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import os |
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import requests |
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from openai import OpenAI |
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class GaiaAgent: |
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def __init__(self): |
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self.client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) |
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self.instructions = ( |
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"You are a highly skilled research assistant solving GAIA benchmark questions. " |
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"You can analyze documents, perform reasoning, and answer with a single factual answer only." |
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) |
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self.api_url = "https://agents-course-unit4-scoring.hf.space" |
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def fetch_file_content(self, task_id: str) -> str: |
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try: |
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url = f"{self.api_url}/files/{task_id}" |
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response = requests.get(url, timeout=10) |
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response.raise_for_status() |
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content_type = response.headers.get("Content-Type", "") |
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if "text" in content_type or "csv" in content_type or "json" in content_type: |
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return response.text[:3000] |
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elif "application/pdf" in content_type: |
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return "[PDF file content detected. Summarize manually or use tool.]" |
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else: |
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return f"[Unsupported file type: {content_type}]" |
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except Exception as e: |
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return f"[Error downloading or reading file: {e}]" |
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def __call__(self, question: str, task_id: str = None) -> str: |
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file_context = "" |
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if task_id: |
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file_context = self.fetch_file_content(task_id) |
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if file_context: |
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file_context = f"Here is the related file content:\n{file_context}\n" |
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prompt = f"{self.instructions}\n\n{file_context}Question: {question}\nAnswer:" |
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response = self.client.chat.completions.create( |
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model="gpt-4-turbo", |
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messages=[ |
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{"role": "system", "content": self.instructions}, |
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{"role": "user", "content": prompt} |
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], |
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temperature=0.0, |
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) |
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return response.choices[0].message.content.strip() |
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