Alternatives
Products that do what Valkyric — English to Code does
Ask your data anything. No code. Just English.
- 1WO
Long story short: We (Dataherald) just open-sourced our entire codebase, including the core engine, the clients that interact with it and the backend application layer for authentication and RBAC. You can now use the full solution to build text-to-SQL into your product. The Problem: modern LLMs write syntactically correct SQL, but they struggle with real-world relational data. This is because real world data and schema is messy, natural language can often be ambiguous and LLMs are not trained on your specific dataset. Solution: The core NL-to-SQL engine in Dataherald is an LLM based agent…
2024 · github.com
- 2UC
Paste in my prompt to Claude Code with an embedded API key for accessing my public readonly SQL+vector database, and you have a state-of-the-art research tool over Hacker News, arXiv, LessWrong, and dozens of other high-quality public commons sites. Claude whips up the monster SQL queries that safely run on my machine, to answer your most nuanced questions. There's also an Alerts functionality, where you can just ask Claude to submit a SQL query as an alert, and you'll be emailed when the ultra nuanced criteria is met (and the output changes). Like I want to know when somebody posts about…
Dec 2025 · exopriors.com
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- 4NS
Would love thoughts! Here is the HF page: https://huggingface.co/chatdb/natural-sql-7b
2024 · github.com
- 5DS
I played around with GPT-3 to build this demo. Select a public BigQuery dataset and describe your query in natural English, then edit the generated SQL as needed and execute it. https://app.tabbydata.com/sql-assistant-demo
2021
- 6DA
Hi HN community. We are excited to open source Dataherald’s natural-language-to-SQL engine today (https://github.com/Dataherald/dataherald). This engine allows you to set up an API from your structured database that can answer questions in plain English. GPT-4 class LLMs have gotten remarkably good at writing SQL. However, out-of-the-box LLMs and existing frameworks would not work with our own structured data at a necessary quality level. For example, given the question “what was the average rent in Los Angeles in May 2023?” a reasonable human would either assume the…
2023 · github.com
- 7VA
Wrote this to learn more about the `chumsky` parser combinator library, rustyline, and the `ariadne` error reporting crate. Such a nice DX combo for writing new languages. Still a work in progress, but I thought I'd share :)
2025 · github.com
- 8VT
Hey HN! We're so excited to show you Val Town (https://val.town)! A "val" is a JavaScript/TypeScript function or value that runs on our servers. We aim to get you from idea to running code in seconds: type code, run it, get its API endpoint, schedule it - all from the browser, in a couple keystrokes. We're a startup of 4 people, mostly in NYC. We've been working on this for 6 months and are eager for feedback from the HN community. Why do we need yet another online coding IDE? While researching devtools[1], I found myself wanting something halfway between Replit and Zapier: a…
2023 · val.town
- 9PN
We've been hard at work for a few weeks and thought it's time for another update. In case you missed our first post, PostgresML is an end-to-end machine learning solution, running alongside your favorite database. This time we have more of a suite offering: project management, visibility into the datasets and the deployment pipeline decision making. Let us know what you think! Demo link is on the page, and also here: https://demo.postgresml.org
2022 · postgresml.org
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- 11TE
2019 · github.com
- 12NL
Hi HN- Today, we are releasing the hosted API for our natural language to SQL engine, which allows you to: (1) Explain Your Data: Feed in dictionaries, dbt, schemas, Confluence docs - we'll understand the business context to your data. (2) Train Your AI: Fine-tune an LLM (including GPT-4) specifically for your data, increasing accuracy and lowering latency (3) Trust the Answer: See confidence scores with each AI-generated query, stay in control. (4) Conduct complex SQL queries Problem background - Developers struggle to build NL-to-SQL into products because LLMs do not work out-of-the-box;…
2024 · dataherald.com
- 13SA
Hi HN, We're Luke and Phillip, and we're building Spice.ai OSS - a lightweight, portable runtime, built in Rust and powered by Apache DataFusion to locally materialize, accelerate, and query data tables sourced from any database, data warehouse or data lake. Phillip and I first introduced Spice on Show HN in September 2021. Since then, we’ve been schooled and humbled in every way building 100TB+ data and ML systems for the https://spice.ai cloud platform. Along with our customers, we struggled with getting fast, low-latency, high-concurrency SQL query within a budget, accessing and…
2024 · github.com
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- 15SE
I have been working on SQL Explorer, an open source, Django-based reporting and query tool for (gulp!) almost ten years. It's a tool that fits just right for me and many others, and I love and use almost every day. Write SQL, share results, do some analysis, get insight. No surprises. A live demo instance is here (no login or anything required): https://demo.sqlexplorer.io/ And here's a fairly unprofessional, but very enthusiastic, video tour: https://sql-explorer.s3.amazonaws.com/Sql+Explorer+5.mp4 The UI is constrained enough that there's very little to learn,…
2024 · github.com
- 16VO
Hello HN. I've always found writing data visualisation scripts boring and repetitive in data science workflows earlier in my career, so I built this tool to automate it. The available methods are based on my experience in econometrics where histograms and scatterplots were the starting points to check data distributions. The link is to the documentation and the app is freely available at https://visprex.com, and if you're curious about the implementation it's open source at https://github.com/visprex/visprex. I'd appreciate any comments and feedback!
2024 · docs.visprex.com
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- 19QY
Hi folks, My friend Sami and I recently built Vizly, a Mac application that allows anyone to query their databases using plain English. Vizly is built on Llama 2, llama.cpp, and runs fully on-prem (edit: meaning everything is local and your data never leaves your own computer). We are running two Llama models, one for natural language to SQL translation, and another that uses the results from the SQL to render visualizations. That means there are no external APIs and all the AI models are running locally on your MacBook. We tried to make Vizly very easy to share as well. Every Vizly instance…
2023 · vizly.fyi
- 20CA
Last year we launched ChartDB OSS (https://news.ycombinator.com/item?id=44972238) - an open-source tool that generates ER diagrams from your database (via query/sql/dbml) without needing direct DB access. Now we’re launching the ChartDB Agent. It helps you design databases from scratch or make schema changes with natural language. You can: - Generate schemas by simply describing them in plain English - Brainstorm new tables, columns, and relationships with AI - Iterate visually in a diagram (ERD) - Deterministically export SQL script Try it out here -…
Oct 2025 · app.chartdb.io
- 21SS
SPyQL (https://github.com/dcmoura/spyql) is SQL with Python in the middle, an open-source project fully written in Python for making command-line data processing more intuitive, readable and powerful. Try mixing in the same pot: a SQL SELECT for providing the structure, Python expressions for defining transformations and conditions, the essence of awk as a data-processing language, and the JSON handling capabilities of jq. How does a SPyQL query looks like? $ spyql “ IMPORT pendulum AS p SELECT (p.now() - p.from_timestamp(purchase_ts)).in_days() AS days_ago, sum_agg(price…
2022 · github.com
- 22GA
Simon(sfarshid) and I spend a lot of time on GitHub. As data nerds we put together a quick tool to explore your repository’s data. How it works: - Data Loading: We use dlt to pull data (issues, PRs, commits, stars) from GitHub - Semantic Layer: Relta wraps the underlying dataset into a semantic layer so the LLM doesn’t hallucinate. - Text-to-SQL: A text-to-SQL agent transforms your plain-English question into a query using the semantic layer - Generative Charts: assistant-ui dynamically generates a chart based on the SQL query - Refinements: If the semantic layer can’t handle your question,…
2024 · github.com
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- 24VA
Hey there HN! We've just open-sourced Vanna – a Python package that allows you to transform questions into SQL. We've leveraged LLMs to enable you to "ask" databases what you need, bypassing the need to "write" complex SQL. Quick Overview: - "Train" using DDL statements, documentation, or known correct SQL statements. - "Ask" questions in natural language and receive SQL, tables, and charts in return. - Open Source Flexibility: Swap storage mechanisms, customize LLMs, and choose your databases. - Local or Hosted: Operate everything locally or use our hosted version for free (including…
2023 · vanna.ai
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