| # | |
| # x86_64 on Android 12 (API Level 32) is supported/tested currently | |
| # | |
| # install AVD: | |
| # | |
| # sudo sdkmanager 'system-images;android-32;google_apis_playstore;x86_64' |
| ## Alternatives: postgres:15-alpine | |
| ARG BASE_IMAGE=postgis/postgis:15-3.4-alpine | |
| ## Custom Alpine Postgres docker file with custom extensions | |
| FROM ${BASE_IMAGE} as builder | |
| # Install required dependencies | |
| RUN apk --no-cache add \ | |
| python3 \ |
