Streaming Deep Research

Multi-tool research agent with streaming task cards and suggested prompts

Code

streaming_deep_research.py

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)

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Set Environment Variables

   export SLACK_TOKEN=***
   export SLACK_SIGNING_SECRET=***
   export OPENAI_API_KEY=***
   
3. Install Dependencies

   uv pip install 'agno[slack]' duckduckgo-search yfinance arxiv newspaper4k lxml_html_clean wikipedia
   
4. Run Example

   python streaming_deep_research.py
   

Key Features

• Streaming Task Cards: Each tool call renders as a card in Slack’s collapsible plan block
• 7 Tool Integrations: DuckDuckGo, HackerNews, YFinance, Wikipedia, Arxiv, Calculator, Newspaper4k
• Loading Messages: Custom status messages rotate while the agent processes
• Suggested Prompts: Pre-configured prompts appear when users open a new thread