Generate Advanced Mathematical Questions with the MetaMath-Mistral-7B Cognitive Actions

25 Apr 2025
Generate Advanced Mathematical Questions with the MetaMath-Mistral-7B Cognitive Actions

In the rapidly evolving field of artificial intelligence, the ability to generate and solve mathematical questions has become increasingly valuable. The MetaMath-Mistral-7B Cognitive Actions provide developers with a powerful tool to create and address advanced mathematical problems. Fine-tuned on the MetaMathQA datasets, these actions improve performance on mathematical tasks, notably boosting the GSM8K accuracy from 66.5% to 77.7%. By leveraging these pre-built actions, developers can enhance their applications with sophisticated question generation capabilities.

Prerequisites

Before diving into the integration of the Cognitive Actions, ensure that you have the following prerequisites:

  • An API key for accessing the Cognitive Actions platform.
  • Familiarity with JSON format for structuring requests and handling responses.
  • A basic understanding of making HTTP requests in your preferred programming language.

Authentication typically involves passing the API key in the request headers, ensuring secure access to the actions.

Cognitive Actions Overview

Generate Mathematical Questions

The Generate Mathematical Questions action allows you to create and solve advanced mathematical questions using the MetaMath-Mistral-7B model. This action is categorized under text generation and is designed to improve performance on various mathematical tasks.

Input

The input for this action requires the following fields:

  • prompt (required): The initial text prompt for the model to complete.
  • topK (optional): The number of highest probability tokens to consider for generating the output (default is 50).
  • topP (optional): A probability threshold for generating the output (default is 0.95).
  • temperature (optional): Controls the randomness of the generated output (default is 0.8).
  • maxNewTokens (optional): Specifies the maximum number of tokens the model can generate (default is 128).
  • presencePenalty (optional): Influences the likelihood of discussing new topics (default is 1).

Example Input:

{
  "topK": 50,
  "topP": 0.95,
  "prompt": "Below is an instruction that describes a task.\nWrite a response that appropriately completes the request.\n\n### Instruction:\nGerald works at a daycare that pays him $30 every day. He worked for an entire week and spent a total of $100. How much does he have left?\n\n### Response: Let's think step by step.",
  "temperature": 0.8,
  "maxNewTokens": 128,
  "presencePenalty": 1
}

Output

The output from the action typically returns a string containing the generated solution to the provided mathematical question. The response will also include the final answer to the question.

Example Output:

Gerald earns $30 every day, so in a week, he earns 7 * $30 = $210.
If he spent a total of $100, then he has $210 - $100 = $110 left.
#### 110
The answer is: 110

Conceptual Usage Example (Python)

Here’s a conceptual Python code snippet to illustrate how a developer might call the Cognitive Actions execution endpoint to generate mathematical questions:

import requests
import json

# Replace with your Cognitive Actions API key and endpoint
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute"  # Hypothetical endpoint

action_id = "7c7134b0-d706-4cd1-8a5e-34ca0dc5dae5"  # Action ID for Generate Mathematical Questions

# Construct the input payload based on the action's requirements
payload = {
    "topK": 50,
    "topP": 0.95,
    "prompt": "Below is an instruction that describes a task.\nWrite a response that appropriately completes the request.\n\n### Instruction:\nGerald works at a daycare that pays him $30 every day. He worked for an entire week and spent a total of $100. How much does he have left?\n\n### Response: Let's think step by step.",
    "temperature": 0.8,
    "maxNewTokens": 128,
    "presencePenalty": 1
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json"
}

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json={"action_id": action_id, "inputs": payload}  # Hypothetical structure
    )
    response.raise_for_status()  # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully:")
    print(json.dumps(result, indent=2))

except requests.exceptions.RequestException as e:
    print(f"Error executing action {action_id}: {e}")
    if e.response is not None:
        print(f"Response status: {e.response.status_code}")
        try:
            print(f"Response body: {e.response.json()}")
        except json.JSONDecodeError:
            print(f"Response body: {e.response.text}")

In this code snippet, you replace the COGNITIVE_ACTIONS_API_KEY and COGNITIVE_ACTIONS_EXECUTE_URL with your actual credentials and the endpoint. The action ID and input payload are structured according to the requirements of the Generate Mathematical Questions action.

Conclusion

The MetaMath-Mistral-7B Cognitive Actions provide an excellent opportunity for developers to leverage advanced AI capabilities in generating and solving mathematical questions. By integrating these actions into your applications, you can enhance user engagement and provide valuable educational tools. Consider exploring additional use cases, such as creating interactive learning platforms or automating math tutoring systems, to fully utilize the power of these Cognitive Actions.

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