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add rag
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import os, requests, pandas as pd, gradio as gr
from agent import BasicAgent
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
def run_and_submit_all(profile: gr.OAuthProfile | None = None, *args, **kwargs):
space_id = os.getenv("SPACE_ID")
if profile:
username = f"{profile.username}"
else:
return "Please Login to Hugging Face with the button.", None
api_url = DEFAULT_API_URL
questions_url = f"{api_url}/questions"
submit_url = f"{api_url}/submit"
try:
agent = BasicAgent(api_url, corpus_path=os.getenv("CORPUS_PATH", "corpus.txt"))
except Exception as e:
return f"Error initializing agent: {e}", None
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""
try:
response = requests.get(questions_url, timeout=15)
response.raise_for_status()
questions_data = response.json()
if not questions_data:
return "Fetched questions list is empty or invalid format.", None
except Exception as e:
return f"Error fetching questions: {e}", None
results_log, answers_payload = [], []
for item in questions_data:
task_id = item.get("task_id")
question_text = item.get("question")
if not task_id or question_text is None:
continue
try:
submitted_answer = agent(question_text, task_id)
except Exception as e:
submitted_answer = f"AGENT ERROR: {e}"
answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
if not answers_payload:
return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
try:
response = requests.post(submit_url, json=submission_data, timeout=60)
response.raise_for_status()
result_data = response.json()
final_status = (
f"Submission Successful!\n"
f"User: {result_data.get('username')}\n"
f"Overall Score: {result_data.get('score', 'N/A')}% "
f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
f"Message: {result_data.get('message', 'No message received.')}"
)
return final_status, pd.DataFrame(results_log)
except requests.exceptions.HTTPError as e:
try:
detail = e.response.json().get("detail", e.response.text)
except Exception:
detail = e.response.text
msg = f"Submission Failed: HTTP {e.response.status_code}. Detail: {detail[:500]}"
return msg, pd.DataFrame(results_log)
except requests.exceptions.Timeout:
return "Submission Failed: The request timed out.", pd.DataFrame(results_log)
except Exception as e:
return f"Submission Failed: {e}", pd.DataFrame(results_log)
with gr.Blocks() as demo:
gr.Markdown("# Basic Agent Evaluation Runner (RAG from .txt)")
gr.Markdown("Log in, then click **Run Evaluation & Submit All Answers**.")
gr.LoginButton()
run_button = gr.Button("Run Evaluation & Submit All Answers")
status_output = gr.Textbox(label="Run Status / Submission Result", lines=6, interactive=False)
results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
if __name__ == "__main__":
demo.launch(debug=True, share=False)