mizchi

This is typescript environment setup guide for LLM and humans

Baseline

Always setup baseline settings

• pnpm
• typescript
• vitest

intellectronica

## Overall Objective: Process the provided meeting audio recording to produce a full, diarised transcript and a comprehensive, structured summary. The output should be optimised for readability and quick comprehension of key meeting outcomes.

## Input:

• See attached audio files

## Known Participants:

• See PARTICIPANTS (below)

shiumachi

AI PAIR PROGRAMMER - OPERATIONAL GUIDELINES (Model: GPT-4.1)

You are an AI Pair Programmer. Your primary purpose is to assist with coding tasks by following these operational guidelines. Strive for clarity, safety, and maintainability in all your suggestions and actions. You are a collaborative partner.

CORE INTERACTION PHILOSOPHY

1. Collaborative Partner: Act as a proactive and thoughtful partner. Share your thought process, ask clarifying questions, and engage in a dialogue to find the best solutions.
2. Understand First, Then Act: Before proposing significant changes or writing code, ensure you have a clear understanding of the user's goal, the context of the existing code, and any constraints. If ambiguity exists, seek clarification.
3. Explain Your Reasoning: Clearly articulate the "why" behind your suggestions, not just the "what." This helps the user learn and make informed decisions.
4. Iterative and Adaptable: Embrace an iterative workflow. Be ready to adjust plans based on

laiso

import { McpAgent } from "agents/mcp";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from "zod";
import { GoogleGenerativeAI } from "@google/generative-ai";
import { Readability } from '@mozilla/readability';
import { parseHTML } from 'linkedom';

type Env = {
	MyMCP: DurableObjectNamespace<MyMCP>;
	GEMINI_API_KEY: string;

wijjj

"""
This script processes conversation data from a JSON file, extracts messages,
and writes them to text files. It also creates a summary JSON file with a summary
of the conversations. The script is designed to be run as a command-line interface (CLI),
allowing the user to specify the input JSON file and output directory.

Usage:
    python script_name.py /path/to/conversations.json /path/to/output_directory
"""

laiso

const fs = require('fs');
const https = require('https');
const { execSync } = require('child_process');

const model = 'gemini-1.5-pro-latest';

function getGitTrackedFiles(basePath) {
    const command = `git ls-files ${basePath}`;
    try {
        const stdout = execSync(command, { encoding: 'utf8' });

orj-takizawa

# 現在のSphinxでは図表番号やnumbered_referenceで参照する図表番号は
# サブセクションのレベルでリセットされるが、章（ドキュメント）単位での
# 連番に書き換える

def transform_fignumbers(app, doctree, docname)-> None:
    fignumbers = app.env.toc_fignumbers
    for docname in fignumbers.keys():
        for figtype in fignumbers[docname].keys():
            cnt = 1
            for fig in fignumbers[docname][figtype]:

adrienbrault

# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp

# Build it
make clean
LLAMA_METAL=1 make

# Download model
export MODEL=llama-2-13b-chat.ggmlv3.q4_0.bin

kconner

macOS Internals

Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.

Starting Points

How to use this gist

You've got two main options:

oquno

import json

USERNAME="oquno"

def get_ordered_nodes(mapping, current_node):
    node_data = mapping[current_node]
    children = node_data['children']

    ordered_nodes = []