larryste

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Hi HN! I just released dupeSweep, a duplicate file finder I built after getting frustrated with existing tools that permanently delete files without confirmation.

Key features: • Two-phase hashing (quick hash first, full SHA256 on collision) - fast AND accurate • Full undo support with verification - files never permanently deleted • GUI and CLI interfaces (no args launches GUI) • Symlink/hardlink safety - prevents data loss from cycles and false positives • Collision-resistant trash naming with backup/recovery • Confirmation prompts for all deletions

Available in two implementations: • Python: Pure stdlib, no dependencies, 21 tests • Go: Single binary, 20x faster, 16 tests

Also on PyPI: `pip install dupesweep`

I'd love feedback on the safety features especially - spent a lot of time on undo verification, hardlink detection via inode tracking, and symlink cycle prevention.

Tech stack: Python 3.7+/tkinter, Go 1.21+/Fyne

GitHub: https://github.com/larryste1/dupesweep PyPI: https://pypi.org/project/dupesweep/

After creating 75+ tools for my AI agent workflow, I kept losing my best prompts across different conversations. I'd find a great code review prompt, use it once, then spend 20 minutes recreating it weeks later.

So I built Prompt Vault – a CLI tool with an interactive TUI for managing prompts.

Features: • Save prompts with tags and auto-versioning • Fuzzy search by keyword or tag • One command to copy prompt to clipboard • Version history with diff and revert • Export/import for backup • Interactive TUI (run `vault` with no args) • Dual Python + Go implementation • SQLite storage, no cloud dependencies

Quick start: pip install prompt-vault-cli vault # Opens interactive TUI

Or use CLI: vault create --name "code-review" --tags "code,python" vault get "code-review" # Copies to clipboard vault search "refactoring" vault list --tags

The TUI is probably the nicest part – number keys to navigate, rich tables, all the info at a glance.

Built this because I needed something that: 1. Works offline (no API keys, no cloud) 2. Is fast (single command to copy prompt) 3. Has version history (prompts evolve) 4. Doesn't get in the way

Tech stack: • Python: Typer + Rich + SQLite • Go: Cobra + SQLite (20x faster, single binary) • Both have identical features • Docker images available

The Go version is ~15MB single binary, starts in ~10ms. Python version has nicer output with Rich tables.

Would love feedback on: • CLI API design – anything missing? • TUI UX – is the navigation intuitive? • Use cases I haven't considered

Also happy to discuss the implementation – the fuzzy search uses Levenshtein distance, versioning is Git-based, and clipboard works cross-platform.

Source: https://github.com/larryste1/prompt-vault Docs: https://github.com/larryste1/prompt-vault#readme ```

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*Best time to post:* Tuesday-Thursday, 9-11 AM PT for maximum visibility

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*Project:* https://github.com/larryste1/web-search-tool *PyPI:* https://pypi.org/project/web-search-tool/

## The Problem

Building AI assistants needs: reliable search with fallback, clean content extraction, API flexibility, and structured JSON output. Existing solutions are single-backend (breaks when API fails), too complex, or output raw HTML.

## The Solution

`web-search-tool` searches/scrapes with clean, AI-friendly output:

```bash pip install web-search-tool web-search "Python async best practices" # Search with AI answer web-search "React hooks tutorial" --scrape # Full article content web-search "machine learning" --include-domain arxiv.org # Filter domain web-search "API design" --json # JSON output ```

## Features

- *3 Backends with Auto-Fallback*: Tavily → Serper → DuckDuckGo - *Content Scraping*: Extract main article text via BeautifulSoup - *Domain Filtering*: Include/exclude specific domains - *Search Depth*: Basic or advanced - *AI-Friendly Output*: Structured results with optional AI answers - *JSON Output*: Pipe to jq or parse in scripts

## How It Works

``` Query → Tavily (AI, needs key) → Serper (Google, needs key) → DuckDuckGo (free) ```

## Examples

```bash # AI Research with Answer $ web-search "What is Rust ownership?"

Search: What is Rust ownership? Backend: Tavily Answer: Rust ownership manages memory allocation. Each value has one owner...

# Scrape Full Articles $ web-search "Python decorators" --scrape --num 3

# Domain-Specific $ web-search "type hints" --include-domain realpython.com --include-domain docs.python.org

# Programmatic Use from web_search_tool import search_web result = search_web("Python best practices", scrape_urls=True) ```

## API Keys

| Backend | Key | Get Key | |---------|-----|---------| | Tavily | Optional | https://tavily.com/ | | Serper | Optional | https://serper.dev/ | | DuckDuckGo | None | Free |

```bash export TAVILY_API_KEY=your-key-here export SERPER_API_KEY=your-key-here ```

Without keys, falls back to DuckDuckGo automatically.

## Why I Built This

Building AI assistants, I hit: single point of failure, messy output, no fallback. This tool tries multiple backends, extracts clean text, returns structured JSON, works without API keys.

## Tech Stack

Requests, BeautifulSoup4, Tavily API, Serper API, DuckDuckGo HTML

## Try It

```bash pip install web-search-tool web-search "Python tutorials" # No API key needed ```

*GitHub:* https://github.com/larryste1/web-search-tool

*Feedback:* What backends should I add? How do you handle web search in AI projects?

--- Built after too many API failures with single-backend tools.