Create agent.py

agent.py

@@ -0,0 +1,51 @@
+"""Course agent: tools generate answers; no benchmark answer lookup tables."""
+import os
+import requests
+from smolagents import ToolCallingAgent, InferenceClientModel, DuckDuckGoSearchTool, VisitWebpageTool, tool
+
+@tool
+def guest_search(query: str) -> str:
+    """Retrieve relevant public gala guest records for the Unit 3 use case.
+
+    Args:
+        query: Guest name or topic to search for.
+    """
+    from datasets import load_dataset
+    records = load_dataset('agents-course/unit3-invitees', split='train')
+    terms = set(query.lower().split())
+    ranked = sorted(records, key=lambda r: len(terms & set(str(r).lower().split())), reverse=True)
+    return str(ranked[:3])
+
+def build_agent(use_case=False):
+    token = os.environ.get('HF_TOKEN')
+    if not token:
+        raise RuntimeError('Set HF_TOKEN as a secret with inference permission first.')
+    model = InferenceClientModel(token=token, model_id=os.environ.get('MODEL_ID', 'Qwen/Qwen2.5-Coder-32B-Instruct'))
+    tools = [DuckDuckGoSearchTool(), VisitWebpageTool()]
+    if use_case:
+        tools.append(guest_search)
+    return ToolCallingAgent(tools=tools, model=model, max_steps=12)
+
+def answer(agent, question):
+    return str(agent.run(question + '\nReturn only the exact answer requested, without a FINAL ANSWER prefix or explanation.', reset=True)).strip()
+
+def evaluate(output_path='answers.json'):
+    import json
+    questions = requests.get('https://agents-course-unit4-scoring.hf.space/questions', timeout=60)
+    questions.raise_for_status()
+    agent = build_agent()
+    answers, failures = [], []
+    for item in questions.json():
+        if item.get('file_name'):
+            failures.append({'task_id': item['task_id'], 'reason': 'Attachment processing not implemented; do not claim this task is supported.'})
+            continue
+        try:
+            answers.append({'task_id': item['task_id'], 'submitted_answer': answer(agent, item['question'])})
+        except Exception as exc:
+            failures.append({'task_id': item['task_id'], 'reason': type(exc).__name__})
+    with open(output_path, 'w', encoding='utf-8') as handle:
+        json.dump({'answers': answers, 'failures': failures}, handle, indent=2)
+    return answers, failures
+
+if __name__ == '__main__':
+    evaluate()