diff --git a/AI-MLbenchmarks/llm-rag/ReadMe.md b/AI-MLbenchmarks/llm-rag/ReadMe.md
new file mode 100644
index 00000000..15775096
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/ReadMe.md
@@ -0,0 +1,37 @@
+## LLM+RAG Workload
+
+### Deploy the LLM+RAG Demo
+
+To deploy the demo, run the following command:
+
+```sh
+./deploy.sh <NAMESPACE>
+```
+
+This script performs the following actions:
+- Clone the repo `https://github.com/kusumachalasani/llm-rag-deployment.git`.
+- Deploys the Postgres database
+- Deploys the LLM which uses model MaziyarPanahi/Mistral-7B-Instruct-v0.2
+- Deploys the Gradio service for Q&A.
+- Ingests several sources of data into the database for RAG (Retrieval-Augmented Generation).
+
+### Running the Load
+
+- Command to run the load
+``` 
+docker run -d --rm --network=host quay.io/kruizehub/llmragdemo-load-puppeteer:v1 node load.js --url <GRADIO_Service> [--duration <Duration load runs in ms>:default null] [--delay <Delay between questions in ms>:default 10] [--browsers <Number of browsers running the load in parallel>:default 1] [--loop <No.of times to loop over questions if duration is not set>:default 1]
+
+```
+
+- To run load using script
+```sh
+./run_load.sh <NAMESPACE>
+```
+
+### Cleanup
+```sh
+./cleanup.sh <NAMESPACE>
+```
+
+
+
diff --git a/AI-MLbenchmarks/llm-rag/cleanup.sh b/AI-MLbenchmarks/llm-rag/cleanup.sh
new file mode 100755
index 00000000..8efcb527
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/cleanup.sh
@@ -0,0 +1,45 @@
+#!/bin/bash
+
+if [ -z "$1" ]; then
+  echo "Error: Provide namespace to uninstall the application."
+  exit 1
+fi
+
+NAMESPACE=$1
+
+# Clone the repo
+git clone https://github.com/kusumachalasani/llm-rag-deployment.git -b kruize-ai
+
+cd llm-rag-deployment/
+
+# Update the namespace from `ic-shared-rag-llm` to given namespace
+# Update namespace in `examples/pipelines/data_ingest.py` which is used to ingest data
+sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" examples/pipelines/data_ingest.py
+
+cd bootstrap-rag
+## Update namespace for all yamls
+find ./pgvector-rag-deployment -type f -exec sed -i "s/namespace: ic-shared-rag-llm/namespace: ${NAMESPACE}/g" {} +
+find ./shared-rag-llm -type f -exec sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" {} +
+find ./gradio-rag -type f -exec sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" {} +
+
+# Cleanup jobs
+oc delete -f pgvector-rag-deployment/06-extend-pg-db.yaml
+oc delete -f pgvector-rag-deployment/07-ingest-data.yaml
+
+# Cleanup postgres 
+oc delete -f pgvector-rag-deployment/03-deployment.yaml
+oc delete -f pgvector-rag-deployment/04-services.yaml
+oc delete -f pgvector-rag-deployment/02-pvc.yaml
+oc delete -f pgvector-rag-deployment/01-db-secret.yaml
+
+# Cleanup llm
+oc delete -f shared-rag-llm/deployment.yaml
+oc delete -f shared-rag-llm/service.yaml
+oc delete -f shared-rag-llm/route.yaml
+oc delete -f shared-rag-llm/pvc.yaml
+
+# Cleanup gradio
+oc delete -f gradio-rag/deployment.yaml
+oc delete -f gradio-rag/service.yaml
+oc delete -f gradio-rag/route.yaml
+
diff --git a/AI-MLbenchmarks/llm-rag/deploy.sh b/AI-MLbenchmarks/llm-rag/deploy.sh
new file mode 100755
index 00000000..a9b4147c
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/deploy.sh
@@ -0,0 +1,72 @@
+#!/bin/bash
+
+if [ -z "$1" ]; then
+  echo "Error: Provide namespace to deploy the application."
+  exit 1
+fi
+
+NAMESPACE=$1
+
+# Clone the repo
+git clone https://github.com/kusumachalasani/llm-rag-deployment.git -b kruize-ai
+
+cd llm-rag-deployment/
+
+# Update the namespace from `ic-shared-rag-llm` to given namespace
+# Update namespace in `examples/pipelines/data_ingest.py` which is used to ingest data
+sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" examples/pipelines/data_ingest.py
+
+cd bootstrap-rag
+
+## Update namespace for all yamls
+find ./pgvector-rag-deployment -type f -exec sed -i "s/namespace: ic-shared-rag-llm/namespace: ${NAMESPACE}/g" {} +
+find ./shared-rag-llm -type f -exec sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" {} +
+find ./gradio-rag -type f -exec sed -i "s/ic-shared-rag-llm/${NAMESPACE}/g" {} +
+
+# Pre-requisites
+# Create the Imagestream that supports the demo to start workbench
+#oc apply -f rhoai-rag-configuration/workbench-imagestream.yaml
+
+# Install ODF and ceph-rbd-storage class. <TODO>
+# This is required for llm PVC to support multiprocessing
+# Has issues creating the storage system in AWS. 
+# Workaround to use gp3 which is default Storage system
+
+# Deploy the postgres 
+
+oc apply -f pgvector-rag-deployment/01-db-secret.yaml
+
+# Update StorageClassName for pvc
+sed -i "s/storageClassName: .*/storageClassName: ocs-external-storagecluster-ceph-rbd/" pgvector-rag-deployment/02-pvc.yaml
+
+oc apply -f pgvector-rag-deployment/02-pvc.yaml
+oc apply -f pgvector-rag-deployment/03-deployment.yaml
+oc apply -f pgvector-rag-deployment/04-services.yaml
+oc apply -f pgvector-rag-deployment/05-grant-access-to-db.yaml
+
+# Deploy the llm
+#oc apply -f shared-rag-llm/namespace.yaml
+
+# Update StorageClassName for pvc
+sed -i "s/storageClassName: .*/storageClassName: ocs-external-storagecluster-ceph-rbd/" shared-rag-llm/pvc.yaml
+
+oc apply -f shared-rag-llm/pvc.yaml
+oc apply -f shared-rag-llm/deployment.yaml
+oc apply -f shared-rag-llm/service.yaml
+oc apply -f shared-rag-llm/route.yaml
+
+
+# Deploy gradio
+oc apply -f gradio-rag/deployment.yaml
+oc apply -f gradio-rag/service.yaml
+oc apply -f gradio-rag/route.yaml
+
+# Access gradio service
+GRADIO_ROUTE=$(oc get route -n ${NAMESPACE} --template='{{range .items}}{{.spec.host}}{{"\n"}}{{end}}')
+echo "Access gradio service as  ${GRADIO_ROUTE}"
+
+# Extend pgvector and ingest data to DB 
+oc apply -f pgvector-rag-deployment/06-extend-pg-db.yaml
+oc apply -f pgvector-rag-deployment/07-ingest-data.yaml
+
+ 
diff --git a/AI-MLbenchmarks/llm-rag/load/Dockerfile b/AI-MLbenchmarks/llm-rag/load/Dockerfile
new file mode 100644
index 00000000..2dc56b46
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/load/Dockerfile
@@ -0,0 +1,33 @@
+# Use an official Node.js runtime as a parent image
+FROM node:18
+
+# Set the working directory in the container
+WORKDIR /usr/src/app
+
+# Copy the package.json and package-lock.json files
+COPY package*.json ./
+
+# Install any needed packages
+RUN npm install
+RUN npx puppeteer browsers install chrome
+
+# Install dependencies required by Puppeteer
+RUN apt-get update && apt-get install -y \
+  wget \
+  gnupg \
+  ca-certificates \
+  --no-install-recommends
+
+# Install Chromium
+RUN wget -q -O - https://dl.google.com/linux/linux_signing_key.pub | apt-key add - \
+  && sh -c 'echo "deb [arch=amd64] http://dl.google.com/linux/chrome/deb/ stable main" >> /etc/apt/sources.list.d/google-chrome.list' \
+  && apt-get update \
+  && apt-get install -y google-chrome-stable \
+  && rm -rf /var/lib/apt/lists/*
+
+# Copy the rest of the application code
+COPY . .
+
+# Command to run the script
+CMD ["node", "load.js", "--url", "http://example.com", "--loop", "1", "--browsers", "1", "--duration", "60000", "--delay", "100"]
+
diff --git a/AI-MLbenchmarks/llm-rag/load/load.js b/AI-MLbenchmarks/llm-rag/load/load.js
new file mode 100644
index 00000000..39d5edc9
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/load/load.js
@@ -0,0 +1,192 @@
+const puppeteer = require('puppeteer');
+const fs = require('fs');
+const minimist = require('minimist');
+
+function readQuestionsFromFile(filePath) {
+  const rawData = fs.readFileSync(filePath);
+  return JSON.parse(rawData);
+}
+
+async function askQuestions(page, questions, endTime, delay) {
+  let questionsAnswered = 0;
+  for (const question of questions) {
+      if(endTime != null) {
+        if (Date.now() >= endTime) break;
+      }
+      console.log(question);
+      await page.focus('[data-testid="textbox"]');
+      await page.evaluate(() => {
+        document.querySelector('[data-testid="textbox"]').value = '';
+      });
+
+      await page.type('[data-testid="textbox"]', question.question);
+
+      await page.keyboard.press('Enter');
+
+      console.log("Entered the question and waiting for the response indicator..");
+   
+       // Wait for the bot's response to appear
+      const initialResponses = await page.$$('button[data-testid="bot"]');
+      const initialResponseCount = initialResponses.length;
+      //console.log(initialResponseCount)
+      await page.waitForFunction(
+              initialCount => {
+                      const responses = document.querySelectorAll('button[data-testid="bot"]');
+                      //console.log(`Current response count: ${responses.length}, Initial response: ${responses}`);
+                      return responses.length > initialCount;
+              },
+              {},
+              initialResponseCount,
+              { timeout: 100 }
+      );
+      console.log("Waiting for response....")
+      const latestResponseIndex = initialResponseCount + 1;
+      let stable = false;
+      let lastResponse = '';
+      const stabilityCheckDelay = 5; 
+      const stabilityCheckDuration = 1000; 
+      let stabilityCheckCounter = 0;
+      // Monitor changes in the bot's latest response area until the content stabilizes
+      while (!stable) {
+              let currentResponse;
+              const botButtons = await page.$$('button[data-testid="bot"]');
+              //const buttonCount = botButtons.length;
+              //console.log(`Number of bot buttons found: ${buttonCount}`);
+
+              let retries = 0;
+              const maxRetries = 5; // Adjust based on your needs
+              while (retries < maxRetries) {
+                      try {
+                              currentResponse = await botButtons[latestResponseIndex - 1].evaluate(el => el.innerText);
+                              //console.log(currentResponse);
+                              break;
+                      } catch (error) {
+                              console.error(`Failed to find element: button[data-testid="bot"]:nth-of-type(${latestResponseIndex})`, error);
+                              retries++;
+                              await new Promise(resolve => setTimeout(resolve, delay1));
+                      }
+              }
+              if (retries === maxRetries) {
+                      console.error('Failed to find the current response after multiple attempts.');
+                      break;
+              }
+              if (currentResponse.includes('Loading content')) {
+                      //console.log("Response is still loading...");
+                      stabilityCheckCounter = 0;
+              } else if (currentResponse === lastResponse) {
+                      stabilityCheckCounter += stabilityCheckDelay;
+                      if (stabilityCheckCounter >= stabilityCheckDuration) {
+                              stable = true;
+                      }
+              } else {
+                      lastResponse = currentResponse;
+                      stabilityCheckCounter = 0;
+              }
+              await new Promise(resolve => setTimeout(resolve, stabilityCheckDelay));
+
+      }
+      questionsAnswered++;
+      await delayFunc(delay);
+  }
+  return questionsAnswered;
+
+
+}
+
+// Function to run a browser instance
+async function runBrowser(url, questions, duration, delay, headless) {
+  const headlessBool = (headless === 'true');
+  const browser = await puppeteer.launch({
+	  headless: headlessBool, 
+	  args: ['--no-sandbox', '--disable-setuid-sandbox','--disable-features=BlockInsecurePrivateNetworkRequests'] });
+  const page = await browser.newPage();
+  await page.setCacheEnabled(false);
+  if (url.startsWith('http://')) {
+    await page.setRequestInterception(true);
+  }
+  page.on('request', request => {
+    const requestUrl = request.url();
+    if (url.startsWith('http://')) {
+      if (requestUrl.includes('https')) {
+	request.abort();
+      } else {
+	request.continue();
+      }
+    }
+  });
+
+  await page.goto(url, { waitUntil: 'networkidle2', timeout: 60000 });
+  await page.waitForSelector('[data-testid="textbox"]', { timeout: 120000 });
+  console.log("Page has come up!");
+  let questionsBrowserAnswered = 0;
+  const endTime = Date.now() + duration;
+  const startQATime = performance.now();  
+  if (duration) {
+    console.log("Duration to run the load is set. Loops over the questions until the duration specified!");
+    while(Date.now() < endTime) {
+      const questionsBrowserAnsweredtemp = await askQuestions(page, questions, endTime, delay);
+      questionsBrowserAnswered += questionsBrowserAnsweredtemp;
+    }
+  } else {
+    console.log("No duration is set");
+    if (loop) {
+      console.log(`Runs all the 8 questions ${loop} times`);
+      for (let round = 0; round < loop; round++) {
+        const questionsBrowserAnsweredtemp = await askQuestions(page, questions, null, delay); 
+	questionsBrowserAnswered += questionsBrowserAnsweredtemp;
+      }
+    }
+  }
+  const endQATime = performance.now(); 
+  const QATime = (endQATime - startQATime) / 1000;
+  //console.log(`Time taken to get answers for ${questionsBrowserAnswered} questions : ${(endQATime - startQATime) / 1000} seconds`);
+  return { questionsBrowserAnswered, QATime };
+  await browser.close();
+}
+
+function delayFunc(ms) {
+  return new Promise(resolve => setTimeout(resolve, ms));
+}
+
+async function main(url, numberOfBrowsers, duration, delay, headless) {
+  const startSetTime = performance.now(); 
+  const questions = readQuestionsFromFile('./questions.json');
+  
+  const browserPromises = [];
+
+  for (let i = 0; i < numberOfBrowsers; i++) {
+    browserPromises.push(runBrowser(url, questions, duration, delay, headless));
+    await delayFunc(5000);
+  }
+	
+  const results = await Promise.all(browserPromises);
+  results.forEach((result, index) => {
+    const { questionsBrowserAnswered, QATime } = result;
+    console.log(`Browser ${index + 1} answered ${questionsBrowserAnswered} questions in ${QATime} seconds.`);
+  });
+
+  await Promise.all(browserPromises);
+  const endSetTime = performance.now(); 
+  console.log(`Time taken to complete the load run: ${(endSetTime - startSetTime) / 1000} seconds`);
+}
+
+// Parse command-line arguments
+// Parameters: URL, number of browsers, duration in milliseconds, delay between questions in milliseconds, headless mode (true/false)
+const args = minimist(process.argv.slice(2));
+
+const url = args.url;
+const numberOfBrowsers = parseInt(args.browsers) || 1;
+const duration = parseInt(args.duration) || null;
+const loop = parseInt(args.loop) || 1;
+const delay = parseInt(args.delay) || 100;
+const headless = args.headless || 'true'; 
+
+if (!url) {
+  console.error('Error: URL parameter is required');
+  process.exit(1);
+}
+
+main(url, numberOfBrowsers, duration, delay, headless)
+  .then(() => console.log('All browsers completed'))
+  .catch(error => console.error('Error:', error));
+
diff --git a/AI-MLbenchmarks/llm-rag/load/package-lock.json b/AI-MLbenchmarks/llm-rag/load/package-lock.json
new file mode 100644
index 00000000..ad130372
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/load/package-lock.json
@@ -0,0 +1,1221 @@
+{
+  "name": "load-test-gradio",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "load-test-gradio",
+      "version": "1.0.0",
+      "license": "ISC",
+      "dependencies": {
+        "minimist": "^1.2.8",
+        "puppeteer": "^22.12.1"
+      }
+    },
+    "node_modules/@babel/code-frame": {
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+      "dependencies": {
+        "@babel/highlight": "^7.24.7",
+        "picocolors": "^1.0.0"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-validator-identifier": {
+      "version": "7.24.7",
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+        "chalk": "^2.4.2",
+        "js-tokens": "^4.0.0",
+        "picocolors": "^1.0.0"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@puppeteer/browsers": {
+      "version": "2.2.3",
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+        "progress": "2.0.3",
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+        "semver": "7.6.0",
+        "tar-fs": "3.0.5",
+        "unbzip2-stream": "1.4.3",
+        "yargs": "17.7.2"
+      },
+      "bin": {
+        "browsers": "lib/cjs/main-cli.js"
+      },
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/@tootallnate/quickjs-emscripten": {
+      "version": "0.23.0",
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+    },
+    "node_modules/@types/node": {
+      "version": "20.14.9",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.14.9.tgz",
+      "integrity": "sha512-06OCtnTXtWOZBJlRApleWndH4JsRVs1pDCc8dLSQp+7PpUpX3ePdHyeNSFTeSe7FtKyQkrlPvHwJOW3SLd8Oyg==",
+      "optional": true,
+      "dependencies": {
+        "undici-types": "~5.26.4"
+      }
+    },
+    "node_modules/@types/yauzl": {
+      "version": "2.10.3",
+      "resolved": "https://registry.npmjs.org/@types/yauzl/-/yauzl-2.10.3.tgz",
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+      "optional": true,
+      "dependencies": {
+        "@types/node": "*"
+      }
+    },
+    "node_modules/agent-base": {
+      "version": "7.1.1",
+      "resolved": "https://registry.npmjs.org/agent-base/-/agent-base-7.1.1.tgz",
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+      "dependencies": {
+        "debug": "^4.3.4"
+      },
+      "engines": {
+        "node": ">= 14"
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+      "engines": {
+        "node": ">=8"
+      }
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+    "node_modules/ansi-styles": {
+      "version": "3.2.1",
+      "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-3.2.1.tgz",
+      "integrity": "sha512-VT0ZI6kZRdTh8YyJw3SMbYm/u+NqfsAxEpWO0Pf9sq8/e94WxxOpPKx9FR1FlyCtOVDNOQ+8ntlqFxiRc+r5qA==",
+      "dependencies": {
+        "color-convert": "^1.9.0"
+      },
+      "engines": {
+        "node": ">=4"
+      }
+    },
+    "node_modules/argparse": {
+      "version": "2.0.1",
+      "resolved": "https://registry.npmjs.org/argparse/-/argparse-2.0.1.tgz",
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+    },
+    "node_modules/ast-types": {
+      "version": "0.13.4",
+      "resolved": "https://registry.npmjs.org/ast-types/-/ast-types-0.13.4.tgz",
+      "integrity": "sha512-x1FCFnFifvYDDzTaLII71vG5uvDwgtmDTEVWAxrgeiR8VjMONcCXJx7E+USjDtHlwFmt9MysbqgF9b9Vjr6w+w==",
+      "dependencies": {
+        "tslib": "^2.0.1"
+      },
+      "engines": {
+        "node": ">=4"
+      }
+    },
+    "node_modules/b4a": {
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diff --git a/AI-MLbenchmarks/llm-rag/load/package.json b/AI-MLbenchmarks/llm-rag/load/package.json
new file mode 100644
index 00000000..958ca9cf
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/load/package.json
@@ -0,0 +1,16 @@
+{
+  "name": "load-test-gradio",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "dependencies": {
+    "minimist": "^1.2.8",
+    "puppeteer": "^22.12.1"
+  }
+}
diff --git a/AI-MLbenchmarks/llm-rag/load/questions.json b/AI-MLbenchmarks/llm-rag/load/questions.json
new file mode 100644
index 00000000..5277ab78
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/load/questions.json
@@ -0,0 +1,10 @@
+[
+  {"question": "How to create DS projects in openshift AI?"},
+  {"question": "What is the latest version of openshifAI self manged?"},
+  {"question": "What is the openshifAI self manged?"},
+  {"question": "Concept of AI?"},
+  {"question": "List different components of DS?"},
+  {"question": "what is difference between AI and RHOAI?"},
+  {"question": "how many versions are available?"},
+  {"question": "Do you know everything?"}
+]
diff --git a/AI-MLbenchmarks/llm-rag/run_load.sh b/AI-MLbenchmarks/llm-rag/run_load.sh
new file mode 100755
index 00000000..281a83f7
--- /dev/null
+++ b/AI-MLbenchmarks/llm-rag/run_load.sh
@@ -0,0 +1,46 @@
+#!/bin/bash
+
+if [ -z "$1" ]; then
+  echo "Error: Provide namespace where gradio is deployed to run the load."
+  exit 1
+fi
+
+NAMESPACE=$1
+LOOP=10
+BROWSERS=1
+DURATION=600000
+LOAD_TYPE="loop"
+LOG_FILE="llm_rag_logs.txt"
+
+# Delete the previous log file if exists
+if [ -f "$log_file" ]; then
+  rm "$log_file"
+fi
+
+# Access gradio service
+GRADIO_ROUTE=$(oc get route -n ${NAMESPACE} --template='{{range .items}}{{.spec.host}}{{"\n"}}{{end}}' | grep "gradio")
+GRADIO_URL=$(oc status -n ${NAMESPACE} | grep "gradio-route" | cut -d " " -f1)
+echo "Accessing gradio service using ${GRADIO_URL}"
+
+if [ ${LOAD_TYPE} == "loop" ]; then
+	echo "Running the load with ${BROWSERS} browsers and ${LOOP} loops..."
+	container_id=$(docker run -it --rm --network=host quay.io/kruizehub/llmragdemo-load-puppeteer:v1 node load.js --url ${GRADIO_URL} --loop ${LOOP} --browsers ${BROWSERS})
+
+else
+	echo "Running the load for 10mins... "
+	# Run the load for a specific duration in ms
+	container_id=$(docker run -d --rm --network=host quay.io/kruizehub/llmragdemo-load-puppeteer:v1 node load.js --url ${GRADIO_URL} --duration ${DURATION})
+
+fi
+
+podman logs --follow "$container_id" | while read line
+do
+  echo "$line" >> "$log_file"
+
+  if [[ "$line" == *"Time taken to complete the load run:"* ]]; then
+    cat ${log_file} | grep "Time taken"
+    podman stop "$container_id"
+    exit 1
+  fi
+done
+