How to integrate LangGraph framework with existing AI chatbot for interview automation

Other Questions AI Agent
1

Need help adding LangGraph to my Python interview bot

I built a basic interview chatbot using Google’s Gemini AI and now I want to make it smarter with LangGraph. My current setup works but feels pretty basic.

Here’s what my code looks like right now:

import os
import uuid
import google.generativeai as genai
from personality_types import PERSONALITY_DATA

# Store chat history in files
def store_chat_log(chat_data):
    file_id = str(uuid.uuid4())[:10] + '.txt'
    with open(file_id, 'w', encoding='utf-8') as f:
        for item in chat_data:
            if len(item) == 3:  # Context, Query, Answer
                f.write(f"Context: {item[0]}\nQuery: {item[1]}\nAnswer: {item[2]}\n\n")
            else:  # Query, Answer
                f.write(f"Query: {item[0]}\nAnswer: {item[1]}\n\n")

# Get candidate info at start
def greet_user():
    ai_model = genai.GenerativeModel('gemini-pro')
    greeting_request = "Create a welcoming message to collect the participant's name. Make it sound professional but friendly."
    ai_output = ai_model.generate_content(greeting_request)
    welcome_text = ai_output.text.strip()
    user_name = input(f"\nBot: {welcome_text} ").strip()
    print(f"\nBot: Nice to meet you, {user_name}. Ready to start our conversation?\n")
    return user_name

# Handle user input with validation
def get_user_input(question_text):
    while True:
        user_reply = input(f"\nBot: {question_text}\n\nYou: ").strip()
        if user_reply:
            return user_reply
        else:
            print("Bot: I need an answer to continue.")

# Start the interview process
participant_name = greet_user()
# More conversation logic goes here

My main problem: I tried using Crew AI before but it got complicated fast. Now I hear LangGraph might be better for making conversation flows that actually make sense.

What I already tried:

  • Set up basic Crew AI agents but they felt clunky
  • Got LangGraph installed but don’t know where to start
  • My current bot works but conversations feel robotic

What I’m hoping to achieve:

  • Better conversation flow that feels more natural
  • Smart decision making based on previous answers
  • Maybe some way to analyze personality traits automatically

Anyone here used LangGraph for interview bots? I’m pretty new to this stuff so simple examples would be amazing. Thanks!

2

I made this exact switch about six months ago - from basic Gemini to LangGraph. The biggest mindset shift is moving from linear chat flows to state management. Right now you’re manually handling chat history with files. LangGraph lets you define conversation states that branch based on what users say. Start simple: create nodes for greeting, asking questions, and evaluating responses. Each node checks the conversation state and picks the next step automatically. For personality analysis, add a dedicated node that processes all responses and updates the state with insights. Way easier to debug since you can see exactly where conversations split off. The learning curve’s much gentler than Crew AI. Don’t rebuild everything at once - migrate one conversation flow at a time.

3

Your code already handles conversation state with chat logs, which is solid. LangGraph’s main advantage is graph-based routing - no more linear if-else chains.

I built a recruitment bot with LangGraph last year. Instead of hardcoding question sequences, I created nodes that decide what to ask next based on previous answers. Someone mentions leadership? The graph automatically jumps to management questions.

For your setup, build these core nodes: intake (name/background), technical assessment, behavioral questions, and personality analyzer. Connect them with conditional edges that check response quality and topic relevance.

The best part? Memory persistence across nodes happens automatically. Your file-based storage works, but LangGraph handles state without manual chat log management.

Start simple - greeting node plus one question type. Add routing logic once that’s working. Way easier to debug than Crew AI since you can actually see the conversation path.

This video covers building chatbots with LangGraph from scratch:

For personality analysis, I added a scoring node that runs every few responses. Updates the candidate profile in real time instead of waiting until the end.

4

hey, i tried langgraph for my bot too and it took a bit to get used to! start by breaking ur questions into nodes and build flows from there. way easier than crew ai! keep it simple and focus on response patterns for a more natural chat, u got this!