Results for “openai”

Delegate tasks to OpenAI Codex CLI and Google Antigravity CLI from Claude Code with topic-aware sessions.

Instrument LLM applications with Langfuse for tracing, prompt management, evaluation, and cost tracking, including integrations with OpenAI, LangChain, and LlamaIndex.

Scaffolds a new OpenAI Agents SDK agent with instructions, tools, API route, and bridge wiring, following existing project conventions.

Build cross-platform AI chat interfaces with Makepad using MolyKit, including async utilities, chat widgets, and OpenAI-compatible client integration.

Scaffold, build, and refactor ChatGPT Apps SDK projects with a docs-first workflow, combining MCP servers and widget UIs.

Creates or modifies OpenAI Agents SDK tools with Zod parameters, caching, metrics, and agent registration, following established patterns and best practices.

Build cross-platform AI chat interfaces with Makepad using MolyKit, covering async patterns, chat widgets, and OpenAI-compatible SSE streaming.

Creates or modifies agent tools for OpenAI Agents SDK, covering search, analysis, API integration, and database query patterns with caching and metrics.

Design multi-agent system architectures, generate tool schemas for Anthropic and OpenAI formats, and evaluate execution logs for cost, latency, and failure bottlenecks.

Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.

Scaffold and develop AI agents using OpenAI Agents SDK patterns, covering agent definition, tools, guardrails, handoffs, context, RAG pipelines, streaming, API routes, testing, and debugging.

Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.

Configures Rei Qwen3 Coder as a model provider, including setup, model switching, and troubleshooting 403 errors.

Debug and modify agent streaming behavior, covering SSE and plain-text transports, ChatKit events, and session continuity.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Navigate Oracle Cloud Infrastructure's Enterprise AI services: choose models, build agents with RAG and tools, estimate costs, secure access, and integrate with Oracle Database, APEX, and other platform services.

Build LLM-powered applications with agents, chains, and RAG using a framework that supports multiple providers and 500+ integrations.

Build or modify a RAG retrieval pipeline with vector store search, corpus routing, citation rendering, and book fidelity enforcement.

Builds or modifies a RAG pipeline with intent-based routing, vector store search, citation rendering, and book fidelity enforcement.

Build cross-platform AI chat interfaces with Makepad using MolyKit, covering async patterns, BotClient integration, and chat widgets.

Configures Rei Qwen3 Coder as a model provider for Clawdbot, including setup scripts, model switching, and troubleshooting 403 errors.

Create, run, and analyze evaluation suites for Microsoft 365 Copilot declarative agents using the @microsoft/m365-copilot-eval CLI.

Build cross-platform AI chat interfaces with Makepad using MolyKit, covering async patterns, chat widgets, and BotClient integration.

Build production-ready AI agents with type-safe tool use, structured outputs, dependency injection, and multi-model support using PydanticAI.

Build cross-platform AI chat interfaces with Makepad using MolyKit, covering async patterns, bot client integration, SSE streaming, and chat widgets.

Routes AI model requests to the optimal provider based on task, cost, latency, and capability requirements, managing multi-provider LLM deployments.

Build complex AI systems with declarative programming, optimize prompts automatically, and create modular RAG systems and agents using Stanford NLP's DSPy framework.

Configure Azure API Management as an AI Gateway to govern AI models, MCP tools, and agents with policies for caching, rate limiting, content safety, and cost control.

Adds input and output guardrails to an agent, including validation, content filtering, domain scoping, and rate limiting, with TypeScript examples and wiring instructions.

Configure tools and SDKs to route LLM requests through a single API key with native-compatible endpoints for Claude, GPT, and Gemini, including setup, base URLs, and code examples.