> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2-service-account.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Sequential Workflow - Stock Research Pipeline > Create a workflow with sequential steps. Create a workflow with sequential steps. Each step is handled by a specialized agent, and outputs flow to the next step. ```python sequential_workflow.py theme={null} """ Sequential Workflow - Stock Research Pipeline ============================================== This example shows how to create a workflow with sequential steps. Each step is handled by a specialized agent, and outputs flow to the next step. Different from Teams (agents collaborate dynamically), Workflows give you explicit control over execution order and data flow. Key concepts: - Workflow: Orchestrates a sequence of steps - Step: Wraps an agent with a specific task - Steps execute in order, each building on the previous Example prompts to try: - "Analyze NVDA" - "Research Tesla for investment" - "Give me a report on Apple" """ from agno.agent import Agent from agno.db.sqlite import SqliteDb from agno.models.google import Gemini from agno.tools.yfinance import YFinanceTools from agno.workflow import Step, Workflow # --------------------------------------------------------------------------- # Storage Configuration # --------------------------------------------------------------------------- workflow_db = SqliteDb(db_file="tmp/agents.db") # --------------------------------------------------------------------------- # Step 1: Data Gatherer — Fetches raw market data # --------------------------------------------------------------------------- data_agent = Agent( name="Data Gatherer", model=Gemini(id="gemini-3.5-flash"), tools=[YFinanceTools(all=True)], instructions="""\ You are a data gathering agent. Your job is to fetch comprehensive market data. For the requested stock, gather: - Current price and daily change - Market cap and volume - P/E ratio, EPS, and other key ratios - 52-week high and low - Recent price trends Present the raw data clearly. Don't analyze — just gather and organize.\ """, db=workflow_db, add_datetime_to_context=True, add_history_to_context=True, num_history_runs=5, ) data_step = Step( name="Data Gathering", agent=data_agent, description="Fetch comprehensive market data for the stock", ) # --------------------------------------------------------------------------- # Step 2: Analyst — Interprets the data # --------------------------------------------------------------------------- analyst_agent = Agent( name="Analyst", model=Gemini(id="gemini-3.5-flash"), instructions="""\ You are a financial analyst. You receive raw market data from the data team. Your job is to: - Interpret the key metrics (is the P/E high or low for this sector?) - Identify strengths and weaknesses - Note any red flags or positive signals - Compare to typical industry benchmarks Provide analysis, not recommendations. Be objective and data-driven.\ """, db=workflow_db, add_datetime_to_context=True, add_history_to_context=True, num_history_runs=5, ) analysis_step = Step( name="Analysis", agent=analyst_agent, description="Analyze the market data and identify key insights", ) # --------------------------------------------------------------------------- # Step 3: Report Writer — Produces final output # --------------------------------------------------------------------------- report_agent = Agent( name="Report Writer", model=Gemini(id="gemini-3.5-flash"), instructions="""\ You are a report writer. You receive analysis from the research team. Your job is to: - Synthesize the analysis into a clear investment brief - Lead with a one-line summary - Include a recommendation (Buy/Hold/Sell) with rationale - Keep it concise — max 200 words - End with key metrics in a small table Write for a busy investor who wants the bottom line fast.\ """, db=workflow_db, add_datetime_to_context=True, add_history_to_context=True, num_history_runs=5, markdown=True, ) report_step = Step( name="Report Writing", agent=report_agent, description="Produce a concise investment brief", ) # --------------------------------------------------------------------------- # Create the Workflow # --------------------------------------------------------------------------- sequential_workflow = Workflow( name="Sequential Workflow", description="Three-step research pipeline: Data → Analysis → Report", steps=[ data_step, # Step 1: Gather data analysis_step, # Step 2: Analyze data report_step, # Step 3: Write report ], ) # --------------------------------------------------------------------------- # Run the Workflow # --------------------------------------------------------------------------- if __name__ == "__main__": sequential_workflow.print_response( "Analyze NVIDIA (NVDA) for investment", stream=True, ) # --------------------------------------------------------------------------- # More Examples # --------------------------------------------------------------------------- """ Workflow vs Team: - Workflow: Explicit step order, predictable execution, clear data flow - Team: Dynamic collaboration, leader decides who does what Use Workflow when: - Steps must happen in a specific order - Each step has a clear, specialized role - You want predictable, repeatable execution - Output from step N feeds into step N+1 Use Team when: - Agents need to collaborate dynamically - The leader should decide who to involve - Tasks benefit from back-and-forth discussion Advanced workflow features (not shown here): - Parallel: Run steps concurrently - Condition: Run steps only if criteria met - Loop: Repeat steps until condition met - Router: Dynamically select which step to run """ ``` ## Run the Example ```bash theme={null} uv pip install -U agno fastapi google-genai sqlalchemy yfinance ``` ```bash Mac/Linux theme={null} export GOOGLE_API_KEY="your_google_api_key_here" ``` ```bash Windows theme={null} $Env:GOOGLE_API_KEY="your_google_api_key_here" ``` Save the code above as `sequential_workflow.py`, then run: ```bash theme={null} python sequential_workflow.py ``` Full source: [cookbook/00\_quickstart/sequential\_workflow.py](https://github.com/agno-agi/agno/blob/main/cookbook/00_quickstart/sequential_workflow.py)