Abstract low-level LLM provider APIs and streaming logic for Python applications.
npx skills add https://github.com/vercel-labs/ai-python --skill ai-vercel-labs
Please help me install this Agent Skill. Skill: ai Source: https://github.com/vercel-labs/ai-python/tree/main/skills/ai Command: npx skills add https://github.com/vercel-labs/ai-python --skill ai-vercel-labs
This Skill eliminates the complexity of manually integrating LLM provider APIs, handling async streaming, managing agent loops, and executing custom tools when building LLM-powered applications in Python.
Use the ai skill to build an async weather assistant agent that streams real-time responses and executes custom tool calls for city weather lookups.
High-intent search queries and answers about installing and using this skill.
Build autonomous agents in Python by abstracting low-level LLM provider API integrations and streaming logic. This Skill handles agent orchestration, custom async tool execution, and message history management for multi-step workflows.
Generate structured Pydantic output from LLM calls using built-in validation features. This allows direct data extraction and automated reporting by returning validated Python objects instead of raw text responses.
Yes, it supports OpenAI, Anthropic, and AI Gateway integrations. It uses lazy loading of official SDKs for provider-agnostic model routing, allowing you to switch LLM providers without rewriting core logic.
Yes, you can use async context manager-based streaming for real-time responses. The framework includes built-in event handling for tool calls, hooks, and partial results during media generation and agent loops.
Manage multi-agent orchestration and hook-based approvals by utilizing the built-in event streaming and async context managers. This handles message routing and workflow approvals across multiple autonomous agents.
Yes, it supports text, image, and video media generation directly from LLM calls. This enables content creation and automated reporting workflows alongside structured output generation and tool execution.
juanreSwitch between LLM providers and access raw SDKs via get_provider().
AnandaAnugrahHandyantoConvert unstructured LLM outputs into validated Pydantic schema data.
NicolaiLassenConvert LlmAgent model responses into validated Pydantic objects using output_schema.
Razaib-khanBuild OpenAI Agents SDK agents with tools, guardrails, and streaming.
