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