Natural language generation language
- natural-language-generation
- nlg
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Natural language generation language
MicroPython driver for the AHT10 and AHT20 temperature and humidity sensors.
A Python toolkit for generating human-readable timetables from GTFS data; uses PANDAS and gtfs_kit
A very simple screen magnifier for Ubuntu
Fully typesafe, Rust-like Result and Option types for Python
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
MCP server for spatial transcriptomics analysis through natural language interfaces.
Python package for inverse kinematic calculations of hybrid serial parallel robots
Python Parser for Ring Tone Text Transfer Language (RTTTL)
MicroPython shell
Framework for information extraction from tables
MicroPython driver for MAX7219 8x8 LED matrix
scikit-learn addon to operate on set/"group"-based features
A command line tool and library for generating FFI wrappers for Common Lisp
Test harness for voice agents. Import from Retell, VAPI, Bland, LiveKit. Run autonomous simulations. Evaluate with LLM judges.
Turn CSV, Excel, and read-only databases into verified, editable business reports.
A home-based IoT irrigation system for efficient plant care.
A malware dataset curation tool which helps identify packed samples.
⚡ JEval helps you to evaluate your JMeter test plan and provides recommendation before you start your performance testing. All contributions welcome 🙏.
Classes to count pulses, debounce digital inputs, and calculate moving averages of analog inputs for a micropython board.
Python library for reading and writing GTFS feeds
Enterprise-grade platform to generate and execute Cypress, Playwright, WebdriverIO, and Appium end-to-end tests from natural language requirements. (Appium is experimental and requires external mobile infrastructure.)
Persistent decision memory for AI agents: rationale, rejected approaches, and entity history. Connect any compatible agent through local MCP or the CLI.
A repo-native coding-agent loop harness for Claude, Codex, Copilot, and other CLI agents. Agents can edit. Gates decide what lands. You set the plan in motion. The agents take a prompt, and each iteration must update specs and commit through guardrails.