- 235
- 118 701
Mohamed Naji Aboo
India
Приєднався 19 жов 2021
Nginx Tutorial: Installation, Configuration, and Use Cases on EC2 Ubuntu
In this video, I provide a comprehensive tutorial on Nginx, covering its features, advantages, and disadvantages. We start by creating an EC2 Ubuntu instance on AWS and logging into it via SSH. Step-by-step, I guide you through the installation process of Nginx, explain its default configuration, and demonstrate the structure and use cases of sites-available and sites-enabled.
You'll also learn how to enable outbound rules, create a new server context to display a "Hello World" message, and understand the Nginx root folder and its functionality in serving web content. The video includes practical examples of linking files between sites-available and sites-enabled using symbolic links.
By the end, you'll have the skills to set up, configure, and manage Nginx on an Ubuntu EC2 instance for your web server needs.
Install NGINX
sudo apt update
sudo apt install nginx -y
Start, Restart, and Check Nginx Status:
sudo systemctl start nginx
sudo systemctl restart nginx
sudo systemctl status nginx
Test Nginx Configuration:
sudo nginx -t
List Files in sites-available and sites-enabled:
ls -l /etc/nginx/sites-available
ls -l /etc/nginx/sites-enabled
Create a Symbolic Link Between sites-available and sites-enabled:
sudo ln -s /etc/nginx/sites-available/yourfile /etc/nginx/sites-enabled/
Remove a Symbolic Link:
sudo rm /etc/nginx/sites-enabled/yourfile
Reload Nginx After Configuration Changes:
sudo systemctl reload nginx
Check Open Ports:
sudo ufw status
#Nginx #WebServer #Ubuntu #AWS #EC2 #Linux #NginxTutorial #WebHosting #CloudComputing #AWSUbuntu #ServerConfiguration #LearnNginx #WebDevelopment
You'll also learn how to enable outbound rules, create a new server context to display a "Hello World" message, and understand the Nginx root folder and its functionality in serving web content. The video includes practical examples of linking files between sites-available and sites-enabled using symbolic links.
By the end, you'll have the skills to set up, configure, and manage Nginx on an Ubuntu EC2 instance for your web server needs.
Install NGINX
sudo apt update
sudo apt install nginx -y
Start, Restart, and Check Nginx Status:
sudo systemctl start nginx
sudo systemctl restart nginx
sudo systemctl status nginx
Test Nginx Configuration:
sudo nginx -t
List Files in sites-available and sites-enabled:
ls -l /etc/nginx/sites-available
ls -l /etc/nginx/sites-enabled
Create a Symbolic Link Between sites-available and sites-enabled:
sudo ln -s /etc/nginx/sites-available/yourfile /etc/nginx/sites-enabled/
Remove a Symbolic Link:
sudo rm /etc/nginx/sites-enabled/yourfile
Reload Nginx After Configuration Changes:
sudo systemctl reload nginx
Check Open Ports:
sudo ufw status
#Nginx #WebServer #Ubuntu #AWS #EC2 #Linux #NginxTutorial #WebHosting #CloudComputing #AWSUbuntu #ServerConfiguration #LearnNginx #WebDevelopment
Переглядів: 9
Відео
Crawl4AI:Amazon Product Search Extraction Using Crowl4AI | Title, Image, Price, Reviews & Ratings
Переглядів 407 годин тому
Learn how to extract Amazon product search details effortlessly using the powerful Crowl4AI framework! 🚀 In this video, I demonstrate step-by-step how to scrape essential product information such as titles, images, prices, review counts, and ratings from Amazon. Whether you're building a product research tool, price comparison system, or just exploring web scraping, this tutorial will guide you...
FAST API Tutorial | Path Parameters | Quick Start
Переглядів 1212 годин тому
Unlock the full potential of FastAPI Path Parameters in this detailed tutorial! 🚀 Learn how to: Declare path parameters using Python's format string syntax. Specify parameter types with standard Python type annotations for seamless data conversion. Leverage Pydantic for robust data validation under the hood. Understand the importance of path operation order and how it impacts your API. Use Pyth...
Building a Real-Time RAG System: HTML Processing with LangGraph and Streaming Capabilities
Переглядів 4719 годин тому
An advanced implementation of a Retrieval-Augmented Generation (RAG) system that processes HTML content with state-of-the-art features including real-time streaming, stateful operations, and efficient document processing. Key Features HTML Content Processing: Utilizes WebBaseLoader for efficient web page content extraction Smart Document Chunking: Implements RecursiveCharacterTextSplitter for i...
FAST API Tutorial | Introduction | Install | Run | Hello world
Переглядів 37День тому
In this video, I introduce FastAPI, a modern and fast web framework for building APIs with Python. We'll discuss: - What is FastAPI? - Key advantages and disadvantages of using FastAPI. - How to install FastAPI on your system. - Writing your first "Hello, World!" application using FastAPI. - Running the application and troubleshooting the "port is already in use" error. I'll show you how to res...
Langchain Tutorial : LangSmith | Tutorial: Account Setup, API Key Creation, Logging Mechanisms
Переглядів 67День тому
Dive into this comprehensive LangSmith tutorial, where I explain: What LangChain is and how to get started. Step-by-step guide to creating an account and generating an API key. Setting up a project in LangSmith. Demonstrating code integration with LangSmith. Exploring various logging mechanisms like simple logs, metadata logs, and tags. Managing LangChain threads and waiting for their execution...
DeepSeek R1 Advanced Reasoning Language Model: Run on Laptop with Ollama API Integration
Переглядів 103День тому
Explore the capabilities of DeepSeek R1, a cutting-edge large language model designed for complex reasoning tasks. In this video, learn how DeepSeek R1 uses a specialized training approach emphasizing Reinforcement Learning (RL) over traditional Supervised Fine-Tuning (SFT), enabling advanced problem-solving and logical thinking. We also demonstrate how to interact with DeepSeek R1 through the ...
Crawl4AI : Web crawler & scrapper for LLM | Data Preprocessing Using PruningContentFilter
Переглядів 200День тому
n this video, we provide a comprehensive guide on how to clean up HTML content scraped using Crawl4j, a powerful web crawler. We delve into the process of using the PruningContentFilter, a tool designed to refine and enhance the quality of the scraped content by removing unnecessary or irrelevant data. We demonstrate key features and properties of the PruningContentFilter, including: Threshold:...
Langchain Tutorial | Retrievers| Part 7 | Custom Retriever | Step by Step with code example
Переглядів 3714 днів тому
In this tutorial, learn how to build your own custom retriever in LangChain to efficiently fetch relevant documents for LLM-based applications. Retrievers are key components in applications requiring information retrieval from external data sources like databases or the web. By implementing your custom retriever, you can enhance control and precision over data retrieval. 🚀 What You’ll Learn: Th...
Langchain Tutorial | Retrievers| Part 6 | MultiVectorRetriever
Переглядів 4014 днів тому
In this comprehensive tutorial, learn how to use the powerful LangChain MultiVectorRetriever for efficient document retrieval by associating multiple vectors per document. Whether you're embedding smaller chunks, generating document summaries, or creating hypothetical questions for retrieval, this video covers all methods step-by-step. 🚀 What You’ll Learn: How to split documents into smaller ch...
Langchain Tutorial | Retrievers| Part 5 | Parent Document Retriever | Optimize | Effective Retrieval
Переглядів 3314 днів тому
Discover the ParentDocumentRetriever and its powerful ability to strike the perfect balance between small, meaningful chunks and large, context-rich documents. In this step-by-step tutorial, we explore how to efficiently retrieve documents using LangChain, Chroma, OpenAI Embeddings, and Recursive Character Text Splitter. Whether you're retrieving full documents or larger chunks, this video demo...
Langgraph Tutorial: Conditional Branching Tutorial: Dynamic Workflow Execution with Routes
Переглядів 4614 днів тому
In this tutorial, I demonstrate conditional branching in LangGraph, where the execution path dynamically adapts based on the state. This powerful approach enables workflows that react to input conditions, making them highly flexible and efficient. Key Topics Covered: Dynamic Branching with Conditions: Learn how to create multiple paths using add_conditional_edges. State Management: Use the stat...
Langchain Tutorial | Retrievers| Part 4 | Ensemble Retriever | BM25 + FAISS Hybrid Search
Переглядів 6314 днів тому
Description: In this video, we explore the power of the EnsembleRetriever for combining the strengths of multiple retrievers. Learn how to use Reciprocal Rank Fusion (RRF) to achieve better search results by combining sparse retrievers like BM25 and dense retrievers like FAISS. Discover the basics of hybrid search, its advantages, and step-by-step implementation with LangChain. Watch now to enh...
Langchain Tutorial | Retrievers| Part 3 | Contextual Compression | LLMChainExtractor | FlashRerank
Переглядів 3621 день тому
Optimize your document retrieval system with Contextual Compression in LangChain! In this detailed tutorial, we tackle one of the biggest challenges in retrieval: ensuring that only the most relevant information is surfaced, reducing irrelevant text and minimizing expensive LLM calls. This video covers: The concept of contextual compression and how it improves retrieval efficiency by compressin...
Crawl4AI: Effortlessly Create Screenshots and PDFs of a Webpage
Переглядів 58221 день тому
Unlock the power of Crawl4AI to create high-quality screenshots of webpages and PDFs with ease. This tutorial walks you through the step-by-step process, showcasing how simple and efficient it is to capture visual snapshots of online and document content. Perfect for developers, researchers, and content creators looking to streamline their workflow. 🌟 Key Takeaways: ✅ Generate screenshots of an...
Langchain Tutorial|Retrievers|Part 2|MultiQueryRetriever|Automating Prompt Tuning | Better Retrieval
Переглядів 7721 день тому
Langchain Tutorial|Retrievers|Part 2|MultiQueryRetriever|Automating Prompt Tuning | Better Retrieval
LangGraph Tutorial | Parallel Execution: Fanning Out & Aggregating State with Reducer Functions
Переглядів 10721 день тому
LangGraph Tutorial | Parallel Execution: Fanning Out & Aggregating State with Reducer Functions
Langchain Tutorial | Retrievers| Part 1 | FAISS, MMR, Similarity Search with Examples
Переглядів 7921 день тому
Langchain Tutorial | Retrievers| Part 1 | FAISS, MMR, Similarity Search with Examples
Langchain Tutorial | Vector Store | Part 3 | FAISS VectorStore | Save, Load, Search, & Filter
Переглядів 13028 днів тому
Langchain Tutorial | Vector Store | Part 3 | FAISS VectorStore | Save, Load, Search, & Filter
Crawl4AI: The Ultimate Open-Source Web Crawler & Scraper for LLMs
Переглядів 87828 днів тому
Crawl4AI: The Ultimate Open-Source Web Crawler & Scraper for LLMs
Quick Start with Smolagents: Simplify Building Powerful Code Agents
Переглядів 17428 днів тому
Quick Start with Smolagents: Simplify Building Powerful Code Agents
Langchain Tutorial | Vector Store | Part 2 | Chroma VectorStore | Save, Load, Search, & Filter
Переглядів 8528 днів тому
Langchain Tutorial | Vector Store | Part 2 | Chroma VectorStore | Save, Load, Search, & Filter
Langchain Tutorial | Vector Store | Part 1 | Memory Vector Store | Ollama vs OpenAI Embeddings
Переглядів 96Місяць тому
Langchain Tutorial | Vector Store | Part 1 | Memory Vector Store | Ollama vs OpenAI Embeddings
LangGraph Tutorial: Why LangGraph? Use Cases, Multi-Agent Workflows, and Advanced Architectures
Переглядів 265Місяць тому
LangGraph Tutorial: Why LangGraph? Use Cases, Multi-Agent Workflows, and Advanced Architectures
Langchain Tutorial | Embedding Models | Part 3 | Ollama Embedding Model | Local Installation
Переглядів 108Місяць тому
Langchain Tutorial | Embedding Models | Part 3 | Ollama Embedding Model | Local Installation
How to Use Ollama with Any GGUF Model on Hugging Face Hub and LangChain
Переглядів 258Місяць тому
How to Use Ollama with Any GGUF Model on Hugging Face Hub and LangChain
Langchain Tutorial | Embedding Models | Part 2 | Hugging Face Embedding Model Explained
Переглядів 114Місяць тому
Langchain Tutorial | Embedding Models | Part 2 | Hugging Face Embedding Model Explained
Langchain Tutorial | Embedding Models | Part 1 | OpenAI Embeddings Explained: Step-by-Step Guide
Переглядів 63Місяць тому
Langchain Tutorial | Embedding Models | Part 1 | OpenAI Embeddings Explained: Step-by-Step Guide
Langchain Tutorial | Text Splitters | Part 4 | Json Splitter with Examples
Переглядів 64Місяць тому
Langchain Tutorial | Text Splitters | Part 4 | Json Splitter with Examples
Langchain Tutorial | Text Splitters | Part 3 | HTML Splitter with Examples
Переглядів 82Місяць тому
Langchain Tutorial | Text Splitters | Part 3 | HTML Splitter with Examples
What an excellent video
hello mohammed, i am beginner in Langchain, i have problem with my project, do you work as paid coach also please? @mohamednajiaboo
Do you share on github ?
github.com/NajiAboo/crawl4ai/blob/main/amazon.py
This is awesome, Please make some videos using Crawl LLM Strategy.-much appreciated.
Thanks. will try
Thanks
Thanks
which retriever bst?
Its depends on the use case, If its your document simple, You can go with basic retriever. Parent Retriever is a good option for medium complexity. If you have tables and images, then we need to go with MultiVector . If its too complex, we even need to combine with multiple retrievers.
{ "errorMessage": "module 'os' has no attribute 'add_dll_directory'", "errorType": "AttributeError", "requestId": "", "stackTrace": [ " File \"/var/lang/lib/python3.13/importlib/__init__.py\", line 88, in import_module return _bootstrap._gcd_import(name[level:], package, level) ", " File \"<frozen importlib._bootstrap>\", line 1387, in _gcd_import ", " File \"<frozen importlib._bootstrap>\", line 1360, in _find_and_load ", " File \"<frozen importlib._bootstrap>\", line 1331, in _find_and_load_unlocked ", " File \"<frozen importlib._bootstrap>\", line 935, in _load_unlocked ", " File \"<frozen importlib._bootstrap_external>\", line 1022, in exec_module ", " File \"<frozen importlib._bootstrap>\", line 488, in _call_with_frames_removed ", " File \"/var/task/lambda_function.py\", line 2, in <module> import psycopg2 ", " File \"/var/task/psycopg2/__init__.py\", line 28, in <module> _delvewheel_patch_1_9_0() ", " File \"/var/task/psycopg2/__init__.py\", line 25, in _delvewheel_patch_1_9_0 os.add_dll_directory(libs_dir) " ] } i was getting this error
Nice explanation, thanks
Thanks
Hi. Your videoes are very relevant and interesting for those who want to catch the concepts. Really great work. I wish I could get a video on: Integration with a relational db or call our custom function for an ai bot with agents. Like - Querying list of products with nlp using agent - Querying order status or cancellation of it. - Getting analytics of products or sales.
I commented not just for this video. I liked many of your videoes around Langchain based AI Concepts.
That's a great suggestion! I'll definitely consider making a video about that.
thanks
Sir, you have the fast fingers
Thanks
If anyone’s tried both Crawl4AI and HasData, how do they stack up for real-time data scraping? The speed improvements sound intriguing!
have not tried HasData, But its not free right?
Great. Does it have the ability to scrape a website behind Auth or Cookies?
Thanks for this video
Amazing
Thanks
Nice explanation
Thanks 🙏for this video🎉
Oh! Wow excellent fantastic🎉
Thanks
can you share the code? many thanks. It's very helpful.
Let me check
Thanks
Welcome
Brother why 11 videos are hidden
hi, its because some of them are in draft mode and some of them are scheduled
Oh!Wow exsalent we like this video
👏🏻
Thanks
👍🏻
Thanks
👍🏻👍🏻
Thanks
Wow! wonderful 🎉❤
Thanks
I have installed langchain _community yet i am unable to import it to use document loaders
I am facing issue with langchain _community.. although i have installed it in requirements txt yet i am not able to import it
شكرًااا
Thanks
I like it and wonderful 🎉😮
Thanks
Up to understand. How to ask questions to azure text analytics? I want to query the text analytics from python is there any document can you please share
Where can I get the dataset?
You can check my github repo github.com/NajiAboo/azure-text-analytics-example
Hi, i am working on nemo gaurdrails. i have a issue can you help me out with it!
Few suggestions. 1. I have added my repo in the description. Pls cross check with it 2. Pls share your notebook, i can have a look once free 3. If aboe things not work, May be we can sit some time on weekend
Ohh, great thanks. I will connect if I face any issues after referring that
great explanation
Thanks
Wonder full🎉
you saved me bro, I'm soooooooooooooooooooooooooooooooooooo appreciate to you you are my savior
Thanks for your comment. Happy that it helped you
❤
Thanks
👍
🙏
Thanks
👌
Thanks
👍🏻👍🏻👍🏻
Thanks
Good explanation thank you.
Thanks,
Did the same but can't connect, don't know why
Why did you use Language Services vs Machine Learning for the classification?
Thank you
Great! This video unblock me a lot.
Happy to know its helped. thanks
thanks
You're welcome!
👍
Thanks
Informative
thanks