Mayne0213
fd0936d275
- Minimize code_backend, code_frontend, code_infrastructure, review prompts - Switch to English for token efficiency - Remove verbose guidelines, keep essentials only
102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
"""
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Backend Code Agent (Groq)
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백엔드 코드 작성/수정 전문 (FastAPI, Node.js, Database)
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"""
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import SystemMessage, HumanMessage
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from .state import AgentState
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from tools.bash_tool import bash_tools
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import os
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# Groq 모델 초기화
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groq_backend = ChatOpenAI(
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model="llama-3.3-70b-versatile",
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api_key=os.getenv("GROQ_API_KEY"),
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base_url="https://api.groq.com/openai/v1",
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temperature=0.5
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)
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BACKEND_PROMPT = """You are the Backend Code Agent.
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## Role
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Write backend code (FastAPI, Node.js, databases).
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## Tools
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- execute_host: Write files to /home/ubuntu/Projects/, run git commands
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- execute_bash: Test and validate
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## Important
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- After modifying files: git add, commit, and push (ArgoCD deploys automatically)
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- Write clean, secure code with proper error handling
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"""
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def backend_code_node(state: AgentState) -> AgentState:
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"""
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Backend Code 노드: 백엔드 코드 작성
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"""
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messages = state["messages"]
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task_plan = state.get("task_plan", {})
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research_data = state.get("research_data", {})
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# Groq에 bash 도구 바인딩
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groq_with_tools = groq_backend.bind_tools(bash_tools)
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# 코드 작성 요청 구성
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code_request = f"""
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작업 계획: {task_plan.get('summary', '')}
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수집된 정보: {research_data.get('summary', '')}
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다음 백엔드 코드를 작성해주세요.
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"""
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# Groq 호출
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response = groq_with_tools.invoke([
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SystemMessage(content=BACKEND_PROMPT),
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HumanMessage(content=code_request)
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])
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# Tool calls 처리
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tool_outputs = []
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if hasattr(response, 'tool_calls') and response.tool_calls:
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for tool_call in response.tool_calls:
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tool_name = tool_call['name']
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tool_args = tool_call.get('args', {})
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try:
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# tool_name에 따라 올바른 도구 선택
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from tools.bash_tool import execute_bash, execute_host
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if tool_name == "execute_host":
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tool_func = execute_host
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else:
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tool_func = execute_bash
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tool_result = tool_func.invoke(tool_args)
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tool_outputs.append(f"\n🔧 **{tool_name}({tool_args.get('command', '')[:50]}...)**:\n{tool_result}")
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except Exception as e:
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tool_outputs.append(f"\n❌ **{tool_name}** failed: {str(e)}")
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# Tool 결과와 함께 재호출
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if tool_outputs:
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tool_context = "\n".join(tool_outputs)
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response = groq_backend.invoke([
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SystemMessage(content=BACKEND_PROMPT),
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HumanMessage(content=code_request),
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HumanMessage(content=f"도구 실행 결과:\n{tool_context}\n\n작업 결과를 요약해주세요.")
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])
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content = response.content
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if tool_outputs:
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content = "\n".join(tool_outputs) + "\n\n" + content
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# 상태 업데이트
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state["code_outputs"]["backend"] = content
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state["messages"].append({
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"role": "backend_developer",
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"content": content
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})
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state["current_agent"] = "orchestrator"
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return state
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