Why Use This
This skill provides specialized capabilities for aiskillstore's codebase.
Use Cases
- Developing new features in the aiskillstore repository
- Refactoring existing code to follow aiskillstore standards
- Understanding and working with aiskillstore's codebase structure
Install Guide
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Click Install Skill, paste the link below, then press Install.
https://github.com/aiskillstore/marketplace/tree/main/skills/abdulsamad94/chatbot-implementation
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Updated At Jan 19, 2026, 04:39 AM
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License NOASSERTION
---
name: chatbot-implementation
description: Details of the RAG Chatbot, including UI and backend logic.
---
# Chatbot Logic
## Overview
A specialized RAG (Retrieval Augmented Generation) chatbot that helps users learn from the textbook content.
## Backend
- **Route**: `app/api/chat/route.ts`
- **Logic**:
1. Receives `query` and `history`.
2. Embeds query using Gemini or OpenAI embedding model.
3. Searches Qdrant (vector DB) for relevant textbook chunks.
4. Constructs context from matches.
5. Generates response using Gemini Flash/Pro.
## Vector Search (Qdrant)
We use Qdrant for storing embeddings of the textbook.
- Collection: `textbook_chunks` (or similar).
- Fields: `text`, `source`, `chunk_id`.
## UI Component
- **Location**: `textbook/src/components/Chatbot/index.tsx`.
- **Features**:
- Floating chat window.
- Size controls (Small, Medium, Large).
- Markdown rendering of responses.
- Context selection (highlight text to ask about it).
- Mobile responsive design.
- Auth awareness (personalizes answer based on user profile).
## Styling
- **CSS**: `styles.module.css` (Premium animations, shadow effects).
- **Themes**: Dark/Light mode compatible (using `--ifm` variables).
