Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.
| Date | Stars |
|---|---|
| 2026-07-31 | 18213 |
| 2026-08-01 | 18213 |
| 2026-08-02 | 18227 |
| 2026-08-06 | 18227 |
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Momentum
5.0
growth rate 0.00%/day
<div align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://github.com/emcie-co/parlant/blob/develop/docs/LogoTransparentLight.png?raw=true"> <img alt="Parlant" src="https://github.com/emcie-co/parlant/blob/develop/docs/LogoTransparentDark.png?raw=true" width=400 /> </picture> ### The interaction control harness for customer-facing AI agents <p> <a href="https://pypi.org/project/parlant/"><img alt="PyPI" src="https://img.shields.io/pypi/v/parlant?color=blue"></a> <img alt="Python 3.10+" src="https://img.shields.io/badge/python-3.10+-blue"> <a href="https://opensource.org/licenses/Apache-2.0"><img alt="License" src="https://img.shields.io/badge/license-Apache%202.0-green"></a> <a href="https://discord.gg/duxWqxKk6J"><img alt="Discord" src="https://img.shields.io/discord/1312378700993663007?color=7289da&logo=discord&logoColor=white"></a> <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/emcie-co/parlant?style=social"> </p> <p> <a href="https://www.parlant.io/" target="_blank">Website</a> • <a href="https://www.parlant.io/docs/quickstart/installation" target="_blank">Quick Start</a> • <a href="https://www.parlant.io/docs/quickstart/examples" target="_blank">Examples</a> • <a href="https://discord.gg/duxWqxKk6J" target="_blank">Discord</a> </p> <p> <a href="https://zdoc.app/de/emcie-co/parlant">Deutsch</a> | <a href="https://zdoc.app/es/emcie-co/parlant">Español</a> | <a href="https://zdoc.app/fr/emcie-co/parlant">français</a> | <a href="https://zdoc.app/ja/emcie-co/parlant">日本語</a> | <a href="https://zdoc.app/ko/emcie-co/parlant">한국어</a> | <a href="https://zdoc.app/pt/emcie-co/parlant">Português</a> | <a href="https://zdoc.app/ru/emcie-co/parlant">Русский</a> | <a href="https://zdoc.app/zh/emcie-co/parlant">中文</a> </p> <a href="https://trendshift.io/repositories/12768" target="_blank"> <img src="https://trendshift.io/api/badge/repositories/12768" alt="Trending" style="width: 250px; height: 55px;" width="250" height="55"/> </a> </div> > **Looking for an open-source alternative to Ada, Decagon, or Sierra?** **Parlant is production-ready. It streamlines the development and maintenance of enterprise-grade B2C (business-to-consumer) and sensitive B2B interactions that need to be consistent, compliant, on-brand, and comprehensively traceable.** ## Why Parlant? Conversational context engineering is hard because real-world interactions are diverse, nuanced, and non-linear. ### ❌ The Problem: What you've probably tried and couldn't get to work at scale **System prompts** work until production complexity kicks in. The more instructions you add to a prompt, the faster your agent stops paying attention to any of them. **Routed graphs** solve the prompt-overload problem, but the more routing you add, the more fragile it becomes when faced with the chaos of natural interactions. ### 🔑 The Solution: Context engineering, optimized for conversational control Parlant is an agentic harness offering optimized [context engineering](https://www.gartner.com/en/articles/context-engineering) for conversational use cases: getting the right context, no more and no less, into the prompt at the right time. You define rules, knowledge, and tools once, while the engine narrows the context down in real-time to what's immediately relevant to each turn of the conversation. <img alt="Parlant Demo" src="https://github.com/emcie-co/parlant/blob/develop/docs/demo.gif?raw=true" width="100%" /> ### How is Parlant different from LangGraph or DSPy? Parlant focuses on conversational governance and behavioral control and consistency, while LangGraph is ideal for workflow automation, and DSPy is ideal for low-level prompt optimization. ## Design goals Parlant is built around three goals that shape every decision in the framework: ### 1. Maximum control over the conversation experience Parlant was designed around a simple idea: developers sh
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d8c518a59a9c3c1c, topic:ai-agents, desc:ai agents
matched fp:d8c518a59a9c3c1c, topic:llm