plz-cli
lmql
| plz-cli | lmql | |
|---|---|---|
| 5 | 30 | |
| 1,576 | 3,438 | |
| - | 3.4% | |
| 4.5 | 9.3 | |
| 5 months ago | 14 days ago | |
| Rust | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
plz-cli
- Ask HN: I want to learn to use the terminal, where do I start
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Show HN: Think, CL tool that makes AI your command line copilot (written in Go)
A friend just mentioned to me https://github.com/m1guelpf/plz-cli (whose tagline I unknowingly reproduced). The difference is that with think you are able to keep the conversation going, which allows you to easily ask for followup tasks.
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Ask HN: What's your favorite GPT powered tool?
Ones that actually save me a lot of time I would otherwise spend googling:
plz-cli, a terminal copilot, https://github.com/m1guelpf/plz-cli
Code GPT, a Visual Studio Code copilot, https://marketplace.visualstudio.com/items?itemName=DanielSa...
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aicmd - A CLI copilot that helps you write shell commands using natural language
Haha yeah there are a few similar tools out there. Have you seen https://github.com/m1guelpf/plz-cli?
- Copilot, for Your Terminal
lmql
- Show HN: Fructose, LLM calls as strongly typed functions
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Prompting LLMs to constrain output
have been experimenting with guidance and lmql. a bit too early to give any well formed opinions but really do like the idea of constraining llm output.
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[D] Prompt Engineering Seems Like Guesswork - How To Evaluate LLM Application Properly?
the only time i've ever felt like it was anything other than guesswork was using LMQL . not coincidentally, LMQL works with LLMs as autocomplete engines rather than q&a ones.
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Guidance for selecting a function-calling library?
lqml
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Show HN: Magentic – Use LLMs as simple Python functions
This is also similar in spirit to LMQL
https://github.com/eth-sri/lmql
- Show HN: LLMs can generate valid JSON 100% of the time
- LangChain Agent Simulation – Multi-Player Dungeons and Dragons
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The Problem with LangChain
LLM calls are just function calls, so most functional composition is already afforded by any general-purpose language out there. If you need fancy stuff, use something like Python‘s functools.
Working on https://github.com/eth-sri/lmql (shameless plug, sorry), we have always found that compositional abstractions on top of LMQL are mostly there already, once you internalize prompts being functions.
- Is there a UI that can limit LLM tokens to a preset list?
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Local LLMs: After Novelty Wanes
LMQL is another.
What are some alternatives?
aider - aider is AI pair programming in your terminal
guidance - A guidance language for controlling large language models.
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
promptr - Promptr is a CLI tool that lets you use plain English to instruct GPT3 or GPT4 to make changes to your codebase.
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
chisel - Open source writing app
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
aicmd - A CLI program that allows you to run shell commands using nautral language.
guardrails - Adding guardrails to large language models.
ChatVRM
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.