78 lines
1.7 KiB
Markdown
78 lines
1.7 KiB
Markdown
# ToolAgent
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基于 vLLM + opencode 的 AI 编程助手服务。
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## Requirements
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- NVIDIA GPU with ≥24 GiB memory (e.g. L20)
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- CUDA driver ≥570.x (CUDA 12.8)
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- Python 3.12
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## Installation
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```bash
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bash install.sh
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```
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或手动三步：
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```bash
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pip install torch==2.10.0 torchvision==0.25.0 \
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--index-url https://download.pytorch.org/whl/cu128
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pip install vllm==0.18.0 flashinfer-python==0.6.6
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pip install transformers==5.12.0
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```
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## 启动
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### 一键启动
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```bash
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./start.sh # 前后端同时启动
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./start.sh backend # 仅后端
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./start.sh frontend # 仅前端
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./start.sh all 3 # 指定 GPU 3
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```
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### 手动启动
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#### 后端 (vLLM)
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```bash
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source /home/kxqandccx/miniconda3/bin/activate agent_use
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CUDA_VISIBLE_DEVICES=2 nohup python server.py > server.log 2>&1 &
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```
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模型加载约 30-60 秒。日志在 `server.log`。
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#### 前端 (opencode web)
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```bash
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cd /home/kxqandccx/kxq/llm_tool_use
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nohup opencode web --port 3000 > web.log 2>&1 &
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```
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访问 `http://127.0.0.1:3000/`。
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## 验证
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```bash
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# 查看可用模型
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curl http://localhost:8000/v1/models
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# 文本对话
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curl http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{"model":"Qwen2.5-7B-Instruct","messages":[{"role":"user","content":"你好"}]}'
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# 工具调用
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curl http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model":"Qwen2.5-7B-Instruct",
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"messages":[{"role":"user","content":"北京天气"}],
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"tools":[{"type":"function","function":{"name":"get_weather","description":"获取天气","parameters":{"type":"object","properties":{"city":{"type":"string"}},"required":["city"]}}}],
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"tool_choice":"auto"
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}'
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```
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