Prevent LLM AIs like ChatGPT, Claude, or Gemini, and more from generating you code and instead providing useful diagrams and roadmaps.

Built real-world LLM apps using LangChain, including an AI Code Tutor, CV Assistant, and smart chatbots powered by RAG and agentic workflows. Hands-on projects showcasing practical use of Generative AI.

Structured YAML catalog of 4,587 AI models across 95 providers — pricing, context windows, modalities, capabilities. First-party data with TypeScript types and Zod validation.

A collection of hands-on examples and core components for building LLM-powered applications. This repository explores Large Language Models (LLMs), Chat Models, and Embedding Models to create complex, multi-step AI workflows.

This is the langchain content I practiced during learning it. It contains code snippets and mini projects that could be done using LangChain

LangChain learning projects covering LLMs, Chat Models, and Embeddings using Python, HuggingFace & OpenAI.

🛠️ Enhance LLM productivity without coding by using MGGU to guide your projects with research and actionable insights.

A comprehensive collection of LangChain Output Parser implementations demonstrating how to transform Large Language Model (LLM) responses into structured, validated, and application-ready data formats.

LangChain-based exploration of chat models, embeddings, and document similarity using OpenAI, Anthropic, Google Gemini, and Hugging Face models.