AI · alternatives · 2026

24 alternatives to Tsellm: Interactive SQLite shell with LLM support

Hello HN, While browsing the Python docs yesterday, I discovered that the latest 3.12 version has added support for a `python3 -m sqlite3` interactive shell. I looked into the source code, and its implementation was simple, giving me an idea: Why not hook the beautiful llm library by simonw into such an interactive shell, and thus have direct LLM support in SQLite? Without writing a C extension, build a shared object and all that fuss. Well, now you can `pip install tsellm` and do just that. demo gif:…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Tsellm: Interactive SQLite shell with LLM support launched in 2024; newer entries below may have overtaken it.

1
My LLM CLI tool can run tools now, from Python code or plugins▲529
LLM 0.26 is out with the biggest new feature since I started the project: support for tools. You can now use the LLM CLI tool—and Python library—to grant LLMs from …
2025 · simonwillison.net · its alternatives →
2
Magentic – Use LLMs as simple Python functions▲283
This is a Python package that allows you to write function signatures to define LLM queries. This makes it easy to mix regular code with calls to LLMs, which enables you to use the LLM for its creativity and reasoning while also enforcing structure/logic as necessary. LLM output is parsed for you according to the return type annotation of the function, including complex return types such as streaming an array of structured objects. I built this to show that we can think about using LLMs more fluidly than just chains and chats, i.e. more interchangeably with regular code, and to make it…
2023 · github.com · its alternatives →
3
Llm2sh – Translate plain-language requests into shell commands▲67
This is my take on the common "use llms to generate shell commands" utility. Emphasis is placed on good CLI UX, simplicity, and flexibility. `llm2sh` supports multiple LLM providers and lets LLMs generate multi-command sequences to handle complex tasks. There is also limited support for commands requiring `sudo` and other basic input. I recommend using Groq llama3-70b for day-to-day use. The ultra-low latency is a game-changer - its near-instant responses helps `llm2sh` integrate seamlessly into day-to-day tasks without breaking you out of the 'zone'. For more advanced tasks, swapping to…
2024 · github.com · its alternatives →
4
I wrote a RDBMS (SQLite clone) from scratch in pure Python▲371
I wrote a relational database management system (RDBMS) (sqlite clone) from scratch in pure Python.
2023 · github.com · its alternatives →
5SQ
SQLite query inside a Bash function▲134
Part of the workflow for building my website is the generation of a table in tab-separated column format (.tsv). The source data is found in four other .tsv files. I use an SQLite query to perform a 4-way join and write out the new table. For convenience, I wrote a script that encapsulates the query inside a Bash function. The example below illustrates this technique. repertoire() { pushd $CMM_SOURCES/_data sqlite3 <<EOS .headers on .mode tabs .import category.tsv category .import composition.tsv composition .import concert.tsv concert .import program.tsv program .once repertoire.tsv…
2021 · its alternatives →
6
I wrote an open-source browser alternative for Computer Use for any LLM▲180
Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…
2024 · github.com · its alternatives →
7
A local-first memory store for LLM agents (SQLite)▲48
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc. - CaviraOSS/LongMemory
Dec 2025 · github.com · its alternatives →
8
(bits) of a Libc, Optimized for Wasm▲78
I make a no-CGO Go SQLite driver, by compiling the amalgamation to Wasm, then loading the result with wazero (a CGO-free Wasm runtime). To compile SQLite, I use wasi-sdk, which uses wasi-libc, which is based on musl. It's been said that musl is slow(er than glibc), which is true, to a point. musl uses SWAR on a size_t to implement various functions in string.h. This is fine, except size_t is just 32-bit on Wasm. I found that implementing a few of those functions with Wasm SIMD128 can make them go around 4x faster. Other functions don't even use SWAR; redoing those can make them 16x faster.…
2025 · github.com · its alternatives →
9LS
Llm.sql – Run a 640MB LLM on SQLite, with 210MB peak RSS and 7.4 tok/s▲8
Hi HN, I built llm.sql, an LLM inference framework that reimagines the LLM execution pipeline as a series of structured SQL queries atop SQLite. The motivation: Edge LLMs are getting better, but hardware remains a bottleneck, especially RAM (size and bandwidth). When available memory is less than the model size and KV cache, the OS incurs page faults and swaps pages using LRU-like strategies, resulting in throughput degradation that's hard to notice and even harder to debug. In fact, the memory access pattern during LLM inference is deterministic - we know exactly which weights are needed…
Apr 2026 · its alternatives →
10SP
Sultan – Pythonic interface to your shell▲155
2017 · sultan.readthedocs.io · its alternatives →
11
Marvin – build AI functions that use an LLM as a runtime▲127
Hey HN! We're excited to share our new open-source project, Marvin. Marvin is a high-level library for building AI-powered software. We developed it to address the challenges of integrating LLMs into more traditional applications. One of the biggest issues is the fact that LLMs only deal with strings (and conversational strings at that), so using them to process structured data is especially difficult. Marvin introduces a new concept called AI Functions. These look and feel just like regular Python functions: you provide typed inputs, outputs, and docstrings. However, instead of relying on…
2023 · github.com · its alternatives →
12
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
13
Bash4LLM+ – A lightweight, dependency-free Bash wrapper for LLM APIs▲60
Bash4LLM is a single-file Bash wrapper for interacting with LLMs from the terminal. I created it because I wanted something simple that worked without installing Python, Node, or any other runtime. It uses only Bash, curl, and jq. You can send prompts, start a small chat, process files line by line, stream output, and save session metadata in JSON format. I tried to make it safe and predictable: no use of the system /tmp, no use of eval. Groq is supported by default, and other providers can be added with dedicated Bash scripts in the extras/providers/ folder. Example: echo…
Jun 2026 · github.com · its alternatives →
14
OpenSheet▲86
Hi folks. I've been doing some experiments on how LLMs could get more handy in the day to day of working with files (CSV, Parquet, etc). Earlier last year, I built https://datakit.page and evolved it over and over into an all in-browser experience with help of duckdb-wasm. Got loads of feedbacks and I think it turned into a good shape with being an adhoc local data studio, but I kept hearing two main things/issues: Why can't the AI also change cells in the file we give to it? Why can't we modify this grid ourselves? So besides the whole READ and text-to-SQL flows, what seemed…
Feb 2026 · opensheet.app · its alternatives →
15MG
macOS GUI for running LLMs locally▲58
Hello HN, I've been working on this project for a while, and it has been in an "open" beta for some time. I finally believe it's ready for its first release. I hope you like it. Here are some potential questions that may arise: 1. How does it compare to LM Studio? It's likely that if you're already using LM Studio, you'll continue to do so. This project is designed to be more user-friendly. 2. Is it open-source? No, it is not. 3. Does it use any open-source libraries? Yes, it uses llama.cpp and a few others, as indicated in the license information included with the application. 4. Why is not…
2023 · avapls.com · its alternatives →
16
LLM-Term – Simple Rust-based CLI assist tool▲32
Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com · its alternatives →
17
Litellm – Simple library to standardize OpenAI, Cohere, Azure LLM I/O▲62
I built this library because langchain was too bloated and I needed a simple abstraction to call multiple LLM APIs. litellm has two functions - completion(), embedding()
2023 · github.com · its alternatives →
18
Clamshell- an experimental Python based shell▲51
About a month ago I started a suprisingly-not-that tricky project to build an experimental python repl that I could use instead of bash as a daily shell in windows, mac or linux. It"s more hack-for-exploration than a production ready shell, but here it is! Hope somebody finds it anywhere near as interesting to check out as I found making it. Disclaimer: I know about xonsh and love it (if you haven't heard of it, google it). This project is more pure python and less python and bash interacting - see the readme for more details.
2023 · github.com · its alternatives →
19IG
Interactive Graph by LLM (GPT-4o)▲45
Data automation and visualization platform for spreadsheet users.
2024 · columns.ai · its alternatives →
20
Local LLM Notepad – run a GPT-style model from a USB stick▲40
What it is A single 45 MB Windows .exe that embeds llama.cpp and a minimal Tk UI. Copy it (plus any .gguf model) to a flash drive, double-click on any Windows PC, and you’re chatting with an LLM—no admin rights, Cloud, or network. Why I built it Existing “local LLM” GUIs assume you can pip install, pass long CLI flags, or download GBs of extras. I wanted something my less-technical colleagues could run during a client visit by literally plugging in a USB drive. How it works PyInstaller one-file build → bundles Python runtime, llama_cpp_python, and the UI into a single PE. On first launch, it…
2025 · github.com · its alternatives →
21
Trieve CLI – Terminal-based LLM agent loop with search tool for PDFs▲35
Hi HN, I built a CLI for uploading documents and querying them with an LLM agent that uses search tools rather than stuffing everything into the context window. I recorded a demo using the CrossFit 2025 rulebook that shows how this approach compares to traditional RAG and direct context injection[1]. The core insight is that LLMs running in loops with tool access are unreasonably effective at this kind of knowledge retrieval task[2]. Instead of hoping the right chunks make it into your context, the agent can iteratively search, refine queries, and reason about what it finds. The CLI handles…
2025 · github.com · its alternatives →
22
Python package for generating accurate SQL via LLMs using RAG▲7
Hello HN! We’ve been working hard on Vanna, our RAG framework for SQL generation and we’ve been updating our documentation. Please have a look — we have a ton of Jupyter notebooks for any combination of desired use cases. At it’s heart, we have abstractions that help you: - “train” a RAG “model” i.e. add metadata for the retrieval augmentation system to reference when constructing the LLM prompt (yes, we know that the terms “train” and “model” are somewhat confusing and we’re open to changing those terms if you can suggest better ones) - “ask” questions, which will generate SQL, run it,…
2023 · github.com · its alternatives →
23
Improve Text-to-SQL Accuracy with LLM▲17
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub
2023 · github.com · its alternatives →
24
How to use LLMs to generate accurate SQL for real-world data▲21
Hey HN, We are Zain and Ashish, founders of Vanna AI. We recently embarked on an experiment to see if large language models (specifically LLMs) could help in generating SQL queries for real-world datasets. We initially started this project as a web app but realized that it was most useful and had broadest applicability as a Python package since you can then incorporate it into an existing workflow (Jupyter notebook, Slackbot, etc). We've had some good success with customer datasets but we've generally heard a lot of skepticism so we decided to write a paper about the methodology we're using…
2023 · github.com · its alternatives →

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