Update app.py

app.py

@@ -25,7 +25,7 @@ def document_parser_tool(file_path_or_url: str) -> str:
         if file_path_or_url.startswith('http'):
             local_path = "temp_financial_doc.pdf"
             urllib.request.urlretrieve(file_path_or_url, local_path)
-        
+            
         extracted_text = ""
         with open(local_path, 'rb') as file:
             reader = PyPDF2.PdfReader(file)
@@ -77,12 +77,14 @@ class BasicAgent:
         self.model = OpenAIServerModel(
             model_id="llama-3.3-70b-versatile",
             api_base="https://api.groq.com/openai/v1",
-            api_key=os.environ.get("GROQ_API_KEY")
+            api_key=os.environ.get("GROQ_API_KEY"),
+            max_retries=1 # <--- ADDED: Stops infinite hanging on API limits
         )
         
         self.agent = CodeAgent(
             tools=[self.search_tool, document_parser_tool, visit_webpage_tool],
             model=self.model,
+            max_steps=4, # <--- ADDED: Forces the agent to give up and move on if stuck
             additional_authorized_imports=[
                 "math", "pandas", "datetime", "requests", "bs4", "re", "time"
             ]
@@ -175,15 +177,16 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     # 3. Run your Agent
     results_log = []
     answers_payload = []
-    print(f"Running agent on {len(questions_data)} questions...")
-    for item in questions_data:
+    
+    # ---> ADDED: [:1] forces "Test Mode" to only run the VERY FIRST question <---
+    print(f"Running agent on 1 test question...")
+    for item in questions_data[:1]: 
         task_id = item.get("task_id")
         question_text = item.get("question")
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            # ---> UPDATED LINE HERE: Passing task_id <---
             submitted_answer = agent(task_id, question_text)
             
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
@@ -191,8 +194,10 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         except Exception as e:
              print(f"Error running agent on task {task_id}: {e}")
              results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
-        time.sleep(10)
-        
+             
+        # ---> CHANGED: Reduced sleep time since Groq is fast <---
+        time.sleep(2)
+
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
@@ -245,7 +250,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
     gr.Markdown("# Financial Due Diligence Agent Evaluation Runner")
@@ -255,9 +259,6 @@ with gr.Blocks() as demo:
         1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
         2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
         3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-        ---
-        **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
         """
     )