DiPeO, Diagrammed People (agents) & Organizations (agent system)

• The whole codebase was created by vibe-coding, with Claude code & Codex.

Start with dipeo ask --to "the command you want to ask" --and-run

• This will generate diagram and run it as you want to create.

Why diagram?

• To show how it is structured, and how it works in realtime.
• For consistent outputs, rather than asking to code.

Hmm, so can I tweak it?

• Definitely. You can just run make dev-web and tweak it in localhost:3000
• The whole procedure works inside your computer. Nothing is in cloud or somewhere in network.

How about the diagram file?

• You can see the diagram file in .yaml

The diagram file content we created looks like...

version: light
nodes:
- label: start
  type: start
  position:
    x: 330
    y: 200
  trigger_mode: manual
- label: printer
  type: person_job
  position:
    x: 632
    y: 231
  default_prompt: say hi
  max_iteration: 3
  memorize_to: ALL_MESSAGES
  person: person 1
- label: endpoint
  type: endpoint
  position:
    x: 0
    y: 437
  file_format: txt
  save_to_file: true
  file_path: files/results/total.txt
connections:
- from: start
  to: printer
  content_type: raw_text
- from: printer
  to: endpoint
  content_type: raw_text
persons:
  person 1:
    service: openai
    model: gpt-5-nano-2025-08-07
    api_key_id: APIKEY_52609F

• For example, the diagram you generated with dipeo ask ... will be placed in projects/dipeodipeo/generated
• We support .light.yaml format which will format the diagram in readable format.

How can I start?

# Clone the repository first
make install          # Install all dependencies (installs uv if needed)
make graphql-schema   # Generate GraphQL types
make dev-all          # Start both frontend and backend servers

Ok. So is there a rule for diagram? Or, would you explain more detail?

• Yes, here is the documentary in detail.
  • Full Documentation Index - Complete list of guides and technical documentation
  • User Guide - Getting started with DiPeO diagram editor
  • We are developing some interesting projects using dipeo itself. Take a look at projects

---

DiPeO(daɪpiːɔː) is a monorepo for building, executing, and monitoring AI‑powered agent workflows through an intuitive visual programming environment. The repository is composed of a feature-based React frontend (apps/web/), a domain-driven FastAPI backend (apps/server/), and a CLI tool (apps/server/src/dipeo_server/cli/) that work together to deliver real‑time, multi‑LLM automation at scale.

핵심 기능

1. LLM과 작업 블록의 분리를 통한 직관적인 컨텍스트 관리
2. diagram의 yaml 형태 표현 및 실행 tool 제공
3. 다이어그램 엔드포인트를 활용한 A2A canvas 제공 (구현 예정)

For motivations, guide, details in Korean, read Korean docs

Code Generation (For Development)

If you need to modify the codebase or add new features:

# After modifying TypeScript specifications in /dipeo/models/src/
cd dipeo/models && pnpm build     # Build TypeScript models
make codegen                      # Generate code (includes parse-typescript)
make diff-staged                  # Review changes
make apply-syntax-only            # Apply staged changes
make graphql-schema              # Update GraphQL types

Major Features

1. Claude Code Integration

DiPeO features built-in support for Anthropic's Claude Code SDK, enabling seamless integration with Claude's advanced AI capabilities. Simply configure your diagram with Claude Code agents:

persons:
  Frontend Generator:
    service: claude-code
    model: claude-code
    api_key_id: APIKEY_CLAUDE
    system_prompt: |
        You are an expert React/TypeScript engineer.
        Generate clean, production-ready code.

Key Benefits:

• Streaming-first architecture for real-time responses
• Built-in conversation management
• Automatic retry logic with exponential backoff
• Context manager pattern for efficient resource usage

For detailed setup and usage, see Claude Code Integration Guide.

2. Frontend Auto - Rapid Application Generation

Generate complete, production-ready React applications in 30 minutes with Frontend Auto. This streamlined system creates fully deployable frontends with modern tech stack:

# Generate a complete chat application
dipeo run projects/frontend_auto/consolidated_generator --light --debug --timeout=120

# Generate with specific variant (e.g., e-commerce, analytics, banking)
dipeo run projects/frontend_auto/consolidated_generator --light --debug --timeout=120 \
  --input-data '{"config_file": "variants/ecommerce_config.json"}'

Generated Features:

• React 18 + TypeScript + Vite
• Tailwind CSS styling
• TanStack Query for data fetching
• React Router v6 navigation
• Complete component architecture (atoms/molecules/organisms)
• Mock API with real-time features
• Vercel-ready deployment configuration

Available Variants: Chat applications, e-commerce stores, analytics dashboards, banking portals, CMS systems, healthcare portals, learning platforms, project management tools, and more.

For comprehensive details, see the Frontend Auto project files in projects/frontend_auto/.

3. Multi-LLM Support

Beyond Claude Code, DiPeO supports multiple LLM providers:

Ollama (Local Models):

persons:
  Frontend Generator:
    service: ollama
    model: gpt-oss:20b
    api_key_id: APIKEY_OLLAMA
    system_prompt: |
        You are an expert React/TypeScript engineer.
        Generate clean, production-ready code.

Custom APIs and Services:

• Notion integration
• Custom LLM endpoints via cURL
• Any RESTful API service

Thanks to our schema-driven integration system, adding new external API features is straightforward. See integrations/ directory for examples.

For local model examples, see Ollama example.

dipeo - Run Diagrams with CLI

Run existing diagrams

# Run diagram with automatic server startup
dipeo run examples/simple_diagrams/simple_iter --light --debug --timeout=25
# Run with specific diagram file
dipeo run examples/simple_diagrams/simple_iter.light.yaml --light --debug
# Run with input data
dipeo run [diagram] --input-data '{"key": "value"}' --light --debug

Generate diagrams from natural language

# Generate a diagram from natural language request
dipeo ask --to "create csv preprocessor" --timeout=90

# Generate and immediately run the created diagram
dipeo ask --to "create csv preprocessor" --and-run --timeout=90

# With additional options
dipeo ask --to "build data pipeline" --and-run --timeout=120

Note: The dipeo ask command uses AI to generate DiPeO diagrams from your natural language description. Generation typically takes 150-250 seconds due to multiple LLM calls.

Convert Claude Code Sessions to Diagrams

# List your recent Claude Code sessions
dipeocc list --limit 50

# Convert the latest session to a DiPeO diagram
dipeocc convert --latest

# Convert a specific session by ID
dipeocc convert <session_id> --output-dir projects/claude_code/

# Watch for new sessions and auto-convert them
dipeocc watch --interval 30 --auto-execute

# View session statistics
dipeocc stats <session_id>

Options:

• --format: Output format (light/native/readable, default: light)
• --merge-reads: Combine consecutive file reads into single nodes
• --simplify: Remove intermediate results for cleaner diagrams

This feature enables you to automatically transform your Claude Code interactions into reusable DiPeO diagrams, making your AI workflows reproducible and shareable.

Export Diagrams to Standalone Python Scripts

# Export a diagram to a Python script that runs without DiPeO
dipeo export examples/simple_diagrams/simple_iter.light.yaml output.py --light

# Run the exported script directly
python output.py

Supported Features:

• LLM calls (person_job nodes) → Direct OpenAI/Anthropic API calls
• Database operations → File I/O
• Code execution → Inline Python
• Control flow → Native Python structures

The exported scripts are self-contained and only require Python 3.10+ and the openai/anthropic packages. Perfect for deploying DiPeO workflows as standalone applications.

For detailed usage and examples, see Diagram-to-Python Export Guide.

Requirements

• Python 3.13+ (required for uv support)
• Node.js 22+ with pnpm 10+ (not npm/yarn)
• uv package manager (auto-installed via make install)
• Default LLM: gpt-5-nano-2025-08-07