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LCEL Langchain Tutorial
Scripts for testing LangChain functionalities
ATS is a web application where the user on uploading the resume and the Job Description can get the percentage match of the job and their strength and weakness in the resume
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.
Discover LangSmith: Your gateway to crafting production-grade LLM (Large Language Model) applications with ease. Dive into a world of innovation and efficiency as LangSmith empowers you to create sophisticated language-driven solutions effortlessly.
LangChain agent that given a name, searches in google to find Linkedin and Twitter profiles, scrape the internet for information about a name you provide and generate a couple of personalized ice breakers to kick off a conversation with the person.
Simple LangChain app used to demo LangSmith
Exploring SOTA Advanced RAG techniques: This project implements a self reflective RAG, seamlessly integrating multiple knowledge sources (website, SQL, PDFs) while meticulously aligning with business requirements.
Redis Database offers unique capability to keep your data fresh while serving through LLM chatbot
"Chat with Databases using RAG" is a cutting-edge project that seamlessly integrates natural language inputs with database interactions. By leveraging advanced techniques like RAG and few-shot learning, it generates SQL queries from plain text and retrieves human-like responses from the database, revolutionizing the way we interact with data.
Ice Breaker is comprehensive fullstack app leveraging generative AI and LangChain to find LinkedIn profiles and generate engaging ice breakers. LangChain ReAct agents ensure accurate URL retrieval and JSON cleaning, identifying a summary, facts, topics, and ice breakers. The frontend is built with HTML/CSS, and Flask powers the backend development.
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