version complète v03

agent.py

@@ -1,4 +1,3 @@
-import gradio as gr
 from llama_index.llms.openai import OpenAI
 from llama_index.agent.openai import OpenAIAgent
 from tools import TOOLS

gaia_submit.py

@@ -1,7 +1,11 @@
+import os
 import requests
 from pydantic import BaseModel
 from agent import run_agent
 
+# Récupération automatique de l’URL du repo (via SPACE_ID)
+space_id = os.getenv("SPACE_ID", "doxiy/exam-agent")  # Valeur par défaut si non dans un Space
+agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
 #structure attendu
 class Question(BaseModel):
@@ -16,10 +20,13 @@ class Answer(BaseModel):
 def answer_question(question:str) -> str:
     return str(run_agent(question)).strip()
 
+BASE_URL = "https://agents-course-unit4-scoring.hf.space"
+questions_url = f"{BASE_URL}/questions"
+submit_url = f"{BASE_URL}/submit"
 
 def run_agent_on_all_questions():
     #1. Obtenir les question
-    response = requests.get("https://gaia-course-api.spaces.huggingface.tech/questions")
+    response = requests.get(questions_url)
     questions = response.json()
 
     answers = []
@@ -37,12 +44,12 @@ def run_agent_on_all_questions():
     #2. envoi de la reponse
     payload = {
         "username": "Doxiy",
-        "agent_code": "https://huggingface.co/spaces/doxiy/exam-agent/tree/main",
+        "agent_code": agent_code,
         "answers": answers
     }
         
 
-    r = requests.post("https://gaia-course-api.spaces.huggingface.tech/submit", json=payload)
+    r = requests.post(submit_url, json=payload)
     if r.status_code == 200:
         logs += "\n✅ Envoi avec succes. Resultat:\n" + str(r.json())
     else: