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+# Multilingual Knowledge RAG Bot – Cross-Lingual Retrieval-Augmented Generation
+
+This model is designed for **cross-lingual question answering** using Retrieval-Augmented Generation (RAG).  
+It can take documents in multiple languages — Urdu, Hindi, Spanish, English — and answer in the same or different language.
+
+## Key Features
+- **LLM Used:** LLaMA 2 / Mistral (depending on runtime availability in Colab)
+- **Embedding Model:** `sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2`
+- **RAG Pipeline:** FAISS-based vector search + context injection
+- **Training/Processing:** Implemented entirely in Google Colab using open-source tools only
+- **Zero paid APIs** — 100% free and deployable
+
+## Techniques Used
+- **Vector Database:** FAISS for similarity search
+- **Cross-Lingual Embeddings:** multilingual sentence transformers
+- **Prompt Engineering:** Context-aware question answering
+- **Open-Source Deployment Ready:** Hugging Face Spaces compatible
+
+---
+
+### License
+Apache-2.0