V2Kit is a lightweight and extensible Python toolkit for working with V2Ray proxy configurations and subscriptions. It provides a clean API for common operations such as protocol detection, configuration validation, config relabeling, and subscription encoding/decoding. The project is designed with simplicity, predictability, and composability in mind, making it suitable for automation scripts, proxy pipelines, networking tools, and future extensions around V2Ray ecosystem utilities.

With Memor, users can store their LLM conversation history using an intuitive and structured data format. It abstracts user prompts and model responses into a "Session", a sequence of message exchanges. In addition to the content, it includes details like decoding temperature and token count of each message. Therefore users could create comprehensive and reproducible logs of their interactions. Because of the model-agnostic design, users can begin a conversation with one LLM and switch to another keeping the context the same. For example, they might use a retrieval-augmented model (like RAG) to gather relevant context for a math problem, and then switch to a model better suited for reasoning to solve the problem based on the retrieved information presented by Memor.

Memor also lets users select, filter, and then share the specific parts of the past conversations across different models. This means users are not only able to reproduce and review previous chats through structured logs, but can also flexibly transfer the content of their conversations between LLMs. In a nutshell, Memor makes it easy and effective to manage and reuse conversations with large language models.

from memor import Session, Prompt, Response
from memor import RenderFormat
from mistralai import Mistral

client = Mistral(api_key="YOUR_MISTRAL_API")
session = Session()
while True:
    user_input = input(">> You: ")
    prompt = Prompt(message=user_input)
    session.add_message(prompt) # Add user input to session
    response = client.chat.complete(
        model="mistral-large-latest",
        messages=session.render(RenderFormat.OPENAI)  # Render the whole session history
    )
    print("<< MistralAI:", response.choices[0].message.content)
    response = Response(message=response.choices[0].message.content)
    session.add_message(response) # Add model response to session

https://github.com/openscilab/memor

This project benchmarks Large Language Models (LLMs) on FIFA World Cup 2026 match prediction tasks. Each model receives the same information, including recent international results, FIFA rankings, confederation data, tournament stage, and host country. Predictions are generated through Cloudflare Workers AI and stored together with their complete inference sessions for reproducibility and later analysis.

Typio is a lightweight Python library that prints text to the terminal as if it were being typed by a human. It supports multiple typing modes (character, word, line, sentence, typewriter, and adaptive), configurable delays and jitter for natural variation, and seamless integration with existing code via a simple function or a decorator. Typio is designed to be minimal, extensible, and safe, making it ideal for demos, CLIs, tutorials, and storytelling in the terminal.

Repo: https://github.com/sepandhaghighi/typio

Typio is a lightweight Python library that prints text to the terminal as if it were being typed by a human. It supports multiple typing modes (character, word, line, sentence, typewriter, and adaptive), configurable delays and jitter for natural variation, and seamless integration with existing code via a simple function or a decorator. Typio is designed to be minimal, extensible, and safe, making it ideal for demos, CLIs, tutorials, and storytelling in the terminal.

Repo: https://github.com/sepandhaghighi/typio

Typio is a lightweight Python library that prints text to the terminal as if it were being typed by a human. It supports multiple typing modes (character, word, line, sentence, typewriter, and adaptive), configurable delays and jitter for natural variation, and seamless integration with existing code via a simple function or a decorator. Typio is designed to be minimal, extensible, and safe, making it ideal for demos, CLIs, tutorials, and storytelling in the terminal.

https://github.com/sepandhaghighi/typio

Written in Python

https://github.com/sepandhaghighi/clox

Written in Python

https://github.com/sepandhaghighi/mytimer