You 14:32
帮我分析一下这个项目的架构,并给出优化建议
🤖 Assistant 14:32

我来分析这个项目的代码结构。让我先读取核心文件...

read src/limbo/config.py ✓ Completed
from pydantic import BaseModel
class Config(BaseModel):
    model: str = "deepseek-chat"
    api_key: str = ""
    temperature: float = 0.2
read src/limbo/agent.py ✓ Completed

基于分析,这个项目是一个基于 Textual 的 TUI Coding Agent,整体架构清晰:

architecture.md Markdown
# 核心架构
- Agent: 对话循环 orchestrator
- LLMClient: OpenAI-compatible streaming
- ToolRegistry: 7 个工具的统一注册与分发
- UI: Textual 三栏布局 (sidebar + chat + preview)

优化建议:

1. UI 层目前缺乏自定义样式,建议引入完整的 CSS 主题系统

2. Chat 区域消息展示过于简陋,需要消息气泡和代码高亮

3. 工具调用过程缺乏可视化,建议增加工具链步骤指示器

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src/limbo/agent.py Python
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import asyncio from typing import AsyncIterator class Agent: """Conversation loop orchestrator.""" def __init__( self, config: Config, llm_client: LLMClient, workdir: Path, ): self.config = config self.llm_client = llm_client self.workdir = workdir self.messages = [] async def run(self, user_input: str): # Main conversation loop pass