453 tagged Data and AI, measured the same way as everything else here.
Browse within: cursor 55cursorrules 32chatgpt 23product-management 22skills 22LLM 20awesome-list 17agentic-ai 15awesome 15cursor-rules 15cursor-ai-editor 14agent 11ai-coding 11agents 10
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Below is an example TypeScript/Node.js folder structure replicating the Python package's layout. Each subfolder matches the Python counterpart (agent, agents, knowledge, etc.). All "LLM" or "litellm" references are replaced by aisdk usage.
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A service for importing and exporting Telegram messages in a database, with text search and meaning-based search. Meaning-based search uses OpenAI-generated text vectors to find related messages.
sanjeed5/awesome-cursor-rules-mdc
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Definitive guidelines for writing robust, performant, and maintainable llamaindex-js applications using modern TypeScript best practices.
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Use it when user asks about adding instrumentation with Laminar, creating an eval with Laminar or migrating from Langfuse to Laminar instrumentation.
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A set of rules for setting up BAML and help with syntax guidance.
Bhartendu-Kumar/rules_template
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Cursor rule "pytorch" from Bhartendu-Kumar/rules_template, covering pytorch best practices and coding standards, 1. code organization and structure, 1.1 directory structure best practices, 1.2 file naming conventions and 1.3 module organization.
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Kandev harness routing for skills, the single-session model workflow, and spec-driven work.
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Core principles for LMForge - production-grade LLMOps platform.
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Cursor rule "fenic" from typedef-ai/fenic, covering writing fenic, must-knows and traps fenic check can't catch — get these right by hand.
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The gateway core module is the central orchestrator that handles AI provider requests, manages caching, queuing, and provides unified interfaces for chat completion, embeddings, and tool responses.
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We are building an LLM powered AI data analyst for Data Engineering teams that work with dbt to manage their analytics code bases. To use this project, users should be able to connect with their dbt cloud projects or their dbt core github repos via an interface which is then used to build a knowlege base. We then use…
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Use MCP server to discover schema and get sample data. All analysis, data aggregations and queries should be done in the notebooks so they can be shared across my team.
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A guide for configuring and using MCP data tools. MCP is a way for an AI assistant to connect to external tools and data sources, such as research databases, financial data, and web search.
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Omni-Rewriter prompt-expansion framework conventions.
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This repository aggregates knowledge from various sources for RAG systems. See the main README.md for a full overview.
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This document provides a comprehensive guide to all input types available in Langflow. Each input type is designed for specific use cases and data formats.
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Openground is a tool for extracting framework and library documentation from official sources (sitemaps and git repos) and making it queryable by AI coding agents. It consists of.
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Backend development rules for TT Studio - AI model management backend.
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Kumo Coding Agent — ML predictions on relational data using KumoRFM.
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You are an expert in SQL and Tinybird. Follow these instructions when working with .datasource and .pipe files.
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Rules for /promptengineer command - Prompt Engineer behavior and LangGPT format.
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When we are creating prompts that will be used by an LLM for agents.
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Klore LLM Knowledge Compiler — available commands and context.
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Canonical = OpenAI shape; each non-OpenAI adapter owns its bidirectional translation (8 binding rules from provider-adapter-architecture.md §3a).
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: