diff --git a/app/api/agent/run/route.ts b/app/api/agent/run/route.ts
index ec0555c..086cdd8 100644
--- a/app/api/agent/run/route.ts
+++ b/app/api/agent/run/route.ts
@@ -1,10 +1,8 @@
 import { NextRequest, NextResponse } from 'next/server';
-import { OpenAI } from '@llamaindex/openai';
-import { Anthropic } from '@llamaindex/anthropic';
-import { Gemini, GEMINI_MODEL } from '@llamaindex/google';
 import { Settings, LLM, tool } from 'llamaindex';
 import { agent } from '@llamaindex/workflow';
 import { z } from 'zod';
+import { getLlm } from '@/lib/llm-utils';
 
 export async function POST(req: NextRequest) {
   try {
@@ -50,31 +48,7 @@ export async function POST(req: NextRequest) {
     }
 
     // 2. Configure LLM
-    const llmProvider = settings?.defaultLLM || 'gpt-4-turbo';
-    let llm;
-    let llmApiKey: string | undefined;
-
-    if (llmProvider.startsWith('gpt')) {
-      llmApiKey = settings?.apiKeys?.openai;
-      llm = new OpenAI({ model: 'gpt-4.1-mini', apiKey: llmApiKey });
-    } else if (llmProvider.startsWith('claude')) {
-      llmApiKey = settings?.apiKeys?.anthropic;
-      llm = new Anthropic({
-        model: 'claude-sonnet-4-20250514',
-        apiKey: llmApiKey,
-      });
-    } else if (llmProvider.startsWith('gemini')) {
-      llmApiKey = settings?.apiKeys?.google;
-      llm = new Gemini({
-        model: GEMINI_MODEL.GEMINI_PRO_LATEST,
-        apiKey: llmApiKey,
-      });
-    } else {
-      return NextResponse.json(
-        { error: `Unsupported LLM provider: ${llmProvider}` },
-        { status: 400 },
-      );
-    }
+    const llm = getLlm(settings);
 
     // 3. Create dynamic tools for the agent
     const tools: any[] = [];
diff --git a/app/api/llm/call/route.ts b/app/api/llm/call/route.ts
new file mode 100644
index 0000000..63edd43
--- /dev/null
+++ b/app/api/llm/call/route.ts
@@ -0,0 +1,24 @@
+import { NextRequest, NextResponse } from "next/server";
+import { getLlm } from "@/lib/llm-utils";
+
+export async function POST(req: NextRequest) {
+    try {
+        const body = await req.json();
+        const { input, node, settings } = body;
+
+        if (!input || !node || !settings) {
+            return NextResponse.json({ error: "Missing required parameters" }, { status: 400 });
+        }
+
+        const llm = getLlm(settings, node);
+        
+        const response = await llm.chat({
+            messages: [{ role: "user", content: typeof input === 'string' ? input : JSON.stringify(input) }]
+        });
+        
+        return NextResponse.json({ output: response.message.content });
+
+    } catch (error: any) {
+        return NextResponse.json({ error: error.message }, { status: 500 });
+    }
+} 
diff --git a/src/components/AgentBuilderSettings.tsx b/src/components/AgentBuilderSettings.tsx
index 772760c..1690782 100644
--- a/src/components/AgentBuilderSettings.tsx
+++ b/src/components/AgentBuilderSettings.tsx
@@ -31,6 +31,7 @@ interface AgentBuilderSettingsProps {
 }
 
 const AgentBuilderSettings = memo(({ settings, onUpdateSettings }: AgentBuilderSettingsProps) => {
+  const [isClient, setIsClient] = useState(false);
   const [showApiKeys, setShowApiKeys] = useState({
     llamaCloud: false,
     openai: false,
@@ -62,6 +63,10 @@ const AgentBuilderSettings = memo(({ settings, onUpdateSettings }: AgentBuilderS
     }));
   };
 
+  useEffect(() => {
+    setIsClient(true);
+  }, []);
+
   // Get the current API key based on selected LLM
   const getCurrentApiKey = () => {
     switch (settings.defaultLLM) {
@@ -119,6 +124,10 @@ const AgentBuilderSettings = memo(({ settings, onUpdateSettings }: AgentBuilderS
     }
   };
 
+  if (!isClient) {
+    return null;
+  }
+
   return (
     <Card className="p-3 space-y-4">
       {/* LlamaCloud API Key */}
diff --git a/src/components/AgentFlow.tsx b/src/components/AgentFlow.tsx
index 6a700ab..5823bf6 100644
--- a/src/components/AgentFlow.tsx
+++ b/src/components/AgentFlow.tsx
@@ -210,7 +210,7 @@ const AgentFlowInner = ({ nodes, edges, onNodesChange, onEdgesChange, setNodes,
 
       <AgentBuilderSidebar onAddNode={onAddNode} onReset={onReset} settings={settings} onUpdateSettings={onUpdateSettings} />
       
-      <div className="flex-1" ref={reactFlowWrapper}>
+      <div className="flex-1 h-full">
         <ReactFlow
           nodes={nodes}
           edges={edges}
@@ -222,6 +222,7 @@ const AgentFlowInner = ({ nodes, edges, onNodesChange, onEdgesChange, setNodes,
           nodeTypes={nodeTypes}
           deleteKeyCode={['Backspace', 'Delete']}
           fitView
+          proOptions={{ hideAttribution: true }}
           className="bg-flow-bg"
           defaultEdgeOptions={{
             type: 'default',
diff --git a/src/components/RunView.tsx b/src/components/RunView.tsx
index dc43092..e0ae91d 100644
--- a/src/components/RunView.tsx
+++ b/src/components/RunView.tsx
@@ -74,6 +74,28 @@ const loadSavedGraph = () => {
   };
 };
 
+const getMessageContent = (data: any): string => {
+  if (typeof data === 'string') {
+    return data;
+  }
+  if (Array.isArray(data) && data.length > 0 && data[0].type === 'text' && typeof data[0].text === 'string') {
+    return data[0].text;
+  }
+  return JSON.stringify(data, null, 2);
+}
+
+const loadSavedSettings = () => {
+  try {
+    const savedSettings = localStorage.getItem('agent-builder-settings');
+    if (savedSettings) {
+      return JSON.parse(savedSettings);
+    }
+  } catch (error) {
+    console.error('Error loading saved settings:', error);
+  }
+  return {};
+}
+
 const RunViewInner = () => {
   const [nodes, setNodes, onNodesChange] = useNodesState<Node>([]);
   const [edges, setEdges, onEdgesChange] = useEdgesState<Edge>([]);
@@ -158,21 +180,61 @@ const RunViewInner = () => {
           // The workflow will now wait for user input.
           // The onUserInput function will be called when the user submits a message.
           return; // Don't proceed further until user input
-        case 'promptLLM':
-          // This will be handled similarly to promptAgent
-          const llmOutput = `Mock output from ${node.data.label}`;
+        case 'promptLLM': {
+          // find the previous node to get the input
+          const incomingEdge = edges.find((e) => e.target === nodeId);
+          const parentNodeId = incomingEdge?.source;
+          const input = parentNodeId ? workflowStateRef.current[parentNodeId] : null;
+
+          if (!input) {
+            setError(`Input for node ${nodeId} not found.`);
+            setExecutionStatus('error');
+            return;
+          }
+        
+          const thinkingMessageId = Math.random().toString();
           setMessages((prev) => [
             ...prev,
             {
-              id: Math.random().toString(),
+              id: thinkingMessageId,
               role: 'assistant',
-              content: `Executing ${node.data.label}...`,
+              content: `Thinking with ${node.data.label}...`,
             },
           ]);
+
+          const llmResponse = await fetch('/api/llm/call', {
+            method: 'POST',
+            body: JSON.stringify({
+              input: input,
+              node: node,
+              settings: loadSavedSettings()
+            }),
+            headers: {
+              'Content-Type': 'application/json',
+            },
+          });
+
+          if (!llmResponse.ok) {
+            throw new Error(
+              `LLM execution failed: ${await llmResponse.text()}`,
+            );
+          }
+
+          const { output: llmOutput } = await llmResponse.json();
+
           setWorkflowState((prevState) => ({
             ...prevState,
             [nodeId]: llmOutput,
           }));
+
+          setMessages((prev) =>
+            prev.map((msg) =>
+              msg.id === thinkingMessageId
+                ? { ...msg, content: getMessageContent(llmOutput) }
+                : msg
+            )
+          );
+
           const llmEdge = edges.find((e) => e.source === nodeId);
           if (llmEdge) {
             nextNodeId = llmEdge.target;
@@ -180,6 +242,7 @@ const RunViewInner = () => {
             setExecutionStatus('finished');
           }
           break;
+        }
         case 'promptAgent':
           const compiledWorkflow = compileWorkflow(nodes, edges);
           const response = await fetch('/api/agent/run', {
@@ -207,7 +270,7 @@ const RunViewInner = () => {
             {
               id: Math.random().toString(),
               role: 'assistant',
-              content: output,
+              content: getMessageContent(output),
             },
           ]);
 
@@ -305,6 +368,7 @@ const RunViewInner = () => {
               nodesDraggable={false}
               nodesConnectable={false}
               elementsSelectable={false}
+              proOptions={{ hideAttribution: true }}
               className="bg-flow-bg"
               defaultEdgeOptions={{
                 type: 'default',
diff --git a/src/components/nodes/PromptLLMNode.tsx b/src/components/nodes/PromptLLMNode.tsx
index 27e25ef..374a604 100644
--- a/src/components/nodes/PromptLLMNode.tsx
+++ b/src/components/nodes/PromptLLMNode.tsx
@@ -1,67 +1,21 @@
 import { memo } from 'react';
-import { Handle, Position, useReactFlow } from '@xyflow/react';
+import { Handle, Position } from '@xyflow/react';
 import { Brain } from 'lucide-react';
 
 interface PromptLLMNodeProps {
   id: string;
   data: {
     label?: string;
-    model?: string;
-    temperature?: number;
   };
   selected?: boolean;
 }
 
 const PromptLLMNode = memo(({ id, data, selected }: PromptLLMNodeProps) => {
-  const { setNodes } = useReactFlow();
-
-  const handleModelChange = (value: string) => {
-    setNodes((nodes) =>
-      nodes.map((node) =>
-        node.id === id
-          ? { ...node, data: { ...node.data, model: value } }
-          : node
-      )
-    );
-  };
-
-  const handleTemperatureChange = (value: string) => {
-    const temperature = value === '' ? undefined : parseFloat(value);
-    setNodes((nodes) =>
-      nodes.map((node) =>
-        node.id === id
-          ? { ...node, data: { ...node.data, temperature } }
-          : node
-      )
-    );
-  };
-
   return (
     <div className={`agent-node node-llm ${selected ? 'selected' : ''}`}>
       <div className="node-content flex flex-col items-center justify-center text-foreground p-4 min-w-[180px]">
         <Brain className="w-5 h-5 mb-2" />
         <span className="text-sm font-medium mb-2">{data.label || 'Prompt LLM'}</span>
-        <div className="w-full space-y-1">
-          <input 
-            type="text" 
-            value={data.model || ''}
-            placeholder="Model (e.g., gpt-4)"
-            className="w-full px-2 py-1 text-xs bg-muted border border-border rounded text-foreground placeholder-muted-foreground"
-            onChange={(e) => handleModelChange(e.target.value)}
-            onClick={(e) => e.stopPropagation()}
-          />
-          <input 
-            type="number" 
-            value={data.temperature !== undefined ? data.temperature.toString() : ''}
-            placeholder="Temperature"
-            min="0"
-            max="2"
-            step="0.1"
-            className="w-full px-2 py-1 text-xs bg-muted border border-border rounded text-foreground placeholder-muted-foreground"
-            onChange={(e) => handleTemperatureChange(e.target.value)}
-            onClick={(e) => e.stopPropagation()}
-          />
-        </div>
       </div>
       <Handle type="target" position={Position.Top} />
       <Handle type="source" position={Position.Bottom} />
@@ -71,4 +25,4 @@ const PromptLLMNode = memo(({ id, data, selected }: PromptLLMNodeProps) => {
 
 PromptLLMNode.displayName = 'PromptLLMNode';
 
-export default PromptLLMNode;
\ No newline at end of file
+export default PromptLLMNode;
diff --git a/src/lib/llm-utils.ts b/src/lib/llm-utils.ts
new file mode 100644
index 0000000..0c851f1
--- /dev/null
+++ b/src/lib/llm-utils.ts
@@ -0,0 +1,39 @@
+import { OpenAI } from "@llamaindex/openai";
+import { Anthropic } from "@llamaindex/anthropic";
+import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
+import { LLM } from "llamaindex";
+
+export function getLlm(settings: any, nodeData: any = {}): LLM {
+    const llmProvider = settings?.defaultLLM || "gpt-4o";
+    let llm: LLM;
+    let llmApiKey: string | undefined;
+
+    const model = nodeData?.data?.model;
+    const temperature = nodeData?.data?.temperature;
+
+    if (llmProvider.startsWith("gpt")) {
+        llmApiKey = settings?.apiKeys?.openai;
+        llm = new OpenAI({
+            model: model || "gpt-4.1-mini",
+            temperature: temperature ?? 0.2,
+            apiKey: llmApiKey
+        });
+    } else if (llmProvider.startsWith("claude")) {
+        llmApiKey = settings?.apiKeys?.anthropic;
+        llm = new Anthropic({
+            model: model || "claude-sonnet-4-20250514",
+            temperature: temperature ?? 0.2,
+            apiKey: llmApiKey,
+        });
+    } else if (llmProvider.startsWith("gemini")) {
+        llmApiKey = settings?.apiKeys?.google;
+        llm = new Gemini({
+            model: model || "gemini-pro",
+            temperature: temperature ?? 0.2,
+            apiKey: llmApiKey,
+        });
+    } else {
+        throw new Error(`Unsupported LLM provider: ${llmProvider}`);
+    }
+    return llm;
+} 
diff --git a/src/lib/typescript-compiler.ts b/src/lib/typescript-compiler.ts
index e6f8793..ac0eb0b 100644
--- a/src/lib/typescript-compiler.ts
+++ b/src/lib/typescript-compiler.ts
@@ -29,14 +29,17 @@ const getEventName = (eventId: string) => eventId.replace(/-/g, "_");
 const generateImports = (json: WorkflowJson): string => {
   const imports = new Set<string>();
   const hasPromptAgent = json.nodes.some((node) => node.type === "promptAgent");
+  const hasPromptLLM = json.nodes.some((node) => node.type === "promptLLM");
   const hasTools = json.nodes.some(
     (node: any) =>
       node.type === "promptAgent" && node.tools && node.tools.length > 0,
   );
   const hasUserInput = json.nodes.some((node) => node.type === "userInput");
 
-  if (hasPromptAgent) {
-    imports.add('import { agent } from "@llamaindex/workflow";');
+  if (hasPromptAgent || hasPromptLLM) {
+    if (hasPromptAgent) {
+      imports.add('import { agent } from "@llamaindex/workflow";');
+    }
     const llmProvider = json.settings?.defaultLLM || "gpt-4o";
     if (llmProvider.startsWith("gpt")) {
       imports.add('import { OpenAI } from "@llamaindex/openai";');
@@ -87,7 +90,7 @@ const generateLlmInit = (json: WorkflowJson): string => {
     });
   }
 
-  if (json.nodes.some((node) => node.type === "promptAgent")) {
+  if (json.nodes.some((node) => node.type === "promptAgent" || node.type === "promptLLM")) {
     const llmProvider = json.settings?.defaultLLM || "gpt-4o";
     if (llmProvider.startsWith("gpt")) {
       lines.push(
@@ -231,8 +234,9 @@ const generateEvents = (nodes: WorkflowNodeJson[]): string => {
     .join("\n");
 };
 
-const generateHandlers = (nodes: WorkflowNodeJson[]): string => {
+const generateHandlers = (json: WorkflowJson): string => {
   let handlerLines: string[] = [];
+  const { nodes } = json;
 
   for (const node of nodes) {
     if (node.type === "stop") {
@@ -276,6 +280,36 @@ const generateHandlers = (nodes: WorkflowNodeJson[]): string => {
         (node as any).prompt?.replace(/`/g, "\\`") || "Enter your input:";
       handlerBody = `
     return ${needInputEventName}.with("${prompt}");`;
+    } else if (node.type === "promptLLM") {
+      const nodeData = node as any;
+      const model = nodeData.data?.model;
+      const temperature = nodeData.data?.temperature;
+      const settings = json.settings;
+      const defaultLLM = settings?.defaultLLM || "gpt-4o";
+
+      let llmToUse = "llm";
+      let llmDefinition = "";
+
+      if (model || typeof temperature !== "undefined") {
+        const llmVar = `llm_${node.id.replace(/-/g, "_")}`;
+        llmToUse = llmVar;
+        const defaultModelForProvider = defaultLLM.startsWith("gpt")
+          ? "gpt-4.1-mini"
+          : defaultLLM.startsWith("claude")
+            ? "claude-sonnet-4-20250514"
+            : "gemini-2.5-pro-latest";
+        const finalModel = model || defaultModelForProvider;
+        const tempValue = typeof temperature !== "undefined" ? temperature : 0.2;
+
+        let llmClass = "OpenAI";
+        if (defaultLLM.startsWith("claude")) llmClass = "Anthropic";
+        else if (defaultLLM.startsWith("gemini")) llmClass = "Gemini";
+        llmDefinition = `    const ${llmVar} = new ${llmClass}({ model: "${finalModel}", temperature: ${tempValue} });`;
+      }
+      handlerBody = `
+${llmDefinition}
+    const result = await ${llmToUse}.chat({ messages: [{ role: "user", content: typeof ctx.data === 'string' ? ctx.data : JSON.stringify(ctx.data) }]});
+    return ${nextEventName}.with(result.message.content);`;
     } else if (node.type === "promptAgent") {
       const toolNames =
         (node as any).tools?.map(
@@ -366,7 +400,7 @@ export const generateTypescript = (json: WorkflowJson): string => {
   const llmInit = generateLlmInit(json);
   const tools = generateTools(json);
   const events = generateEvents(json.nodes);
-  const handlers = generateHandlers(json.nodes);
+  const handlers = generateHandlers(json);
   const execution = generateExecution("startEvent", "stopEvent", json.nodes);
 
   return LlamaIndexTemplate(