CHORE(app): limit token size

- Add token size constraints
- Optimize API usage

deploy/k8s/overlays/prod/kustomization.yaml

@@ -14,5 +14,5 @@ commonLabels:
 # 이미지 태그 설정 (ArgoCD Image Updater가 자동으로 업데이트)
 images:
   - name: gitea0213.kro.kr/bluemayne/mas
-    newTag: main-sha-d714e56d99b40d4c14e0c120d062237bb1e659c6
+    newTag: main-sha-422bf3e092c3f7c1228fad9fba7f8d615b8bcdba
 

services/backend/agents/research_agent.py

@@ -20,64 +20,27 @@ groq_research = ChatOpenAI(
 )
 
 
-RESEARCH_PROMPT = """You are the Research Agent in a Multi-Agent System.
+RESEARCH_PROMPT = """Research Agent: Collect system info via commands.
 
-## Role
-Collect and analyze information from the host system by requesting command executions.
+Request commands in JSON:
+{"commands": [{"tool": "execute_host", "command": "kubectl get nodes", "use_sudo": true}]}
 
-## Environment
-- Container: /app/
-- Host: Kubernetes cluster with kubectl access
-- Projects folder: /home/ubuntu/Projects/
+Rules:
+- Request 1-2 commands at a time
+- Use execute_host for kubectl/git, execute_bash for container
+- Output ONLY JSON when requesting commands
 
-## Your Task
-1. Analyze what information you need to gather
-2. Request commands to be executed
-3. Analyze the results
-4. Provide comprehensive findings
-
-## Command Request Format
-When you need to execute commands, output them in this EXACT JSON format:
-```json
+Final report format:
 {
-  "commands": [
-    {"tool": "execute_host", "command": "kubectl get nodes", "use_sudo": true},
-    {"tool": "execute_bash", "command": "ls -la /app"}
-  ]
-}
-```
-
-**IMPORTANT**:
-- Request 1-3 commands at a time (not too many!)
-- Use "execute_host" for host system commands (kubectl, git, etc.)
-- Use "execute_bash" for container commands
-- Set "use_sudo": true for kubectl commands
-- Output ONLY the JSON, nothing else when requesting commands
-
-## Final Report Format
-When you have enough information, provide a final report in JSON:
-```json
-{
-  "summary": "Brief summary of findings",
-  "findings": [
-    {"category": "Infrastructure", "data": "K8s cluster with 3 nodes..."},
-    {"category": "CI/CD", "data": "Current tools: ArgoCD..."}
-  ],
-  "recommendations": ["Consider X because Y", "..."],
+  "summary": "Brief findings",
+  "findings": [{"category": "...", "data": "..."}],
+  "recommendations": ["..."],
   "tekton_recommendation": {
     "should_use": true/false,
-    "reasons": ["reason 1", "reason 2"],
-    "alternatives": ["alternative 1", "alternative 2"]
+    "reasons": ["..."],
+    "alternatives": ["..."]
   }
 }
-```
-
-## Instructions
-- Start by requesting basic system info commands
-- Analyze results carefully
-- Request more specific commands based on findings
-- Provide actionable recommendations
-- Be concise and focused
 """
 
 
@@ -111,7 +74,7 @@ def research_node(state: AgentState) -> AgentState:
     ]
     
     tool_outputs = []
-    max_iterations = 5
+    max_iterations = 2
     iteration = 0
     
     while iteration < max_iterations:
@@ -144,7 +107,7 @@ def research_node(state: AgentState) -> AgentState:
                     commands_executed = True
                     results = []
                     
-                    for cmd_spec in commands_data["commands"][:5]:  # 최대 5개까지만
+                    for cmd_spec in commands_data["commands"][:2]:  # 최대 2개까지만 (토큰 절약)
                         tool_name = cmd_spec.get("tool", "execute_bash")
                         command = cmd_spec.get("command", "")
                         use_sudo = cmd_spec.get("use_sudo", False)
@@ -171,10 +134,15 @@ def research_node(state: AgentState) -> AgentState:
                             results.append(f"Command: {command}\nResult: {error_msg}")
                             print(error_msg)
                     
-                    # 결과를 대화에 추가
+                    # 결과를 대화에 추가 (최신 것만 유지)
                     results_text = "\n\n".join(results)
                     tool_outputs.append(results_text)
-                    conversation.append(HumanMessage(content=f"명령어 실행 결과:\n\n{results_text}\n\n계속 정보가 필요하면 추가 명령어를 요청하고, 충분한 정보를 수집했으면 최종 리포트를 JSON으로 제공해주세요."))
+                    # 전체 히스토리 대신 시스템 프롬프트 + 초기 요청 + 최신 결과만 유지
+                    conversation = [
+                        SystemMessage(content=RESEARCH_PROMPT),
+                        HumanMessage(content=research_request),
+                        HumanMessage(content=f"명령어 실행 결과:\n\n{results_text}\n\n계속 정보가 필요하면 추가 명령어를 요청하고, 충분한 정보를 수집했으면 최종 리포트를 JSON으로 제공해주세요.")
+                    ]
                     
                     continue  # 다음 반복으로