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agenticx-quickstartlisted

AgenticX zero-to-hero quickstart guide. Use when the user wants to get started with AgenticX, create their first project, build their first agent, or run their first workflow. Covers installation, project scaffolding, agent creation, task execution, and CLI basics.
opencue/cue · ★ 1 · AI & Automation · score 77
Install: claude install-skill opencue/cue
# AgenticX Quickstart Guide for getting a user from zero to a running AgenticX agent in under 5 minutes. ## Installation ```bash # Core install (lightweight, ~27 deps, installs in seconds) pip install agenticx # Verify agx --version ``` Optional extras — install only what you need: | Extra | What it adds | Command | |-------|-------------|---------| | `memory` | Mem0, ChromaDB, Qdrant | `pip install "agenticx[memory]"` | | `document` | PDF/PPT/Word parsing | `pip install "agenticx[document]"` | | `server` | API server (`agx serve`) | `pip install "agenticx[server]"` | | `volcengine` | Volcengine AgentKit | `pip install "agenticx[volcengine]"` | | `all` | Everything | `pip install "agenticx[all]"` | ## Environment ```bash export OPENAI_API_KEY="sk-..." # Optional export ANTHROPIC_API_KEY="sk-ant-..." ``` ## Create a Project ```bash agx project create my-first-agent --template basic cd my-first-agent agx project info ``` ## Create Your First Agent (Python) ```python from agenticx import Agent, Task, AgentExecutor from agenticx.llms import OpenAIProvider agent = Agent( id="data-analyst", name="Data Analyst", role="Data Analysis Expert", goal="Help users analyze and understand data", organization_id="my-org" ) task = Task( id="analysis-task", description="Analyze sales data trends", expected_output="Detailed analysis report" ) llm = OpenAIProvider(model="gpt-4") executor = AgentExecutor(agent=agent, llm=llm) result = executor.run(tas