| import os | |
| import requests | |
| from langchain_core.messages import HumanMessage | |
| from agent import build_graph | |
| from huggingface_hub import hf_hub_download | |
| import pyarrow.parquet as pq | |
| from dotenv import load_dotenv | |
| load_dotenv(override=True) | |
| graph = build_graph() | |
| resp = requests.get("https://agents-course-unit4-scoring.hf.space/questions") | |
| questions = resp.json() | |
| # Q19 | |
| q = questions[18] | |
| question = q['question'] | |
| print(f"Q19: {question}") | |
| print(f"Contains 'excel': {'excel' in question.lower()}") | |
| print(f"Contains 'food': {'food' in question.lower()}") | |
| print(f"Contains 'drinks': {'drinks' in question.lower()}") | |
| print() | |
| result = graph.invoke({"messages": [HumanMessage(content=question)]}) | |
| print(f"Answer: {result['messages'][-1].content}") | |