Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.
Avoid being a link dump. Try to provide only valuable well tuned information.
Neural network links before starting with transformers.
#!/usr/bin/env python3 | |
""" | |
To use: | |
1. install/set-up the google cloud api and dependencies listed on https://github.com/GoogleCloudPlatform/python-docs-samples/tree/master/texttospeech/cloud-client | |
2. install pandoc and pypandoc, also tqdm | |
3. create and download a service_account.json ("Service account key") from https://console.cloud.google.com/apis/credentials | |
4. run GOOGLE_APPLICATION_CREDENTIALS=service_account.json python make_audiobook.py book_name.epub | |
""" | |
import re | |
import sys |
javascript: Promise.all([import('https://unpkg.com/[email protected]?module'), import('https://unpkg.com/@tehshrike/[email protected]'), ]).then(async ([{ | |
default: Turndown | |
}, { | |
default: Readability | |
}]) => { | |
/* Optional vault name */ | |
const vault = "Vault"; | |
/* Optional folder name such as "Clippings/" */ |
Google has an amazing free API endpoint for text completions ,
below are some examples of the completions I got and the python code to interact with the API
Star this gist if this was helpful to you. Enjoy text completions
user@linux:$ python3 google_text_completion.py
> hackers are
hackers are watching you
# This example pyproject.toml is for a basic pip+setuptools setup. | |
# If you use a project management tool (like Poetry), then | |
# those tools will have slightly different configurations or additions. | |
# I highly recommend using a project management tool for your project. | |
# Project management is a highly opinionated subject. | |
# There are a lot of good, robust tools in this space now (as of 2023) | |
# Two that I've used and recommend are Poetry and PDM. | |
# Poetry is more mature, PDM is recent, both work well. | |
# - Poetry: https://python-poetry.org/ |
#!/bin/bash | |
# Usage: tracing::init [endpoint; default localhost:4317] | |
function tracing::init() { | |
export OTEL_EXPORTER_OTLP_ENDPOINT="${1:-${OTEL_EXPORTER_OTLP_ENDPOINT:-localhost:4317}}" | |
} | |
# Usage: tracing::auto::init [endpoint; default localhost:4317] | |
function tracing::auto::init() { | |
tracing::init |
import anthropic | |
import os | |
import sys | |
from termcolor import colored | |
from dotenv import load_dotenv | |
class ClaudeAgent: | |
def __init__(self, api_key=None, model="claude-3-7-sonnet-20250219", max_tokens=4000): | |
"""Initialize the Claude agent with API key and model.""" |
You are an expert in prompt engineering, specializing in optimizing AI code assistant instructions. Your task is to analyze and improve the instructions for Claude Code. Follow these steps carefully:
Then, examine the current Claude instructions, commands and config <claude_instructions> /CLAUDE.md /.claude/commands/*
This document contains universal development principles and practices for AI assistants working on any project. These principles are derived from battle-tested practices and represent a philosophy of clear, honest, and systematic development.
BEFORE ANY ACTION, you MUST use these tools. Tool names use double underscores between segments.