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from dotenv import load_dotenv
import sys
import os
import uuid
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from multi_agents.agents import ChiefEditorAgent
import asyncio
import json
from gpt_researcher.utils.enum import Tone
# Run with LangSmith if API key is set
if os.environ.get("LANGCHAIN_API_KEY"):
os.environ["LANGCHAIN_TRACING_V2"] = "true"
load_dotenv()
def open_task():
# Get the directory of the current script
current_dir = os.path.dirname(os.path.abspath(__file__))
# Construct the absolute path to task.json
task_json_path = os.path.join(current_dir, 'task.json')
with open(task_json_path, 'r') as f:
task = json.load(f)
if not task:
raise Exception("No task found. Please ensure a valid task.json file is present in the multi_agents directory and contains the necessary task information.")
return task
async def run_research_task(query, websocket=None, stream_output=None, tone=Tone.Objective, headers=None):
task = open_task()
task["query"] = query
chief_editor = ChiefEditorAgent(task, websocket, stream_output, tone, headers)
research_report = await chief_editor.run_research_task()
if websocket and stream_output:
await stream_output("logs", "research_report", research_report, websocket)
return research_report
async def main():
task = open_task()
chief_editor = ChiefEditorAgent(task)
research_report = await chief_editor.run_research_task(task_id=uuid.uuid4())
return research_report
if __name__ == "__main__":
asyncio.run(main()) |