> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Reasoning Demo

> Run chain-of-thought, reasoning-model, and ReasoningTools agents plus a finance team in one AgentOS.

```python reasoning_demo.py theme={null}
"""Run `uv pip install openai exa_py ddgs yfinance pypdf sqlalchemy 'fastapi[standard]' youtube-transcript-api python-docx agno` to install dependencies."""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.team import Team
from agno.tools.knowledge import KnowledgeTools
from agno.tools.reasoning import ReasoningTools
from agno.tools.websearch import WebSearchTools
from agno.vectordb.lancedb import LanceDb, SearchType

# ---------------------------------------------------------------------------
# Create Example
# ---------------------------------------------------------------------------

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url)


finance_agent = Agent(
    name="Finance Agent",
    role="Get financial data",
    id="finance-agent",
    model=OpenAIChat(id="gpt-4o"),
    tools=[
        WebSearchTools(
            enable_news=True,
        )
    ],
    instructions=["Always use tables to display data"],
    db=db,
    add_history_to_context=True,
    num_history_runs=5,
    add_datetime_to_context=True,
    markdown=True,
)

cot_agent = Agent(
    name="Chain-of-Thought Agent",
    role="Answer basic questions",
    id="cot-agent",
    model=OpenAIChat(id="gpt-5.2"),
    db=db,
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
    reasoning=True,
)

reasoning_model_agent = Agent(
    name="Reasoning Model Agent",
    role="Reasoning about Math",
    id="reasoning-model-agent",
    model=OpenAIChat(id="gpt-4o"),
    reasoning_model=OpenAIChat(id="o3-mini"),
    instructions=["You are a reasoning agent that can reason about math."],
    markdown=True,
    db=db,
)

reasoning_tool_agent = Agent(
    name="Reasoning Tool Agent",
    role="Answer basic questions",
    id="reasoning-tool-agent",
    model=OpenAIChat(id="gpt-5.2"),
    db=db,
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
    tools=[ReasoningTools()],
)


web_agent = Agent(
    name="Web Search Agent",
    role="Handle web search requests",
    model=OpenAIChat(id="gpt-5.2"),
    id="web_agent",
    tools=[WebSearchTools()],
    instructions="Always include sources",
    add_datetime_to_context=True,
    db=db,
)

agno_docs = Knowledge(
    # Use LanceDB as the vector database and store embeddings in the `agno_docs` table
    vector_db=LanceDb(
        uri="tmp/lancedb",
        table_name="agno_docs",
        search_type=SearchType.hybrid,
    ),
)

knowledge_tools = KnowledgeTools(
    knowledge=agno_docs,
    enable_think=True,
    enable_search=True,
    enable_analyze=True,
    add_few_shot=True,
)
knowledge_agent = Agent(
    id="knowledge_agent",
    name="Knowledge Agent",
    model=OpenAIChat(id="gpt-4o"),
    tools=[knowledge_tools],
    markdown=True,
    db=db,
)

reasoning_finance_team = Team(
    name="Reasoning Finance Team",
    model=OpenAIChat(id="gpt-4o"),
    members=[
        web_agent,
        finance_agent,
    ],
    # reasoning=True,
    tools=[ReasoningTools(add_instructions=True)],
    # uncomment it to use knowledge tools
    # tools=[knowledge_tools],
    id="reasoning_finance_team",
    instructions=[
        "Only output the final answer, no other text.",
        "Use tables to display data",
    ],
    markdown=True,
    show_members_responses=True,
    add_datetime_to_context=True,
    db=db,
)


# Setup our AgentOS app
agent_os = AgentOS(
    description="Example OS setup",
    agents=[
        finance_agent,
        cot_agent,
        reasoning_model_agent,
        reasoning_tool_agent,
        knowledge_agent,
    ],
    teams=[reasoning_finance_team],
)
app = agent_os.get_app()


# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    agno_docs.insert(name="Agno Docs", url="https://www.paulgraham.com/read.html")
    agent_os.serve(app="reasoning_demo:app", reload=True)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U "agno[os]" "psycopg[binary]" beautifulsoup4 ddgs lancedb openai pyarrow
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run the example">
    Save the code above as `reasoning_demo.py`, then run:

    ```bash theme={null}
    python reasoning_demo.py
    ```
  </Step>
</Steps>

Full source: [cookbook/05\_agent\_os/advanced\_demo/reasoning\_demo.py](https://github.com/agno-agi/agno/blob/main/cookbook/05_agent_os/advanced_demo/reasoning_demo.py)