Overview
Chat is Wegent's core interaction feature that allows you to have real-time conversations with AI agents to complete various tasks.
π Core Conceptsβ
Chat Tasksβ
A Chat Task is the basic unit of the Chat feature. Every interaction with AI creates a task:
- Single-turn: Simple one-time Q&A
- Multi-turn: Continuous contextual conversation
- Code Task: Programming tasks related to code repositories
Chat Modesβ
Wegent provides multiple conversation modes for different scenarios:
| Mode | Description | Use Case |
|---|---|---|
| Smart Follow-up | AI asks questions to clarify requirements | Complex tasks with unclear requirements |
| AI Cross-Validation | AI suggests modifications | Code review, document optimization |
| Direct Execution | AI executes tasks immediately | Simple tasks with clear requirements |
π― Main Featuresβ
1. Task Managementβ
Centralized management of all chat tasks:
- View conversation history list
- Filter by status (in progress, completed, failed)
- Search and archive tasks
- Export conversation records
2. Multi-Agent Collaborationβ
Support for various collaboration methods:
- Single Agent: One-on-one conversation with one agent
- Group Chat: Multiple agents participating in discussions
- Team Mode: Agents collaborate with assigned roles
3. Code Tasksβ
Enhanced features designed for programming:
- Automatic code repository cloning
- Agents read and analyze code
- Execute code modifications and commits
- Real-time execution monitoring
4. Conversation Controlβ
Flexible conversation control options:
- Pause/resume conversation
- Regenerate responses
- Modify context
- Switch agents
5. Runtime Model Switchingβ
After a task has started, you can adjust the model used for later responses in the current task. The change only affects the current task. It does not modify the agent, bot, or model defaults, and it does not affect other tasks or newly created conversations.
To keep the runtime protocol consistent, WeWork limits model switching for already running tasks to the same runtime model family in the model selector. Wegent derives the API response field runtime.family from the combination of the model CRD's modelConfig.env.model and spec.protocol values:
- The current task model and the target model must have the same
runtime.familyvalue - For example, Claude, Kimi, or DeepSeek-compatible models whose
runtime.familyisclaude.claudecan be switched between each other - Models with the same
env.modelbut differentspec.protocolvalues are treated as different runtime families - Models without
runtime.familystay visible for an already running task, but are disabled
Models with a different runtime.family value remain visible, but are disabled in the selector.
π Documentation Navigationβ
| Document | Description |
|---|---|
| Managing Tasks | Creating and managing chat tasks |
| Smart Follow-up Mode | Using smart follow-up mode to clarify requirements |
| AI Cross-Validation | Using AI cross-validation to optimize results |
π Quick Startβ
Create Your First Conversationβ
- Navigate to the Chat page
- Click New Conversation
- Select an agent or agent team
- Enter your question or task description
- Wait for AI response
Create a Code Taskβ
- Click New Task
- Select a programming-type agent
- Select a code repository
- Describe the task to complete
- AI will automatically clone the repository and start working
π‘ Use Casesβ
Programming Assistanceβ
- Code Review: Have AI check code quality and potential issues
- Bug Fixing: Describe the problem, let AI locate and fix it
- Feature Development: Describe requirements, let AI implement new features
- Code Explanation: Have AI explain complex code logic
Content Creationβ
- Documentation Writing: Have AI help write technical documents
- Content Polishing: Optimize existing content expression
- Translation Services: Multi-language content translation
Knowledge Q&Aβ
- Technical Consulting: Ask technical questions and best practices
- Concept Explanation: Understand complex technical concepts
- Solution Design: Discuss system architecture and design solutions
π Related Resourcesβ
- Agent Settings - Configure agents
- Configuring Models - Set up AI models
- Feed Overview - Automated task execution