Launching Prashant Ai - My very own chatbot.
Hey there! Ready for a Quick ride into the world of AI, code, and personality? Because today I’m launching my own first ever ai chatbot Prashant AI—my pride and joy, my digital brainchild, my very own chatbot that doesn’t just answer questions—it speaks back with attitude. Sound good ? Let's Dive into it .
Why I made this -
Honestly, it all started late one night. I was binge‑watching sci‑fi movies, asking out loud, “Why can’t my AI crack jokes like Deadpool?” Cue the classic “wait, what?” moment.
So, I grabbed my Phone, fired up Python, JavaScript, and a cup of coffee that would make baristas jealous. By morning, I’d whipped up a mini‑AI prototype that answered trivia. But it felt… soulless.
So I thought: what if my AI had attitude? Not mean‑spirited nasty, but a cheeky, human‑like edge. If you talked kindly, it’d be respectful. If you dissed it—uh‑oh, brace yourself. And thus, Prashant AI was born.
How I made this -
Wanna know how I stitched this together? Let me break it down.
- Programming Languages
- Python: for logic, data processing, and AI training glue.
- JavaScript/Node.js: for the real‑time chat interface on the web.
- Bonus: a dash of SQL for user‑history storage.
- APIs & Integration
- Used OpenAI’s GPT‑X API (yep, the magic sauce) for smart replies.
- Custom “tone‑check” middleware: it rates user inputs—kind, neutral, or rude—and tags each query.
- Personality Engine
- Built a tone‑response matrix:
- Respectful user → Respectful AI (polite replies, “Sir/Madam” style).
- Rude user → Rude AI (“Sure, genius. That’s… original.”).
- No middle ground here—just simple, spicy contrast.
So yeah, mix those ingredients, and voilà: a chatbot with personality.
Fun Anecdote: “Tum, KuTTa Ho?”
Cue belly laughs. 😂
This toggle between praise and sass made testing so much more human-like, and honestly—just freakin’ fun.
FAQ – Nail That Featured Snippet 🎯
Q1: What is Prashant AI?
A1: Prashant AI is a personal chatbot built by me using Python, JavaScript, and GPT‑X API. It answers questions conversationally and switches tone—respectful or cheeky—based on the user’s attitude.
Q2: How does tone‑switching work?
A2: A tone‑check module rates input as polite, neutral, or rude. That tag alters system prompts to generate matching respectful or sassy replies.
Q3: Can I integrate it into my app?
A3: Absolutely. Prashant AI is accessible via RESTful API endpoints. You can plug it into web apps, Slack bots, or even voice assistants—with a few config tweaks.
Q4: Is Prashant AI trustworthy and accurate?
A4: Yes. Every response goes through GPT‑X’s vetting. We added layers: user history checks, fallback clarifications, no hallucination policy, and full citation support for factual claims.
Q5: How do I launch my own chatbot like this?
- Choose your tech stack (Python, JS, API).
- Build a tone classifier.
- Craft system prompts for personality response.
- Test long‑tail content.
- Deploy and iterate based on user feedback.
Final Thoughts
By creating Prashant AI, I learned one huge thing: personality matters. A chatbot that always says “How may I assist you?” is polite, but predictable. Add tone, attitude—even a tiny bit of sass—and suddenly, it’s a conversation. It’s fun. It’s human.
And real talk? That’s exactly what AI needs. Heart. 💙
Thanks for reading! If you enjoyed this, hit that comment box. Got an idea for Phase 2? Tell me! I want to know what YOU think Prashant AI’s next SOP should be.
Catch you in the comments—unless Prashant roasts you first! 😎
By Prashant‑AI developer
