Spaces:
Runtime error
Runtime error
File size: 5,418 Bytes
fa70ae5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 |
# LLM agent player using HuggingFace's smolagent
from wiki_run_engine import WikiRunEnvironment
from rich.console import Console
console = Console()
try:
from smolagent import Agent, AgentConfig
except ImportError:
console.print("[red]smolagent package not found. Please install with 'uv pip install smolagent'[/red]")
raise
class AgentPlayer:
def __init__(self, wiki_data_path, model_name="HuggingFaceH4/zephyr-7b-beta"):
"""Initialize agent player"""
self.env = WikiRunEnvironment(wiki_data_path)
# Initialize LLM agent
config = AgentConfig(
model=model_name,
output_parser="json"
)
self.agent = Agent(config)
def play(self, start_article=None, target_article=None, max_steps=20):
"""Play a game of Wiki Run using the LLM agent"""
# Reset environment
state = self.env.reset(start_article, target_article)
console.print("[bold]Agent Wiki Run[/bold]")
console.print(f"Starting article: [cyan]{state['current_article']}[/cyan]")
console.print(f"Target article: [red]{state['target_article']}[/red]")
console.print()
steps = 0
while not state['is_complete'] and steps < max_steps:
console.print(f"[bold]Step {steps + 1}:[/bold]")
console.print(f"Current article: [cyan]{state['current_article']}[/cyan]")
# Create prompt for agent
prompt = self._create_agent_prompt(state)
# Get agent's decision
tool_result = self.agent.run(
prompt,
tools=[
{
"name": "choose_next_article",
"description": "Choose the next Wikipedia article to navigate to",
"parameters": {
"type": "object",
"properties": {
"article": {
"type": "string",
"description": "The title of the next article to navigate to"
},
"reasoning": {
"type": "string",
"description": "Explanation of why this article was chosen"
}
},
"required": ["article", "reasoning"]
}
}
]
)
# Extract agent's choice
choice = tool_result.get("choose_next_article", {})
next_article = choice.get("article", "")
reasoning = choice.get("reasoning", "")
console.print(f"[yellow]Agent reasoning: {reasoning}[/yellow]")
console.print(f"Agent chooses: [green]{next_article}[/green]")
# Verify the choice is valid
if next_article in state['available_links']:
state, message = self.env.step(next_article)
if message:
console.print(f"[bold]{message}[/bold]")
else:
console.print("[red]Invalid choice! Agent selected an article that's not in the available links.[/red]")
# Choose a random valid link as fallback
import random
next_article = random.choice(state['available_links'])
console.print(f"[yellow]Falling back to random choice: {next_article}[/yellow]")
state, _ = self.env.step(next_article)
steps += 1
console.print()
# Game complete
if state['is_complete']:
console.print("[bold green]Success! Agent reached the target article![/bold green]")
else:
console.print("[bold red]Failed to reach target within step limit.[/bold red]")
console.print(f"Steps taken: [bold]{state['steps_taken']}[/bold]")
console.print(f"Path: [italic]{' → '.join(state['path_taken'])}[/italic]")
return state
def _create_agent_prompt(self, state):
"""Create prompt for the agent"""
current = state['current_article']
target = state['target_article']
links = state['available_links']
prompt = f"""You are playing the Wiki Run game. Your goal is to navigate from the current Wikipedia article to the target article using only the available links.
Current article: {current}
Target article: {target}
Available links (choose one):
{', '.join(links)}
Choose the link that you think will get you closest to the target article. Consider:
1. Direct connections to the target
2. Articles that might be in the same category as the target
3. General articles that might have many links to other topics
Use the choose_next_article tool to make your selection."""
return prompt
if __name__ == "__main__":
import sys
if len(sys.argv) < 2:
console.print("[red]Please provide the path to Wikipedia data[/red]")
console.print("Usage: python agent.py <wiki_data_path>")
sys.exit(1)
wiki_data_path = sys.argv[1]
agent = AgentPlayer(wiki_data_path)
agent.play()
|