Create agent.py

agent.py

@@ -0,0 +1,113 @@
+"""
+Agent for the Agents Course GAIA final assignment.
+This file must be named agent.py and placed in the root of your Space,
+next to app.py.
+"""
+
+import os
+import re
+import requests
+from smolagents import (
+    CodeAgent,
+    DuckDuckGoSearchTool,
+    VisitWebpageTool,
+    InferenceClientModel,
+    tool,
+)
+
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+
+
+@tool
+def download_task_file(task_id: str) -> str:
+    """
+    Downloads the file attached to a GAIA task (if any) and saves it locally.
+    Use this when a question references an attached file (image, spreadsheet,
+    audio, etc). Returns the local file path, or an error message if there is
+    no file for this task.
+
+    Args:
+        task_id: The task_id string for the current question.
+    """
+    url = f"{DEFAULT_API_URL}/files/{task_id}"
+    try:
+        resp = requests.get(url, timeout=30)
+        if resp.status_code != 200:
+            return f"No file available for task_id {task_id} (status {resp.status_code})"
+        cd = resp.headers.get("content-disposition", "")
+        match = re.search(r'filename="?([^"]+)"?', cd)
+        filename = match.group(1) if match else f"{task_id}.bin"
+        local_path = os.path.join("/tmp", filename)
+        with open(local_path, "wb") as f:
+            f.write(resp.content)
+        return local_path
+    except Exception as e:
+        return f"Error downloading file: {e}"
+
+
+@tool
+def read_text_file(path: str) -> str:
+    """
+    Reads and returns the text content of a local file (e.g. .txt, .csv, .py).
+    Use this after download_task_file when the file is plain text or CSV.
+
+    Args:
+        path: Local filesystem path to the file.
+    """
+    try:
+        with open(path, "r", errors="ignore") as f:
+            return f.read()[:20000]
+    except Exception as e:
+        return f"Error reading file: {e}"
+
+
+class BasicAgent:
+    def __init__(self):
+        print("BasicAgent initialized.")
+
+        model = InferenceClientModel(
+            model_id="Qwen/Qwen2.5-Coder-32B-Instruct"
+        )
+
+        self.agent = CodeAgent(
+            tools=[
+                DuckDuckGoSearchTool(),
+                VisitWebpageTool(),
+                download_task_file,
+                read_text_file,
+            ],
+            model=model,
+            max_steps=12,
+            additional_authorized_imports=["re", "itertools", "math", "statistics"],
+        )
+
+    def __call__(self, question: str, task_id: str = None) -> str:
+        print(f"Agent received question (first 80 chars): {question[:80]}...")
+
+        instructions = (
+            "You are answering a benchmark question that will be graded by EXACT "
+            "STRING MATCH. Follow these rules strictly:\n"
+            "1. Reply with ONLY the final answer — no explanation, no restating "
+            "the question, no leading phrases like 'The answer is'.\n"
+            "2. Do not include the words 'FINAL ANSWER' in your reply.\n"
+            "3. Match the exact format requested (e.g. a number with no commas "
+            "unless asked, a comma-separated list with no extra spaces unless "
+            "shown otherwise, exact capitalization/pluralization as requested).\n"
+            "4. If the question references an attached file, call "
+            f"download_task_file(task_id='{task_id}') first to fetch it, then "
+            "read/inspect it before answering.\n"
+            "5. If you are not fully sure, still give your best single-guess "
+            "answer in the correct format — never leave it blank or explain "
+            "why you're unsure.\n\n"
+            f"Question:\n{question}"
+        )
+
+        try:
+            answer = self.agent.run(instructions)
+        except Exception as e:
+            print(f"Agent error: {e}")
+            answer = ""
+
+        answer = str(answer).strip()
+        print(f"Agent returning answer: {answer}")
+        return answer