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https://github.com/ananthakrishnan12/techbot


https://github.com/ananthakrishnan12/techbot

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README

          

## **TechBOT - IT Education Chatbot**
**A chatbot that provides IT learning resources, course recommendations, interview tips, and more using LSTM, FastAPI, and a frontend built with HTML & CSS.**

### 🚀 **Project Overview**
TechBOT is an AI-powered chatbot designed to assist users in the IT industry by answering queries about programming, certifications, job opportunities, and interview tips. It uses **LSTM** for intent classification, **FastAPI** for backend deployment, and an interactive **HTML/CSS frontend** for user interaction.

---

## 📌 **Features**
✅ **IT Course Recommendations** - Suggests IT courses & certifications.
✅ **Programming Guidance** - Tips to learn Python, coding, and improving programming skills.
✅ **Job Opportunities** - Provides insights into high-demand IT jobs.
✅ **Interview Preparation** - Helps with coding interview strategies and system design concepts.
✅ **LSTM-based Intent Recognition** - Uses deep learning (LSTM) for chatbot responses.
✅ **FastAPI Backend** - API-driven chatbot with real-time responses.
✅ **Frontend with HTML/CSS** - Interactive web-based chatbot UI.

---

## 🛠️ **Tech Stack**
### **Backend**
- **Python 3.12.2**
- **TensorFlow/Keras (LSTM model)**
- **FastAPI**
- **Joblib (for saving tokenizer & label encoder)**

### **Frontend**
- **HTML, CSS**
- **JavaScript (to communicate with FastAPI backend via AJAX)**

### **Deployment**
- **FastAPI Server** (Backend API)
- **HTML/CSS Frontend** (User Interface)

---

## 🛠️ **Installation & Setup**

### **1️⃣ Clone the Repository**
```sh
git clone https://github.com/Ananthakrishnan12/TechBOT.git
cd TechBOT
```

### **2️⃣ Create a Virtual Environment & Install Dependencies**
```sh
python -m venv Techbot
source Techbot/bin/activate # For Linux/Mac
Techbot\Scripts\activate # For Windows
pip install -r requirements.txt
```

### **3️⃣ Train the LSTM Model & Save Artifacts**
```sh
python train_model.py # Train the chatbot model
```
This will generate:
✅ `chatbot.h5` - Trained LSTM model
✅ `tokenizer.joblib` - Tokenizer for text preprocessing
✅ `label_encoder.joblib` - Label encoder for intent classification

---

## 🚀 **Run the Chatbot API**
```sh
uvicorn main:app --reload
```
The FastAPI server will start at **http://127.0.0.1:8000/**

✅ Visit **http://127.0.0.1:8000/docs** for API documentation

---

DEMO : ![Chatbot Demo](https://github.com/Ananthakrishnan12/TechBOT/blob/main/Techbot.gif)