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from crewai import Agent, Task, Crew | |
from langchain_groq import ChatGroq | |
from dotenv import load_dotenv | |
import os | |
from datetime import datetime, timedelta | |
import logging | |
load_dotenv() | |
logging.basicConfig(filename="app.log", level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") | |
llm = ChatGroq( | |
api_key=os.getenv("GROQ_API_KEY"), | |
model="llama3-70b-8192", | |
temperature=0.5, | |
max_tokens=1000 | |
) | |
interview_scheduler = Agent( | |
role="Interview Scheduler", | |
goal="Schedule interviews based on candidate availability and provide summaries", | |
backstory="An expert in coordinating schedules for AI-driven interviews", | |
llm=llm, | |
verbose=True, | |
allow_delegation=False | |
) | |
# Simulated Google Calendar API | |
def simulate_calendar_api(candidate_name, job_title, start_time): | |
event = { | |
"summary": f"Interview: {candidate_name} for {job_title}", | |
"start": start_time.isoformat(), | |
"end": (start_time + timedelta(hours=1)).isoformat() | |
} | |
logging.info(f"Simulated Calendar Event Created: {event}") | |
return {"status": "success", "event": event} | |
# Task to suggest a time based on candidate availability | |
def create_schedule_time_task(job_title, candidate_name, candidate_availability): | |
prompt = f"Given the job title: {job_title} and candidate {candidate_name}'s availability: {candidate_availability}, suggest an interview time in the format 'March 25, 2025, 10:00 AM'. The interviewer is an AI chatbot, so only the candidate’s availability matters. Pick a suitable time within the provided range." | |
return Task( | |
description=prompt, | |
agent=interview_scheduler, | |
expected_output="A suggested interview time in the format 'March 25, 2025, 10:00 AM'." | |
) | |
# Task to generate a summary | |
def create_schedule_summary_task(candidate_name, job_title, scheduled_time): | |
prompt = f"Generate a concise summary for an interview scheduled for {candidate_name} for the role of {job_title} at {scheduled_time}. Keep it short and professional." | |
return Task( | |
description=prompt, | |
agent=interview_scheduler, | |
expected_output="A brief summary of the scheduled interview." | |
) | |
# Main scheduling function | |
def create_schedule_task(job_title, candidate_name, candidate_availability): | |
time_task = create_schedule_time_task(job_title, candidate_name, candidate_availability) | |
return time_task # Return only the time task; summary is generated separately in app.py | |
if __name__ == "__main__": | |
task = create_schedule_task( | |
"Senior Python Developer", | |
"John Doe", | |
"March 25, 2025, 9 AM - 12 PM" | |
) | |
crew = Crew(agents=[interview_scheduler], tasks=[task], verbose=True) | |
time = crew.kickoff() | |
scheduled_time = datetime.strptime(time, "%B %d, %Y, %I:%M %p") | |
result = simulate_calendar_api("John Doe", "Senior Python Developer", scheduled_time) | |
print("Scheduled Time:", time) | |
print("Calendar Response:", result) |