Results for “pipeline-generation”

Retrieval-Augmented Generation pipelines — ingestion, chunking, embedding, vector stores, retrieval, evaluation. Use when building a RAG pipeline, choosing chunking strategies or embedding models, debugging retrieval quality or hallucinations, evaluating an existing RAG system, or scaling/migrating vector stores.

Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.

Produces a complete narrated, subtitled, scored explainer video from a single topic prompt using a six-stage pipeline with script, voiceover, keyframes, animation, music, and local assembly.

Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.

AI 3D model generation agent. Generates text-to-3D and image-to-3D code (Python/JS/OpenSCAD) using Meshy, Tripo, Hunyuan3D, Rodin, Sloyd, and Stability APIs. Handles game pipeline integration, LOD, retopology, UV, and QC validation.

Generates and writes unit tests for any programming language using a multi-agent pipeline that researches, plans, and implements tests with build and verification steps.

Builds and validates DeepStream GStreamer pipelines through an interactive questionnaire and a BM25 retrieval engine over 270+ verified pipelines.

Proposal strategist and pipeline orchestrator — routes multimodal briefs through intake, research, pricing, and generation with guided check-ins or autonomous mode. Use when the user wants to run a full proposal pipeline, start a new proposal, resume an in-progress run, record win/loss outcomes, or get routed to the right proposal workflow. Triggers: 'run a proposal', 'proposal pipeline', 'start a new proposal', 'guided proposal mode', 'autonomous proposal', 'record proposal outcome', 're-price Acme brief', 'where is my proposal', 'proposal orchestrator'.

Detect stack and generate CI/CD pipeline configs. Usage: /pipeline <detect|generate> [options]

End-to-end source processing -- seed, reduce, process all claims through reflect/reweave/verify, archive. The full pipeline in one command. Triggers on "/pipeline", "/pipeline [file]", "process this end to end", "full pipeline".

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

Configurable pipeline orchestrator for sequencing stages

Import object detection models from HuggingFace or NVIDIA NGC into a DeepStream pipeline with automated ONNX download, TensorRT engine build, custom parser, multi-stream benchmark, and PDF report generation.

Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement.

Weekly pipeline health analysis with velocity metrics, stage distribution, forecasting, and actionable recommendations

Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.

Build and release pipeline for the Pump SDK — tsup TypeScript builds, Cargo release profiles, semantic release with commitizen, npm publishing, linting, Makefile targets, Vercel deployment, and MCP server distribution.

Designs and implements CI/CD pipelines, automating build, test, and deployment processes with security scanning and deployment strategies.

Coordinate multi-stage edge research pipelines from candidate detection through strategy design, review, revision, and export.

Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Design or repair a CI/CD pipeline with well-ordered parallel stages, lockfile-keyed caching, quality gates, and build-once artifact promotion.

Guides project-level decisions for LLM-powered systems: task-model fit, pipeline architecture, token and cost estimation, and agent-assisted iteration.

Revenue forecast from pipeline data with stage-weighted probability and sensitivity analysis

Weekly pipeline metrics, forecast, and trend dashboard in structured markdown

Defines a gated Research-Plan-TDD-Review-Commit pipeline for orchestrating feature development, defect fixes, and refactoring tasks through composable phases and human approval gates.

CI/CD Pipeline Builder

Guided webinar creation pipeline from vague idea to production-ready deliverables. Use when creating a webinar from scratch. Triggers: 'create a webinar', 'build a webinar', 'webinar creation', 'new webinar', 'help me make a webinar'.

Wire ETL, ingestion, cron, edge-function, and queue jobs correctly. Use for "build a pipeline", "sync X into Y", "nightly aggregation", "cron double-counts", "dedupe", "backfill", "the numbers are wrong after a retry". Bakes in idempotency, atomic writes, data contracts, dead-letter, and observability.

Identifies, assesses, and mitigates risks at every phase of a development pipeline.