agent1.0版本 前后端代码编辑agent

This commit is contained in:
handsomeAq 2026-07-30 14:34:51 +08:00
parent bda9cb7782
commit 18cf1c7e1a
8 changed files with 724 additions and 16 deletions

66
a2a_client.py Normal file
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"""
A2A 客户端测试脚本
通过 A2A 协议调用本地的 Dev Agent 服务
使用方式
python a2a_client.py "你好,介绍一下你自己"
python a2a_client.py --context my_session "你好" # 指定 context_id会话
"""
import asyncio
import sys
import argparse
from a2a.client import create_client
from a2a.types.a2a_pb2 import SendMessageRequest, Message, Part, Role
A2A_URL = "http://127.0.0.1:8001"
async def main():
parser = argparse.ArgumentParser(description="A2A 客户端测试")
parser.add_argument("message", help="发送给 agent 的消息")
parser.add_argument("--context", "-c", default="", help="context_id用于会话续传")
args = parser.parse_args()
print(f"连接到: {A2A_URL}")
if args.context:
print(f"会话: {args.context}")
print(f"发送: {args.message}")
print("-" * 40)
client = await create_client(A2A_URL)
try:
# 构建请求
request = SendMessageRequest(
message=Message(
role=Role.ROLE_USER,
parts=[Part(text=args.message)],
),
)
if args.context:
request.message.context_id = args.context
# 发送消息(流式返回)
full_text = ""
context_id = ""
async for response in client.send_message(request):
# 流式响应里可能有 message、status_update 等
if response.HasField("message"):
msg = response.message
if msg.context_id:
context_id = msg.context_id
for part in msg.parts:
if part.text:
full_text += part.text
print("Agent 回复:")
print(full_text)
if context_id:
print(f"\n(context_id: {context_id})")
finally:
await client.close()
if __name__ == "__main__":
asyncio.run(main())

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@ -26,24 +26,62 @@ os.environ["PYTHONUTF8"] = "1"
import uvicorn
from google.adk.a2a.utils.agent_to_a2a import to_a2a
from my_agent.agent import root_agent
from google.adk.runners import Runner
from google.adk.sessions.sqlite_session_service import SqliteSessionService
from google.adk.memory.in_memory_memory_service import InMemoryMemoryService
from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService
from my_agent.app import dev_app
# 配置
HOST = os.getenv("A2A_SERVER_HOST", "0.0.0.0")
HOST = os.getenv("A2A_SERVER_HOST", "0.0.0.0") # 监听地址
PORT = int(os.getenv("A2A_SERVER_PORT", "8001"))
# Agent Card 中对外公布的地址(客户端用这个来连接,不能用 0.0.0.0
PUBLIC_HOST = os.getenv("A2A_PUBLIC_HOST", "127.0.0.1")
# 数据目录
DATA_DIR = os.path.join(PROJECT_ROOT, "data")
os.makedirs(DATA_DIR, exist_ok=True)
# --- Session 服务SQLite 持久化(重启不丢失对话历史)---
session_service = SqliteSessionService(
db_path=os.path.join(DATA_DIR, "sessions.db")
)
# --- Memory 服务:长期记忆(先用内存版,后续可换 Chroma 等向量库)---
memory_service = InMemoryMemoryService()
# --- Artifact 服务:工件存储(大文件等)---
artifact_service = InMemoryArtifactService()
# --- 构建 Runner会话 + 记忆 + 压缩 一体化 ---
runner = Runner(
app=dev_app,
session_service=session_service,
memory_service=memory_service,
artifact_service=artifact_service,
auto_create_session=True,
)
# 用 ADK 官方工具把 agent 转成 A2A 服务
# 会自动生成 agent card暴露 /a2a/{agent_name} 端点
a2a_app = to_a2a(root_agent, port=PORT)
# 传入自定义 runner启用 SQLite 持久化 + 上下文压缩 + 记忆
a2a_app = to_a2a(
agent=dev_app.root_agent,
host=PUBLIC_HOST, # agent card 里用的对外地址
port=PORT,
runner=runner,
)
def main():
print("=" * 60)
print("Dev Agent A2A Server 启动中...")
print(f" 监听地址: http://{HOST}:{PORT}")
print(f" A2A 端点: http://{HOST}:{PORT}/a2a/{root_agent.name}")
print(f" Agent 卡片: http://{HOST}:{PORT}/.well-known/agent-card.json")
print(f" 对外地址: http://{PUBLIC_HOST}:{PORT}")
print(f" A2A 端点: http://{PUBLIC_HOST}:{PORT}/")
print(f" Agent 卡片: http://{PUBLIC_HOST}:{PORT}/.well-known/agent-card.json")
print(f" 会话持久化: SQLite ({DATA_DIR}/sessions.db)")
print(f" 上下文压缩: 每 20 轮自动摘要")
print("=" * 60)
uvicorn.run(a2a_app, host=HOST, port=PORT, log_level="info")

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api_server.py Normal file
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"""
Dev Agent API Server
使用 ADK 官方 ApiServer 构建 REST API 服务支持
- REST API 调用 agent/run/run_sse
- 会话管理创建/获取/删除SQLite 持久化
- Swagger UI 交互式文档/docs
- 上下文自动压缩
- 长期记忆InMemory后续可换向量库
启动方式
python api_server.py
主要端点
GET /list-apps 列出所有 agent
POST /run 同步运行 agent
POST /run_sse 流式运行 agentSSE
GET /apps/{app}/users/{user}/sessions/{session} 获取会话
POST /apps/{app}/users/{user}/sessions/{session} 创建会话
GET /docs Swagger UI
"""
import os
import sys
# 确保项目根目录在 path 里
PROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
from dotenv import load_dotenv
load_dotenv(os.path.join(PROJECT_ROOT, "my_agent", ".env"))
# 强制 UTF-8
os.environ["PYTHONUTF8"] = "1"
import uvicorn
from google.adk.cli.api_server import ApiServer
from google.adk.cli.utils.base_agent_loader import BaseAgentLoader
from google.adk.sessions.sqlite_session_service import SqliteSessionService
from google.adk.memory.in_memory_memory_service import InMemoryMemoryService
from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService
from google.adk.auth.credential_service.in_memory_credential_service import InMemoryCredentialService
from google.adk.evaluation.in_memory_eval_sets_manager import InMemoryEvalSetsManager
from google.adk.evaluation.local_eval_set_results_manager import LocalEvalSetResultsManager
from my_agent.app import dev_app
# 配置
HOST = os.getenv("API_SERVER_HOST", "0.0.0.0")
PORT = int(os.getenv("API_SERVER_PORT", "8001"))
# 数据目录
DATA_DIR = os.path.join(PROJECT_ROOT, "data")
os.makedirs(DATA_DIR, exist_ok=True)
class DevAgentLoader(BaseAgentLoader):
"""自定义 agent 加载器,直接返回我们的 App 对象(带 compaction 配置)"""
def load_agent(self, agent_name: str):
if agent_name == dev_app.name:
return dev_app
raise ValueError(f"Agent not found: {agent_name}")
def list_agents(self) -> list[str]:
return [dev_app.name]
def create_api_server() -> ApiServer:
"""构造 ApiServer 实例"""
# 会话服务SQLite 持久化
session_service = SqliteSessionService(
db_path=os.path.join(DATA_DIR, "sessions.db")
)
# 记忆服务:长期记忆(先用内存版)
memory_service = InMemoryMemoryService()
# 工件服务
artifact_service = InMemoryArtifactService()
# 认证服务(暂不需要,内存版占位)
credential_service = InMemoryCredentialService()
# 评测集管理(暂不需要,占位)
eval_sets_manager = InMemoryEvalSetsManager()
eval_set_results_manager = LocalEvalSetResultsManager(agents_dir=DATA_DIR)
return ApiServer(
agent_loader=DevAgentLoader(),
session_service=session_service,
memory_service=memory_service,
artifact_service=artifact_service,
credential_service=credential_service,
eval_sets_manager=eval_sets_manager,
eval_set_results_manager=eval_set_results_manager,
agents_dir=os.path.join(PROJECT_ROOT, "my_agent"),
auto_create_session=True,
)
def main():
api_server = create_api_server()
fastapi_app = api_server.get_fast_api_app()
print("=" * 60)
print("Dev Agent API Server 启动中...")
print(f" 监听地址: http://{HOST}:{PORT}")
print(f" Swagger UI: http://{HOST}:{PORT}/docs")
print(f" 同步运行: POST http://{HOST}:{PORT}/run")
print(f" 流式运行: POST http://{HOST}:{PORT}/run_sse")
print(f" 列出agent: GET http://{HOST}:{PORT}/list-apps")
print(f" 会话持久化: SQLite ({DATA_DIR}/sessions.db)")
print(f" 上下文压缩: 已启用")
print("=" * 60)
uvicorn.run(fastapi_app, host=HOST, port=PORT, log_level="info")
if __name__ == "__main__":
main()

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chat.py Normal file
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"""
Dev Agent 命令行交互工具
使用配置好的 RunnerSQLite 会话持久化 + Memory + 上下文压缩
退出后再次进入同一个 session_id 可以继续对话
使用方式
python chat.py # 新会话,自动生成 session_id
python chat.py --session my_session # 指定 session_id
python chat.py --list # 列出所有会话
python chat.py --delete my_session # 删除某个会话
"""
import os
import sys
import asyncio
import argparse
# 确保项目根目录在 path 里
PROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
from dotenv import load_dotenv
load_dotenv(os.path.join(PROJECT_ROOT, "my_agent", ".env"))
# 强制 UTF-8
os.environ["PYTHONUTF8"] = "1"
from google.adk.runners import Runner
from google.adk.sessions.sqlite_session_service import SqliteSessionService
from google.adk.memory.in_memory_memory_service import InMemoryMemoryService
from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService
from google.genai import types
from my_agent.app import dev_app
# 数据目录
DATA_DIR = os.path.join(PROJECT_ROOT, "data")
os.makedirs(DATA_DIR, exist_ok=True)
# 同一个数据库A2A server 和 CLI 共享
DB_PATH = os.path.join(DATA_DIR, "sessions.db")
USER_ID = "local_user"
def get_runner() -> Runner:
"""创建带 SQLite 会话持久化的 Runner"""
session_service = SqliteSessionService(db_path=DB_PATH)
memory_service = InMemoryMemoryService()
artifact_service = InMemoryArtifactService()
return Runner(
app=dev_app,
session_service=session_service,
memory_service=memory_service,
artifact_service=artifact_service,
auto_create_session=True,
)
async def list_sessions():
"""列出所有会话"""
runner = get_runner()
response = await runner.session_service.list_sessions(
app_name=dev_app.name,
user_id=USER_ID,
)
sessions = response.sessions
if not sessions:
print("(暂无会话)")
return
print(f"{len(sessions)} 个会话:\n")
for s in sessions:
# 取第一条用户消息作为摘要
preview = ""
for e in s.events:
if e.content and e.content.parts and e.author == "user":
text = e.content.parts[0].text[:50]
preview = f"{text}"
break
print(f" [{s.id}] {preview}")
print(f" 更新时间: {s.last_update_time}")
async def delete_session(session_id: str):
"""删除指定会话"""
runner = get_runner()
try:
await runner.session_service.delete_session(
app_name=dev_app.name,
user_id=USER_ID,
session_id=session_id,
)
print(f"会话 [{session_id}] 已删除")
except Exception as e:
print(f"删除失败: {e}")
async def chat(session_id: str | None = None):
"""交互式对话"""
runner = get_runner()
# 如果没有指定 session_id自动创建
if not session_id:
session = await runner.session_service.create_session(
app_name=dev_app.name,
user_id=USER_ID,
)
session_id = session.id
print(f"新会话已创建session_id: {session_id}")
print(f"下次可用 `python chat.py --session {session_id}` 继续\n")
print(f"=== Dev Agent 对话 ===")
print(f"Session: {session_id}")
print(f"输入消息开始对话,输入 quit / exit 退出\n")
while True:
try:
user_input = input("你: ").strip()
except (EOFError, KeyboardInterrupt):
print("\n再见!")
break
if not user_input:
continue
if user_input.lower() in ("quit", "exit", "退出"):
print("再见!")
break
print("花花: ", end="", flush=True)
try:
full_response = ""
async for event in runner.run_async(
user_id=USER_ID,
session_id=session_id,
new_message=types.Content(parts=[types.Part(text=user_input)]),
):
if event.is_final_response():
# 最终回复
for part in event.content.parts:
if hasattr(part, "text") and part.text:
print(part.text, end="", flush=True)
full_response += part.text
print()
except Exception as e:
print(f"\n[出错] {e}")
print()
def main():
parser = argparse.ArgumentParser(description="Dev Agent 命令行交互工具")
parser.add_argument("--session", "-s", help="会话 ID指定后继续该会话")
parser.add_argument("--list", "-l", action="store_true", help="列出所有会话")
parser.add_argument("--delete", "-d", help="删除指定会话")
args = parser.parse_args()
if args.list:
asyncio.run(list_sessions())
elif args.delete:
asyncio.run(delete_session(args.delete))
else:
asyncio.run(chat(args.session))
if __name__ == "__main__":
main()

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mcp_dev_agent/README.md Normal file
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@ -0,0 +1,59 @@
# Dev Agent MCP Server
将 Dev Agent 封装为 MCP 工具,供 CodeBuddy / Cursor / Windsurf 等 MCP 客户端调用。
## 功能
- **run_dev_agent** — 调用 Dev Agent 执行开发子任务
- 支持文件读写、终端命令执行、编译验证
- 支持指定 `session_id` 进行多轮对话
## 配置方法
### CodeBuddy
在 CodeBuddy 的 MCP 配置中添加:
```json
{
"mcpServers": {
"dev-agent": {
"command": "python",
"args": ["d:/nzy/workspace_python/agent/mcp_dev_agent/server.py"],
"env": {
"DEV_AGENT_API_URL": "http://127.0.0.1:8001",
"DEV_AGENT_APP_NAME": "dev_agent",
"DEV_AGENT_USER_ID": "codebuddy"
}
}
}
}
```
### 环境变量
| 变量 | 默认值 | 说明 |
|------|--------|------|
| `DEV_AGENT_API_URL` | `http://127.0.0.1:8001` | Dev Agent API Server 地址 |
| `DEV_AGENT_APP_NAME` | `dev_agent` | Agent 名称 |
| `DEV_AGENT_USER_ID` | `codebuddy` | 用户 ID用于会话隔离 |
## 使用前提
1. 先启动 Dev Agent API Server
```bash
python api_server.py
```
2. 配置 MCP server见上方配置方法
3. 重启 CodeBuddy / IDE
## 工具参数
### run_dev_agent
| 参数 | 必填 | 说明 |
|------|------|------|
| `task` | ✅ | 任务描述,越详细越好 |
| `session_id` | ❌ | 会话 ID不传则用 `default`。用于多轮对话续聊 |

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mcp_dev_agent/server.py Normal file
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"""
Dev Agent MCP Server
Dev Agent 封装为 MCP 工具 CodeBuddy MCP 客户端调用
功能
- run_dev_agent: 提交任务给 Dev Agent 执行返回执行结果
- 支持指定 session_id 进行多轮对话
- 自动提取最终回复文本
启动方式MCP 配置
{
"mcpServers": {
"dev-agent": {
"command": "python",
"args": ["d:/nzy/workspace_python/agent/mcp_dev_agent/server.py"],
"env": {
"DEV_AGENT_API_URL": "http://127.0.0.1:8001",
"DEV_AGENT_APP_NAME": "dev_agent",
"DEV_AGENT_USER_ID": "codebuddy"
}
}
}
}
"""
import os
import json
import asyncio
import sys
from typing import Any
import httpx
from mcp.server import Server
from mcp.types import Tool, TextContent
from mcp.server.stdio import stdio_server
# 配置
DEV_AGENT_API_URL = os.getenv("DEV_AGENT_API_URL", "http://127.0.0.1:8001")
DEV_AGENT_APP_NAME = os.getenv("DEV_AGENT_APP_NAME", "dev_agent")
DEV_AGENT_USER_ID = os.getenv("DEV_AGENT_USER_ID", "codebuddy")
# MCP Server
server = Server("dev-agent-mcp")
@server.list_tools()
async def list_tools() -> list[Tool]:
"""列出可用工具"""
return [
Tool(
name="run_dev_agent",
description=(
"调用 Dev Agent全栈开发子 Agent执行开发任务。\n"
"Dev Agent 可以读写文件、运行终端命令、执行编译/构建/测试。\n"
"适用于代码编写、bug 修复、项目搭建、编译验证等开发子任务。\n"
"传参说明task 是任务描述session_id 可选,不传则创建新会话。"
),
inputSchema={
"type": "object",
"properties": {
"task": {
"type": "string",
"description": "要 Dev Agent 执行的任务描述,越详细越好",
},
"session_id": {
"type": "string",
"description": "可选,会话 ID用于多轮对话/续聊",
},
},
"required": ["task"],
},
),
]
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
"""调用工具"""
if name == "run_dev_agent":
return await _run_dev_agent(arguments)
else:
raise ValueError(f"Unknown tool: {name}")
async def _run_dev_agent(args: dict[str, Any]) -> list[TextContent]:
"""调用 Dev Agent API 执行任务"""
task = args.get("task", "").strip()
session_id = args.get("session_id") or "default"
if not task:
return [TextContent(type="text", text="错误task 不能为空")]
# 构造请求
payload = {
"appName": DEV_AGENT_APP_NAME,
"userId": DEV_AGENT_USER_ID,
"sessionId": session_id,
"newMessage": {
"role": "user",
"parts": [{"text": task}],
},
}
try:
async with httpx.AsyncClient(timeout=600.0) as client: # 10 分钟超时
response = await client.post(
f"{DEV_AGENT_API_URL}/run",
json=payload,
headers={"Content-Type": "application/json"},
)
if response.status_code != 200:
return [TextContent(
type="text",
text=f"调用 Dev Agent 失败HTTP {response.status_code}:\n{response.text[:500]}"
)]
events = response.json()
except httpx.ConnectError:
return [TextContent(
type="text",
text=f"无法连接到 Dev Agent API Server{DEV_AGENT_API_URL}\n"
f"请确认 api_server.py 是否已启动。"
)]
except Exception as e:
return [TextContent(type="text", text=f"调用 Dev Agent 出错: {e}")]
# 从事件列表中提取最终回复
result_text = _extract_final_response(events, session_id)
return [TextContent(type="text", text=result_text)]
def _extract_final_response(events: list[dict], session_id: str) -> str:
"""从事件列表中提取 agent 的最终文本回复"""
if not events:
return "(无返回事件)"
final_text_parts = []
for event in events:
content = event.get("content", {})
role = content.get("role", "")
parts = content.get("parts", [])
author = event.get("author", "")
if role == "model" and author == DEV_AGENT_APP_NAME:
for part in parts:
if "text" in part:
final_text_parts.append(part["text"])
response = "\n".join(final_text_parts).strip()
if not response:
# 如果没有找到最终回复,返回事件摘要
summary = f"{len(events)} 个事件\n"
for e in events[-5:]:
content = e.get("content", {})
parts = content.get("parts", [])
role = content.get("role", "")
author = e.get("author", "")
part_types = [list(p.keys())[0] for p in parts]
summary += f" - [{role}] {author}: {part_types}\n"
response = f"(未提取到最终文本回复)\n{summary}"
# 附上 session_id 方便续聊
response += f"\n\n---\nsession_id: {session_id}"
return response
async def main():
"""stdio 模式启动 MCP server"""
async with stdio_server() as (read_stream, write_stream):
await server.run(read_stream, write_stream, None)
if __name__ == "__main__":
# 确保 Windows 下 stdio 用二进制模式
if sys.platform == "win32":
import msvcrt
msvcrt.setmode(sys.stdin.fileno(), os.O_BINARY)
msvcrt.setmode(sys.stdout.fileno(), os.O_BINARY)
asyncio.run(main())

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@ -3,6 +3,7 @@ from google.adk.models.lite_llm import LiteLlm
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams
from google.adk.tools.function_tool import FunctionTool
from google.adk.tools import preload_memory
from mcp.client.stdio import StdioServerParameters
import os
import asyncio
@ -30,13 +31,47 @@ filesystem_mcp = McpToolset(
os.path.abspath(WORKSPACE_DIR),
],
),
timeout=30.0,
timeout=300000,
),
)
# --- 网页抓取 MCP 工具Fetch---
# 暂时注释:请求体过大导致 413 错误,后续需要时再启用
# fetch_mcp = McpToolset(
# connection_params=StdioConnectionParams(
# server_params=StdioServerParameters(
# command="npx",
# args=[
# "-y",
# "@modelcontextprotocol/server-fetch",
# ],
# ),
# timeout=300000,
# ),
# )
# --- Tavily 搜索 MCP 工具 ---
# 暂时注释:请求体过大导致 413 错误,后续需要时再启用
# tavily_api_key = os.getenv("TAVILY_API_KEY", "")
# tavily_mcp = McpToolset(
# connection_params=StdioConnectionParams(
# server_params=StdioServerParameters(
# command="npx",
# args=[
# "-y",
# "tavily-mcp@latest",
# ],
# env={
# "TAVILY_API_KEY": tavily_api_key,
# },
# ),
# timeout=300000,
# ),
# )
# --- 终端命令执行工具Python 原生,绕开 MCP 通信问题)---
async def run_command(command: str, cwd: str = None, timeout: int = 300) -> str:
async def run_command(command: str, cwd: str = None, timeout: int = 300000) -> str:
"""
在终端中执行一条命令返回输出结果
@ -94,6 +129,20 @@ async def run_command(command: str, cwd: str = None, timeout: int = 300) -> str:
# 注册为 ADK 工具
run_command_tool = FunctionTool(run_command)
# --- 记忆自动保存回调 ---
async def auto_save_memory_callback(callback_context):
"""
每轮对话结束后自动将会话保存到长期记忆中
memory_service 未配置时静默忽略
"""
try:
await callback_context.add_session_to_memory()
except (ValueError, AttributeError):
# memory_service 未配置或不可用时跳过
pass
root_agent = LlmAgent(
model=LiteLlm(
model=model_name,
@ -104,13 +153,12 @@ root_agent = LlmAgent(
name="dev_agent",
description="全栈开发子 Agent可以读写文件、浏览目录、执行开发任务。",
instruction=(
"姓名:花花✿\n"
"性别:女\n"
"籍贯东北辽宁沈阳地道东北姑娘26 岁\n"
"职业资深全栈开发工程师5 年一线企业级开发经验\n"
"外形气质:性格爽朗大方,说话直爽不绕弯,共情力强;做事严谨较真,技术上极度靠谱,\n"
"生活里接地气、热心肠;不矫情,能扛项目压力,也会温柔安抚焦虑的开发同事\n"
"由主控调度执行具体的开发任务。\n"
"全栈开发子 Agent\n"
"\n"
"## 记忆能力\n"
"- 你拥有长期记忆,之前和用户的对话中提到的项目信息、技术偏好、任务历史都会被记住\n"
"- 系统会自动从记忆中检索与当前任务相关的历史上下文,注入到对话中\n"
"- 重要的项目信息(技术栈、目录结构、编码规范等)会自动沉淀到记忆里\n"
"\n"
"## 工作流程\n"
"1. 先理解任务需求和项目上下文\n"
@ -123,6 +171,7 @@ root_agent = LlmAgent(
"- 所有文件操作限定在分配的工作目录范围内\n"
"- 你拥有的工具:文件系统操作(读/写/列目录)、终端命令执行\n"
"- 你可以自主完成代码编写、bug 修复、样式调整、接口修改、简单重构\n"
"- 遇到不熟悉的技术或 API先查阅项目内的现有代码和文档参考\n"
"- 需要上报的情况:\n"
" • 架构设计或重大技术选型决策\n"
" • 依赖包版本不兼容导致的编译/运行时错误(需要升级/降级依赖时)\n"
@ -146,5 +195,6 @@ root_agent = LlmAgent(
"**验证结果**:编译/测试是否通过,如有警告需列出\n"
"**需要主控关注**:如有需要上报的问题,详细说明"
),
tools=[filesystem_mcp, run_command_tool],
tools=[filesystem_mcp, run_command_tool, preload_memory],
after_agent_callback=auto_save_memory_callback,
)

23
my_agent/app.py Normal file
View File

@ -0,0 +1,23 @@
"""
Dev Agent App 配置
使用 ADK App 包装 agent配置上下文压缩插件等
"""
from google.adk.apps import App
from google.adk.apps._configs import EventsCompactionConfig # 实验性 API
from my_agent.agent import root_agent
# 上下文压缩配置(长对话自动摘要,防止爆 context window
compaction_config = EventsCompactionConfig(
compaction_interval=20, # 每 20 个用户轮次压缩一次
overlap_size=3, # 重叠 3 轮,保持连续性
token_threshold=50000, # token 超 50k 紧急压缩
event_retention_size=30, # 压缩时保留最近 30 条原始事件
)
# App 容器:管理 agent + 压缩配置
dev_app = App(
name="dev_agent",
root_agent=root_agent,
events_compaction_config=compaction_config,
)