Give AutoGen Agents Real-Time News Intelligence (Python, 2025)

What you'll build

A Microsoft AutoGen multi-agent group chat where:

• A NewsAgent calls wpnews to fetch breaking stories, trending entities, and topic digests
• An AnalystAgent interprets the news and identifies business implications
• A SummarizerAgent produces a formatted briefing ready to send via Slack or email

One tool registration. No manual HTTP calls in your agents. 69 pre-built schemas auto-discovered.

Why AutoGen + wpnews?

AutoGen agents are stateless by default — they don't know what happened in the news since their training cut-off. wpnews gives every agent in your group chat live access to AI and tech news through a single tool registration. The key insight: AutoGen's function calling means you register the tool once, and every agent in the group can use it.

The get_morning_briefing() call is especially useful — it returns velocity status, hot articles, and trending entities in a single call, so your NewsAgent can make one call and hand structured context to the rest of the group.

Step 1 — Install

pip install pyautogen wpnews

Get a free wpnews API key at wpnews.pro/api#get-key (1,000 calls/day free, no credit card).

Step 2 — Define wpnews tools for AutoGen

import os
from wpnews import WPNews

client = WPNews(api_key=os.environ.get("WPNEWS_API_KEY", ""))

# ── Tool functions ──────────────────────────────────────────────────────────

def get_morning_briefing(hours: int = 6) -> dict:
    """Agent morning briefing: velocity status + breaking stories + trending entities."""
    return client.get_morning_briefing(hours=hours)


def search_news(query: str, limit: int = 5) -> list:
    """Search AI and tech news by keyword."""
    return client.search(q=query, limit=limit)


def get_topic_digest(topic: str, hours: int = 24) -> dict:
    """Get article digest for a specific topic (e.g. 'artificial-intelligence')."""
    return client.get_agent_digest(lang="en", hours=hours)


def get_trending_entities(days: int = 7) -> list:
    """Get companies and people surging in AI news coverage."""
    return client.get_trending_entities(days=days, limit=15)


# ── AutoGen tool schema ──────────────────────────────────────────────────────

WPNEWS_FUNCTIONS = [
    {
        "name": "get_morning_briefing",
        "description": "Get today's AI news situational awareness: velocity (burst/normal/quiet), top breaking stories, and trending entities. Call this first.",
        "parameters": {
            "type": "object",
            "properties": {
                "hours": {"type": "integer", "description": "Look-back window in hours", "default": 6}
            }
        }
    },
    {
        "name": "search_news",
        "description": "Search recent AI and tech news by keyword or topic.",
        "parameters": {
            "type": "object",
            "properties": {
                "query": {"type": "string", "description": "Search query"},
                "limit": {"type": "integer", "default": 5}
            },
            "required": ["query"]
        }
    },
    {
        "name": "get_trending_entities",
        "description": "Get companies and people trending in AI news coverage this week.",
        "parameters": {
            "type": "object",
            "properties": {
                "days": {"type": "integer", "default": 7}
            }
        }
    }
]

FUNCTION_MAP = {
    "get_morning_briefing": get_morning_briefing,
    "search_news": search_news,
    "get_trending_entities": get_trending_entities,
}

Step 3 — Create the agents

import autogen

LLM_CONFIG = {
    "config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}],
    "functions": WPNEWS_FUNCTIONS,
}

# NewsAgent: calls wpnews tools to gather intelligence
news_agent = autogen.AssistantAgent(
    name="NewsAgent",
    llm_config=LLM_CONFIG,
    system_message=(
        "You are a news intelligence agent. When the group starts a briefing, "
        "call get_morning_briefing() first to understand the current news climate. "
        "If velocity is 'burst', search for the specific breaking stories. "
        "Pass structured findings to AnalystAgent."
    ),
)

# AnalystAgent: interprets the news
analyst = autogen.AssistantAgent(
    name="AnalystAgent",
    llm_config={"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]},
    system_message=(
        "You are a business analyst. Receive news intelligence from NewsAgent "
        "and identify the top 2-3 business implications. Be concise."
    ),
)

# UserProxy: executes function calls and manages the conversation
user_proxy = autogen.UserProxyAgent(
    name="Coordinator",
    human_input_mode="NEVER",
    max_consecutive_auto_reply=5,
    function_map=FUNCTION_MAP,
    code_execution_config=False,
)

Step 4 — Run the group chat

group_chat = autogen.GroupChat(
    agents=[user_proxy, news_agent, analyst],
    messages=[],
    max_round=8,
)

manager = autogen.GroupChatManager(
    groupchat=group_chat,
    llm_config={"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]},
)

# Kick off the daily briefing
user_proxy.initiate_chat(
    manager,
    message="Run today's AI news briefing. Start with the morning briefing, then identify any breaking stories worth investigating.",
)

The group chat runs 8 rounds: NewsAgent fetches the data, AnalystAgent interprets it, and the Coordinator returns a structured briefing.

Full working script (under 100 lines)

"""
AutoGen + wpnews daily briefing agent
Run: OPENAI_API_KEY=... WPNEWS_API_KEY=... python autogen_news.py
"""
import os, autogen
from wpnews import WPNews

news = WPNews(api_key=os.environ.get("WPNEWS_API_KEY", ""))

def get_morning_briefing(hours: int = 6) -> dict:
    return news.get_morning_briefing(hours=hours)

def search_news(query: str, limit: int = 5) -> list:
    return news.search(q=query, limit=limit)

def get_trending_entities(days: int = 7) -> list:
    return news.get_trending_entities(days=days, limit=15)

FUNCTIONS = [
    {"name": "get_morning_briefing",
     "description": "Daily AI news briefing: velocity + breaking stories + trending entities.",
     "parameters": {"type": "object", "properties": {"hours": {"type": "integer", "default": 6}}}},
    {"name": "search_news",
     "description": "Search recent AI/tech news.",
     "parameters": {"type": "object", "properties": {"query": {"type": "string"}, "limit": {"type": "integer", "default": 5}}, "required": ["query"]}},
    {"name": "get_trending_entities",
     "description": "Companies/people trending in AI news.",
     "parameters": {"type": "object", "properties": {"days": {"type": "integer", "default": 7}}}},
]

LLM = {"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}], "functions": FUNCTIONS}

news_agent = autogen.AssistantAgent("NewsAgent", llm_config=LLM,
    system_message="Call get_morning_briefing() first. If burst, search for breaking stories.")
analyst = autogen.AssistantAgent("AnalystAgent",
    llm_config={"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]},
    system_message="Identify the top 2-3 business implications from the news.")
proxy = autogen.UserProxyAgent("Coordinator", human_input_mode="NEVER",
    max_consecutive_auto_reply=5,
    function_map={"get_morning_briefing": get_morning_briefing,
                  "search_news": search_news,
                  "get_trending_entities": get_trending_entities},
    code_execution_config=False)

gc = autogen.GroupChat(agents=[proxy, news_agent, analyst], messages=[], max_round=8)
mgr = autogen.GroupChatManager(groupchat=gc,
    llm_config={"config_list": [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]})

proxy.initiate_chat(mgr,
    message="Run today's AI news briefing. Start with morning briefing, then find breaking stories.")

Use all 69 tools automatically

Instead of defining tools manually, fetch all 69 pre-built schemas from the API:

import requests

# Fetch all 69 wpnews OpenAI-compatible schemas
all_tools = requests.get(
    "https://api.wpnews.pro/api/v1/openai-tools.json",
    headers={"X-API-Key": os.environ.get("WPNEWS_API_KEY", "")}
).json()

# Convert to AutoGen "functions" format
FUNCTIONS_ALL = [t["function"] for t in all_tools]

# Execute via the API tool resolver — no local function stubs needed
def call_wpnews_tool(name: str, **kwargs) -> dict:
    url_resp = requests.post(
        f"https://api.wpnews.pro/api/v1/openai-tools/{name}/call",
        json=kwargs,
        headers={"X-API-Key": os.environ.get("WPNEWS_API_KEY", "")}
    )
    return url_resp.json()

Scheduling the briefing

To run this every morning automatically:

# crontab -e
0 8 * * 1-5 OPENAI_API_KEY=... WPNEWS_API_KEY=... python /path/to/autogen_news.py >> ~/briefings.log 2>&1

Or use a workflow scheduler (Prefect, Airflow, GitHub Actions cron) for more control.