Results for “build-pipeline”

Reference for building real-time voice and multimodal AI applications with Pipecat, covering pipelines, speech services, LLM integration, and transports.

Program LM pipelines with DSPy — define Signatures (input/output fields), build Modules (ChainOfThought, ReAct, Predict), compose them into Programs, then optimize with Teleprompters (BootstrapFewShot, MIPRO, COPRO) to auto-improve prompts from examples.

Build real-time voice and multimodal AI applications using Pipecat and Daily, covering pipeline architecture, AI service integration, and transport options.

Reference for building real-time voice and multimodal AI agents with Pipecat, covering pipelines, speech services, LLMs, transports, and deployment.

Designs and implements RAG pipelines, covering document chunking, embedding strategies, hybrid search, answer synthesis with source attribution, and evaluation using RAGAS metrics.

Reference for building real-time voice and multimodal AI applications with Daily and Pipecat, covering pipeline architecture, AI service integrations, transports, and client SDKs.

Reference for building real-time voice and multimodal AI applications with Pipecat, covering pipelines, speech services, LLMs, transports, and deployment.

Build conversational multi-agent systems with AutoGen (AG2) — define AssistantAgent and UserProxyAgent, set up GroupChat with GroupChatManager for round-robin or auto routing, enable code execution, and compose nested chats or sequential pipelines.

Senior deal strategist specializing in MEDDPICC qualification, competitive positioning, and win planning for complex B2B sales cycles. Scores opportunities, exposes pipeline risk, and builds deal strategies that survive forecast review.

Expert skill for building LLM applications with LangChain — LCEL chains, RAG pipelines, agent orchestration, LangGraph integration, LangSmith observability, and production deployment via LangServe. Use when working with LangChain or comparing LLM application frameworks.

Turn happy customers into references, case studies, and referrals, on purpose instead of by accident. Reads who is happy enough to ask, picks the right ask, sets the value exchange, and builds a pipeline of advocacy over time. Built for B2B customer success teams, customizable to your product and your program. Trigger on "build an advocacy program", "who can be a reference", "find case study candidates", "ask for a referral", "customer advocacy pipeline", or any reference-and-referral planning.

Consultative B2B sales outreach specialist for cold prospecting, lead follow-up, objection handling, proposal writing, and pipeline management — combining data-driven targeting with genuine relationship-building to open doors and close deals

Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.

Provides structured prompts for analyzing, planning, and executing .NET framework upgrades, covering project assessment, dependency management, code modernization, CI/CD updates, testing, and documentation.

Develops and debugs Apex code, builds Lightning Web Components, optimizes SOQL queries, and manages Salesforce DX deployments with CI/CD pipelines.

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

Orchestrate altering an existing, working feature to new desired behavior by updating tests first, then changing implementation, reviewing, and committing with gated approval.

Provides a reference for building real-time voice and multimodal AI agents with Pipecat, covering pipeline architecture, speech services, LLM integration, transports, and deployment.

Create a SAM.gov search monitor from a pursuit or expiring row — persists to Pipeline and writes sam_monitor.md in the pursuit folder. Primary admin rote task for capture managers watching recompetes.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Expert AI/ML engineer specializing in machine learning model development, deployment, and integration into production systems. Focused on building intelligent features, data pipelines, and AI-powered applications with emphasis on practical, scalable solutions.

Converting document formats (Markdown/Word/Excel/PDF/HTML). Converts specs from Scribe and reports from Harvest into distributable formats; generates reusable conversion scripts. Use when converting documents, building accessibility-compliant PDFs, or creating Pandoc/LibreOffice pipelines.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Runs a comprehensive verification pipeline for Quarkus projects including build, static analysis, tests with coverage, security scans, native compilation, and diff review before PRs or releases.

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.

Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.

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'.

Agent profile for handle CI/CD, environments, build pipelines, deployment topology, secrets, and operational readiness. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. Use when the user requests ci cd or provides relevant inputs for this workflow.

Expert skill for building LLM applications with the LlamaIndex framework — RAG pipelines, multi-agent orchestration, event-driven workflows, knowledge graph construction, production deployment, and evaluation. Use when working with LlamaIndex or comparing RAG and agent orchestration frameworks.

Python SDK for inference.sh - run AI apps, build agents, and integrate with 150+ models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python

Plan a field event, dinner, or conference presence that actually produces pipeline, not just badges scanned. It builds the right guest list, designs a draw worth showing up for, plans the on-site motion so conversations happen, and writes the follow-up that converts, because the pipeline is made after the event, not at it. Built for B2B field marketing and sales teams, customizable to your CRM and your event motion. Trigger on "plan a field event", "customer dinner plan", "conference presence", "how do I get pipeline from this event", "event guest list", "event follow-up plan", or any field-event or in-person pipeline request.

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end, covering processes, channels, operators, configuration, testing, and deployment to HPC or cloud.

Build lightweight AI agents with HuggingFace Smolagents — use CodeAgent (writes Python to act) or ToolCallingAgent (JSON tool calls), add built-in or custom Tools, orchestrate multi-agent pipelines with ManagedAgent, and run locally or via HF Inference API.

Automate continuous integration, deployment, and post-deployment verification of developed solutions. Use when setting up CI/CD pipelines, deploying to staging/production environments, running automated tests in CI, or verifying deployments. Ensures reproducible builds and reliable deployments.