Add benchmark test scripts (#19)

Signed-off-by: lvliang-intel <[email protected]>

GenAIEval/benchmark/__init__.py

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+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0

GenAIEval/benchmark/chatqna_benchmark.py

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+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import argparse
+import concurrent.futures
+import json
+import random
+import time
+
+import numpy
+import requests
+
+response_times = []
+
+
+def extract_qText(json_data):
+    try:
+        file = open("data.json")
+        data = json.load(file)
+        post_json_data = {}
+        post_json_data["model"] = "Intel/neural-chat-7b-v3-3"
+        post_json_data["messages"] = data[random.randint(0, len(data) - 1)]["qText"]
+        return json.dumps(post_json_data)
+    except (json.JSONDecodeError, KeyError, IndexError):
+        return None
+
+
+def send_request(url, json_data):
+    global response_times
+    print(f"Sending request to {url} with data {json_data}")
+    start_time = time.time()
+    headers = {"Content-Type": "application/json"}
+    response = requests.post(url, data=json_data, headers=headers)
+    end_time = time.time()
+    response_times.append(end_time - start_time)
+    print(f"Question: {json_data} Response: {response.status_code} - {response.text}")
+
+
+def main(url, json_data, concurrency):
+    global response_times
+    with concurrent.futures.ThreadPoolExecutor(max_workers=concurrency) as executor:
+        future_to_url = {
+            executor.submit(send_request, url, extract_qText(json_data)): url for _ in range(concurrency * 2)
+        }
+        for future in concurrent.futures.as_completed(future_to_url):
+            _ = future_to_url[future]
+
+    print(f"Total Requests: {concurrency*2}")
+
+    # Calculate the P50 (median)
+    p50 = numpy.percentile(response_times, 50)
+    print("P50 latency is ", p50, "s")
+
+    # Calculate the P99
+    p99 = numpy.percentile(response_times, 99)
+    print("P99 latency is ", p99, "s")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Concurrent client to send POST requests")
+    parser.add_argument(
+        "--backend_url", type=str, default="http://localhost:8888/v1/chatqna", help="Service URL to send requests to"
+    )
+    parser.add_argument(
+        "--json_data",
+        type=str,
+        default='{"inputs":"Which NFL team won the Super Bowl in the 2010 season?","parameters":{"do_sample": true}}',
+        help="JSON data to send",
+    )
+    parser.add_argument("--concurrency", type=int, default=100, help="Concurrency level")
+    args = parser.parse_args()
+    main(args.backend_url, args.json_data, args.concurrency)