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import os |
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import asyncio |
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import re |
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from typing import Any |
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from llama_index.llms.openai import OpenAI |
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from llama_index.core.agent.react import ReActAgent |
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from llama_index.core.tools import FunctionTool |
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from llama_index.tools.duckduckgo_search import DuckDuckGoSearchTool |
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def eval_python_code(code: str) -> str: |
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try: |
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return str(eval(code, {"__builtins__": {}})) |
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except Exception as e: |
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return f"ERROR: {e}" |
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def format_gaia_answer(answer: str, question: str = "") -> str: |
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if not answer: |
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return "" |
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answer = re.sub(r'(?i)final answer:?\s*', '', answer).strip() |
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answer = re.sub(r'(?i)i(\'?m| cannot| can\'t| unable to| apologize| not available|process the file).*', '', answer).strip() |
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if answer.startswith('"') and answer.endswith('"'): answer = answer[1:-1] |
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if answer.startswith('[') and answer.endswith(']'): answer = answer[1:-1] |
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if not re.match(r'^[A-Za-z]+\.$', answer): answer = re.sub(r'\.$', '', answer) |
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if question: |
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if re.search(r'how many|number of|at bats|total sales|albums|output.*python|highest number', question, re.I): |
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num = re.search(r'(\$?\d[\d,\.]*)', answer) |
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if num: return num.group(1).replace(',', '') |
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if 'first name' in question: return answer.split()[0] |
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if 'surname' in question: return answer.split()[-1] |
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if 'city' in question: return answer.split()[0] |
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if re.search(r'IOC country code|award number|NASA', question, re.I): |
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code = re.search(r'[A-Z0-9]{3,}', answer) |
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if code: return code.group(0) |
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if re.search(r'list|comma.*separated|page numbers', question, re.I): |
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items = [x.strip('",.').lower() for x in re.split(r'[,\n]', answer) if x.strip()] |
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if 'page numbers' in question: |
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nums = [int(x) for x in re.findall(r'\d+', answer)] |
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return ', '.join(str(n) for n in sorted(nums)) |
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if 'ingredient' in question or 'vegetable' in question: |
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merged = [] |
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skip = False |
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for i, item in enumerate(items): |
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if skip: skip = False; continue |
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if i+1 < len(items) and item in ['sweet', 'green', 'lemon', 'ripe', 'whole', 'fresh']: |
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merged.append(f"{item} {items[i+1]}") |
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skip = True |
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else: merged.append(item) |
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merged = sorted(set(merged)) |
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return ', '.join(merged) |
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return ', '.join(items) |
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return answer.strip().rstrip('.').strip() |
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llm = OpenAI(model="gpt-4o", api_key=os.environ.get("OPENAI_API_KEY")) |
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tools = [ |
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DuckDuckGoSearchTool(), |
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FunctionTool.from_defaults( |
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eval_python_code, |
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name="python_eval", |
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description="Evaluate simple Python code and return result as string. Use for math or code output." |
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), |
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FunctionTool.from_defaults( |
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format_gaia_answer, |
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name="format_gaia_answer", |
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description="Postprocess and enforce strict GAIA format on answers given a question." |
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), |
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] |
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agent = ReActAgent.from_tools( |
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tools=tools, |
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llm=llm, |
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system_prompt="You are a helpful GAIA benchmark agent. For every question, use the best tools available and always return only the final answer in the strict GAIA-required format—never explain, never apologize.", |
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verbose=False |
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) |
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async def answer_question(question: str, task_id: str = None, file_path: str = None) -> str: |
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result = await agent.achat(question) |
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return result.response |
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def answer_question_sync(question: str, task_id: str = None, file_path: str = None) -> str: |
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return asyncio.run(answer_question(question, task_id, file_path)) |
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class GaiaAgent: |
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def __call__(self, question: str, task_id: str = None, file_path: str = None) -> str: |
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return answer_question_sync(question, task_id, file_path) |