Adhoc showcase using LangChain

以Langchain, Faiss, Langchain serve 建立基於向量搜索的商品推薦聊天機器人

your personal research assistant!

This project aims to empower diabetic patients with a patient-centric care solution using conversational agents and generative AI. It delivers personalized support, accessible education for better diabetes management.

Deploying a LangChain application on AWS with LangServe

Chat with the ChatGPT to change the state and color of the lock.

LCEL Langchain Tutorial

Your personal assistant on structure data!

Scripts for testing LangChain functionalities

This repository features a Streamlit app for translating text using the GROQ API, offering both formal and informal styles. It also includes a FastAPI server for efficient translation requests. Enhance your language translation experience!

Chat with an AI version of me, Alvin.

Chatbot capable of answering questions about the company Promptior

LLM Agent with access to multiple tools. Ask for information about the weather, current events, YouTube links, math questions or itself. Acts as Romeo from Romeo and Juliet.

BankLLM is an AI-driven recommendation engine for banking, using OpenAI's models to analyze customer data and generate personalized product suggestions. It integrates LangChain, FAISS, and LangServe, with a FastAPI backend and Streamlit frontend, following an LLMOps approach for scalable deployment.

A starter repo on how to create your first simple LLM application using LangChain

The project is a LangChain-based demo application integrated with Google's Gemini API, built using the Streamlit framework. It allows users to input a query or search topic through a text box, which is processed by a language model to generate helpful responses.

[📚] Continuously learning and practicing concepts from Langchain + LLMs.

Get started with LangChain Agents, part of the zero-to-hero series

Gpt-recruit.com is a service that allows users to inquire about registered job postings and generate cover letters through an AI chatbot.

This repository explores the full potential of Langchain-based Large Language Models (LLMs). It covers deployment using Langserve and FastAPI, fine-tuning techniques, integration methods, and API usage with interactive documentation. Ideal for developers looking to implement scalable, efficient LLMs in real-world applications.