preparatory changes

.gitignore

@@ -0,0 +1 @@
+**/__pycache__/

agents.py

@@ -0,0 +1,21 @@
+
+
+# --- Basic Agent Definition ---
+class BasicAgent:
+    def __init__(self):
+        print("BasicAgent initialized.")
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        fixed_answer = "This is a default answer."
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return fixed_answer
+    
+
+class LangAgent:
+    def __init__(self):
+        print("BasicAgent initialized.")
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        fixed_answer = "This is a default answer."
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return fixed_answer

app.py

@@ -3,21 +3,12 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from agents import BasicAgent
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-class BasicAgent:
-    def __init__(self):
-        print("BasicAgent initialized.")
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -58,6 +49,26 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
              print("Fetched questions list is empty.")
              return "Fetched questions list is empty or invalid format.", None
         print(f"Fetched {len(questions_data)} questions.")
+        # Log a quick overview so we can debug availability, especially file_name fields.
+        with_file = [q for q in questions_data if q.get("file_name")]
+        without_file = len(questions_data) - len(with_file)
+        print(f"Questions with file_name set: {len(with_file)}; without: {without_file}")
+        for q in with_file:
+            print(f"Task {q.get('task_id')} expects file: {q.get('file_name')}")
+        # Probe file availability so we can see what the backend returns.
+        for q in with_file:
+            task_id = q.get("task_id")
+            file_url = f"{api_url}/files/{task_id}"
+            try:
+                probe = requests.get(file_url, timeout=15)
+                print(
+                    f"Attempted access to resource at {file_url} -> "
+                    f"status {probe.status_code}, "
+                    f"content-type {probe.headers.get('content-type')}, "
+                    f"bytes {len(probe.content)}"
+                )
+            except Exception as e:
+                print(f"Attempted access to resource at {file_url} -> error: {e}")
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
@@ -193,4 +204,4 @@ if __name__ == "__main__":
     print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)

requirements.txt

@@ -1,2 +1,5 @@
 gradio
-requests
+requests
+
+langgraph
+langchain_openai