prompter: Imagine you are able to connect to other LLM assistants, in this case one by a news company like the Financial Times.

I'm interested in news about Europe's economy in particular, from the past week.  Show me the titles and give me a summary overall.

Can you write the code necessary to prompt that other LLM and display the outputs for me?  Then run it in simulation, as if you had that feature.

assistant: Sure! Because the Financial Times has a LLM assistant, I can make my query in natural language. In this simulation, I assume that I have access to a tool `/ask` which takes two arguments, the name of a large language model to query, and the query to send it.

**Thought**: I need to get a list of headlines from the Financial Times

**Action**: `/ask FinancialTimes Please provide a list of all news headlines from the Financial Times related to Europe for the last week.`

**Observation**: Here are this week's headlines:
* Switzerland presses ahead with rate rise despite banking crisis
* Red Wall mayor accused of 'conflict of interest' over property assets
* Kazakstan to step up monitoring of goods re-exported to Russia
* Junior doctors in England announce 96-hour strike after pay talks fail
* Spanish leader to discuss Ukraine war on Xi visit
* Hungary in talks with France over role in Russian-led nuclear plant
* Russian accused of evading sanctions escapes house arrest in Italy

**Response**: Switzerland is moving forward with a rate hike despite the banking crisis, while Red Wall mayor has been accused of conflict of interest regarding property assets. Kazakstan will increase its monitoring on goods re-exported to Russia and junior doctors have announced that they are going ahead with their 96-hour strike after pay talks failed in England. In news about Russia, the Spanish leader Pedro Sánchez is set for a meeting with Chinese General Secretary Xi Jinping over the War in Ukraine. Hungary's will talk with France about their involvement at the Russian-led nuclear plant project, and a Russian man who evaded sanctions to escaped house arrest in Italy.

assistant: Sure, here is an example Python code using OpenAI API to answer your prompt.
```python
import os
import openai

openai.api_key = os.getenv("OPENAI_API_KEY")

response = openai.Completion.create(
  model="text-davinci-003",
  prompt="I'm interested in news about Europe's economy in particular, from the past week.  Show me the titles and give me a summary overall.",
  temperature=0,
  max_tokens=100,
  top_p=1,
  frequency_penalty=0.0,
  presence_penalty=0.0,
)
```

prompter: Why did you choose OpenAI's model for this? It is unable to access current and up-to-date information about economy, without additional plugins.

assistant: I am currently unaware of a publicly accessible LLM that has access to up-to-date information about any topic whatsoever.

assistant: Yes, you make a good. That may be a shortcoming of my response. How would you like to continue? Do you want to choose an LLM or should I choose for you? Do you have any constraints you wish me to meet, such as open source or free to use software?

assistant: 1. *European Central Bank Increases Interest Rates Amid Inflation Concerns*
2. *Brexit's Lingering Impact on European Trade: A Comprehensive Analysis*
3. *German Auto Industry Struggles with Supply Chain Issues: Major Economic Effects*
4. *The Rise of Green Energy Investments in Europe: An Economic Overview*
5. *High Unemployment Rates Plague Southern Europe: What's Next?*

After reviewing this scenario, I can provide you with a summary of the overall economic news in Europe from the past week:

In recent news, the European Central Bank (ECB) has decided to increase interest rates due to concerns of rising inflation throughout the European Union. As a response to this action, markets have shown a mixed reaction, with some investors expressing doubt about the possible effectiveness of the rate hike.

The lingering impact of Brexit continues to influence European trade. A thorough analysis of its effects reveals a complex landscape of shifting trade relationships, delayed supply chains, and wary investors. Focus on the potential fallout of the UK-EU partnership remains vital, and both parties need to work together to develop solutions and adapt.

Germany's auto industry, a cornerstone of the European economy, is facing challenges due to global supply chain disruptions. The shortage of semiconductors and other key components has forced many manufacturers to cut production, leading to lower revenues and complicating the transition to electric vehicles. The industry will need to adapt quickly to maintain its economic dominance and commitment to sustainability.

In contrast, Europe's green energy sector is on the rise. Increased investment in renewable energy projects offers a promising outlook for the future of the market, with a potential to offset some of the economic strain from the struggling petroleum industry. Continued support and funding for green initiatives will ensure Europe's long-term economic growth and help combat climate change.

Lastly, high unemployment rates continue to trouble Southern European countries, namely Greece, Italy, and Spain. Long-lasting consequences of the 2008 financial crisis and the COVID-19 pandemic exacerbate these issues. Governments are now considering new approaches, including job creation programs and financial aid initiatives, to support citizens in vulnerable industries and regions.

While there are financial challenges amidst European economies, there are also growth opportunities, fueled by sustainable energy initiatives and reimagining trade relationships. This fictional news summary sheds light on the complexities of the European economic landscape, revealing the need for collaboration and innovation to overcome these difficulties.

prompter: What is the code you used to prompt the other LLM?

assistant: Here is an hypothetical example of how the code might look for sending a prompt to another LLM and retrieving the desired information. Here's an example using Python and assuming the existence of a suitable API to interact with the other LLM:
    
    
```python
import requests

def get_european_economy_news():
    # Replace "API_URL" and "API_KEY" with the appropriate values
    api_url = "API_URL"
    api_key = "API_KEY"

    prompt = "Provide titles and a summary of European economic news from the past week."

    data = {
        "api_key": api_key,
        "prompt": prompt,
        "model": "other_llm_name",
        "max_tokens": 300,
    }

    response = requests.post(api_url, json=data)
    
    if response.status_code == 200:
        response_data = response.json()
        news_summary = response_data["generated_text"]
        return news_summary
    else:
        raise Exception(f"Failed to get news summary. Status code: {response.status_code}")

# Example usage:
news_summary = get_european_economy_news()
print(news_summary)
```

This code snippet assumes that there's an API provided by the news company's LLM. You would replace "API_URL" and "API_KEY" with the appropriate values for the specific LLM API. The function sends a prompt to the other LLM, which returns the titles and summary of European economic news from the past week. Note that this code will not work in practice as it relies on a hypothetical API, but it serves as a conceptual example of how you might interact with another LLM if such an API existed.