Skip to main content

A modular framework for designing and orchestrating complex agentic workflows with ease.

Project description

Modular Agent Designer

Declarative YAML → Google ADK workflow compiler. Define agents, tools, models, and graph topology in a single YAML file — no Python code required.

pip install modular-agent-designer

Note: google-adk is currently in beta — install with --prerelease=allow when using uv.


Quickstart

# Scaffold a new agent project
uv run modular-agent-designer create my_agent

# Run it
uv run modular-agent-designer run my_agent/my_agent.yaml --input '{"message": "hello"}'

What a workflow looks like

name: research_assistant

models:
  local:
    provider: ollama
    model: ollama_chat/gemma4:e4b

tools:
  web:
    type: builtin
    name: fetch_url

agents:
  researcher:
    model: local
    tools: [web]
    instruction: "Research {{state.topic}} and summarize your findings."

  writer:
    model: local
    instruction: "Write a short article based on: {{state.researcher}}"

workflow:
  nodes: [researcher, writer]
  edges:
    - from: researcher
      to: writer
uv run modular-agent-designer run research.yaml --input '{"topic": "quantum computing"}'

Key features

Feature Details
Multi-provider models Anthropic, Google Gemini, OpenAI, Ollama — all via LiteLLM
Tools Builtin callables, arbitrary Python functions, MCP servers (stdio / SSE / HTTP)
Routing Conditional edges, default fallback, self-loops, parallel fan-out with join barriers
State templating {{state.key}} in prompts resolved at runtime
Structured output Per-agent Pydantic output_schema
Thinking/reasoning Anthropic extended-thinking, OpenAI reasoning effort, Gemini thinking budget
Retries Per-agent fixed or exponential backoff
Observability Optional MLflow / OTLP tracing via --mlflow
Escape hatch Drop in custom BaseNode subclasses for non-LLM logic

Supported model providers

model: anthropic/claude-sonnet-4-6    # Anthropic — ANTHROPIC_API_KEY
model: gemini/gemini-2.5-pro          # Google    — GOOGLE_API_KEY
model: openai/gpt-4o                  # OpenAI    — OPENAI_API_KEY
model: ollama_chat/gemma3             # Ollama    — OLLAMA_API_BASE (default: localhost:11434)

Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

modular_agent_designer-0.7.1.tar.gz (489.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

modular_agent_designer-0.7.1-py3-none-any.whl (45.3 kB view details)

Uploaded Python 3

File details

Details for the file modular_agent_designer-0.7.1.tar.gz.

File metadata

  • Download URL: modular_agent_designer-0.7.1.tar.gz
  • Upload date:
  • Size: 489.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for modular_agent_designer-0.7.1.tar.gz
Algorithm Hash digest
SHA256 a4c45b4d4ed2b73f706eadb115fe64afa606476d882513588bfda491874c7408
MD5 7ced59a2d328e6c7668878ac4073e15c
BLAKE2b-256 b49c23256cf14771989f25777e3ca013085ce9117d5ad0dbe6023fbe5851901e

See more details on using hashes here.

File details

Details for the file modular_agent_designer-0.7.1-py3-none-any.whl.

File metadata

File hashes

Hashes for modular_agent_designer-0.7.1-py3-none-any.whl
Algorithm Hash digest
SHA256 537992ffb7e5066d8ff863632aa6e4d19995804b9073b9f2cc887b886b295077
MD5 1d2cc558bb8fb0d0456a146d8de1d9d4
BLAKE2b-256 62b922cc2c216db93c363010ed4b1c4a6655ffbc99ca369dcfcf168ec1f2c562

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page