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

# Streaming Deep Research Agent

> A multi-tool research agent that exercises many different tool types to stress-test the Slack streaming plan block UI.

```python streaming_deep_research.py theme={null}
"""
Streaming Deep Research Agent
==============================

A multi-tool research agent that exercises many different tool types
to stress-test the Slack streaming plan block UI.

Uses 7 toolkits across web search, finance, news, academic papers,
and calculations — a single query can trigger 8-12+ tool calls,
each rendering as a card in the plan block.

Slack scopes: app_mentions:read, assistant:write, chat:write, im:history
"""

from agno.agent import Agent
from agno.db.sqlite.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.os.app import AgentOS
from agno.os.interfaces.slack import Slack
from agno.tools.arxiv import ArxivTools
from agno.tools.calculator import CalculatorTools
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.hackernews import HackerNewsTools
from agno.tools.newspaper4k import Newspaper4kTools
from agno.tools.wikipedia import WikipediaTools
from agno.tools.yfinance import YFinanceTools

agent_db = SqliteDb(
    session_table="deep_research_sessions", db_file="tmp/deep_research.db"
)

deep_research_agent = Agent(
    name="Deep Research Agent",
    model=OpenAIChat(id="gpt-4.1"),
    tools=[
        DuckDuckGoTools(),
        HackerNewsTools(),
        YFinanceTools(
            enable_stock_price=True,
            enable_company_info=True,
            enable_analyst_recommendations=True,
            enable_company_news=True,
        ),
        WikipediaTools(),
        ArxivTools(),
        CalculatorTools(),
        Newspaper4kTools(),
    ],
    instructions=[
        "You are a deep research assistant that gathers information from MANY sources.",
        "For every query, use AT LEAST 4 different tools to provide comprehensive answers.",
        "Always search the web AND check HackerNews AND Wikipedia for context.",
        "For finance questions, pull stock data, analyst recommendations, AND company news.",
        "For technical topics, also search Arxiv for relevant research papers.",
        "Use the calculator for any numerical analysis or comparisons.",
        "Use newspaper4k to read full articles when you find interesting URLs.",
        "Synthesize all findings into a well-structured summary with sections.",
    ],
    db=agent_db,
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
)

agent_os = AgentOS(
    agents=[deep_research_agent],
    interfaces=[
        Slack(
            agent=deep_research_agent,
            streaming=True,
            reply_to_mentions_only=True,
            loading_messages=[
                "Researching across multiple sources...",
                "Gathering data from 7 different tools...",
                "Cross-referencing findings...",
                "Analyzing and synthesizing results...",
            ],
            suggested_prompts=[
                {
                    "title": "Deep Stock Analysis",
                    "message": "Do a deep analysis of NVDA: get the stock price, company info, analyst recommendations, latest news, search the web for recent developments, check HackerNews discussions, and look up Nvidia on Wikipedia for company background",
                },
                {
                    "title": "AI Research Deep Dive",
                    "message": "Research the latest developments in large language models: search the web, check HackerNews, look up recent Arxiv papers on LLMs, and read the Wikipedia article on large language models for background context",
                },
                {
                    "title": "Tech Company Comparison",
                    "message": "Compare AAPL and MSFT: get both stock prices, analyst recommendations, company info, search for recent news about both, and calculate the price-to-earnings ratio difference",
                },
                {
                    "title": "Trending Tech News",
                    "message": "What are the biggest tech stories today? Check HackerNews top stories, search the web for breaking tech news, and read the full text of the top 2 articles you find",
                },
            ],
        )
    ],
)
app = agent_os.get_app()


if __name__ == "__main__":
    agent_os.serve(app="streaming_deep_research: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,slack]" arxiv ddgs fastmcp lxml-html-clean newspaper4k openai pypdf starlette wikipedia yfinance
    ```
  </Step>

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

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

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

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

Full source: [cookbook/05\_agent\_os/interfaces/slack/streaming\_deep\_research.py](https://github.com/agno-agi/agno/blob/main/cookbook/05_agent_os/interfaces/slack/streaming_deep_research.py)