first challenge try

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from agent import LangGraphAgent
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -10,14 +11,7 @@ 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):
     """
@@ -40,14 +34,14 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = LangGraphAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
     # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(agent_code)
-
+    #agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    #print(agent_code)
+    agent_code = ""
     # 2. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
     try:
@@ -76,10 +70,18 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
+        file_name = item.get("file_name")
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
+            if file_name:
+                question_text += f"\n\nFile url: {api_url}/files/{task_id}"
+                try:
+                    ext = file_name.split('.')[-1]
+                    question_text += f"\n File extension is (.{ext} file)"
+                except:
+                    pass
             submitted_answer = agent(question_text)
             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})

requirements.txt

@@ -1,2 +1,18 @@
 gradio
-requests
+requests
+langchain
+langchain-community
+langchain-core
+langchain-google-genai
+langchain-huggingface
+langchain-groq
+langchain-tavily
+langchain-chroma
+langgraph
+huggingface_hub
+supabase
+arxiv
+pymupdf
+wikipedia
+pgvector
+python-dotenv