Update interview_scheduler.py

interview_scheduler.py

@@ -1,71 +1,71 @@
-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="Logs/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)
+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)