Format Benchmark Code (#399)

benchmark/tip_suggestion/bench_other.py

@@ -1,22 +1,25 @@
 import argparse
-import asyncio
-from concurrent.futures import ThreadPoolExecutor
-from functools import partial
 import json
 import time
+from concurrent.futures import ThreadPoolExecutor
+from functools import partial
 
 from tqdm import tqdm
-import numpy as np
-from sglang.test.test_utils import add_common_other_args_and_parse, call_generate_lightllm, call_generate_vllm, call_generate_srt_raw
-from sglang.utils import read_jsonl, dump_state_text
 
+from sglang.test.test_utils import (
+    add_common_other_args_and_parse,
+    call_generate_lightllm,
+    call_generate_srt_raw,
+    call_generate_vllm,
+)
+from sglang.utils import dump_state_text, read_jsonl
 
 number = 5
 
 
 def expand_tip(topic, tip, generate):
     s = (
-"""Please expand a tip for a topic into a detailed paragraph.
+        """Please expand a tip for a topic into a detailed paragraph.
 
 Topic: staying healthy
 Tip: Regular Exercise
@@ -30,14 +33,23 @@ Topic: writing a blog post
 Tip: structure your content effectively
 Paragraph: A well-structured post is easier to read and more enjoyable. Start with an engaging introduction that hooks the reader and clearly states the purpose of your post. Use headings and subheadings to break up the text and guide readers through your content. Bullet points and numbered lists can make information more digestible. Ensure each paragraph flows logically into the next, and conclude with a summary or call-to-action that encourages reader engagement.
 
-Topic: """ + topic + "\nTip: " + tip + "\nParagraph:")
+Topic: """
+        + topic
+        + "\nTip: "
+        + tip
+        + "\nParagraph:"
+    )
     return generate(s, max_tokens=128, stop=["\n\n"])
 
 
 def suggest_tips(topic, generate):
     s = "Please act as a helpful assistant. Your job is to provide users with useful tips on a specific topic.\n"
     s += "USER: Give some tips for " + topic + ".\n"
-    s += ("ASSISTANT: Okay. Here are " + str(number) + " concise tips, each under 8 words:\n")
+    s += (
+        "ASSISTANT: Okay. Here are "
+        + str(number)
+        + " concise tips, each under 8 words:\n"
+    )
 
     tips = []
     for i in range(1, 1 + number):
@@ -49,12 +61,12 @@ def suggest_tips(topic, generate):
     paragraphs = [expand_tip(topic, tip, generate=generate) for tip in tips]
 
     for i in range(1, 1 + number):
-        s += f"Tip {i}:" + paragraphs[i-1] + "\n"
+        s += f"Tip {i}:" + paragraphs[i - 1] + "\n"
     return s
 
 
 def main(args):
-    lines = read_jsonl(args.data_path)[:args.num_questions]
+    lines = read_jsonl(args.data_path)[: args.num_questions]
     states = [None] * len(lines)
 
     # Select backend
@@ -68,13 +80,20 @@ def main(args):
         url = f"{args.host}:{args.port}/generate"
         generate = partial(call_generate_srt_raw, url=url, temperature=0)
     elif args.backend == "guidance":
-        from guidance import models, gen
+        from guidance import gen, models
 
-        model = models.LlamaCpp("/home/ubuntu/model_weights/Llama-2-7b-chat.gguf", n_gpu_layers=-1, n_ctx=4096)
+        model = models.LlamaCpp(
+            "/home/ubuntu/model_weights/Llama-2-7b-chat.gguf",
+            n_gpu_layers=-1,
+            n_ctx=4096,
+        )
 
         def generate(prompt, max_tokens, stop):
-            out = model + prompt + gen(name="answer",
-                max_tokens=max_tokens, temperature=0, stop=stop)
+            out = (
+                model
+                + prompt
+                + gen(name="answer", max_tokens=max_tokens, temperature=0, stop=stop)
+            )
             return out["answer"]
 
         # warmup
@@ -111,7 +130,7 @@ def main(args):
             "other": {
                 "num_questions": args.num_questions,
                 "parallel": args.parallel,
-            }
+            },
         }
         fout.write(json.dumps(value) + "\n")