feat: add news-summarizer-agent using NewsAPI and ASI:One LLM

news-summarizer-agent/.env.example

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+# ASI One API key
+ASI1_API_KEY=your_asi1_api_key_here
+
+# NewsAPI key (free tier at newsapi.org/register)
+NEWS_API_KEY=your_news_api_key_here

news-summarizer-agent/README.md

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+# News Summarizer Agent
+
+A beginner-friendly Fetch.ai agent that fetches top news headlines for any topic using [NewsAPI](https://newsapi.org/) and summarizes them using the [ASI:One](https://asi1.ai/) LLM.
+
+## What It Does
+
+1. You provide a topic (e.g. "AI", "climate", "sports")
+2. The agent fetches the top 5 latest headlines from NewsAPI
+3. The headlines are sent to ASI:One LLM for summarization
+4. A short, readable summary is printed to the terminal
+
+## Tech Stack
+
+- Python 3.10+
+- NewsAPI - free tier, no credit card required
+- ASI:One - Fetch.ai's LLM API
+- requests - HTTP calls
+- python-dotenv - environment variable management
+
+## Setup
+
+### 1. Clone the repo
+
+git clone https://github.com/fetchai/innovation-lab-examples.git
+cd innovation-lab-examples/news-summarizer-agent
+
+### 2. Install dependencies
+
+pip install -r requirements.txt
+
+### 3. Set up environment variables
+
+cp .env.example .env
+
+Edit .env and fill in your API keys:
+
+ASI1_API_KEY=your_asi1_api_key_here
+NEWS_API_KEY=your_news_api_key_here
+
+- Get a free NewsAPI key at: https://newsapi.org/register
+- Get your ASI:One API key at: https://asi1.ai/
+
+### 4. Run the agent
+
+python agent.py
+
+When prompted, enter a topic like AI, climate, or sports.
+
+## Demo
+
+![Demo output](demo.png)
+
+## Environment Variables
+
+| Variable | Description |
+|---|---|
+| ASI1_API_KEY | Your ASI:One API key from asi1.ai |
+| NEWS_API_KEY | Your NewsAPI key from newsapi.org |
+
+## Project Structure
+
+news-summarizer-agent/
+├── agent.py          # Main agent logic
+├── requirements.txt  # Python dependencies
+├── .env.example      # Environment variable template
+├── demo.png          # Demo screenshot
+└── README.md         # This file

news-summarizer-agent/agent.py

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+import os
+import requests
+from dotenv import load_dotenv
+
+load_dotenv()
+
+load_dotenv()
+
+ASI1_API_KEY = os.getenv("ASI1_API_KEY")
+NEWS_API_KEY = os.getenv("NEWS_API_KEY")
+
+NEWS_API_URL = "https://newsapi.org/v2/everything"
+ASI1_API_URL = "https://api.asi1.ai/v1/chat/completions"
+
+
+def fetch_headlines(topic: str) -> list[str]:
+    """Fetch top 5 news headlines for a given topic using NewsAPI."""
+    params = {
+        "q": topic,
+        "pageSize": 5,
+        "sortBy": "publishedAt",
+        "language": "en",
+        "apiKey": NEWS_API_KEY,
+    }
+    response = requests.get(NEWS_API_URL, params=params)
+    response.raise_for_status()
+    articles = response.json().get("articles", [])
+    headlines = [a["title"] for a in articles if a.get("title")]
+    return headlines
+
+
+def summarize_with_asi1(topic: str, headlines: list[str]) -> str:
+    """Send headlines to ASI:One LLM and get a readable summary."""
+    headlines_text = "\n".join(f"- {h}" for h in headlines)
+    prompt = (
+        f"Here are the top 5 recent news headlines about '{topic}':\n\n"
+        f"{headlines_text}\n\n"
+        f"Please write a short, clear, 3-4 sentence summary of what is "
+        f"currently happening with '{topic}' based on these headlines."
+    )
+
+    headers = {
+        "Authorization": f"Bearer {ASI1_API_KEY}",
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "model": "asi1-mini",
+        "messages": [{"role": "user", "content": prompt}],
+        "temperature": 0.7,
+        "max_tokens": 300,
+        "stream": False,
+    }
+
+    response = requests.post(ASI1_API_URL, headers=headers, json=payload)
+    response.raise_for_status()
+    data = response.json()
+    return data["choices"][0]["message"]["content"]
+
+
+def run_agent(topic: str) -> None:
+    """Main agent flow: fetch headlines then summarize."""
+    print(f"\nFetching top headlines for topic: '{topic}'...")
+    headlines = fetch_headlines(topic)
+
+    if not headlines:
+        print("No headlines found for this topic. Try a different one.")
+        return
+
+    print(f"\nFound {len(headlines)} headlines:")
+    for h in headlines:
+        print(f"  - {h}")
+
+    print("\nSummarizing with ASI:One LLM...")
+    summary = summarize_with_asi1(topic, headlines)
+
+    print("\n--- Summary ---")
+    print(summary)
+    print("---------------\n")
+
+
+if __name__ == "__main__":
+    topic = input("Enter a topic to summarize news for (e.g. AI, climate, sports): ")
+    run_agent(topic.strip())

news-summarizer-agent/requirements.txt

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+requests>=2.28.0
+python-dotenv>=1.0.0