update the id

agent.py

@@ -124,8 +124,8 @@ sys_msg = SystemMessage(content=system_prompt)
 # build a retriever
 embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
 supabase: Client = create_client(
-    "https://kghadsdyocxyfohvdldg.supabase.co", 
-    "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImtnaGFkc2R5b2N4eWZvaHZkbGRnIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTExODk4MjAsImV4cCI6MjA2Njc2NTgyMH0.fKKUi0B9vG4tiz7Fi2cZ_rol64hBcOX4xtNWxs9SesM")
+    os.environ.get("SUPABASE_URL"), 
+    os.environ.get("SUPABASE_SERVICE_KEY"))
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding= embeddings,
@@ -155,7 +155,6 @@ tools = [
 def build_graph(provider: str = "groq"):
     """Build the graph"""
     # Load environment variables from .env file
-    HF_API_KEY=os.getenv("HF_API_KEY")
     if provider == "google":
         # Google Gemini
         llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
@@ -168,9 +167,6 @@ def build_graph(provider: str = "groq"):
             llm=HuggingFaceEndpoint(
                 url="https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf",
                 temperature=0,
-                headers={
-                    "Authorization": f"Bearer {HF_API_KEY}"  # 硬编码方式传递 API 密钥
-                }
             ),
         )
     else:

app.py

@@ -12,6 +12,7 @@ from agent import build_graph
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+SUBMISSION_FILE = "submission.jsonl"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
@@ -38,7 +39,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = "kingkaikai/Final_Assignment_Template_2" # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
 
     if profile:
         username= f"{profile.username}"
@@ -104,6 +105,17 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
+    # Generate JSON-line submission file
+    try:
+        with open(SUBMISSION_FILE, "w") as f:
+            for entry in answers_payload:
+                json.dump(entry, f)
+                f.write("\n")
+        print(f"Successfully generated submission file: {SUBMISSION_FILE}")
+    except Exception as e:
+        print(f"Error generating submission file: {e}")
+        return f"Error generating submission file: {e}", pd.DataFrame(results_log)
+
     # 4. Prepare Submission 
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
@@ -120,6 +132,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             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"Submission file generated: {SUBMISSION_FILE}\n"
             f"Message: {result_data.get('message', 'No message received.')}"
         )
         print("Submission successful.")