| import gradio as gr |
| import time |
|
|
| class PlannerAgent: |
| def run(self, query): |
| return { |
| "goal": query, |
| "tasks": [ |
| "Understand the topic", |
| "Collect important information", |
| "Generate final report" |
| ] |
| } |
|
|
| class ResearchAgent: |
| def run(self, plan): |
| topic = plan["goal"] |
|
|
| research = f""" |
| Topic: {topic} |
| |
| Key Points: |
| • Definition and overview |
| • Major applications |
| • Advantages |
| • Challenges |
| • Future scope |
| """ |
| return research |
|
|
| class WriterAgent: |
| def run(self, research): |
| report = f""" |
| # AI Generated Report |
| |
| {research} |
| |
| Conclusion: |
| This report summarizes the important aspects of the topic and provides a concise overview. |
| """ |
| return report |
|
|
| planner = PlannerAgent() |
| researcher = ResearchAgent() |
| writer = WriterAgent() |
|
|
| def multi_agent_workflow(query): |
|
|
| if not query.strip(): |
| return "Please enter a topic." |
|
|
| plan = planner.run(query) |
| time.sleep(1) |
|
|
| research = researcher.run(plan) |
| time.sleep(1) |
|
|
| final_report = writer.run(research) |
|
|
| return final_report |
|
|
| demo = gr.Interface( |
| fn=multi_agent_workflow, |
| inputs=gr.Textbox( |
| lines=2, |
| placeholder="Enter any topic..." |
| ), |
| outputs=gr.Markdown(), |
| title="Multi-Agent AI Research Assistant", |
| description=""" |
| Planner Agent → Research Agent → Writer Agent |
| |
| Enter a topic and the agents will collaborate to generate a report. |
| """ |
| ) |
|
|
| demo.launch() |
