record result

app.py

@@ -1,19 +1,32 @@
 import gradio as gr
 from chatbot_simulator import ChatbotSimulation
-from task_specific_data_population import DataPopulation
+from huggingface_hub import HfApi, create_repo
 from datasets import load_dataset
 import json_repair
 import random
 import os
+import re
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 
-openai_api_key = os.getenv("OPENAI_API_KEY")
+openai_api_key = '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'#os.getenv("OPENAI_API_KEY")
+
+task_completed = 0
+task_completed_steps = None
+
+
+def is_task_incomplete(example):
+    return example["task_completed"] is None and example["task_completed_steps"] is None
+
+
+def is_task_given_up(example):
+    return example["task_completed"] == 0 and example["task_completed_steps"] == 0
 
 
 class AppSimulator:
     def __init__(self, openai_api_key):
         self.simulation = None
         self.openai_api_key = openai_api_key
+        self.app_name = None
 
     def initialize_simulator(self, sitemap_url, progress=gr.Progress(track_tqdm=True)):
         """Initialize the simulator with retries and elapsed time tracking."""
@@ -31,12 +44,24 @@ class AppSimulator:
             elif row['name'] == 'system_data':
                 system_data = json_repair.loads(row['value'])
 
-        synthetic_tasks = load_dataset(sitemap_url, "tasks", split='train')
-        random_index = random.randint(0, len(synthetic_tasks) - 1)  # Generate a random index
-        random_row = synthetic_tasks[random_index]
-        task = random_row['tasks']
-        solution = random_row['steps']
-        user_data = random_row['attributes']['user_data']
+        self.app_name = app_name
+        human_result_url = "jjz5463/simulator_human_result"
+        synthetic_tasks = load_dataset(human_result_url, app_name, split='train')
+
+        incomplete_tasks = synthetic_tasks.filter(is_task_incomplete)
+        give_up_tasks = synthetic_tasks.filter(is_task_given_up)
+        if len(incomplete_tasks) > 0:
+            incomplete_task = incomplete_tasks[0]
+            task = incomplete_task["tasks"]
+            solution = incomplete_task["steps"]
+            user_data = incomplete_task["attributes"]["user_data"]
+        elif len(give_up_tasks) > 0:
+            give_up_task = give_up_tasks[0]
+            task = give_up_task["tasks"]
+            solution = give_up_task["steps"]
+            user_data = give_up_task["attributes"]["user_data"]
+        else:
+            return "All tasks in this app have been completed!"
 
         self.simulation = ChatbotSimulation(
             app_name=app_name,
@@ -68,9 +93,75 @@ simulator_app = AppSimulator(openai_api_key=openai_api_key)
 def chat(user_input, history):
     """Chat handler that validates input and interacts with the simulator."""
     response = simulator_app.chat_interaction(user_input, history)
+
+    # Initialize variables for task completion and steps
+
+    # Define the pattern for matching the response
+    pattern = r"Task completed! You took (\d+) steps\."
+    match = re.match(pattern, response)
+
+    global task_completed
+    global task_completed_steps
+    task_completed = 0
+    task_completed_steps = None
+    if match:
+        task_completed = 1
+        task_completed_steps = int(match.group(1))
+        human_result_url = "jjz5463/simulator_human_result"
+        app_name = simulator_app.app_name
+        synthetic_tasks = load_dataset(human_result_url, app_name, split='train')
+        incomplete_tasks = synthetic_tasks.filter(is_task_incomplete)
+        if len(incomplete_tasks) > 0:
+            incomplete_task_index = incomplete_tasks['__index_level_0__'][0]
+            synthetic_tasks = synthetic_tasks.map(
+                lambda example, idx: {
+                    "task_completed": task_completed if idx == incomplete_task_index else example["task_completed"],
+                    "task_completed_steps": task_completed_steps if idx == incomplete_task_index else example["task_completed_steps"],
+                },
+                with_indices=True,
+            )
+            # Push the updated dataset back to Hugging Face
+            synthetic_tasks.push_to_hub(human_result_url)
+
     return response
 
 
+def give_up():
+    """Handle the Give-Up action by marking the first incomplete task as abandoned."""
+    global task_completed, task_completed_steps
+    task_completed = 0
+    task_completed_steps = 0
+
+    # Access the app_name from the simulator instance
+    app_name = simulator_app.app_name
+    if not app_name:
+        return "Simulator has not been initialized with an app!"
+
+    # Load the human result dataset
+    human_result_url = "jjz5463/simulator_human_result"
+    synthetic_tasks = load_dataset(human_result_url, app_name, split='train')
+
+    # Find the first incomplete task
+    incomplete_tasks = synthetic_tasks.filter(is_task_incomplete)
+    if len(incomplete_tasks) > 0:
+        incomplete_task_index = incomplete_tasks['__index_level_0__'][0]
+
+        # Update the dataset to mark the task as abandoned
+        synthetic_tasks = synthetic_tasks.map(
+            lambda example, idx: {
+                "task_completed": task_completed if idx == incomplete_task_index else example["task_completed"],
+                "steps": task_completed_steps if idx == incomplete_task_index else example["steps"],
+            },
+            with_indices=True,
+        )
+
+        # Push the updated dataset back to Hugging Face
+        synthetic_tasks.push_to_hub(human_result_url)
+        return "Task marked as abandoned (Give-Up action)."
+    else:
+        return "No incomplete tasks found to abandon!"
+
+
 # Gradio Interface using ChatInterface
 with gr.Blocks(fill_height=True) as demo:
     gr.Markdown("## Simulator Setup")
@@ -85,6 +176,8 @@ with gr.Blocks(fill_height=True) as demo:
     # Chat interface to handle user interactions
     chat_interface = gr.ChatInterface(fn=chat, type='messages')
 
+    give_up_button = gr.Button("Give Up")
+
     # Define the callback function to initialize the simulator and update status
     def initialize_and_start_chat(sitemap):
         return simulator_app.initialize_simulator(sitemap)  # Use progress tracking
@@ -96,5 +189,12 @@ with gr.Blocks(fill_height=True) as demo:
         outputs=status  # Update only the status block
     )
 
+    # Set up the Give-Up button click to update the dataset
+    give_up_button.click(
+        fn=give_up,
+        inputs=[],
+        outputs=status  # Update the status with the give-up message
+    )
+
 # Launch the app
 demo.launch()

chatbot_simulator.py

@@ -179,7 +179,7 @@ class ChatbotSimulation:
         return gpt_instruction
 
     def start_conversation(self):
-        greeting = f'\nWelcome to {self.app_name} simulator! Your task is: {self.task}. \n'
+        greeting = f'\nWelcome to {self.app_name} simulator! Your task is: {self.task} \n'
         system_prompt = self._generate_system_prompt()
         # GPT generates the page instructions
         self.conversation.append({"role": "system", "content": system_prompt})