Dialogue Agent

tod_agent

Author: svcvit Version: 0.0.2 Type: agent

Description

A powerful task-oriented dialogue agent that can collect information through structured conversations. It supports dynamic field validation, multi-field information extraction, and state management.

Features

• Task-oriented dialogue management
• Dynamic field validation
• Multi-field information extraction
• Conversation state persistence
• Automatic answer validation
• Context-aware information collection
• Natural language interaction

Usage Guide

Parameters

1. task_schema (Required)

   • Type: string (JSON)
   • Description: Schema defining the fields to collect
   • Example（Please use this code to test it out. There should be a space in front of the {）:

      {
       "fields": [
         {
           "name": "destination",
           "question": "请问您想去哪里旅行？",
           "required": true
         },
         {
           "name": "duration",
           "question": "您计划旅行多长时间？",
           "required": true
         },
         {
           "name": "budget",
           "question": "您的预算大约是多少？",
           "required": true
         }
       ]
     }

2. query (Required)

   • Type: string
   • Description: User's input text
   • Example: "我想去日本玩三天"

3. model (Required)

   • Type: AgentModelConfig
   • Description: LLM model configuration
   • Example: Configuration for GPT or other LLM models

4. storage_key (Required)

   • Type: string
   • Description: Unique key for storing conversation state
   • Example: "conversation-123"

Response Format

The agent returns messages in the following formats:

1. Text messages for questions and responses
2. JSON message with collected data when complete
3. Summary message when all fields are collected

Changelog

v0.0.2

• Added logging functionality
• Added token usage statistics
• Optimized code structure and performance

v0.0.1

• Project initialization
• Implemented multi-turn dialogue
• Implemented conversation state storage
• Implemented intelligent Q&A content extraction