From 14c9bd00c76ce117c3c6b038984bbd7847729d89 Mon Sep 17 00:00:00 2001
From: Amith M P <amithmp676@gmail.com>
Date: Sun, 26 Oct 2025 19:45:53 +0530
Subject: [PATCH 1/4] Chatbot init

---
 backend/app/agents/chatbot_agent.py     | 69 ++++++++++++++++++
 backend/app/api/chat.py                 | 39 ++++++++++
 backend/main.py                         |  5 +-
 frontend/app/api/chat/route.ts          | 29 ++++++++
 frontend/app/layout.tsx                 |  2 +
 frontend/components/chat/Chat.tsx       | 16 ++++
 frontend/components/chat/ChatButton.tsx | 16 ++++
 frontend/components/chat/ChatDialog.tsx | 97 +++++++++++++++++++++++++
 frontend/components/index.ts            |  3 +-
 frontend/lib/api/chat.ts                | 17 +++++
 frontend/lib/api/client.ts              |  2 +-
 11 files changed, 291 insertions(+), 4 deletions(-)
 create mode 100644 backend/app/agents/chatbot_agent.py
 create mode 100644 backend/app/api/chat.py
 create mode 100644 frontend/app/api/chat/route.ts
 create mode 100644 frontend/components/chat/Chat.tsx
 create mode 100644 frontend/components/chat/ChatButton.tsx
 create mode 100644 frontend/components/chat/ChatDialog.tsx
 create mode 100644 frontend/lib/api/chat.ts

diff --git a/backend/app/agents/chatbot_agent.py b/backend/app/agents/chatbot_agent.py
new file mode 100644
index 0000000..ff24c47
--- /dev/null
+++ b/backend/app/agents/chatbot_agent.py
@@ -0,0 +1,69 @@
+from typing import Dict, Any, Optional
+from .base import ProactivePulseAgent
+from .orchestrator import OrchestratorAgent
+import boto3
+import json
+import logging
+
+logger = logging.getLogger(__name__)
+
+class ChatbotAgent(ProactivePulseAgent):
+    """Chatbot agent using AWS Bedrock for natural language interactions."""
+    
+    def __init__(self, config):
+        super().__init__(
+            name="Chatbot Agent",
+            description="Natural language interface powered by AWS Bedrock"
+        )
+        
+        self.config = config
+        self.orchestrator = OrchestratorAgent()
+        self.bedrock_client = boto3.client('bedrock-runtime')
+        
+    async def process_message(self, message: str, conversation_id: str = None) -> Dict[str, Any]:
+        try:
+            # Prepare the prompt for Bedrock
+            prompt = {
+                "prompt": message,
+                "max_tokens": 512,
+                "temperature": 0.7,
+                "model": self.config.aws_bedrock_model_text
+            }
+            
+            # Get response from Bedrock
+            response = self.bedrock_client.invoke_model(
+                modelId=self.config.aws_bedrock_model_text,
+                body=json.dumps(prompt)
+            )
+            
+            # Parse response and determine if we need to call other agents
+            response_body = json.loads(response['body'].read())
+            
+            # Check if we need to perform any specific actions
+            if "analyze" in message.lower():
+                analysis_results = await self.orchestrator.run_analysis()
+                return {
+                    "type": "analysis",
+                    "message": response_body['completion'],
+                    "data": analysis_results
+                }
+            
+            if "health" in message.lower():
+                health_status = await self.orchestrator.get_health_status()
+                return {
+                    "type": "health",
+                    "message": response_body['completion'],
+                    "data": health_status
+                }
+            
+            return {
+                "type": "chat",
+                "message": response_body['completion']
+            }
+            
+        except Exception as e:
+            logger.error(f"ChatbotAgent error: {str(e)}")
+            return {
+                "type": "error",
+                "message": "I encountered an error processing your request."
+            }
\ No newline at end of file
diff --git a/backend/app/api/chat.py b/backend/app/api/chat.py
new file mode 100644
index 0000000..0cfa650
--- /dev/null
+++ b/backend/app/api/chat.py
@@ -0,0 +1,39 @@
+from fastapi import APIRouter, Depends
+from pydantic import BaseModel
+from typing import Dict, Any, Optional
+from ..agents.chatbot_agent import ChatbotAgent
+from ..config import get_settings
+import logging
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/chat", tags=["chat"])
+
+class ChatMessage(BaseModel):
+    text: str
+
+class ChatResponse(BaseModel):
+    type: str
+    message: str
+    data: Optional[Dict[str, Any]] = None
+
+@router.post("/", response_model=ChatResponse)
+async def process_chat(
+    message: ChatMessage,
+    settings = Depends(get_settings)
+):
+    try:
+        # Create chatbot instance with settings
+        chatbot = ChatbotAgent(settings)
+        
+        # Process message
+        response = await chatbot.process_message(message.text)
+        return response
+        
+    except Exception as e:
+        logger.error(f"Chat processing error: {str(e)}")
+        return ChatResponse(
+            type="error",
+            message="An error occurred while processing your message",
+            data={"error": str(e)}
+        )
\ No newline at end of file
diff --git a/backend/main.py b/backend/main.py
index 06fce55..ae99664 100644
--- a/backend/main.py
+++ b/backend/main.py
@@ -16,7 +16,7 @@
 import sys
 from io import StringIO
 from app.config import get_settings
-from app.api import insights, analysis, health
+from app.api import chat, insights, analysis, health
 from app.utils.logging import setup_logging
 from app.agents.orchestrator import OrchestratorAgent
 from app.storage.factory import get_storage_service
@@ -138,7 +138,7 @@ async def lifespan(app: FastAPI):
 # Add CORS middleware
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=settings.allowed_origins,
+    allow_origins=["http://localhost:3000"],
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
@@ -173,6 +173,7 @@ async def global_exception_handler(request: Request, exc: Exception):
 
 
 # Include routers
+app.include_router(chat.router)
 app.include_router(health.router, prefix="/health", tags=["health"])
 app.include_router(insights.router, prefix="/insights", tags=["insights"])
 app.include_router(analysis.router, prefix="/analysis", tags=["analysis"])
diff --git a/frontend/app/api/chat/route.ts b/frontend/app/api/chat/route.ts
new file mode 100644
index 0000000..509aed1
--- /dev/null
+++ b/frontend/app/api/chat/route.ts
@@ -0,0 +1,29 @@
+import { NextResponse } from 'next/server'
+
+export async function POST(req: Request) {
+  try {
+    const body = await req.json()
+    
+    const response = await fetch('http://localhost:8000/api/chat/', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify(body)
+    })
+
+    const data = await response.json()
+    return NextResponse.json(data)
+    
+  } catch (error) {
+    console.error('Chat API error:', error)
+    return NextResponse.json(
+      { 
+        type: 'error',
+        message: 'Failed to process chat message',
+        data: { error: error instanceof Error ? error.message : String(error) }
+      },
+      { status: 500 }
+    )
+  }
+}
\ No newline at end of file
diff --git a/frontend/app/layout.tsx b/frontend/app/layout.tsx
index 725c913..2facc0d 100644
--- a/frontend/app/layout.tsx
+++ b/frontend/app/layout.tsx
@@ -6,6 +6,7 @@ import { SidebarProvider } from '@/components/layout/MainLayout';
 import { Toaster } from 'react-hot-toast';
 import { SWRConfig } from 'swr';
 import { REFRESH_INTERVAL } from '@/lib/utils/constants';
+import { Chat } from '@/components/chat/Chat';
 
 const inter = Inter({ subsets: ['latin'] });
 
@@ -55,6 +56,7 @@ export default function RootLayout({
             </SWRConfig>
           </SidebarProvider>
         </ThemeProvider>
+        <Chat />
       </body>
     </html>
   );
diff --git a/frontend/components/chat/Chat.tsx b/frontend/components/chat/Chat.tsx
new file mode 100644
index 0000000..d4610eb
--- /dev/null
+++ b/frontend/components/chat/Chat.tsx
@@ -0,0 +1,16 @@
+'use client';
+
+import React, { useState } from 'react';
+import { ChatButton } from './ChatButton';
+import { ChatDialog } from './ChatDialog';
+
+export const Chat: React.FC = () => {
+  const [isOpen, setIsOpen] = useState(false);
+
+  return (
+    <>
+      {!isOpen && <ChatButton onClick={() => setIsOpen(true)} />}
+      {isOpen && <ChatDialog onClose={() => setIsOpen(false)} />}
+    </>
+  );
+};
\ No newline at end of file
diff --git a/frontend/components/chat/ChatButton.tsx b/frontend/components/chat/ChatButton.tsx
new file mode 100644
index 0000000..1abb6ad
--- /dev/null
+++ b/frontend/components/chat/ChatButton.tsx
@@ -0,0 +1,16 @@
+'use client';
+
+import React from 'react';
+import { ChatBubbleLeftIcon } from '@heroicons/react/24/outline';
+
+export const ChatButton: React.FC<{ onClick: () => void }> = ({ onClick }) => {
+  return (
+    <button
+      onClick={onClick}
+      className="fixed bottom-6 right-6 p-4 bg-blue-600 text-white rounded-full shadow-lg hover:bg-blue-700 transition-all"
+      aria-label="Open Chat"
+    >
+      <ChatBubbleLeftIcon className="h-6 w-6" />
+    </button>
+  );
+};
\ No newline at end of file
diff --git a/frontend/components/chat/ChatDialog.tsx b/frontend/components/chat/ChatDialog.tsx
new file mode 100644
index 0000000..5acb129
--- /dev/null
+++ b/frontend/components/chat/ChatDialog.tsx
@@ -0,0 +1,97 @@
+'use client';
+
+import React, { useState } from 'react';
+import { XMarkIcon } from '@heroicons/react/24/outline';
+import { Card } from '../shared/Card';
+import { Button } from '../shared/Button';
+import { LoadingSpinner } from '../shared/LoadingSpinner';
+import { sendChatMessage } from '../../lib/api/chat';
+import type { ChatResponse } from '../../lib/api/chat';
+
+interface Message {
+  type: 'user' | 'bot';
+  text: string;
+  data?: any;
+}
+
+export const ChatDialog: React.FC<{ onClose: () => void }> = ({ onClose }) => {
+  const [messages, setMessages] = useState<Message[]>([]);
+  const [input, setInput] = useState('');
+  const [isLoading, setIsLoading] = useState(false);
+
+  const sendMessage = async () => {
+    if (!input.trim() || isLoading) return;
+
+    try {
+      setIsLoading(true);
+      setMessages(prev => [...prev, { type: 'user', text: input }]);
+
+      const response = await sendChatMessage({ text: input });
+      
+      setMessages(prev => [...prev, { 
+        type: 'bot', 
+        text: response.message,
+        data: response.data 
+      }]);
+      
+    } catch (error) {
+      console.error('Chat error:', error);
+      setMessages(prev => [...prev, {
+        type: 'bot',
+        text: 'Sorry, I encountered an error processing your request.'
+      }]);
+    } finally {
+      setIsLoading(false);
+      setInput('');
+    }
+  };
+
+  return (
+    <div className="fixed bottom-24 right-6 w-96 shadow-2xl rounded-lg bg-white dark:bg-gray-800">
+      <Card>
+        <div className="flex justify-between items-center p-4 border-b">
+          <h3 className="font-semibold">ProactivePulse AI Assistant</h3>
+          <button onClick={onClose} className="text-gray-500 hover:text-gray-700">
+            <XMarkIcon className="h-5 w-5" />
+          </button>
+        </div>
+        
+        <div className="h-[400px] overflow-y-auto p-4 space-y-4">
+          {messages.map((msg, i) => (
+            <div key={i} className={`flex ${msg.type === 'user' ? 'justify-end' : 'justify-start'}`}>
+              <div className={`max-w-[80%] rounded-lg p-3 ${
+                msg.type === 'user' 
+                  ? 'bg-blue-600 text-white' 
+                  : 'bg-gray-100 dark:bg-gray-700'
+              }`}>
+                <p>{msg.text}</p>
+                {msg.data && (
+                  <pre className="mt-2 text-xs bg-black/10 p-2 rounded overflow-x-auto">
+                    {JSON.stringify(msg.data, null, 2)}
+                  </pre>
+                )}
+              </div>
+            </div>
+          ))}
+        </div>
+
+        <div className="p-4 border-t">
+          <div className="flex gap-2">
+            <input
+              type="text"
+              value={input}
+              onChange={(e) => setInput(e.target.value)}
+              onKeyPress={(e) => e.key === 'Enter' && sendMessage()}
+              placeholder="Ask me anything..."
+              className="flex-1 p-2 border rounded"
+              disabled={isLoading}
+            />
+            <Button onClick={sendMessage} disabled={isLoading}>
+              {isLoading ? <LoadingSpinner size="sm" /> : 'Send'}
+            </Button>
+          </div>
+        </div>
+      </Card>
+    </div>
+  );
+};
\ No newline at end of file
diff --git a/frontend/components/index.ts b/frontend/components/index.ts
index f7a5f5b..62c3b8d 100644
--- a/frontend/components/index.ts
+++ b/frontend/components/index.ts
@@ -13,4 +13,5 @@ export { Dashboard } from './dashboard/Dashboard';
 export { Button } from './shared/Button';
 export { Badge } from './shared/Badge';
 export { Card, CardHeader } from './shared/Card';
-export { LoadingSpinner, LoadingPage } from './shared/LoadingSpinner';
\ No newline at end of file
+export { LoadingSpinner, LoadingPage } from './shared/LoadingSpinner';
+export { Chat } from './chat/Chat';
\ No newline at end of file
diff --git a/frontend/lib/api/chat.ts b/frontend/lib/api/chat.ts
new file mode 100644
index 0000000..5cb40a0
--- /dev/null
+++ b/frontend/lib/api/chat.ts
@@ -0,0 +1,17 @@
+import apiClient from './client';
+
+export interface ChatMessage {
+  text: string;
+}
+
+export interface ChatResponse {
+  type: string;
+  message: string;
+  data?: any;
+}
+
+// Send chat message
+export const sendChatMessage = async (message: ChatMessage): Promise<ChatResponse> => {
+  const response = await apiClient.post<ChatResponse>('/api/chat', message);
+  return response.data;
+};
\ No newline at end of file
diff --git a/frontend/lib/api/client.ts b/frontend/lib/api/client.ts
index 48b61fe..c07f4ed 100644
--- a/frontend/lib/api/client.ts
+++ b/frontend/lib/api/client.ts
@@ -6,7 +6,7 @@ const BASE_URL = process.env.NEXT_PUBLIC_API_URL || 'http://localhost:8000';
 // Create axios instance with default config
 const apiClient = axios.create({
   baseURL: BASE_URL,
-  timeout: 10000,
+  timeout: 25000,
   headers: {
     'Content-Type': 'application/json',
   },

From a0ba597a25c3fa6eeb5402d9d3982117648dc6f2 Mon Sep 17 00:00:00 2001
From: Amith M P <amithmp676@gmail.com>
Date: Sun, 26 Oct 2025 20:27:58 +0530
Subject: [PATCH 2/4] chatbot message template update

---
 backend/app/agents/chatbot_agent.py | 73 ++++++++++++++++++++---------
 1 file changed, 50 insertions(+), 23 deletions(-)

diff --git a/backend/app/agents/chatbot_agent.py b/backend/app/agents/chatbot_agent.py
index ff24c47..9d8d434 100644
--- a/backend/app/agents/chatbot_agent.py
+++ b/backend/app/agents/chatbot_agent.py
@@ -1,15 +1,13 @@
-from typing import Dict, Any, Optional
-from .base import ProactivePulseAgent
-from .orchestrator import OrchestratorAgent
 import boto3
 import json
 import logging
+from typing import Dict, Any, Optional
+from .base import ProactivePulseAgent
+from .orchestrator import OrchestratorAgent
 
 logger = logging.getLogger(__name__)
 
 class ChatbotAgent(ProactivePulseAgent):
-    """Chatbot agent using AWS Bedrock for natural language interactions."""
-    
     def __init__(self, config):
         super().__init__(
             name="Chatbot Agent",
@@ -18,33 +16,61 @@ def __init__(self, config):
         
         self.config = config
         self.orchestrator = OrchestratorAgent()
-        self.bedrock_client = boto3.client('bedrock-runtime')
         
+        try:
+            # Create session using SSO profile
+            session = boto3.Session(
+                profile_name='proactive-pulse',  # Using the SSO profile
+                region_name=config.aws_region
+            )
+            
+            # Initialize Bedrock client with session
+            self.bedrock_client = session.client('bedrock-runtime')
+            logger.info(f"Successfully initialized Bedrock client using SSO profile in region {config.aws_region}")
+            
+        except Exception as e:
+            logger.error(f"Failed to initialize Bedrock client: {str(e)}")
+            raise
+
     async def process_message(self, message: str, conversation_id: str = None) -> Dict[str, Any]:
         try:
-            # Prepare the prompt for Bedrock
-            prompt = {
-                "prompt": message,
-                "max_tokens": 512,
-                "temperature": 0.7,
-                "model": self.config.aws_bedrock_model_text
+            logger.info(f"Processing message using Bedrock model: {self.config.aws_bedrock_model_text}")
+            
+            # Prepare message payload
+            body = {
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "text": message
+                            }
+                        ]
+                    }
+                ],
+                "inferenceConfig": {
+                    "maxTokens": 512,
+                    "temperature": 0.7,
+                    "topP": 0.9
+                }
             }
             
-            # Get response from Bedrock
+            # Invoke model
             response = self.bedrock_client.invoke_model(
                 modelId=self.config.aws_bedrock_model_text,
-                body=json.dumps(prompt)
+                body=json.dumps(body)
             )
+
+            # Parse response
+            response_body = json.loads(response["body"].read())
+            completion = response_body.get('messages', [])[0].get('content', [])[0].get('text', '') if response_body.get('messages') else ''
             
-            # Parse response and determine if we need to call other agents
-            response_body = json.loads(response['body'].read())
-            
-            # Check if we need to perform any specific actions
+            # Check for specific intents
             if "analyze" in message.lower():
                 analysis_results = await self.orchestrator.run_analysis()
                 return {
                     "type": "analysis",
-                    "message": response_body['completion'],
+                    "message": completion,
                     "data": analysis_results
                 }
             
@@ -52,18 +78,19 @@ async def process_message(self, message: str, conversation_id: str = None) -> Di
                 health_status = await self.orchestrator.get_health_status()
                 return {
                     "type": "health",
-                    "message": response_body['completion'],
+                    "message": completion,
                     "data": health_status
                 }
             
             return {
                 "type": "chat",
-                "message": response_body['completion']
+                "message": completion
             }
             
         except Exception as e:
-            logger.error(f"ChatbotAgent error: {str(e)}")
+            logger.error(f"Error processing message: {e}", exc_info=True)
             return {
                 "type": "error",
-                "message": "I encountered an error processing your request."
+                "message": "I encountered an error processing your request.",
+                "data": {"error": str(e)}
             }
\ No newline at end of file

From 99dab3f6a148c3e098d86333c3d1c7b552b5d9fb Mon Sep 17 00:00:00 2001
From: Amith M P <amithmp676@gmail.com>
Date: Sun, 26 Oct 2025 22:22:32 +0530
Subject: [PATCH 3/4] Chatbot markdown and list changes

---
 backend/app/agents/chatbot_agent.py           |  230 +++-
 backend/app/agents/insight_fetch.py           |   66 +
 frontend/components/chat/ChatDialog.tsx       |   93 +-
 frontend/components/insights/InsightTable.tsx |   84 ++
 frontend/package-lock.json                    | 1173 ++++++++++++++++-
 frontend/package.json                         |    1 +
 6 files changed, 1596 insertions(+), 51 deletions(-)
 create mode 100644 backend/app/agents/insight_fetch.py
 create mode 100644 frontend/components/insights/InsightTable.tsx

diff --git a/backend/app/agents/chatbot_agent.py b/backend/app/agents/chatbot_agent.py
index 9d8d434..d3a05f6 100644
--- a/backend/app/agents/chatbot_agent.py
+++ b/backend/app/agents/chatbot_agent.py
@@ -1,9 +1,10 @@
 import boto3
 import json
 import logging
-from typing import Dict, Any, Optional
+from typing import Dict, Any, List
 from .base import ProactivePulseAgent
 from .orchestrator import OrchestratorAgent
+from .insight_fetch import InsightFetchAgent
 
 logger = logging.getLogger(__name__)
 
@@ -16,81 +17,232 @@ def __init__(self, config):
         
         self.config = config
         self.orchestrator = OrchestratorAgent()
+        self.insight_fetch = InsightFetchAgent(config)
         
         try:
-            # Create session using SSO profile
             session = boto3.Session(
-                profile_name='proactive-pulse',  # Using the SSO profile
+                profile_name='proactive-pulse',
                 region_name=config.aws_region
             )
-            
-            # Initialize Bedrock client with session
             self.bedrock_client = session.client('bedrock-runtime')
-            logger.info(f"Successfully initialized Bedrock client using SSO profile in region {config.aws_region}")
-            
+            logger.info(f"✅ Bedrock client initialized in region {config.aws_region}")
         except Exception as e:
-            logger.error(f"Failed to initialize Bedrock client: {str(e)}")
+            logger.error(f"❌ Failed to initialize Bedrock client: {str(e)}")
             raise
 
+    # ============================================================
+    # Main conversational logic with Nova-Lite compliant message body
+    # ============================================================
     async def process_message(self, message: str, conversation_id: str = None) -> Dict[str, Any]:
         try:
             logger.info(f"Processing message using Bedrock model: {self.config.aws_bedrock_model_text}")
-            
-            # Prepare message payload
+
+            # Step 1: Analyze user intent
+            text_lower = message.lower()
+            data = None
+            resp_type = "chat"
+            context = ""
+
+            # --- HEALTH STATUS ---
+            if "health" in text_lower or "status" in text_lower:
+                resp_type = "health"
+                data = await self.orchestrator.get_health_status()
+
+                # Explicitly include raw JSON for accurate summarization
+                health_json_str = json.dumps(data, indent=2)
+                context = (
+                    "You are analyzing the following raw system health JSON. "
+                    "Summarize it accurately and do NOT invent or guess any values. "
+                    "If metrics like CPU, memory, or disk are missing, explicitly say 'not available'.\n\n"
+                    f"```json\n{health_json_str}\n```"
+                )
+
+            # --- CRITICAL INSIGHTS ---
+            elif "critical" in text_lower or "urgent" in text_lower:
+                resp_type = "insights"
+                insights = await self.insight_fetch.fetch_critical_insights()
+                data = {"insights": insights}
+
+                # Detect if user only wants a list
+                if "list" in text_lower or "show" in text_lower:
+                    context = self._format_insights_list(insights)
+                else:
+                    context = self._format_insights_context(insights, "critical")
+
+            # --- RECENT INSIGHTS ---
+            elif "recent" in text_lower and ("insight" in text_lower or "analysis" in text_lower):
+                resp_type = "insights"
+                insights = await self.insight_fetch.fetch_recent_insights()
+                data = {"insights": insights}
+
+                if "list" in text_lower or "show" in text_lower:
+                    context = self._format_insights_list(insights)
+                else:
+                    context = self._format_insights_context(insights, "recent")
+
+            # --- SYSTEM ANALYSIS ---
+            elif any(k in text_lower for k in ("analy", "analysis", "metrics")):
+                resp_type = "analysis"
+                data = await self.orchestrator.run_analysis(window_minutes=15)
+                if data.get("findings"):
+                    context = self._format_analysis_context(data)
+
+            # --- ANOMALIES ---
+            elif any(k in text_lower for k in ("anomal", "anomaly")):
+                resp_type = "anomaly"
+                if hasattr(self.orchestrator, "detect_anomalies"):
+                    data = await self.orchestrator.detect_anomalies(window_minutes=15)
+                else:
+                    data = await self.orchestrator.run_analysis(window_minutes=15)
+                context = self._format_anomaly_context(data)
+
+            # ============================================================
+            # Step 2: Build Nova-Lite message payload (NO system role!)
+            # ============================================================
             body = {
                 "messages": [
                     {
                         "role": "user",
                         "content": [
                             {
-                                "text": message
+                                "text": (
+                                    "You are ProactivePulse AI, a helpful assistant that analyzes system health "
+                                    "and performance. Use markdown for readability. "
+                                    "If the user asks to *list* insights, respond with a clean bullet list only, "
+                                    "no explanations or analysis.\n\n"
+                                    f"{context}\n\nUser Question: {message}"
+                                )
                             }
                         ]
                     }
                 ],
                 "inferenceConfig": {
                     "maxTokens": 512,
-                    "temperature": 0.7,
+                    "temperature": 0.5,
                     "topP": 0.9
                 }
             }
-            
-            # Invoke model
+
+            # Step 3: Invoke Bedrock Nova-Lite model
             response = self.bedrock_client.invoke_model(
                 modelId=self.config.aws_bedrock_model_text,
                 body=json.dumps(body)
             )
 
-            # Parse response
-            response_body = json.loads(response["body"].read())
-            completion = response_body.get('messages', [])[0].get('content', [])[0].get('text', '') if response_body.get('messages') else ''
-            
-            # Check for specific intents
-            if "analyze" in message.lower():
-                analysis_results = await self.orchestrator.run_analysis()
-                return {
-                    "type": "analysis",
-                    "message": completion,
-                    "data": analysis_results
-                }
-            
-            if "health" in message.lower():
-                health_status = await self.orchestrator.get_health_status()
-                return {
-                    "type": "health",
-                    "message": completion,
-                    "data": health_status
-                }
-            
+            # Step 4: Parse and extract completion
+            result_body = response["body"].read() if hasattr(response["body"], "read") else response["body"]
+            result = json.loads(result_body)
+
+            completion = self._extract_completion(result)
+
+            # Step 5: Ensure data is non-null and formatted
+            if data is None:
+                data = {}
+
+            if resp_type == "insights":
+                data["formatted"] = self._format_insights_for_display(data.get("insights", []))
+
             return {
-                "type": "chat",
-                "message": completion
+                "type": resp_type,
+                "message": completion,
+                "data": data
             }
-            
+
         except Exception as e:
             logger.error(f"Error processing message: {e}", exc_info=True)
             return {
                 "type": "error",
                 "message": "I encountered an error processing your request.",
                 "data": {"error": str(e)}
-            }
\ No newline at end of file
+            }
+
+    # ============================================================
+    # Helper Functions
+    # ============================================================
+
+    def _format_insights_context(self, insights: List[Dict], insight_type: str) -> str:
+        """Format insights for conversational LLM context"""
+        context = f"Based on {insight_type} system insights:\n\n"
+        for insight in insights:
+            context += f"- Issue: {insight['hypothesis']}\n"
+            context += f"  Priority: {insight['priority'].upper()}\n"
+            context += f"  Confidence: {insight['confidence']*100:.1f}%\n"
+            context += f"  Finding: {insight['narrative']}\n"
+            if insight.get('recommended_actions'):
+                context += "  Recommended Actions:\n"
+                for action in insight['recommended_actions'][:2]:
+                    context += f"    * {action}\n"
+            context += "\n"
+        return context
+
+    def _format_insights_list(self, insights: List[Dict]) -> str:
+        """Return only a clean bullet list of critical insights"""
+        if not insights:
+            return "No critical insights available."
+        lines = ["List of critical insights:"]
+        for i, ins in enumerate(insights, start=1):
+            lines.append(f"{i}. {ins['hypothesis']} (Priority: {ins['priority'].upper()}, Confidence: {ins['confidence']*100:.1f}%)")
+        return "\n".join(lines)
+
+    def _format_analysis_context(self, analysis_data: Dict) -> str:
+        """Format analysis data for LLM context"""
+        context = "Based on recent system analysis:\n\n"
+        if analysis_data.get("findings"):
+            context += "Key Findings:\n"
+            for finding in analysis_data["findings"]:
+                context += f"- {finding}\n"
+        return context
+
+    def _format_anomaly_context(self, anomaly_data: Dict) -> str:
+        """Format anomaly data for LLM context"""
+        context = "Recent system anomalies detected:\n\n"
+        if anomaly_data.get("anomalies"):
+            for anomaly in anomaly_data["anomalies"]:
+                context += f"- {anomaly['metric']} on {anomaly['asset']}\n"
+                context += f"  Score: {anomaly['score']*100:.1f}%\n"
+                context += f"  Value: {anomaly['value']}\n\n"
+        return context
+
+    def _extract_completion(self, result: Dict) -> str:
+        """Extract and clean up the model's response"""
+        try:
+            if "output" in result and "message" in result["output"]:
+                content = result["output"]["message"].get("content", [])
+                if content and isinstance(content[0], dict):
+                    return content[0].get("text", "")
+            if isinstance(result.get("messages"), list) and result["messages"]:
+                return result["messages"][0].get("content", [])[0].get("text", "")
+            return result.get("outputText", "") or result.get("text", "") or ""
+        except Exception:
+            return ""
+
+    def _format_insights_for_display(self, insights: List[Dict]) -> Dict[str, Any]:
+        """Format insights into structured display data"""
+        return {
+            "tables": {
+                "critical_issues": [
+                    {
+                        "issue": i['hypothesis'],
+                        "priority": i['priority'],
+                        "confidence": f"{i['confidence']*100:.1f}%",
+                        "actions": i['recommended_actions']
+                    }
+                    for i in insights if i['priority'] == 'critical'
+                ],
+                "affected_systems": [
+                    {
+                        "asset": a['asset'],
+                        "metric": a['metric'],
+                        "value": f"{a['value']:.2f}",
+                        "score": f"{a['score']*100:.1f}%"
+                    }
+                    for i in insights
+                    for a in i.get('anomaly_refs', [])
+                ]
+            },
+            "summary": {
+                "total_insights": len(insights),
+                "critical_count": len([i for i in insights if i['priority'] == 'critical']),
+                "affected_systems": len(set(a['asset'] for i in insights for a in i.get('anomaly_refs', [])))
+            }
+        }
diff --git a/backend/app/agents/insight_fetch.py b/backend/app/agents/insight_fetch.py
new file mode 100644
index 0000000..18f7a2c
--- /dev/null
+++ b/backend/app/agents/insight_fetch.py
@@ -0,0 +1,66 @@
+from typing import Dict, Any, List, Optional
+from datetime import datetime, timedelta
+from .base import ProactivePulseAgent
+from app.dependencies import get_storage_dependency
+import logging
+
+logger = logging.getLogger(__name__)
+
+class InsightFetchAgent(ProactivePulseAgent):
+    """Agent responsible for fetching and querying insights from storage."""
+    
+    def __init__(self, config):
+        super().__init__(
+            name="Insight Fetch Agent",
+            description="Retrieves and filters insights from storage"
+        )
+        self.config = config
+        self.storage = get_storage_dependency()
+
+    async def fetch_recent_insights(self, limit: int = 5) -> List[Dict[str, Any]]:
+        """Fetch most recent insights."""
+        try:
+            insights, _ = await self.storage.list_insights(limit=limit)
+            return [insight.dict() for insight in insights]
+        except Exception as e:
+            logger.error(f"Error fetching recent insights: {e}")
+            return []
+
+    async def fetch_insights_by_type(self, insight_type: str, limit: int = 5) -> List[Dict[str, Any]]:
+        """Fetch insights by type (analysis, anomaly, etc)."""
+        try:
+            insights, _ = await self.storage.list_insights(
+                limit=limit,
+                filters={"type": insight_type}
+            )
+            return [insight.dict() for insight in insights]
+        except Exception as e:
+            logger.error(f"Error fetching insights by type: {e}")
+            return []
+
+    async def fetch_critical_insights(self, limit: int = 5) -> List[Dict[str, Any]]:
+        """Fetch critical priority insights."""
+        try:
+            insights, _ = await self.storage.list_insights(
+                limit=limit,
+                filters={"priority": "CRITICAL"}
+            )
+            return [insight.dict() for insight in insights]
+        except Exception as e:
+            logger.error(f"Error fetching critical insights: {e}")
+            return []
+
+    async def search_insights(self, query: str, limit: int = 5) -> List[Dict[str, Any]]:
+        """Search insights by content."""
+        try:
+            # Basic keyword filtering (enhance with proper text search)
+            insights, _ = await self.storage.list_insights(limit=50)  # Get more to filter
+            matched = [
+                insight.dict() for insight in insights
+                if query.lower() in insight.summary.lower()
+                or query.lower() in insight.explanation.lower()
+            ]
+            return matched[:limit]
+        except Exception as e:
+            logger.error(f"Error searching insights: {e}")
+            return []
\ No newline at end of file
diff --git a/frontend/components/chat/ChatDialog.tsx b/frontend/components/chat/ChatDialog.tsx
index 5acb129..c836e18 100644
--- a/frontend/components/chat/ChatDialog.tsx
+++ b/frontend/components/chat/ChatDialog.tsx
@@ -2,11 +2,12 @@
 
 import React, { useState } from 'react';
 import { XMarkIcon } from '@heroicons/react/24/outline';
+import ReactMarkdown from 'react-markdown';
 import { Card } from '../shared/Card';
 import { Button } from '../shared/Button';
 import { LoadingSpinner } from '../shared/LoadingSpinner';
 import { sendChatMessage } from '../../lib/api/chat';
-import type { ChatResponse } from '../../lib/api/chat';
+import { InsightTable } from '../insights/InsightTable';
 
 interface Message {
   type: 'user' | 'bot';
@@ -14,6 +15,89 @@ interface Message {
   data?: any;
 }
 
+const MessageContent: React.FC<{ message: Message }> = ({ message }) => {
+  // Handle user messages
+  if (message.type === 'user') {
+    return <p className="text-gray-800 dark:text-gray-200">{message.text}</p>;
+  }
+
+  // Handle bot messages with markdown and data
+  return (
+    <div className="space-y-4">
+      {/* Markdown Content */}
+      <div className="prose dark:prose-invert max-w-none">
+        <ReactMarkdown>{message.text}</ReactMarkdown>
+      </div>
+
+      {/* Structured Data Display */}
+      {message.data && (
+        <div className="mt-4">
+          {/* Health Data */}
+          {message.data.services && (
+            <div className="space-y-2">
+              {Object.entries(message.data.services).map(([service, data]: [string, any]) => (
+                <Card key={service} className="p-4">
+                  <h4 className="text-lg font-semibold mb-2">{service}</h4>
+                  <div className="grid grid-cols-2 gap-2">
+                    <span className="text-gray-500">Status:</span>
+                    <span className={`font-medium ${
+                      data.status === 'healthy' ? 'text-green-600' : 'text-red-600'
+                    }`}>
+                      {data.status}
+                    </span>
+                    {data.metrics && Object.entries(data.metrics).map(([metric, value]) => (
+                      <React.Fragment key={metric}>
+                        <span className="text-gray-500">{metric}:</span>
+                        <span>{String(value)}</span>
+                      </React.Fragment>
+                    ))}
+                  </div>
+                </Card>
+              ))}
+            </div>
+          )}
+
+          {/* Insights Data */}
+          {message.data.insights && (
+            <div className="space-y-4">
+              {message.data.formatted && (
+                <div className="grid grid-cols-1 md:grid-cols-2 gap-4">
+                  <Card className="p-4">
+                    <h4 className="text-lg font-semibold mb-2">Summary</h4>
+                    <div className="grid grid-cols-2 gap-2">
+                      <span className="text-gray-500">Total Insights:</span>
+                      <span>{message.data.formatted.summary.total_insights}</span>
+                      <span className="text-gray-500">Critical Issues:</span>
+                      <span>{message.data.formatted.summary.critical_count}</span>
+                      <span className="text-gray-500">Affected Systems:</span>
+                      <span>{message.data.formatted.summary.affected_systems}</span>
+                    </div>
+                  </Card>
+                </div>
+              )}
+              <InsightTable insights={message.data.insights} />
+            </div>
+          )}
+
+          {/* Analysis Data */}
+          {message.data.findings && (
+            <Card className="p-4 mt-4">
+              <h4 className="text-lg font-semibold mb-2">Analysis Findings</h4>
+              <ul className="list-disc list-inside space-y-2">
+                {message.data.findings.map((finding: string, index: number) => (
+                  <li key={index} className="text-gray-700 dark:text-gray-300">
+                    {finding}
+                  </li>
+                ))}
+              </ul>
+            </Card>
+          )}
+        </div>
+      )}
+    </div>
+  );
+};
+
 export const ChatDialog: React.FC<{ onClose: () => void }> = ({ onClose }) => {
   const [messages, setMessages] = useState<Message[]>([]);
   const [input, setInput] = useState('');
@@ -64,12 +148,7 @@ export const ChatDialog: React.FC<{ onClose: () => void }> = ({ onClose }) => {
                   ? 'bg-blue-600 text-white' 
                   : 'bg-gray-100 dark:bg-gray-700'
               }`}>
-                <p>{msg.text}</p>
-                {msg.data && (
-                  <pre className="mt-2 text-xs bg-black/10 p-2 rounded overflow-x-auto">
-                    {JSON.stringify(msg.data, null, 2)}
-                  </pre>
-                )}
+                <MessageContent message={msg} />
               </div>
             </div>
           ))}
diff --git a/frontend/components/insights/InsightTable.tsx b/frontend/components/insights/InsightTable.tsx
new file mode 100644
index 0000000..73c060b
--- /dev/null
+++ b/frontend/components/insights/InsightTable.tsx
@@ -0,0 +1,84 @@
+import React from 'react';
+import { Badge } from '../shared/Badge';
+import { Card } from '../shared/Card';
+import { formatRelativeTime, formatPercentage } from '@/lib/utils/formatters';
+import type { Insight } from '@/lib/types';
+
+interface InsightTableProps {
+  insights: Insight[];
+}
+
+export const InsightTable: React.FC<InsightTableProps> = ({ insights }) => {
+  return (
+    <Card className="overflow-hidden">
+      <div className="overflow-x-auto">
+        <table className="min-w-full divide-y divide-gray-200 dark:divide-slate-light">
+          <thead className="bg-gray-50 dark:bg-slate-dark">
+            <tr>
+              <th className="px-6 py-3 text-left text-xs font-medium text-gray-500 dark:text-gray-400 uppercase tracking-wider">
+                Priority
+              </th>
+              <th className="px-6 py-3 text-left text-xs font-medium text-gray-500 dark:text-gray-400 uppercase tracking-wider">
+                Hypothesis
+              </th>
+              <th className="px-6 py-3 text-left text-xs font-medium text-gray-500 dark:text-gray-400 uppercase tracking-wider">
+                Score
+              </th>
+              <th className="px-6 py-3 text-left text-xs font-medium text-gray-500 dark:text-gray-400 uppercase tracking-wider">
+                Time
+              </th>
+              <th className="px-6 py-3 text-left text-xs font-medium text-gray-500 dark:text-gray-400 uppercase tracking-wider">
+                Actions
+              </th>
+            </tr>
+          </thead>
+          <tbody className="bg-white dark:bg-slate divide-y divide-gray-200 dark:divide-slate-light">
+            {insights.map((insight) => (
+              <tr key={insight.id}>
+                <td className="px-6 py-4 whitespace-nowrap">
+                  <Badge 
+                    variant={
+                      insight.priority === 'critical' ? 'error' :
+                      insight.priority === 'high' ? 'warning' :
+                      insight.priority === 'medium' ? 'info' : 'default'
+                    }
+                  >
+                    {insight.priority.toUpperCase()}
+                  </Badge>
+                </td>
+                <td className="px-6 py-4">
+                  <div className="text-sm text-gray-900 dark:text-gray-100">
+                    {insight.hypothesis}
+                  </div>
+                  <div className="text-sm text-gray-500 dark:text-gray-400">
+                    {insight.narrative}
+                  </div>
+                </td>
+                <td className="px-6 py-4 whitespace-nowrap">
+                  <div className="text-sm text-gray-900 dark:text-gray-100">
+                    {formatPercentage(insight.correlation_score)}
+                  </div>
+                  <div className="text-sm text-gray-500 dark:text-gray-400">
+                    Confidence: {formatPercentage(insight.confidence)}
+                  </div>
+                </td>
+                <td className="px-6 py-4 whitespace-nowrap text-sm text-gray-500 dark:text-gray-400">
+                  {formatRelativeTime(insight.created_at)}
+                </td>
+                <td className="px-6 py-4 whitespace-nowrap text-sm">
+                  <div className="space-y-2">
+                    {insight.recommended_actions.slice(0, 2).map((action, index) => (
+                      <div key={index} className="text-gray-600 dark:text-gray-300">
+                        • {action}
+                      </div>
+                    ))}
+                  </div>
+                </td>
+              </tr>
+            ))}
+          </tbody>
+        </table>
+      </div>
+    </Card>
+  );
+};
\ No newline at end of file
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
index 798f657..468f61b 100644
--- a/frontend/package-lock.json
+++ b/frontend/package-lock.json
@@ -28,6 +28,7 @@
         "react-dom": "18.2.0",
         "react-hook-form": "7.47.0",
         "react-hot-toast": "2.4.1",
+        "react-markdown": "^9.0.0",
         "recharts": "2.8.0",
         "swr": "^2.3.6",
         "tailwind-merge": "^3.3.1",
@@ -611,6 +612,39 @@
       "resolved": "https://registry.npmjs.org/@types/d3-timer/-/d3-timer-3.0.2.tgz",
       "integrity": "sha512-Ps3T8E8dZDam6fUyNiMkekK3XUsaUEik+idO9/YjPtfj2qruF8tFBXS7XhtE4iIXBLxhmLjP3SXpLhVf21I9Lw=="
     },
+    "node_modules/@types/debug": {
+      "version": "4.1.12",
+      "resolved": "https://registry.npmjs.org/@types/debug/-/debug-4.1.12.tgz",
+      "integrity": "sha512-vIChWdVG3LG1SMxEvI/AK+FWJthlrqlTu7fbrlywTkkaONwk/UAGaULXRlf8vkzFBLVm0zkMdCquhL5aOjhXPQ==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/ms": "*"
+      }
+    },
+    "node_modules/@types/estree": {
+      "version": "1.0.8",
+      "resolved": "https://registry.npmjs.org/@types/estree/-/estree-1.0.8.tgz",
+      "integrity": "sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w==",
+      "license": "MIT"
+    },
+    "node_modules/@types/estree-jsx": {
+      "version": "1.0.5",
+      "resolved": "https://registry.npmjs.org/@types/estree-jsx/-/estree-jsx-1.0.5.tgz",
+      "integrity": "sha512-52CcUVNFyfb1A2ALocQw/Dd1BQFNmSdkuC3BkZ6iqhdMfQz7JWOFRuJFloOzjk+6WijU56m9oKXFAXc7o3Towg==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/estree": "*"
+      }
+    },
+    "node_modules/@types/hast": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@types/hast/-/hast-3.0.4.tgz",
+      "integrity": "sha512-WPs+bbQw5aCj+x6laNGWLH3wviHtoCv/P3+otBhbOhJgG8qtpdAMlTCxLtsTWA7LH1Oh/bFCHsBn0TPS5m30EQ==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "*"
+      }
+    },
     "node_modules/@types/json-schema": {
       "version": "7.0.15",
       "resolved": "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.15.tgz",
@@ -623,6 +657,21 @@
       "integrity": "sha512-dRLjCWHYg4oaA77cxO64oO+7JwCwnIzkZPdrrC71jQmQtlhM556pwKo5bUzqvZndkVbeFLIIi+9TC40JNF5hNQ==",
       "dev": true
     },
+    "node_modules/@types/mdast": {
+      "version": "4.0.4",
+      "resolved": "https://registry.npmjs.org/@types/mdast/-/mdast-4.0.4.tgz",
+      "integrity": "sha512-kGaNbPh1k7AFzgpud/gMdvIm5xuECykRR+JnWKQno9TAXVa6WIVCGTPvYGekIDL4uwCZQSYbUxNBSb1aUo79oA==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "*"
+      }
+    },
+    "node_modules/@types/ms": {
+      "version": "2.1.0",
+      "resolved": "https://registry.npmjs.org/@types/ms/-/ms-2.1.0.tgz",
+      "integrity": "sha512-GsCCIZDE/p3i96vtEqx+7dBUGXrc7zeSK3wwPHIaRThS+9OhWIXRqzs4d6k1SVU8g91DrNRWxWUGhp5KXQb2VA==",
+      "license": "MIT"
+    },
     "node_modules/@types/node": {
       "version": "20.9.0",
       "resolved": "https://registry.npmjs.org/@types/node/-/node-20.9.0.tgz",
@@ -665,6 +714,12 @@
       "integrity": "sha512-FmgJfu+MOcQ370SD0ev7EI8TlCAfKYU+B4m5T3yXc1CiRN94g/SZPtsCkk506aUDtlMnFZvasDwHHUcZUEaYuA==",
       "dev": true
     },
+    "node_modules/@types/unist": {
+      "version": "3.0.3",
+      "resolved": "https://registry.npmjs.org/@types/unist/-/unist-3.0.3.tgz",
+      "integrity": "sha512-ko/gIFJRv177XgZsZcBwnqJN5x/Gien8qNOn0D5bQU/zAzVf9Zt3BlcUiLqhV9y4ARk0GbT3tnUiPNgnTXzc/Q==",
+      "license": "MIT"
+    },
     "node_modules/@typescript-eslint/eslint-plugin": {
       "version": "6.11.0",
       "resolved": "https://registry.npmjs.org/@typescript-eslint/eslint-plugin/-/eslint-plugin-6.11.0.tgz",
@@ -857,8 +912,7 @@
     "node_modules/@ungap/structured-clone": {
       "version": "1.3.0",
       "resolved": "https://registry.npmjs.org/@ungap/structured-clone/-/structured-clone-1.3.0.tgz",
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-      "dev": true
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+          "type": "GitHub Sponsors",
+          "url": "https://github.com/sponsors/unifiedjs"
+        },
+        {
+          "type": "OpenCollective",
+          "url": "https://opencollective.com/unified"
+        }
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+      "license": "MIT",
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+        "micromark-util-symbol": "^2.0.0",
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+      "funding": [
+        {
+          "type": "GitHub Sponsors",
+          "url": "https://github.com/sponsors/unifiedjs"
+        },
+        {
+          "type": "OpenCollective",
+          "url": "https://opencollective.com/unified"
+        }
+      ],
+      "license": "MIT"
+    },
+    "node_modules/micromark-util-types": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/micromark-util-types/-/micromark-util-types-2.0.2.tgz",
+      "integrity": "sha512-Yw0ECSpJoViF1qTU4DC6NwtC4aWGt1EkzaQB8KPPyCRR8z9TWeV0HbEFGTO+ZY1wB22zmxnJqhPyTpOVCpeHTA==",
+      "funding": [
+        {
+          "type": "GitHub Sponsors",
+          "url": "https://github.com/sponsors/unifiedjs"
+        },
+        {
+          "type": "OpenCollective",
+          "url": "https://opencollective.com/unified"
+        }
+      ],
+      "license": "MIT"
+    },
     "node_modules/micromatch": {
       "version": "4.0.8",
       "resolved": "https://registry.npmjs.org/micromatch/-/micromatch-4.0.8.tgz",
@@ -4071,8 +4953,7 @@
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       "resolved": "https://registry.npmjs.org/ms/-/ms-2.1.3.tgz",
-      "integrity": "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==",
-      "dev": true
+      "integrity": "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="
     },
     "node_modules/mz": {
       "version": "2.7.0",
@@ -4400,6 +5281,31 @@
         "node": ">=6"
       }
     },
+    "node_modules/parse-entities": {
+      "version": "4.0.2",
+      "resolved": "https://registry.npmjs.org/parse-entities/-/parse-entities-4.0.2.tgz",
+      "integrity": "sha512-GG2AQYWoLgL877gQIKeRPGO1xF9+eG1ujIb5soS5gPvLQ1y2o8FL90w2QWNdf9I361Mpp7726c+lj3U0qK1uGw==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^2.0.0",
+        "character-entities-legacy": "^3.0.0",
+        "character-reference-invalid": "^2.0.0",
+        "decode-named-character-reference": "^1.0.0",
+        "is-alphanumerical": "^2.0.0",
+        "is-decimal": "^2.0.0",
+        "is-hexadecimal": "^2.0.0"
+      },
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
+    "node_modules/parse-entities/node_modules/@types/unist": {
+      "version": "2.0.11",
+      "resolved": "https://registry.npmjs.org/@types/unist/-/unist-2.0.11.tgz",
+      "integrity": "sha512-CmBKiL6NNo/OqgmMn95Fk9Whlp2mtvIv+KNpQKN2F4SjvrEesubTRWGYSg+BnWZOnlCaSTU1sMpsBOzgbYhnsA==",
+      "license": "MIT"
+    },
     "node_modules/path-exists": {
       "version": "4.0.0",
       "resolved": "https://registry.npmjs.org/path-exists/-/path-exists-4.0.0.tgz",
@@ -4722,6 +5628,16 @@
         "react-is": "^16.13.1"
       }
     },
+    "node_modules/property-information": {
+      "version": "7.1.0",
+      "resolved": "https://registry.npmjs.org/property-information/-/property-information-7.1.0.tgz",
+      "integrity": "sha512-TwEZ+X+yCJmYfL7TPUOcvBZ4QfoT5YenQiJuX//0th53DE6w0xxLEtfK3iyryQFddXuvkIk51EEgrJQ0WJkOmQ==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
     "node_modules/proxy-from-env": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-1.1.0.tgz",
@@ -4818,6 +5734,33 @@
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+    "node_modules/react-markdown": {
+      "version": "9.1.0",
+      "resolved": "https://registry.npmjs.org/react-markdown/-/react-markdown-9.1.0.tgz",
+      "integrity": "sha512-xaijuJB0kzGiUdG7nc2MOMDUDBWPyGAjZtUrow9XxUeua8IqeP+VlIfAZ3bphpcLTnSZXz6z9jcVC/TCwbfgdw==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/hast": "^3.0.0",
+        "@types/mdast": "^4.0.0",
+        "devlop": "^1.0.0",
+        "hast-util-to-jsx-runtime": "^2.0.0",
+        "html-url-attributes": "^3.0.0",
+        "mdast-util-to-hast": "^13.0.0",
+        "remark-parse": "^11.0.0",
+        "remark-rehype": "^11.0.0",
+        "unified": "^11.0.0",
+        "unist-util-visit": "^5.0.0",
+        "vfile": "^6.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      },
+      "peerDependencies": {
+        "@types/react": ">=18",
+        "react": ">=18"
+      }
+    },
     "node_modules/react-resize-detector": {
       "version": "8.1.0",
       "resolved": "https://registry.npmjs.org/react-resize-detector/-/react-resize-detector-8.1.0.tgz",
@@ -4966,6 +5909,39 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/remark-parse": {
+      "version": "11.0.0",
+      "resolved": "https://registry.npmjs.org/remark-parse/-/remark-parse-11.0.0.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "@types/mdast": "^4.0.0",
+        "mdast-util-from-markdown": "^2.0.0",
+        "micromark-util-types": "^2.0.0",
+        "unified": "^11.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/remark-rehype": {
+      "version": "11.1.2",
+      "resolved": "https://registry.npmjs.org/remark-rehype/-/remark-rehype-11.1.2.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "@types/hast": "^3.0.0",
+        "@types/mdast": "^4.0.0",
+        "mdast-util-to-hast": "^13.0.0",
+        "unified": "^11.0.0",
+        "vfile": "^6.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
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       "resolved": "https://registry.npmjs.org/resolve/-/resolve-1.22.10.tgz",
@@ -5287,6 +6263,16 @@
         "node": ">=0.10.0"
       }
     },
+    "node_modules/space-separated-tokens": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/space-separated-tokens/-/space-separated-tokens-2.0.2.tgz",
+      "integrity": "sha512-PEGlAwrG8yXGXRjW32fGbg66JAlOAwbObuqVoJpv/mRgoWDQfgH1wDPvtzWyUSNAXBGSk8h755YDbbcEy3SH2Q==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
     "node_modules/stable-hash": {
       "version": "0.0.5",
       "resolved": "https://registry.npmjs.org/stable-hash/-/stable-hash-0.0.5.tgz",
@@ -5481,6 +6467,20 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/stringify-entities": {
+      "version": "4.0.4",
+      "resolved": "https://registry.npmjs.org/stringify-entities/-/stringify-entities-4.0.4.tgz",
+      "integrity": "sha512-IwfBptatlO+QCJUo19AqvrPNqlVMpW9YEL2LIVY+Rpv2qsjCGxaDLNRgeGsQWJhfItebuJhsGSLjaBbNSQ+ieg==",
+      "license": "MIT",
+      "dependencies": {
+        "character-entities-html4": "^2.0.0",
+        "character-entities-legacy": "^3.0.0"
+      },
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
     "node_modules/strip-ansi": {
       "version": "6.0.1",
       "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
@@ -5525,6 +6525,24 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
+    "node_modules/style-to-js": {
+      "version": "1.1.18",
+      "resolved": "https://registry.npmjs.org/style-to-js/-/style-to-js-1.1.18.tgz",
+      "integrity": "sha512-JFPn62D4kJaPTnhFUI244MThx+FEGbi+9dw1b9yBBQ+1CZpV7QAT8kUtJ7b7EUNdHajjF/0x8fT+16oLJoojLg==",
+      "license": "MIT",
+      "dependencies": {
+        "style-to-object": "1.0.11"
+      }
+    },
+    "node_modules/style-to-object": {
+      "version": "1.0.11",
+      "resolved": "https://registry.npmjs.org/style-to-object/-/style-to-object-1.0.11.tgz",
+      "integrity": "sha512-5A560JmXr7wDyGLK12Nq/EYS38VkGlglVzkis1JEdbGWSnbQIEhZzTJhzURXN5/8WwwFCs/f/VVcmkTppbXLow==",
+      "license": "MIT",
+      "dependencies": {
+        "inline-style-parser": "0.2.4"
+      }
+    },
     "node_modules/styled-jsx": {
       "version": "5.1.1",
       "resolved": "https://registry.npmjs.org/styled-jsx/-/styled-jsx-5.1.1.tgz",
@@ -5827,6 +6845,26 @@
         "node": ">=8.0"
       }
     },
+    "node_modules/trim-lines": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/trim-lines/-/trim-lines-3.0.1.tgz",
+      "integrity": "sha512-kRj8B+YHZCc9kQYdWfJB2/oUl9rA99qbowYYBtr4ui4mZyAQ2JpvVBd/6U2YloATfqBhBTSMhTpgBHtU0Mf3Rg==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
+    "node_modules/trough": {
+      "version": "2.2.0",
+      "resolved": "https://registry.npmjs.org/trough/-/trough-2.2.0.tgz",
+      "integrity": "sha512-tmMpK00BjZiUyVyvrBK7knerNgmgvcV/KLVyuma/SC+TQN167GrMRciANTz09+k3zW8L8t60jWO1GpfkZdjTaw==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
+    },
     "node_modules/ts-api-utils": {
       "version": "1.4.3",
       "resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-1.4.3.tgz",
@@ -5994,6 +7032,93 @@
       "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-5.26.5.tgz",
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     },
+    "node_modules/unified": {
+      "version": "11.0.5",
+      "resolved": "https://registry.npmjs.org/unified/-/unified-11.0.5.tgz",
+      "integrity": "sha512-xKvGhPWw3k84Qjh8bI3ZeJjqnyadK+GEFtazSfZv/rKeTkTjOJho6mFqh2SM96iIcZokxiOpg78GazTSg8+KHA==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0",
+        "bail": "^2.0.0",
+        "devlop": "^1.0.0",
+        "extend": "^3.0.0",
+        "is-plain-obj": "^4.0.0",
+        "trough": "^2.0.0",
+        "vfile": "^6.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/unist-util-is": {
+      "version": "6.0.1",
+      "resolved": "https://registry.npmjs.org/unist-util-is/-/unist-util-is-6.0.1.tgz",
+      "integrity": "sha512-LsiILbtBETkDz8I9p1dQ0uyRUWuaQzd/cuEeS1hoRSyW5E5XGmTzlwY1OrNzzakGowI9Dr/I8HVaw4hTtnxy8g==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0"
+      },
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+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
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+    "node_modules/unist-util-position": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/unist-util-position/-/unist-util-position-5.0.0.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0"
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+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/unist-util-stringify-position": {
+      "version": "4.0.0",
+      "resolved": "https://registry.npmjs.org/unist-util-stringify-position/-/unist-util-stringify-position-4.0.0.tgz",
+      "integrity": "sha512-0ASV06AAoKCDkS2+xw5RXJywruurpbC4JZSm7nr7MOt1ojAzvyyaO+UxZf18j8FCF6kmzCZKcAgN/yu2gm2XgQ==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/unist-util-visit": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/unist-util-visit/-/unist-util-visit-5.0.0.tgz",
+      "integrity": "sha512-MR04uvD+07cwl/yhVuVWAtw+3GOR/knlL55Nd/wAdblk27GCVt3lqpTivy/tkJcZoNPzTwS1Y+KMojlLDhoTzg==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0",
+        "unist-util-is": "^6.0.0",
+        "unist-util-visit-parents": "^6.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/unist-util-visit-parents": {
+      "version": "6.0.2",
+      "resolved": "https://registry.npmjs.org/unist-util-visit-parents/-/unist-util-visit-parents-6.0.2.tgz",
+      "integrity": "sha512-goh1s1TBrqSqukSc8wrjwWhL0hiJxgA8m4kFxGlQ+8FYQ3C/m11FcTs4YYem7V664AhHVvgoQLk890Ssdsr2IQ==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0",
+        "unist-util-is": "^6.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
     "node_modules/unrs-resolver": {
       "version": "1.11.1",
       "resolved": "https://registry.npmjs.org/unrs-resolver/-/unrs-resolver-1.11.1.tgz",
@@ -6079,6 +7204,34 @@
       "resolved": "https://registry.npmjs.org/util-deprecate/-/util-deprecate-1.0.2.tgz",
       "integrity": "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="
     },
+    "node_modules/vfile": {
+      "version": "6.0.3",
+      "resolved": "https://registry.npmjs.org/vfile/-/vfile-6.0.3.tgz",
+      "integrity": "sha512-KzIbH/9tXat2u30jf+smMwFCsno4wHVdNmzFyL+T/L3UGqqk6JKfVqOFOZEpZSHADH1k40ab6NUIXZq422ov3Q==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0",
+        "vfile-message": "^4.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
+    "node_modules/vfile-message": {
+      "version": "4.0.3",
+      "resolved": "https://registry.npmjs.org/vfile-message/-/vfile-message-4.0.3.tgz",
+      "integrity": "sha512-QTHzsGd1EhbZs4AsQ20JX1rC3cOlt/IWJruk893DfLRr57lcnOeMaWG4K0JrRta4mIJZKth2Au3mM3u03/JWKw==",
+      "license": "MIT",
+      "dependencies": {
+        "@types/unist": "^3.0.0",
+        "unist-util-stringify-position": "^4.0.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/unified"
+      }
+    },
     "node_modules/victory-vendor": {
       "version": "36.9.2",
       "resolved": "https://registry.npmjs.org/victory-vendor/-/victory-vendor-36.9.2.tgz",
@@ -6343,6 +7496,16 @@
       "funding": {
         "url": "https://github.com/sponsors/colinhacks"
       }
+    },
+    "node_modules/zwitch": {
+      "version": "2.0.4",
+      "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz",
+      "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/wooorm"
+      }
     }
   }
 }
diff --git a/frontend/package.json b/frontend/package.json
index f8282b2..31e830f 100644
--- a/frontend/package.json
+++ b/frontend/package.json
@@ -36,6 +36,7 @@
     "tailwind-merge": "^3.3.1",
     "tailwindcss": "3.3.6",
     "typescript": "5.2.2",
+    "react-markdown": "^9.0.0",
     "zod": "3.22.4"
   },
   "devDependencies": {

From 8615ca01c93999baaebc642fbe9c96883f6d2ff8 Mon Sep 17 00:00:00 2001
From: Amith M P <amithmp676@gmail.com>
Date: Sat, 1 Nov 2025 19:36:32 +0530
Subject: [PATCH 4/4] chatbot changes

---
 backend/app/agents/chatbot_agent.py | 205 +++++++++++++++-------------
 1 file changed, 109 insertions(+), 96 deletions(-)

diff --git a/backend/app/agents/chatbot_agent.py b/backend/app/agents/chatbot_agent.py
index d3a05f6..a63264a 100644
--- a/backend/app/agents/chatbot_agent.py
+++ b/backend/app/agents/chatbot_agent.py
@@ -2,6 +2,7 @@
 import json
 import logging
 from typing import Dict, Any, List
+import httpx
 from .base import ProactivePulseAgent
 from .orchestrator import OrchestratorAgent
 from .insight_fetch import InsightFetchAgent
@@ -38,67 +39,36 @@ async def process_message(self, message: str, conversation_id: str = None) -> Di
             logger.info(f"Processing message using Bedrock model: {self.config.aws_bedrock_model_text}")
 
             # Step 1: Analyze user intent
-            text_lower = message.lower()
+            intent, resp_type = self._classify_intent(message)
             data = None
-            resp_type = "chat"
             context = ""
 
-            # --- HEALTH STATUS ---
-            if "health" in text_lower or "status" in text_lower:
-                resp_type = "health"
-                data = await self.orchestrator.get_health_status()
-
-                # Explicitly include raw JSON for accurate summarization
-                health_json_str = json.dumps(data, indent=2)
-                context = (
-                    "You are analyzing the following raw system health JSON. "
-                    "Summarize it accurately and do NOT invent or guess any values. "
-                    "If metrics like CPU, memory, or disk are missing, explicitly say 'not available'.\n\n"
-                    f"```json\n{health_json_str}\n```"
-                )
-
-            # --- CRITICAL INSIGHTS ---
-            elif "critical" in text_lower or "urgent" in text_lower:
-                resp_type = "insights"
+            # Step 2: Execute agent based on intent
+            if intent == 'get_health_status':
+                async with httpx.AsyncClient() as client:
+                    response = await client.get("http://localhost:8000/health/", timeout=30.0)
+                    response.raise_for_status()
+                    data = response.json()
+                context = self._get_intent_prompt(intent, data)
+            elif intent == 'get_critical_insights':
                 insights = await self.insight_fetch.fetch_critical_insights()
                 data = {"insights": insights}
-
-                # Detect if user only wants a list
-                if "list" in text_lower or "show" in text_lower:
-                    context = self._format_insights_list(insights)
-                else:
-                    context = self._format_insights_context(insights, "critical")
-
-            # --- RECENT INSIGHTS ---
-            elif "recent" in text_lower and ("insight" in text_lower or "analysis" in text_lower):
-                resp_type = "insights"
+                context = self._get_intent_prompt(intent, data, message)
+            elif intent == 'get_recent_insights':
                 insights = await self.insight_fetch.fetch_recent_insights()
                 data = {"insights": insights}
-
-                if "list" in text_lower or "show" in text_lower:
-                    context = self._format_insights_list(insights)
-                else:
-                    context = self._format_insights_context(insights, "recent")
-
-            # --- SYSTEM ANALYSIS ---
-            elif any(k in text_lower for k in ("analy", "analysis", "metrics")):
-                resp_type = "analysis"
+                context = self._get_intent_prompt(intent, data, message)
+            elif intent == 'run_analysis':
                 data = await self.orchestrator.run_analysis(window_minutes=15)
-                if data.get("findings"):
-                    context = self._format_analysis_context(data)
-
-            # --- ANOMALIES ---
-            elif any(k in text_lower for k in ("anomal", "anomaly")):
-                resp_type = "anomaly"
+                context = self._get_intent_prompt(intent, data)
+            elif intent == 'detect_anomalies':
                 if hasattr(self.orchestrator, "detect_anomalies"):
                     data = await self.orchestrator.detect_anomalies(window_minutes=15)
                 else:
                     data = await self.orchestrator.run_analysis(window_minutes=15)
-                context = self._format_anomaly_context(data)
+                context = self._get_intent_prompt(intent, data)
 
-            # ============================================================
-            # Step 2: Build Nova-Lite message payload (NO system role!)
-            # ============================================================
+            # Step 3: Build Nova-Lite message payload
             body = {
                 "messages": [
                     {
@@ -123,22 +93,20 @@ async def process_message(self, message: str, conversation_id: str = None) -> Di
                 }
             }
 
-            # Step 3: Invoke Bedrock Nova-Lite model
+            # Step 4: Invoke Bedrock Nova-Lite model
             response = self.bedrock_client.invoke_model(
                 modelId=self.config.aws_bedrock_model_text,
                 body=json.dumps(body)
             )
 
-            # Step 4: Parse and extract completion
+            # Step 5: Parse and extract completion
             result_body = response["body"].read() if hasattr(response["body"], "read") else response["body"]
             result = json.loads(result_body)
-
             completion = self._extract_completion(result)
 
-            # Step 5: Ensure data is non-null and formatted
+            # Step 6: Ensure data is non-null and formatted
             if data is None:
                 data = {}
-
             if resp_type == "insights":
                 data["formatted"] = self._format_insights_for_display(data.get("insights", []))
 
@@ -157,51 +125,96 @@ async def process_message(self, message: str, conversation_id: str = None) -> Di
             }
 
     # ============================================================
-    # Helper Functions
+    # Intent Classification and Prompt Generation
     # ============================================================
 
-    def _format_insights_context(self, insights: List[Dict], insight_type: str) -> str:
-        """Format insights for conversational LLM context"""
-        context = f"Based on {insight_type} system insights:\n\n"
-        for insight in insights:
-            context += f"- Issue: {insight['hypothesis']}\n"
-            context += f"  Priority: {insight['priority'].upper()}\n"
-            context += f"  Confidence: {insight['confidence']*100:.1f}%\n"
-            context += f"  Finding: {insight['narrative']}\n"
-            if insight.get('recommended_actions'):
-                context += "  Recommended Actions:\n"
-                for action in insight['recommended_actions'][:2]:
-                    context += f"    * {action}\n"
-            context += "\n"
-        return context
-
-    def _format_insights_list(self, insights: List[Dict]) -> str:
-        """Return only a clean bullet list of critical insights"""
-        if not insights:
-            return "No critical insights available."
-        lines = ["List of critical insights:"]
-        for i, ins in enumerate(insights, start=1):
-            lines.append(f"{i}. {ins['hypothesis']} (Priority: {ins['priority'].upper()}, Confidence: {ins['confidence']*100:.1f}%)")
-        return "\n".join(lines)
-
-    def _format_analysis_context(self, analysis_data: Dict) -> str:
-        """Format analysis data for LLM context"""
-        context = "Based on recent system analysis:\n\n"
-        if analysis_data.get("findings"):
-            context += "Key Findings:\n"
-            for finding in analysis_data["findings"]:
-                context += f"- {finding}\n"
-        return context
-
-    def _format_anomaly_context(self, anomaly_data: Dict) -> str:
-        """Format anomaly data for LLM context"""
-        context = "Recent system anomalies detected:\n\n"
-        if anomaly_data.get("anomalies"):
-            for anomaly in anomaly_data["anomalies"]:
-                context += f"- {anomaly['metric']} on {anomaly['asset']}\n"
-                context += f"  Score: {anomaly['score']*100:.1f}%\n"
-                context += f"  Value: {anomaly['value']}\n\n"
-        return context
+    def _classify_intent(self, message: str) -> (str, str):
+        """Classify user intent from the message."""
+        text_lower = message.lower()
+        
+        if "health" in text_lower or "status" in text_lower:
+            return "get_health_status", "health"
+        if "critical" in text_lower or "urgent" in text_lower:
+            return "get_critical_insights", "insights"
+        if "recent" in text_lower and ("insight" in text_lower or "analysis" in text_lower):
+            return "get_recent_insights", "insights"
+        if any(k in text_lower for k in ("analy", "analysis", "metrics")):
+            return "run_analysis", "analysis"
+        if any(k in text_lower for k in ("anomal", "anomaly")):
+            return "detect_anomalies", "anomaly"
+            
+        return "chat", "chat"
+
+    def _get_intent_prompt(self, intent: str, data: Dict, message: str = "") -> str:
+        """Generate a generalized prompt for the LLM based on the intent."""
+        prompts = self._get_agent_prompts()
+        prompt_template = prompts.get(intent, prompts["chat"])
+        
+        formatted_data = self._format_data_for_llm(intent, data, message)
+        
+        return prompt_template.format(data=formatted_data)
+
+    def _get_agent_prompts(self) -> Dict[str, str]:
+        """Returns a dictionary of prompts for each agent."""
+        return {
+            "get_health_status": "Analyze the following system health data and provide a summary. Do not invent values. If metrics are missing, state they are 'not available'.\n\n```json\n{data}\n```",
+            "get_critical_insights": "Analyze these critical system insights. If the user wants a list, provide a bulleted list of issues. Otherwise, summarize the findings.\n\n{data}",
+            "get_recent_insights": "Analyze these recent system insights. If the user wants a list, provide a bulleted list of issues. Otherwise, summarize the findings.\n\n{data}",
+            "run_analysis": "Summarize the key findings from the recent system analysis provided below.\n\n{data}",
+            "detect_anomalies": "Summarize the detected system anomalies provided below.\n\n{data}",
+            "chat": "You are a helpful assistant. Please respond to the user's question.",
+        }
+
+    def _format_data_for_llm(self, intent: str, data: Dict, message: str) -> str:
+        """Formats data for the LLM based on the intent."""
+        if not data:
+            return "No data available."
+
+        if intent == "get_health_status":
+            return json.dumps(data.get('services', {}), indent=2)
+
+        if intent in ["get_critical_insights", "get_recent_insights"]:
+            insights = data.get("insights", [])
+            if not insights:
+                return "No insights available."
+            
+            text_lower = message.lower()
+            if "list" in text_lower or "show" in text_lower:
+                lines = ["List of insights:"]
+                for i, ins in enumerate(insights, start=1):
+                    lines.append(f"{i}. {ins['hypothesis']} (Priority: {ins['priority'].upper()}, Confidence: {ins['confidence']*100:.1f}%)")
+                return "\n".join(lines)
+
+            context = ""
+            for insight in insights:
+                context += f"- Issue: {insight['hypothesis']}\n"
+                context += f"  Priority: {insight['priority'].upper()}\n"
+                context += f"  Confidence: {insight['confidence']*100:.1f}%\n"
+                context += f"  Finding: {insight['narrative']}\n"
+                if insight.get('recommended_actions'):
+                    context += "  Recommended Actions:\n"
+                    for action in insight['recommended_actions'][:2]:
+                        context += f"    * {action}\n"
+                context += "\n"
+            return context
+
+        if intent == "run_analysis":
+            if data.get("findings"):
+                return "Key Findings:\n" + "\n".join([f"- {finding}" for finding in data["findings"]])
+            return "No findings from the analysis."
+
+        if intent == "detect_anomalies":
+            if data.get("anomalies"):
+                context = ""
+                for anomaly in data["anomalies"]:
+                    context += f"- {anomaly['metric']} on {anomaly['asset']}\n"
+                    context += f"  Score: {anomaly['score']*100:.1f}%\n"
+                    context += f"  Value: {anomaly['value']}\n\n"
+                return context
+            return "No anomalies detected."
+
+        return json.dumps(data, indent=2)
+
 
     def _extract_completion(self, result: Dict) -> str:
         """Extract and clean up the model's response"""