“Data pipelines”

Data pipeline patterns: ingestion, ETL, serialisation, partitioned reads/writes, file conversion, parallel batch processing, Lambda-triggered ingestion.

Primary entry point for building, managing, and orchestrating data pipelines on Google Cloud.

Guide a developer through building a Solana data pipeline or indexer.

Universal data connector for CSV, Postgres, and REST APIs via DuckDB

Manage Jitsu data pipelines: destinations, streams, connections, functions, live events.

Darshan I/O profiler MCP server for analyzing I/O trace files

Python framework for live data processing and RAG pipelines that run on a Rust engine.

Microsoft Research pipeline that builds knowledge graphs from text to improve LLM question answering.

Durable orchestration for data, ML and agent workflows, written as Python functions.

Retrieve web pages for AI agents.

Personal agent on your own machine with file-based memory, a background consolidation engine and skills that are tested before use.

Measures and fixes how AI assistants and agents see a brand.

Framework for Python or Node.js programs that join LiveKit rooms as realtime voice and video agents.

Open-source Python framework for multi-agent systems: agent societies, memory, RAG, code interpreters, synthetic data and large-scale simulation.

Minimal Python graph framework of about 100 lines for LLM agents, workflows, RAG and map-reduce pipelines.

Open-source RAG engine under Apache-2.0 with a visual agent builder, hybrid search and a data ingestion pipeline

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