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README.md

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-title: CXRAG
-emoji: 🏃
-colorFrom: green
-colorTo: indigo
-sdk: gradio
-sdk_version: 5.28.0
-app_file: app.py
-pinned: false
-short_description: Junk DATA RAG CAG
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-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+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.
+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.
+
+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.
+
+Usage
+
+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.
+Example output:
+Response: “Go to the login page, click ‘Forgot Password,’...”
+Cleanup Stats: “Cleaned FAQs: 3 (removed 2 junk entries)”
+
+
+
+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.
+
+Technical Details
+
+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).
+
+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.