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import os
from dotenv import load_dotenv
from evoagentx.models import OpenAILLMConfig, OpenAILLM
from evoagentx.workflow import WorkFlowGenerator, WorkFlowGraph, WorkFlow
from evoagentx.agents import AgentManager
from evoagentx.tools.file_tool import FileToolkit
from evoagentx.tools import ArxivToolkit
load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
def main():
openai_config = OpenAILLMConfig(
model="gpt-4o",
openai_key=OPENAI_API_KEY,
stream=True,
output_response=True,
max_tokens=16000
)
llm = OpenAILLM(config=openai_config)
keywords = "medical, multiagent"
max_results = 10
date_from = "2024-01-01"
categories = ["cs.AI", "cs.LG"]
search_constraints = f"""
Search constraints:
- Query keywords: {keywords}
- Max results: {max_results}
- Date from: {date_from}
- Categories: {', '.join(categories)}
"""
goal = f"""Create a daily research paper recommendation assistant that takes user keywords and pushes new relevant papers with summaries.
The assistant should:
1. Use the ArxivToolkit to search for the latest papers using the given keywords.
2. Apply the following search constraints:
{search_constraints}
3. Summarize the search results.
4. Compile the summaries into a well-formatted Markdown digest.
### Output
daily_paper_digest
"""
target_directory = "EvoAgentX/examples/output/paper_push"
module_save_path = os.path.join(target_directory, "paper_push_workflow.json")
result_path = os.path.join(target_directory, "daily_paper_digest.md")
os.makedirs(target_directory, exist_ok=True)
arxiv_toolkit = ArxivToolkit()
tools = [arxiv_toolkit, FileToolkit()]
wf_generator = WorkFlowGenerator(llm=llm, tools=tools)
workflow_graph: WorkFlowGraph = wf_generator.generate_workflow(goal=goal)
workflow_graph.save_module(module_save_path)
workflow_graph.display()
agent_manager = AgentManager(tools=tools)
agent_manager.add_agents_from_workflow(workflow_graph, llm_config=openai_config)
workflow = WorkFlow(graph=workflow_graph, agent_manager=agent_manager, llm=llm)
output = workflow.execute()
with open(result_path, "w", encoding="utf-8") as f:
f.write(output)
print(f"✅ Your file has been saved to：{result_path}")
print("📬 You can run this script everyday to obtain daily recommendation")
if __name__ == "__main__":
main()
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