# parlant **Repository Path**: daunty/parlant ## Basic Information - **Project Name**: parlant - **Description**: Parlant 是一个用于 LLM agent 的开源代理行为建模引擎，旨在帮助开发人员快速创建具有控制力、清晰度和信心的客户参与、业务一致的对话代理 - **Primary Language**: Python - **License**: Apache-2.0 - **Default Branch**: develop - **Homepage**: https://www.oschina.net/p/parlant - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 1 - **Created**: 2025-11-04 - **Last Updated**: 2025-11-04 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

Finally, LLM agents that actually follow instructions

🌐 Website • ⚡ Quick Start • 💬 Discord • 📖 Examples

## 🎯 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) - 🆚 [Blog: Parlant vs LangGraph](https://www.parlant.io/blog/parlant-vs-langgraph) - 🆚 [Blog: Parlant vs DSPy](https://www.parlant.io/blog/parlant-vs-dspy) #### 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.

## 🚀 Get Your Agent Running in 60 Seconds

```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 Parlant Demo

## 🔥 Why Developers Are Switching to Parlant

### 🏗️ Traditional AI Frameworks	### ⚡ Parlant
- Write complex system prompts - Hope the LLM follows them - Debug unpredictable behaviors - Scale by prompt engineering - Cross fingers for reliability	- Define rules in natural language - Ensured rule compliance - Predictable, consistent behavior - Scale by adding guidelines - Production-ready from day one

## 🎯 Perfect For Your Use Case

## 🛠️ 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

**Companies using Parlant:** _Financial institutions • Healthcare providers • Legal firms • E-commerce platforms_ [![Star History Chart](https://api.star-history.com/svg?repos=emcie-co/parlant&type=Date)](https://star-history.com/#emcie-co/parlant&Date)

## 🌟 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

🎯 I want to test it myself	→ 5-minute quickstart
🛠️ I want to see an example	→ Healthcare agent example
🚀 I want to get involved	→ Join our Discord community

## 🤝 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. ---

**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)_

### 🏗️ Traditional AI Frameworks	### ⚡ Parlant
- Write complex system prompts - Hope the LLM follows them - Debug unpredictable behaviors - Scale by prompt engineering - Cross fingers for reliability	- Define rules in natural language - Ensured rule compliance - Predictable, consistent behavior - Scale by adding guidelines - Production-ready from day one