LangChain Practice Tasks using FastAPI and LCEL
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Updated
Jun 26, 2026 - Python
LangChain Practice Tasks using FastAPI and LCEL
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
Production-ready AI Study Assistant built with LangChain, Google Gemini, RunnableParallel, RunnableBranch, and Streamlit. Generates notes, interview questions, answers, and sentiment-based feedback.
LLM-powered search router that chooses direct answers or live web retrieval, returning concise, validated responses with optional source citations via a modular Express + LangChain backend.
Successfully developed a Multi-Domain AI Personal Assistant using LangChain, OpenAI, and Streamlit. The application seamlessly integrates multiple specialized capabilities, including document-based question answering (QA), Python code execution, debugging, explanation and optimization, web search, latest news retrieval, and currency conversion.
A practical collection of LangChain chain implementations demonstrating how to orchestrate Large Language Models (LLMs) into structured workflows
A collection of practical examples demonstrating LangChain's Runnable architecture for building modular, scalable, and production-ready LLM applications.
A collection of basic code snippets and experiments created while learning Generative AI fundamentals.
RAG-powered tourism guide for Colombia using LangChain, Gemini, and ChromaDB
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