base on LLM agents built for control. Designed for real-world use. Deployed in minutes. <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 - AI Agent Framework" src="https://github.com/emcie-co/parlant/blob/develop/docs/LogoTransparentDark.png?raw=true" width=400 /> </picture> <h3>Finally, LLM agents that actually follow instructions</h3> <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://discord.gg/duxWqxKk6J" target="_blank">💬 Discord</a> • <a href="https://www.parlant.io/docs/quickstart/examples" target="_blank">📖 Examples</a> </p> <p> <!-- Keep these links. Translations will automatically update with the README. --> <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> <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> <a href="https://trendshift.io/repositories/12768" target="_blank"> <img src="https://trendshift.io/api/badge/repositories/12768" alt="Trending on TrendShift" style="width: 250px; height: 55px;" width="250" height="55"/> </a> </div> ## 🎯 The Problem Every AI Developer Faces You build an AI agent. It works great in testing. Then real users start talking to it and... - ❌ It ignores your carefully crafted system prompts - ❌ It hallucinates responses in critical moments - ❌ It can't handle edge cases consistently - ❌ Each conversation feels like a roll of the dice **Sound familiar?** You're not alone. This is the #1 pain point for developers building production AI agents. ## ⚡ The Solution: Stop Fighting Prompts, Teach Principles Parlant flips the script on AI agent development. Instead of hoping your LLM will follow instructions, **Parlant ensures it**. ```python # Traditional approach: Cross your fingers 🤞 system_prompt = "You are a helpful assistant. Please follow these 47 rules..." # Parlant approach: Ensured compliance ✅ await agent.create_guideline( condition="Customer asks about refunds", action="Check order status first to see if eligible", tools=[check_order_status], ) ``` [✅ Blog: How Parlant Ensures Agent Compliance](https://www.parlant.io/blog/how-parlant-guarantees-compliance) #### Parlant gives you all the structure you need to build customer-facing agents that behave exactly as your business requires: - **[Journeys](https://parlant.io/docs/concepts/customization/journeys)**: Define clear customer journeys and how your agent should respond at each step. - **[Behavioral Guidelines](https://parlant.io/docs/concepts/customization/guidelines)**: Easily craft agent behavior; Parlant will match the relevant elements contextually. - **[Tool Use](https://parlant.io/docs/concepts/customization/tools)**: Attach external APIs, data fetchers, or backend services to specific interaction events. - **[Domain Adaptation](https://parlant.io/docs/concepts/customization/glossary)**: Teach your agent domain-specific terminology and craft personalized responses. - **[Canned Responses](https://parlant.io/docs/concepts/customization/canned-responses)**: Use response templates to eliminate hallucinations and guarantee style consistency. - **[Explainability](https://parlant.io/docs/advanced/explainability)**: Understand why and when each guideline was matched and followed. <div align="center"> ## 🚀 Get Your Agent Running in 60 Seconds </div> ```bash pip install parlant ``` ```python import parlant.sdk as p @p.tool async def get_weather(context: p.ToolContext, city: str) -> p.ToolResult: # Your weather API logic here return p.ToolResult(f"Sunny, 72°F in {city}") @p.tool async def get_datetime(context: p.ToolContext) -> p.ToolResult: from datetime import datetime return p.ToolResult(datetime.now()) async def main(): async with p.Server() as server: agent = await server.create_agent( name="WeatherBot", description="Helpful weather assistant" ) # Have the agent's context be updated on every response (though # update interval is customizable) using a context variable. await agent.create_variable(name="current-datetime", tool=get_datetime) # Control and guide agent behavior with natural language await agent.create_guideline( condition="User asks about weather", action="Get current weather and provide a friendly response with suggestions", tools=[get_weather] ) # Add other (reliably enforced) behavioral modeling elements # ... # 🎉 Test playground ready at http://localhost:8800 # Integrate the official React widget into your app, # or follow the tutorial to build your own frontend! if __name__ == "__main__": import asyncio asyncio.run(main()) ``` **That's it!** Your agent is running with ensured rule-following behavior. ## 🎬 See It In Action <img alt="Parlant Demo" src="https://github.com/emcie-co/parlant/blob/develop/docs/demo.gif?raw=true" width="100%" /> ## 🔥 Why Developers Are Switching to Parlant <table width="100%"> <tr> <td width="50%"> ### 🏗️ **Traditional AI Frameworks** </td> <td width="50%"> ### ⚡ **Parlant** </td> </tr> <tr> <td width="50%"> - Write complex system prompts - Hope the LLM follows them - Debug unpredictable behaviors - Scale by prompt engineering - Cross fingers for reliability </td> <td width="50%"> - Define rules in natural language - **Ensured** rule compliance - Predictable, consistent behavior - Scale by adding guidelines - Production-ready from day one </td> </tr> </table> ## 🎯 Perfect For Your Use Case <div align="center"> | **Financial Services** | **Healthcare** | **E-commerce** | **Legal Tech** | | :----------------------: | :---------------------: | :-------------------------: | :------------------------: | | Compliance-first design | HIPAA-ready agents | Customer service at scale | Precise legal guidance | | Built-in risk management | Patient data protection | Order processing automation | Document review assistance | </div> ## 🛠️ Enterprise-Grade Features - **🧭 Conversational Journeys** - Lead the customer step-by-step to a goal - **🎯 Dynamic Guideline Matching** - Context-aware rule application - **🔧 Reliable Tool Integration** - APIs, databases, external services - **📊 Conversation Analytics** - Deep insights into agent behavior - **🔄 Iterative Refinement** - Continuously improve agent responses - **🛡️ Built-in Guardrails** - Prevent hallucination and off-topic responses - **📱 React Widget** - [Drop-in chat UI for any web app](https://github.com/emcie-co/parlant-chat-react) - **🔍 Full Explainability** - Understand every decision your agent makes ## 📈 Join 10,000+ Developers Building Better AI <div align="center"> **Companies using Parlant:** _Financial institutions • Healthcare providers • Legal firms • E-commerce platforms_ [](https://star-history.com/#emcie-co/parlant&Date) </div> ## 🌟 What Developers Are Saying > _"By far the most elegant conversational AI framework that I've come across! Developing with Parlant is pure joy."_ **— Vishal Ahuja, Senior Lead, Customer-Facing Conversational AI @ JPMorgan Chase** ## 🏃‍♂️ Quick Start Paths <table border="0"> <tr> <td><strong>🎯 I want to test it myself</strong></td> <td><a href="https://www.parlant.io/docs/quickstart/installation">→ 5-minute quickstart</a></td> </tr> <tr> <td><strong>🛠️ I want to see an example</strong></td> <td><a href="https://www.parlant.io/docs/quickstart/examples">→ Healthcare agent example</a></td> </tr> <tr> <td><strong>🚀 I want to get involved</strong></td> <td><a href="https://discord.gg/duxWqxKk6J">→ Join our Discord community</a></td> </tr> </table> ## 🤝 Community & Support - 💬 **[Discord Community](https://discord.gg/duxWqxKk6J)** - Get help from the team and community - 📖 **[Documentation](https://parlant.io/docs/quickstart/installation)** - Comprehensive guides and examples - 🐛 **[GitHub Issues](https://github.com/emcie-co/parlant/issues)** - Bug reports and feature requests - 📧 **[Direct Support](https://parlant.io/contact)** - Direct line to our engineering team ## 📄 License Apache 2.0 - Use it anywhere, including commercial projects. --- <div align="center"> **Ready to build AI agents that actually work?** ⭐ **Star this repo** • 🚀 **[Try Parlant now](https://parlant.io/)** • 💬 **[Join Discord](https://discord.gg/duxWqxKk6J)** _Built with ❤️ by the team at [Emcie](https://emcie.co)_ </div> ", Assign "at most 3 tags" to the expected json: {"id":"12768","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"