Updated new

app.py

@@ -1,5 +1,61 @@
+from smolagents import CodeAgent, HfApiModel, load_tool, tool
+import datetime
+import requests
+import pytz
+import yaml
+from tools.final_answer import FinalAnswerTool
+from scholarly import scholarly
 import gradio as gr
 
+@tool
+def fetch_latest_research_papers(keywords: list, num_results: int = 5) -> list:
+    """Fetches the latest research papers from Google Scholar based on provided keywords.
+    Args:
+        keywords: A list of keywords to search for relevant papers.
+        num_results: The number of papers to fetch (default is 5).
+    """
+    try:
+        query = " ".join(keywords)
+        search_results = scholarly.search_pubs(query)
+        papers = []
+        for i in range(num_results):
+            paper = next(search_results, None)
+            if paper:
+                papers.append({
+                    "title": paper['bib'].get('title', 'No Title'),
+                    "authors": paper['bib'].get('author', 'Unknown Authors'),
+                    "year": paper['bib'].get('pub_year', 'Unknown Year'),
+                    "abstract": paper['bib'].get('abstract', 'No Abstract Available'),
+                    "link": paper.get('pub_url', 'No Link Available')
+                })
+        return papers
+    except Exception as e:
+        return [f"Error fetching research papers: {str(e)}"]
+
+final_answer = FinalAnswerTool()
+
+model = HfApiModel(
+    max_tokens=2096,
+    temperature=0.5,
+    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+    custom_role_conversions=None,
+)
+
+with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
+    
+agent = CodeAgent(
+    model=model,
+    tools=[final_answer, fetch_latest_research_papers],
+    max_steps=6,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name="ScholarAgent",
+    description="An AI agent that fetches the latest research papers from Google Scholar based on user-defined keywords and filters.",
+    prompt_templates=prompt_templates
+)
+
 def search_papers(user_input):
     keywords = user_input.split(",")  # Split input by commas for multiple keywords
     results = fetch_latest_research_papers(keywords, num_results=5)