Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+metrics:
+- bertscore
+- bleu
+- rouge
+base_model:
+- MBZUAI/LaMini-Flan-T5-248M
+pipeline_tag: question-answering
+library_name: transformers
+tags:
+- RAG
+- FAISS
+- Telecom
+- Question-Answering
+- Flan-T5
+- Sentence-Transformers
+---
+
+
+
+# Telecom Plan Advisor – (RAG-LLM) based Question Answering System
+
+Telecom Plan Advisor is a **Retrieval-Augmented Generation (RAG)** system that helps users compare and choose wireless plans from **Bell, Virgin Plus, and Lucky Mobile**. 
+It combines **FAISS vector search** (MiniLM embeddings) with a lightweight **seq2seq LLM** (`flan-alpaca-base` or `LaMini-Flan-T5-783M`) to answer plan-related questions in natural language.
+
+## How it works
+- **Retrieve**: FAISS finds the most relevant plan descriptions.  
+- **Generate**: LLM produces a concise, friendly answer grounded in retrieved plans.  
+- **Evaluate**: System performance measured with BLEU, ROUGE, and BERTScore.
+
+# Datasets:
+- Synthetic Wireless Plans Dataset (curated from Bell, Virgin Plus and Lucky Mobile)
+
+## Quickstart
+```python
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+import faiss, pandas as pd
+from sentence_transformers import SentenceTransformer
+
+# Load model
+tokenizer = AutoTokenizer.from_pretrained("declare-lab/flan-alpaca-base")
+model = AutoModelForSeq2SeqLM.from_pretrained("declare-lab/flan-alpaca-base")
+qa = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+
+# Example
+print(qa("Best BYOD plan under $50 from Virgin Plus?", max_new_tokens=100)[0]["generated_text"])
+```
+
+📊 Evaluation Results
+
+BLEU: 0.46
+
+ROUGE-1: 0.57
+
+ROUGE-2: 0.35
+
+ROUGE-L: 0.40
+
+BERTScore-F1: 0.93
+
+- The system was evaluated on a small set of plan-related queries using BLEU, ROUGE, and BERTScore.  
+- Sample results show **strong semantic similarity** between generated answers and reference plan descriptions, with **BERTScore F1 around 0.9+**.  
+
+> Note: BLEU/ROUGE are conservative for free-form LLM outputs, and exact values may vary depending on the test set and chosen base model.
+
+
+## Limitations
+
+- Works only on the curated dataset (does not fetch live pricing).
+- Region support (Ontario, Quebec, Alberta) is inferred from plan names.