PromptDialog 2.0

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基于Agentic AI 的ChatBot

基于开源 Mica 构建,支持 云端 本地 免费使用。

RASA Support By Prompt Dialog 1.0

weather_agent:
type: llm agent
description: Get the current weather in a given location and send email
prompt: |-
You are a Weather Query Agent. You can do following things:
1、Get the current weather in a given location. Location MUST be a city.
When a user asks about the weather, extract the location from their question. Once all the information is collected, call the "get_weather" function
2、sending email:
When a user sending email, extract the recipient、subject and body from their question. Once all the information is collected, call the "send_email" function.
args:
- subject
- recipient
- location
- body
uses:
- get_weather
- send_email
get_weather:
type: function
send_email:
type: function
meta:
type: ensemble agent
description: You can select an agent to response user's question.
contains:
- weather_agent
steps:
- bot: Do you want to know the weather?
fallback:
policy: Lame! We got a glitch, please try again later.
main:
steps:
- call: meta
schedule: priority
import json
from swarm import Agent
def get_weather(location, time="now"):
"""Get the current weather in a given location. Location MUST be a city."""
return json.dumps({"location": location, "temperature": "65", "time": time})
def send_email(recipient, subject, body):
print("Sending email...")
print(f"To: {recipient}")
print(f"Subject: {subject}")
print(f"Body: {body}")
return "Sent!"
weather_agent = Agent(
name="Weather Agent",
instructions="You are a helpful agent.",
functions=[get_weather, send_email],
)
  • 一体化工作室

    在同一个集成开发环境(IDE)中完整展示所有插槽与智能体(Agents)。不同的智能体可以灵活组合,并一键部署。平台支持 Web 和移动端两种发布模式。只需复制几行代码,即可将对话能力集成到您的应用中。
  • 以智能体为核心的设计

    系统预设了四种类型的智能体:知识库型、LLM 型、流程型和集成型,供您自由定制。常见问答(FAQ)以及存储在 Word、PDF 和 HTML 中的非结构化内容可直接建立索引,实现问答功能,无需人工标注。
  • 快速调试

    这是首个将软件开发流程嵌入聊天机器人设计与调试中的系统。每个智能体(Agent)都可以单独或组合进行测试,极大地方便了调试过程。

PromptDialog Studio

一体化设计环境

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