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metadata
license: mit
title: Customer Experience Bot Demo
sdk: gradio
colorFrom: purple
colorTo: green
short_description: CX AI LLM

title: Customer Experience Bot Demo emoji: πŸ€– colorFrom: blue colorTo: purple sdk: gradio sdk_version: "4.44.0" app_file: app.py pinned: false

Customer Experience Bot Demo

A Retrieval-Augmented Generation (RAG) based customer experience (CX) bot deployed on Hugging Face Spaces (free tier). Demonstrates robust data cleanup and query validation to deliver high-quality, multilingual CX solutions for enterprise applications in SaaS, HealthTech, FinTech, and eCommerce.

Features

RAG Pipeline: Retrieves FAQs using all-MiniLM-L6-v2 and FAISS for accurate, context-aware responses.

Data Cleanup: Filters nulls, duplicates, and low-quality FAQs (e.g., short answers) to ensure reliable outputs.

Performance Visualization: Displays latency and accuracy metrics with Matplotlib/Seaborn to monitor data quality.

Gradio Interface: User-friendly UI for querying, viewing FAQs, and checking cleanup statistics.

Setup

Clone this repository to a Hugging Face Space (free tier, public).

Create requirements.txt with the listed dependencies.

Upload app.py (includes embedded sample FAQs for simplicity).

Configure the Space to run with Python 3.9+ and no GPU.

Usage

Enter a query (e.g., β€œHow do I reset my password?”) in the Gradio UI.

View the bot’s response, retrieved FAQs, data cleanup statistics, and RAG pipeline plot.

Example output:

Response: β€œGo to the login page, click β€˜Forgot Password,’ and follow the email instructions.”

Cleanup Stats: β€œCleaned FAQs: 3 (removed 2 junk entries)”

Data Cleanup

FAQ Preprocessing: Removes nulls, duplicates, and answers shorter than 20 characters to ensure high-quality data.

Query Validation: Rejects empty or overly short queries (<5 characters) for reliable input processing.

Impact: Clean data is essential for accurate, scalable CX solutions, ensuring robust performance for enterprise Partners.

Technical Details

Stack: Python, Hugging Face (all-MiniLM-L6-v2), FAISS (CPU), Gradio, Pandas, Matplotlib, Seaborn.

Free Tier Compatibility: Lightweight design with no GPU requirements, optimized for Hugging Face Spaces.

Extensibility: Easily adaptable for CRM integrations (e.g., Salesforce) and cloud deployments (e.g., AWS Lambda).

Purpose

Developed to showcase expertise in designing, building, and deploying CX bots with a strong focus on data quality, tailored for AI-driven customer experience platforms.