Deploy Your Agent in Production at Render, Railway, AWS, GCP, and Azure. An OpenAI-compatible FastAPI server powered by RAGWire, supporting multiple agent frameworks (LangChain, LangGraph, CrewAI, AutoGen) with Qdrant vector store and Google Gemini. Environment Variables Create a .env file in the project root: Available Agents Value Agent 01_langchain_agent LangChain (default) 02_langgraph_self_correcting_agent LangGraph Read more
The following endpoints are compatible with OpenAI endpoints to make it compatible with Chat UI Interfaces. GET /health Check if the server is running. Response GET /v1/models List available models. Response GET /v1/models/{model_id} Get a specific model by ID. Response POST /v1/chat/completions Send a chat message and receive a streamed Read more
Blender MCP Repo: https://github.com/ahujasid/blender-mcp YouTube Video Link: https://youtu.be/ZMlEeW3ygqY Part 1 — Blender MCP (Windows) 1. Install Blender Addon Download addon.py from the repo and install in Blender: Edit → Preferences → Add-ons → Install → select addon.py In the 3D Viewport press N → BlenderMCP tab → Start MCP Server Read more
Hardware Target: 24GB VRAM (RTX 3090 / 4090)All model sizes sourced directly from Ollama’s model library (Q4_K_M unless noted). Model Lineup Model Ollama Tag Total Params Active Params Architecture Ollama Size (Q4_K_M) Nemotron 3 Nano 4B nemotron-3-nano:4b 4B 4B Hybrid Mamba 2.8 GB Qwen 3.5 9B qwen3.5:9b 9B 9B Dense Read more
💰LATEST COUPON CODE FOR DISCOUNTS: 17APRIL26 Students who follow this sequence: 95% success rate.Students who skip ahead: 30% success rate. The difference? A structured learning path that builds your skills progressively: This isn’t just a course list. It’s a proven roadmap used by 100,000+ students worldwide to go from beginner Read more
💰LATEST COUPON CODE FOR DISCOUNTS: 17APRIL26 🚀 Build Real AI Agents in 2026 (Not Just Demos) From RAG → Multi-Agent Systems → LangGraph → OpenAI Agents → LLM Fine-tuning 👉 This is a complete Agentic AI journey. 🤖 1. 2026 Deep Agent – Multi-Agent RAG with Gemini & LangChain Build advanced, production-ready Read more
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🎉 Private Agentic RAG with LangGraph and Ollama is now LIVE! 🎉 Hi everyone,I am excited to announce my brand-new course: 🔥 Agentic AI – Private Agentic RAG with LangGraph and Ollama 🔥This course teaches you how to build advanced, private, and production-ready Agentic RAG systems, running fully on your Read more
What is TFIDF? TF-IDF, short for term frequency-inverse document frequency, is a numerical statistic that is used to reflect how important a word is to a document in a corpus of documents. It is commonly used in natural language processing and information retrieval tasks, such as document classification and search Read more
MLOps, or Machine Learning Operations, is the practice of combining machine learning and operations to enable the rapid, reliable, and secure development, deployment, and management of machine learning models. MLOps aims to streamline the process of building and deploying machine learning models in a production environment, by automating and optimizing Read more
Does the magnitude of the variable matter? In Linear Regression models, the scale of variables used to estimate the output matters. Linear models are of the type y = w x + b, where the regression coefficient w represents the expected change in y for a one unit change in x Read more
An outlier is a data point which is significantly different from the remaining data. “An outlier is an observation which deviates so much from the other observations as to arouse suspicions that it was generated by a different mechanism.” [D. Hawkins. Identification of Outliers, Chapman and Hall , 1980.] Should Read more
Linear models make the following assumptions over the independent variables X, used to predict Y: There is a linear relationship between X and the outcome Y The independent variables X are normally distributed There is no or little co-linearity among the independent variables Homoscedasticity (homogeneity of variance) Examples of linear Read more
Labels that occur rarely Categorical variables are those whose values are selected from a group of categories, also called labels. Different labels appear in the dataset with different frequencies. Some categories appear more frequently in the dataset, whereas some other categories appear only in a few number of observations. For Read more
Cardinality refers to the number of possible values that a feature can assume. For example, the variable “US State” is one that has 50 possible values. The binary features, of course, could only assume one of two values (0 or 1). The values of a categorical variable are selected from Read more
Missing data, or missing values, occur when no data / no value is stored for certain observations within a variable. Incomplete data is an unavoidable problem in most data sources, and may have a significant impact on the conclusions that can be derived from the data. Why is data missing? The source of missing Read more
One of the central concepts of data science is gaining insights from data. Statistics is an excellent tool for unlocking such insights in data. In this post, we’ll see some basic types of data(variable) which can be present in your dataset. What is a Variable? A variable is any characteristic, Read more
Data visualization is the discipline of trying to understand data by placing it in a visual context so that patterns, trends and correlations that might not otherwise be detected can be exposed. pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, in Python programming Read more
Resume NER Training In this blog, we are going to create a model using SpaCy which will extract the main points from a resume. We are going to train the model on almost 200 resumes. After the model is ready, we will extract the text from a new resume and Read more
Word Embedding and Sentiment Analysis What is Word Embedding? Natural Language Processing(NLP) refers to computer systems designed to understand human language. Human language, like English or Hindi consists of words and sentences, and NLP attempts to extract information from these sentences. Machine learning and deep learning algorithms only take numeric Read more