Update app.py

app.py

@@ -1,31 +1,26 @@
 import os
 import subprocess
 import sys
+import json
 
-# 克隆代码并设置环境
+# 设置环境
 def setup_environment():
-    # 检查目录是否已存在
     if not os.path.exists("skywork-o1-prm-inference"):
         print("Cloning repository...")
         subprocess.run(["git", "clone", "https://github.com/SkyworkAI/skywork-o1-prm-inference.git"], check=True)
-    
-    # 添加到 Python 路径
     repo_path = os.path.abspath("skywork-o1-prm-inference")
     if repo_path not in sys.path:
         sys.path.append(repo_path)
         print(f"Added {repo_path} to Python path")
 
-# 设置环境
 setup_environment()
 
-# 现在可以导入需要的模块
 import gradio as gr
 from transformers import AutoTokenizer
 from model_utils.prm_model import PRM_MODEL
 from model_utils.io_utils import prepare_input, prepare_batch_input_for_model, derive_step_rewards
 import torch
 
-# 初始化模型和tokenizer
 model_id = "Skywork/Skywork-o1-Open-PRM-Qwen-2.5-1.5B"
 tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
 model = PRM_MODEL.from_pretrained(model_id).to("cpu").eval()
@@ -33,9 +28,7 @@ model = PRM_MODEL.from_pretrained(model_id).to("cpu").eval()
 def evaluate(problem, response):
     try:
         processed_data = prepare_input(problem, response, tokenizer=tokenizer, step_token="\n")
-        input_ids, steps, reward_flags = [processed_data]
-        
-        input_ids, attention_mask, reward_flags = prepare_batch_input_for_model(
+        input_ids, steps, reward_flags = [processed_data]input_ids, attention_mask, reward_flags = prepare_batch_input_for_model(
             input_ids, 
             reward_flags, 
             tokenizer.pad_token_id
@@ -53,9 +46,10 @@ def evaluate(problem, response):
                 return_probs=True
             )
         step_rewards = derive_step_rewards(rewards, reward_flags)
-        return step_rewards[0].tolist()
+        #确保返回的是有效的JSON字符串
+        return json.dumps(step_rewards[0].tolist())
     except Exception as e:
-        return str(e)
+        return json.dumps({"error": str(e)})
 
 # 创建Gradio界面
 iface = gr.Interface(
@@ -64,16 +58,17 @@ iface = gr.Interface(
         gr.Textbox(label="Problem", lines=4),
         gr.Textbox(label="Response", lines=8)
     ],
-    outputs=gr.JSON(label="Step Rewards"),
+    outputs=gr.JSON(),
     title="Problem Response Evaluation",
     description="Enter a problem and its response to get step-wise rewards",
     examples=[
         [
-            "Janet's ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?",
-            "To determine how much money Janet makes every day at the farmers' market, we need to follow these steps:\n1. Calculate the total number of eggs laid by the ducks per day.\n   Janet's ducks lay 16 eggs per day.\n2. Determine the number of eggs Janet uses each day.\n   - She eats 3 eggs for breakfast every morning.\n   - She bakes muffins for her friends every day with 4 eggs.\n   So, the total number of eggs used per day is:\n   3 + 4 = 7 eggs\n3. Calculate the number of eggs Janet sells at the farmers' market each day.\n   Subtract the number of eggs used from the total number of eggs laid:\n   16 - 7 = 9 eggs\n4. Determine how much money Janet makes from selling the eggs.\n   She sells each egg for $2, so the total amount of money she makes is:\n   9 × 2 = 18 dollars\nTherefore, the amount of money Janet makes every day at the farmers' market is $18."
+            "Janet'sducks lay 16 eggs per day...",
+            "To determine how much money Janet makes..."
         ]
-    ]
+    ],
+    cache_examples=False# 禁用示例缓存
 )
 
 # 启动接口
-iface.launch()
+iface.launch(server_name="0.0.0.0")