This code is an implementation of a chatbot using LLM chat model API and Langchain.

ITC Financial AI Analyzer using ai scraping and LLM Integration

Hands-on Lang Chain 2.x runnable demo: generate tweet + LinkedIn post in parallel, with ASCII chain graph.

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

A collection of runnable examples using LangChain and Groq LLMs, demonstrating different AI workflow patterns like sequence, parallel, branch, passthrough, and lambda operations. Perfect for learning modular AI development with LLMs.

A collection of LangChain chain examples — Simple, Sequential, Parallel, and Conditional — showcasing how to build flexible, modular AI workflows. Includes runnable code to help you design efficient and dynamic LLM-powered applications.

This repository showcases Python scripts demonstrating interactions with various models using the LangChain library. From fine-tuning to custom runnables, explore examples with Gemini, Hugging Face, and Mistral AI models.

This repository demonstrates how to use Chains in LangChain to build modular AI pipelines.

A python library implementing a family of Runnables in langchain

Open-source LangChain toolkit with custom Chains, ChatModels, Embeddings, and Output Parsers. Build powerful AI workflows effortlessly. Perfect for developers and businesses leveraging LLMs.

Gen AI with framework Langchain

This project is a modular LangChain-based application that demonstrates how to build, organize, and run LLM-powered systems using modern AI engineering practices. It covers the full pipeline—from LLM and chat models to embeddings, chains, prompts, and Retrieval-Augmented Generation (RAG)—all organized in a clear and scalable folder structure.