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README.md

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-CX Bot Demo
-A RAG-based customer experience (CX) bot deployed on Hugging Face Spaces (free tier). Demonstrates junk data cleanup and client data validation for high-quality, multilingual CX solutions in SaaS, HealthTech, FinTech, and eCommerce.
+title: Customer Experience Bot Demo emoji: 🤖 colorFrom: blue colorTo: purple sdk: gradio sdk_version: "4.44.0" app_file: app.py pinned: false
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+Customer Experience Bot Demo
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+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.
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 Features
 
-RAG Pipeline: Retrieves FAQs using all-MiniLM-L6-v2 and FAISS, delivering accurate responses.
-Data Cleanup: Removes nulls, duplicates, and low-quality FAQs (e.g., short answers) to ensure reliable outputs.
-Performance Plot: Visualizes latency and accuracy with Matplotlib/Seaborn to monitor data quality.
-Gradio UI: User-friendly interface for querying, viewing FAQs, and checking cleanup stats.
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+RAG Pipeline: Retrieves FAQs using all-MiniLM-L6-v2 and FAISS for accurate, context-aware responses.
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+Data Cleanup: Filters nulls, duplicates, and low-quality FAQs (e.g., short answers) to ensure reliable outputs.
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+Performance Visualization: Displays latency and accuracy metrics with Matplotlib/Seaborn to monitor data quality.
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+Gradio Interface: User-friendly UI for querying, viewing FAQs, and checking cleanup statistics.
 
 Setup
 
-Clone this repo to a Hugging Face Space (free tier, public).
-Create requirements.txt with listed dependencies.
-Upload app.py (includes embedded sample FAQs).
-Set Space to run with Python 3.9+ and no GPU.
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+Clone this repository to a Hugging Face Space (free tier, public).
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+Create requirements.txt with the listed dependencies.
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+Upload app.py (includes embedded sample FAQs for simplicity).
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+Configure the Space to run with Python 3.9+ and no GPU.
 
 Usage
 
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 Enter a query (e.g., “How do I reset my password?”) in the Gradio UI.
-View the bot’s response, retrieved FAQs, cleanup stats, and RAG pipeline plot.
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+View the bot’s response, retrieved FAQs, data cleanup statistics, and RAG pipeline plot.
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 Example output:
-Response: “Go to the login page, click ‘Forgot Password,’...”
-Cleanup Stats: “Cleaned FAQs: 3 (removed 2 junk entries)”
 
 
 
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+Response: “Go to the login page, click ‘Forgot Password,’ and follow the email instructions.”
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+Cleanup Stats: “Cleaned FAQs: 3 (removed 2 junk entries)”
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 Data Cleanup
 
-Preprocess FAQs: Removes nulls, duplicates, and answers <20 characters to ensure high-quality data.
-Query Validation: Rejects empty or short queries (<5 characters) for reliable input.
-Why It Matters: Clean data is critical for accurate, scalable CX solutions, ensuring robust performance for enterprise Partners.
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+FAQ Preprocessing: Removes nulls, duplicates, and answers shorter than 20 characters to ensure high-quality data.
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+Query Validation: Rejects empty or overly short queries (<5 characters) for reliable input processing.
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+Impact: Clean data is essential for accurate, scalable CX solutions, ensuring robust performance for enterprise Partners.
 
 Technical Details
 
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 Stack: Python, Hugging Face (all-MiniLM-L6-v2), FAISS (CPU), Gradio, Pandas, Matplotlib, Seaborn.
-Free Tier: Lightweight design (no GPU, small model) for Hugging Face Spaces.
-Extensibility: Adaptable for CRM integrations (e.g., Salesforce) and cloud deployment (e.g., AWS Lambda).
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+Free Tier Compatibility: Lightweight design with no GPU requirements, optimized for Hugging Face Spaces.
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+Extensibility: Easily adaptable for CRM integrations (e.g., Salesforce) and cloud deployments (e.g., AWS Lambda).
 
 Purpose
-Built to demonstrate expertise in designing, building, and deploying CX bots with a focus on data quality, suitable for AI-driven customer experience platforms.
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+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.