Deep_Reaserch_ / research_manager.py
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from agents import Runner, trace, gen_trace_id
from search_agent import search_agent
from planner_agent import planner_agent, WebSearchItem, WebSearchPlan
from writer_agent import writer_agent, ReportData
from email_agent import email_agent
from clarify_agent import clarify_agent
import asyncio
class ResearchManager:
async def conduct_research(self, query: str):
""" Run the deep research process, yielding the status updates and the final report"""
trace_id = gen_trace_id()
with trace("Research trace", trace_id=trace_id):
print(f"View trace: https://platform.openai.com/traces/trace?trace_id={trace_id}")
yield f"View trace: https://platform.openai.com/traces/trace?trace_id={trace_id}"
print("Starting research...")
search_plan = await self.plan_searches(query)
yield "Searches planned, starting to search..."
search_results = await self.perform_searches(search_plan)
yield "Searches complete, writing report..."
report = await self.write_report(query, search_results)
# yield "Report written, sending email..."
# await self.send_email(report)
yield "Research complete"
yield report.markdown_report
async def plan_searches(self, query: str) -> WebSearchPlan:
""" Plan the searches to perform for the query """
print("Planning searches...")
result = await Runner.run(
planner_agent,
f"Query: {query}",
)
print(f"Will perform {len(result.final_output.searches)} searches")
return result.final_output_as(WebSearchPlan)
async def perform_searches(self, search_plan: WebSearchPlan) -> list[str]:
""" Perform the searches to perform for the query """
print("Searching...")
num_completed = 0
tasks = [asyncio.create_task(self.search(item)) for item in search_plan.searches]
results = []
for task in asyncio.as_completed(tasks):
result = await task
if result is not None:
results.append(result)
num_completed += 1
print(f"Searching... {num_completed}/{len(tasks)} completed")
print("Finished searching")
return results
async def search(self, item: WebSearchItem) -> str | None:
""" Perform a search for the query """
input = f"Search term: {item.query}\nReason for searching: {item.reason}"
try:
result = await Runner.run(
search_agent,
input,
)
return str(result.final_output)
except Exception:
return None
async def write_report(self, query: str, search_results: list[str]) -> ReportData:
""" Write the report for the query """
print("Thinking about report...")
input = f"Original query: {query}\nSummarized search results: {search_results}"
result = await Runner.run(
writer_agent,
input,
)
print("Finished writing report")
return result.final_output_as(ReportData)
async def send_email(self, report: ReportData) -> None:
print("Writing email...")
result = await Runner.run(
email_agent,
report.markdown_report,
)
print("Email sent")
return report
async def generate_clarification_questions(self, query: str) -> str:
""" Generate clarification questions based on the user's query """
print("Generating clarification questions...")
input = f"Please analyze this research query and generate 3 clarifying questions that would help focus the research: {query}"
try:
questions = await Runner.run(
clarify_agent,
input
)
print("Generated clarification questions")
return questions.final_output
except Exception as e:
print(f"Error generating questions: {e}")
return ""