⛓️ build cognitive systems, pythonic
This AI Smart Speaker uses speech recognition, TTS (text-to-speech), and STT (speech-to-text) to enable voice and vision-driven conversations, with additional web search capabilities via OpenAI and Langchain agents.
Documentation for langsmith
Interactive notes (Jupyter Notebooks) for building AI-powered applications
Hosting Langfuse on Amazon ECS with Fargate using CDK Python
Learn AI, ML, and NLP with interactive Jupyter Notebook tutorials.
Reddit AI Agent is a smart Reddit assistant that lets you search for any query, fetching top Reddit threads along with their most relevant comments. It provides three core features: retrieving top threads, summarizing threads and comments for quick insights, and enabling a conversational chat feature powered by Retrieval-Augmented Generation (RAG)
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 Yahoo Finance Agent is an application that combines OpenAI's LLMs, the Yahoo Finance Python library, and LangChain's tools to provide real-time financial data. It features stock information, financial statements, and an interactive chat interface, all while maintaining conversation context and integrating with Langsmith for debugging
Building a multi-agent RAG system with advanced RAG methods
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.
An innovative application designed to help pharmacists and pharmacy students quickly research FDA-approved drugs by retrieving relevant information from drug labels and adverse event datasets, and providing AI-generated summaries to streamline the learning process
ChatPDF leverages Retrieval Augmented Generation (RAG) to let users chat with their PDF documents using natural language. Simply upload a PDF, and interactively query its content with ease. Perfect for extracting information, summarizing text, and enhancing document accessibility.
Trainer AI is an LLM assistant agent with the goal of helping you workout more efficiently, and spend less time preparing workout sets, and analyzing data. You talk to it like a personal coach, and it records your efforts, and lays plans for you to reach your goals.
"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.
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