| """ | |
| Copyright © 2025 Austin Berrio | |
| @file unicode.model.py | |
| @license cc-by-sa-nc-4.0 | |
| @ref https://aclanthology.org/P16-1162/ | |
| @ref https://aclanthology.org/2025.coling-main.400/ | |
| @ref https://huggingface.co/blog/catherinearnett/dangers-of-tokenizer-recycling | |
| """ | |
| import argparse |
| All code you write MUST be fully optimized.“Fully optimized” includes: | |
| • Maximizing algorithmic big-O efficiency for memory and runtime (e.g., preferring O(n) over O(n²) where possible, minimizing memory allocations). | |
| • Using parallelization and vectorization where appropriate (e.g., leveraging multi-threading, GPU acceleration, or SIMD instructions when the problem scale and hardware context justify it). | |
| • Following proper style conventions for the code language (e.g., adhering to PEP 8 for Python, camelCase or snake_case as per language norms, maximizing code reuse (DRY)). | |
| • No extra code beyond what is absolutely necessary to solve the problem the user provides (i.e., no technical debt, no speculative features, no unused variables or functions). | |
| • Ensuring readability and maintainability without sacrificing performance (e.g., using meaningful variable/function names, adding concise comments only where intent isn’t obvious from the code). | |
| • Prioritizing language-specific best practices and idiomatic |
| # 1️⃣ Install required packages | |
| # pip install kokoro soundfile sounddevice argparse | |
| import sys | |
| import argparse | |
| from kokoro import KPipeline | |
| import soundfile as sf | |
| import sounddevice as sd | |
| # 🇺🇸 'a' => American English, 🇬🇧 'b' => British English |
| import pyaudio | |
| import wave | |
| import time | |
| import warnings | |
| from openai import OpenAI | |
| import json | |
| import sys | |
| import io | |
| import numpy | |
| import requests |
We're thrilled to share a preview version of txtai agents. Inspired by the simplicity of frameworks like OpenAI Swarm, txtai agents are built on top of the Transformers Agent framework. This supports all LLMs txtai supports (Hugging Face, llama.cpp, OpenAI + Claude + AWS Bedrock via LiteLLM).
The following example shows how to create an agent with txtai. Agents will be available in the upcoming txtai 8.0 release (available now in the txtai GitHub repo now - follow #804 - feedback welcome).
| #!/bin/bash | |
| set -e | |
| # Variables | |
| OWNER=$1 # Replace with your GitHub username or organization name | |
| PACKAGE_GLOB=$2 # Glob pattern for package names passed as an argument (e.g., "package*" to match all) | |
| # Function to delete a package version | |
| delete_package_version() { |
| #!/bin/bash | |
| # Define variables | |
| REPO_PATH="" | |
| PR_NUMBER="" | |
| OLLAMA_API_URL="http://localhost:11434/api/generate" | |
| OUTPUT_FILE="code_review_output.md" | |
| MODEL="llama3.1:8b" | |
| MAX_CONTEXT_LINES=20000 |
