runnables

LangChain Practice Tasks using FastAPI and LCEL

An intelligent LLM-powered research orchestration system built using LangChain Runnables. This project demonstrates modular AI workflow engineering through parallel section generation, prompt orchestration, dynamic pipeline construction, and automated research report synthesis.

Production-ready AI Study Assistant built with LangChain, Google Gemini, RunnableParallel, RunnableBranch, and Streamlit. Generates notes, interview questions, answers, and sentiment-based feedback.

In this repo whatever i learned in the langgraph from different sources putting it in with simple linear graph workflows

LangChainRunnables is a Python-based project showcasing and learing five distinct LangChain workflows—Branch, Lambda, Parallel, Passthrough, and Sequence—using OpenRouter’s free API. It demonstrates AIdriven text processing tasks generating facts, summarizing reports, creating notes and quizzes, responding to sentiment feedback, and crafting jokes

🤖 GenAI: A modular LangChain ⚙️ playground with real-world examples on prompts 📝, agents 🧠, RAG 🔍, embeddings 🧬, and multi-model chat apps 💬.

LLM-powered search router that chooses direct answers or live web retrieval, returning concise, validated responses with optional source citations via a modular Express + LangChain backend.

Successfully developed a Multi-Domain AI Personal Assistant using LangChain, OpenAI, and Streamlit. The application seamlessly integrates multiple specialized capabilities, including document-based question answering (QA), Python code execution, debugging, explanation and optimization, web search, latest news retrieval, and currency conversion.

Multi-agent AI research system - Search, Reader, Writer & Critic agents collaborate to generate research reports

An exploration of the modern LangChain Expression Language (LCEL), showcasing how to build powerful AI workflows with Runnables for RAG, conditional logic, and more.

A repo for learning Generative AI

RAG-powered tourism guide for Colombia using LangChain, Gemini, and ChromaDB

A collection of basic code snippets and experiments created while learning Generative AI fundamentals.

A practical collection of LangChain chain implementations demonstrating how to orchestrate Large Language Models (LLMs) into structured workflows

A collection of practical examples demonstrating LangChain's Runnable architecture for building modular, scalable, and production-ready LLM applications.