Commands Cheat Sheet

All essential commands for AI development tools.

Claude Code

Starting & Modes

claude                              # Start Claude Code
claude --dangerously-skip-permissions  # YOLO mode (auto-accept)

In-Session Commands

Command	Description
/clear	Start new conversation
/compact	Summarize and continue
/init	Generate claude.md file
/help	Show help

Keyboard Shortcuts

Key	Action
Shift+Tab	Cycle through modes
Ctrl+R	View context summary
Escape	Stop current operation
Enter	Submit prompt

Modes

1. Default - Asks permission for changes
2. Auto-accept - Approves changes automatically
3. Planning - Research only, no file changes

FlowiseAI

Installation & Running

# Quick start
npx flowise start

# Custom port
npx flowise start -p 3001

# With persistent data
npx flowise start --FLOWISE_SECRETKEY="your-secret"

Docker

docker run -d -p 3000:3000 flowiseai/flowise

Key Concepts

• Chatflows - Conversation-based AI apps
• Agentflows - Multi-step agent workflows
• Tools - Functions agents can use
• Memory - Conversation history storage
• Vector Stores - Document embeddings storage

n8n

Installation & Running

# Quick start
npx n8n

# With tunnel (for webhooks)
n8n start --tunnel

# Docker
docker run -it --rm -p 5678:5678 n8nio/n8n

Key Nodes

Node Type	Purpose
Trigger	Start workflows
HTTP Request	API calls
AI Agent	LLM interactions
Code	Custom JavaScript
Split in Batches	Process items

Ollama

Basic Commands

# Run a model
ollama run llama3

# List models
ollama list

# Pull a model
ollama pull mistral

# Remove a model
ollama rm modelname

Popular Models

Model	Best For
llama3	General purpose
mistral	Efficient, fast
codellama	Code generation
deepseek-coder	Coding tasks

OpenAI API

Python

from openai import OpenAI
client = OpenAI()

response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)

JavaScript

import OpenAI from 'openai';
const openai = new OpenAI();

const response = await openai.chat.completions.create({
    model: "gpt-4",
    messages: [{ role: "user", content: "Hello!" }]
});

LangChain

Python Setup

from langchain_openai import ChatOpenAI
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate

llm = ChatOpenAI(model="gpt-4")
prompt = PromptTemplate.from_template("Tell me about {topic}")
chain = LLMChain(llm=llm, prompt=prompt)

JavaScript Setup

import { ChatOpenAI } from "@langchain/openai";
import { PromptTemplate } from "@langchain/core/prompts";

const llm = new ChatOpenAI({ modelName: "gpt-4" });
const prompt = PromptTemplate.fromTemplate("Tell me about {topic}");