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README.md

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+# LangChain & LLM Projects Collection
+
+A suite of applications demonstrating document processing, chatbots, and AI-powered question answering using LangChain and various LLMs.
+
+## 📚 Projects Overview
+
+### 1. Book Summaries with LangChain and OpenAI
+![Python](https://img.shields.io/badge/Python-3.8+-blue)
+![LangChain](https://img.shields.io/badge/LangChain-0.0.200-green)
+![OpenAI](https://img.shields.io/badge/OpenAI-gpt3.5-purple)
+
+Automated book summarization system that processes PDFs/epubs and generates concise summaries using OpenAI's models.
+
+**Features:**
+- PDF text extraction
+- Chunking and embeddings
+- Summary generation with temperature control
+
+---
+
+### 2. Chat with Multiple Documents
+![Streamlit](https://img.shields.io/badge/Streamlit-1.22-red)
+![FAISS](https://img.shields.io/badge/FAISS-vector_store-yellow)
+
+Multi-document QA system that allows conversational interaction with your document collection.
+
+**Tech Stack:**
+- Document loading (PDF, DOCX, TXT)
+- Text splitting with RecursiveCharacterTextSplitter
+- FAISS vector store for efficient similarity search
+
+---
+
+### 3. Website Chatbot
+![BeautifulSoup](https://img.shields.io/badge/BeautifulSoup-4.11-orange)
+![Flask](https://img.shields.io/badge/Flask-2.2-lightgrey)
+
+Custom chatbot that can be trained on any website content through web scraping.
+
+**Implementation:**
+- URL-based content ingestion
+- Context-aware responses
+- Conversation memory
+
+---
+
+### 4. LangChain Crash Course
+![Jupyter](https://img.shields.io/badge/Jupyter-Notebook-orange)
+
+Educational materials covering LangChain fundamentals through practical examples.
+
+**Topics Include:**
+- Chains, Agents, and Memory
+- Document Loaders and Text Splitters
+- Vector Stores and Retrievers
+
+---
+
+### 5. Llama2 Integration Projects
+![Llama2](https://img.shields.io/badge/Meta-Llama2-blue)
+![HuggingFace](https://img.shields.io/badge/HuggingFace-Transformers-yellow)
+
+Collection of implementations using Meta's Llama2 models:
+
+#### a. QA Book PDF with LangChain
+- PDF question answering system
+- Custom prompt templates
+- Retrieval-Augmented Generation (RAG)
+
+#### b. Run Llama2 on Google Colab
+- Free-tier Colab implementation
+- Quantized model support
+- Gradio interface
+
+#### c. Local CPU Deployment
+- Optimized for CPU-only environments
+- Quantized model loading
+- Basic chat interface
+
+## 🛠 Installation
+
+```bash
+git clone https://github.com/yourusername/llm-projects.git
+cd llm-projects
+pip install -r requirements.txt