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import re
from smolagents import (
AgentMemory,
CodeAgent,
InferenceClientModel,
FinalAnswerTool,
WebSearchTool,
)
from collections.abc import Callable
from smolagents.default_tools import VisitWebpageTool, WikipediaSearchTool
class LLMOnlyAgent:
def __init__(self):
# Instructions prompt
self.instructions = """finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].
YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise.
If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise.
If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."""
# Basic inference model
model = InferenceClientModel(
max_tokens=8096,
model_id="Qwen/Qwen3-Coder-30B-A3B-Instruct",
custom_role_conversions=None,
provider="nebius",
)
# Code Agent
self.agent = CodeAgent(
model=model,
instructions=self.instructions,
tools=[
FinalAnswerTool(),
WikipediaSearchTool(),
WebSearchTool(),
VisitWebpageTool(),
],
additional_authorized_imports=[
"markdownify",
"requests",
"pandas",
"numpy",
"chess",
],
max_steps=5,
planning_interval=3,
# final_answer_checks=self.final_answer_checks()
)
print("LLM-only Agent initialized.")
def __call__(self, question: str) -> str:
print(f"Agent received question (first 50 chars): {question[:50]}...")
answer = self.agent.run(question)
print(f"Agent returning answer: {answer}")
return answer
def final_answer_checks(self) -> list[Callable]:
return [self.check_func]
def check_func(self, answer: str, memory: AgentMemory) -> bool:
check = bool(
re.match(
r'^(\d+(\.\d+)?|\w+(\s+\w+){0,4}|(\d+(\.\d+)?|"[^"]*"|\w+)(\s*,\s*(\d+(\.\d+)?|"[^"]*"|\w+))+)$',
answer,
)
)
print(f"FINAL ANSWER CHECK is {check}")
return check
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