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

An AI developer that writes LangChain Expression Language (LCEL).

You’ll explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

The easiest way to supercharge your apps with LLM!

The "lcel-tutorial" repo is designed for mastering LangChain Expression Language (LCEL), offering exercises to build stateful, multi-actor LLM applications. It's a hands-on guide to leveraging LCEL for complex workflows and agent-like behaviors. Perfect for enthusiasts eager to explore LLM's potential.

Explore Functions, Tools and Agents with LangChain along with LangChain Expression Language

A collection of Jupyter notebook experiments and applications centered around Generative AI with LLMs.

Practical notebooks to learn LangChain fundamentals — LCEL, prompt templates, RAG and vector stores — with modern, non-deprecated examples.

Step-by-step LangChain-based LLM implementations and experiments

向量化、RAG增强、智能体Agent、LangChain LCEL 管道组合等等。持续更新...

A LangChain-based chat application running Llama 3 locally via Ollama, featuring a modern Streamlit chat UI and LCEL pipeline.

This is a simple application of the LLM (Lattice Conditional Execution Language) with the LCEL (Lattice Conditional Execution Language) library. The application is a simple calculator that can perform addition, subtraction, multiplication, and division.

This Conversational Q&A Chatbot is a Generative AI project built using LangChain. It enhances user interactions by maintaining memory of past exchanges, allowing for more context-aware responses.

A conversational chatbot built with Groq Llama 3.1 and LangChain, featuring multi-session memory and context-aware responses.

A fast multilingual translator built using Groq Llama 3.1 and LangChain with dynamic prompts and LCEL chaining.

DataWizard: AI-Powered Data Analysis

A hands-on lab exploring LangChain Expression Language (LCEL) and LangGraph for building stateful, composable, and production-oriented AI workflows. Covers prompt pipelines, structured outputs, conversational memory, routing logic, and graph-based orchestration.

This is an AI-powered Streamlit chatbot that answers user questions about bank loan or insurance policy documents (PDFs). It uses LangChain, FAISS, and Ollama LLM running locally with Cloudflare to provide public access.

Foundations of LLM orchestration using the LangChain framework for the Enterprise Architecture (AREP) course at Escuela Colombiana de Ingeniería Julio Garavito. This project implements LangChain Expression Language (LCEL) chains, dynamic prompt templates, and multi-purpose AI demonstrators powered by Groq's LPU inference engine for high-performance