# Save Parallel Workflow Steps (/examples/components/workflows/save-parallel-steps) Demonstrates creating a workflow with parallel steps, saving it to the database, and loading it back. Apply the setup adjustment below before saving: the current source omits an explicit model on the research agents, so their tools are not serialized. Reloading executable tools also requires their toolkits in a `Registry`. ```python title="save_parallel_steps.py" """ Save Parallel Workflow Steps ============================ Demonstrates creating a workflow with parallel steps, saving it to the database, and loading it back. """ from agno.agent import Agent from agno.db.postgres import PostgresDb from agno.tools.hackernews import HackerNewsTools from agno.tools.websearch import WebSearchTools from agno.workflow.parallel import Parallel from agno.workflow.step import Step from agno.workflow.workflow import Workflow, get_workflow_by_id # --------------------------------------------------------------------------- # Setup # --------------------------------------------------------------------------- # Database db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai" db = PostgresDb(db_url=db_url) # --------------------------------------------------------------------------- # Create Agents # --------------------------------------------------------------------------- # Agents hackernews_researcher = Agent( name="HackerNews Researcher", instructions="Research tech news and trends from Hacker News", tools=[HackerNewsTools()], ) web_researcher = Agent( name="Web Researcher", instructions="Research general information from the web", tools=[WebSearchTools()], ) writer = Agent( name="Content Writer", instructions="Write well-structured content from research findings", ) reviewer = Agent( name="Content Reviewer", instructions="Review and improve the written content", ) # --------------------------------------------------------------------------- # Create Workflow Steps # --------------------------------------------------------------------------- # Steps research_hn_step = Step( name="ResearchHackerNews", description="Research tech news from Hacker News", agent=hackernews_researcher, ) research_web_step = Step( name="ResearchWeb", description="Research information from the web", agent=web_researcher, ) write_step = Step( name="WriteArticle", description="Write article from research findings", agent=writer, ) review_step = Step( name="ReviewArticle", description="Review and finalize the article", agent=reviewer, ) # --------------------------------------------------------------------------- # Create Workflow # --------------------------------------------------------------------------- # Workflow workflow = Workflow( name="Parallel Research Pipeline", description="Research from multiple sources in parallel, then write and review", steps=[ Parallel( research_hn_step, research_web_step, name="ParallelResearch", description="Run HackerNews and Web research in parallel", ), write_step, review_step, ], db=db, ) # --------------------------------------------------------------------------- # Run Workflow Example # --------------------------------------------------------------------------- if __name__ == "__main__": # Save print("Saving workflow...") version = workflow.save(db=db) print(f"Saved workflow as version {version}") # Load print("\nLoading workflow...") loaded_workflow = get_workflow_by_id(db=db, id="parallel-research-pipeline") if loaded_workflow: print("Workflow loaded successfully!") print(f" Name: {loaded_workflow.name}") print(f" Steps: {len(loaded_workflow.steps) if loaded_workflow.steps else 0}") # Uncomment to run the loaded workflow # loaded_workflow.print_response(input="Latest developments in AI agents", stream=True) else: print("Workflow not found") ``` ## Run the Example [#run-the-example] Mac Windows ```bash uv venv --python 3.12 source .venv/bin/activate ``` ```bash uv venv --python 3.12 .venv\Scripts\activate ``` ```bash uv pip install -U agno "psycopg[binary]" ddgs fastapi openai sqlalchemy ``` Mac/Linux Windows ```bash export OPENAI_API_KEY="your_openai_api_key_here" ``` ```bash $Env:OPENAI_API_KEY="your_openai_api_key_here" ``` macOS / Linux Windows ```bash docker run -d \ -e POSTGRES_DB=ai \ -e POSTGRES_USER=ai \ -e POSTGRES_PASSWORD=ai \ -e PGDATA=/var/lib/postgresql \ -v pgvolume:/var/lib/postgresql \ -p 5532:5432 \ --name pgvector \ agnohq/pgvector:18 ``` ```powershell docker run -d ` -e POSTGRES_DB=ai ` -e POSTGRES_USER=ai ` -e POSTGRES_PASSWORD=ai ` -e PGDATA=/var/lib/postgresql ` -v pgvolume:/var/lib/postgresql ` -p 5532:5432 ` --name pgvector ` agnohq/pgvector:18 ``` Add `from agno.models.openai import OpenAIResponses` to the imports. After constructing the agents and before `workflow.save(...)`, set their models: ```python hackernews_researcher.model = OpenAIResponses(id="gpt-5.6-luna") web_researcher.model = OpenAIResponses(id="gpt-5.6-luna") ``` Add `from agno.registry import Registry` and create this registry before loading: ```python registry = Registry(tools=[HackerNewsTools(), WebSearchTools()]) ``` Add `registry=registry, strict=True` to `get_workflow_by_id(...)`. Save again after these changes; loading an older config cannot recover tools it never stored. The script saves and reloads the configuration. Uncomment its final `loaded_workflow.print_response(...)` call to run the research workflow with real model and search requests. Save the code above as `save_parallel_steps.py`, then run: ```bash python save_parallel_steps.py ``` Full source: [cookbook/93\_components/workflows/save\_parallel\_steps.py](https://github.com/agno-agi/agno/blob/8f36eaf2d18e91afa7b327eec66a3cd3685dcb87/cookbook/93_components/workflows/save_parallel_steps.py)