lcel

Accelerate your Gen AI with NVIDIA NIM and NVIDIA AI Workbench

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.

AI developer that generates LangChain Expression Language code

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.

The easiest way to supercharge your apps with LLM!

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.

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

从 0 到迷你 Claude Code 的 LangChain Agent 学习仓库：LCEL · 记忆 · RAG · LangGraph · 自制 Agent Harness，全部可独立运行、默认走 OpenAI 兼容协议。

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

End-to-end implementation of LangChain Runnables and LCEL with modular Python code, best practices, and real-world examples for building production-ready LLM applications.

CyberSoft Gen AI 01 - 3

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

Enterprise-grade RAG Engine with Persistent Memory. Powered by Llama 3.3 and pure LCEL architecture for seamless corporate automation.

Translation REST API in Python: FastAPI + LangServe serving a LangChain LCEL chain (prompt|model|parser) on Groq Gemma2-9b-It; 9 pytest tests + GitHub Actions CI. Measured probe: 143 tokens end-to-end in 0.226s (LLM 224ms), EN->Kannada.