AI_ASK

=AI_ASK(prompt, [data], [temperature], [max_tokens], [model], [api_key], [api_url])

=AI_ASK("Summarize the key findings from the employee engagement survey:", A1:B5)

=AI_ASK("Provide a brief analysis of the quarterly sales performance:", A1:E4)

=AI_ASK("Summarize the following incident report in one sentence:", A1)

import requests
import json
 
def ai_ask(prompt, data=None, temperature=0.5, max_tokens=250, model="mistral-small-latest", api_key=None, api_url="https://api.mistral.ai/v1/chat/completions"):
    """
    Generate a text response using an AI model based on a prompt and optional tabular data.
 
    This function sends a prompt and optional 2D list data to a Mistral AI-compatible API endpoint and returns the generated response as a string. It is designed for use as a custom Excel function for text analysis, summarization, or business writing.
 
    This example function is provided as-is without any representation of accuracy.
 
    Args:
        prompt (str): The question, instruction, or task for the AI model.
        data (list[list], optional): 2D list (Excel range) to provide additional context. Default is None.
        temperature (float, optional): Controls randomness/creativity (0.0 to 2.0). Default is 0.5.
        max_tokens (float, optional): Maximum number of tokens to generate (5 to 5000). Default is 250.
        model (str, optional): Model ID to use. Default is "mistral-small-latest".
        api_key (str, optional): API key for authentication. Default is None.
        api_url (str, optional): OpenAI-compatible API endpoint URL. Default is "https://api.mistral.ai/v1/chat/completions".
 
    Returns:
        str: The AI-generated response, or an error message if the request fails or parameters are invalid.
    """
    if api_key is None or api_url is None:
        if "idToken" in globals():
            api_key = globals()["idToken"]
            api_url = "https://llm.boardflare.com"
        else:
            return "Login on the Functions tab for limited demo usage, or sign up for a free Mistral AI account at https://console.mistral.ai/ and add your own api_key."
 
    if not isinstance(temperature, (float, int)) or not (0 <= float(temperature) <= 2):
        return "Error: temperature must be a float between 0 and 2 (inclusive)"
    if not isinstance(max_tokens, (float, int)) or not (5 <= float(max_tokens) <= 5000):
        return "Error: max_tokens must be a number between 5 and 5000 (inclusive)"
 
    # Construct the message incorporating both prompt and data if provided
    message = prompt
    if data is not None:
        data_str = json.dumps(data, indent=2)
        message += f"\n\nData to analyze:\n{data_str}"
 
    # Prepare the API request payload
    payload = {
        "messages": [{"role": "user", "content": message}],
        "temperature": float(temperature),
        "model": model,
        "max_tokens": int(max_tokens)
    }
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
        "Accept": "application/json"
    }
 
    # Make the API request
    response = requests.post(api_url, headers=headers, json=payload)
    if response.status_code == 429:
        return "You have hit the rate limit for the API. Please try again later."
    try:
        response.raise_for_status()
        response_data = response.json()
        content = response_data["choices"][0]["message"]["content"]
        return content
    except Exception as e:
        return f"Error: {str(e)}"