Update app.py

app.py

@@ -2,24 +2,25 @@ import feedparser
 import urllib.parse
 import yaml
 import gradio as gr
+from typing import List, Dict
 from smolagents import CodeAgent, HfApiModel, tool
 
 @tool
-def fetch_latest_arxiv_papers(keywords: list, num_results: int = 3) -> list:
+def fetch_latest_arxiv_papers(keywords: List[str], num_results: int = 3) -> List[Dict[str, str]]:
     """
-    Fetch the latest research papers from arXiv.
+    Fetches the latest research papers from arXiv.
 
-    Parameters:
-        keywords (list of str): A list of search keywords. Each keyword is used to filter relevant papers.
+    Args:
+        keywords (List[str]): A list of search keywords to filter relevant papers.
         num_results (int): The maximum number of research papers to fetch. Default is 3.
 
     Returns:
-        list of dict: A list of dictionaries, where each dictionary contains:
-            - title (str): The title of the research paper.
-            - authors (str): The authors of the paper.
-            - year (str): The publication year.
-            - abstract (str): A summary of the research paper.
-            - link (str): A direct link to the paper on arXiv.
+        List[Dict[str, str]]: A list of dictionaries where each dictionary contains:
+            - "title" (str): The title of the research paper.
+            - "authors" (str): The authors of the paper.
+            - "year" (str): The publication year.
+            - "abstract" (str): A summary of the research paper.
+            - "link" (str): A direct link to the paper on arXiv.
     """
     try:
         print(f"DEBUG: Searching arXiv papers with keywords: {keywords}")  # Debug input
@@ -62,7 +63,7 @@ model = HfApiModel(
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
 
-# Create the AI Agent
+# ✅ Create the AI Agent
 agent = CodeAgent(
     model=model,
     tools=[fetch_latest_arxiv_papers],  # Properly registered tool
@@ -75,7 +76,7 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-#Define Gradio Search Function
+# ✅ Define Gradio Search Function
 def search_papers(user_input):
     keywords = [kw.strip() for kw in user_input.split(",") if kw.strip()]  # Ensure valid keywords
     print(f"DEBUG: Received input keywords - {keywords}")  # Debug user input
@@ -96,7 +97,7 @@ def search_papers(user_input):
     print("DEBUG: No results found.")
     return "No results found. Try different keywords."
 
-
+# ✅ Create Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# arXiv Research Paper Fetcher")
     keyword_input = gr.Textbox(label="Enter keywords (comma-separated)", placeholder="e.g., deep learning, reinforcement learning")
@@ -107,5 +108,5 @@ with gr.Blocks() as demo:
 
     print("DEBUG: Gradio UI is running. Waiting for user input...")
 
-
+# ✅ Launch Gradio App
 demo.launch()