Chat with AI in the terminal
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Updated
Nov 13, 2025 - Python
Chat with AI in the terminal
pg_timetable: Advanced scheduling for PostgreSQL
A utility for generating parsed, schema-annotated snapshots of Cosmos chain-registry data - including chains, assets, and IBC metadata - with both human-readable and minimized JSON formats.
Web3 Blockchain Explorer. Validator, Mining Pool, Token and Network Real-time Metrics. Interactive Onchain Dashboard
This code is part of my Ph.D. research. The objective is to test the best chosen hybrid partitions with silhouette coefficient. It's called HPML Clusters Chains because we chain the labels of each cluster with subsequent clusters. It is a version of HPML where there is only the external chaining.
5-72 is an ambitious open-source project aimed to involve novice musicians into the craft of sound engineering. Using the buses of world-famous artists as an example, we will show you what real music consists of. See, listen, create and evolve with us.
Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories.
This repository covers extensive tutorials on how to integrate LangSmith with LangChain with LangGraph to incorporate observability, monitoring, alerting, evaluation, etc. within complex LLM workflows and applications.
This is an End-to-End LangChain Study Ride to learn about all Framework tools. Motive to make to gain the more practical knowledge about all the algo and self study,
This repository contains practice implementations of different LangChain chains. Each file demonstrates how to structure and execute various types of chains in LangChain for building flexible AI workflows
Smart Quiz Generator is a Streamlit-based app that uses GPT-4 to create quizzes (MCQ, True/False, or Fill-in-the-Blank) from your own documents (PDF/TXT) or web pages. It processes content, stores it in a FAISS vector store for quick retrieval, and generates customized quizzes based on a chosen topic.
"My complete LangChain learning journey β from basics to advanced RAG, LCEL, LangGraph, LangServe, LangSmith with hands-on code examples."
My implementations for "AI for Developers" course assignments, in Python and JavaScript.
Explored the power of LangChain Expression Language (LCEL) ! Dived into LCEL enabled seamless chaining of components, making AI workflows more efficient. Learnt about Runnables, async operations, and how to implement streaming for real-time performance.
Python code for label clusters chains - multilabel classification
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