Cognition CEO Denies Report of SpaceX Acquisition Attempt

+-------------------------------------------------------------+
|                        User Prompt                          |
+------------------------------+------------------------------+
                               |
                               v
+------------------------------+------------------------------+
|                       Planner Agent                         |
|             (Decomposes task into sub-tasks)                |
+------------------------------+------------------------------+
                               |
                               v
+------------------------------+------------------------------+
|                       Execution Loop                        |
|  +-------------------------------------------------------+  |
|  |                     1. Code Generator                 |  |
|  |               (Calls LLM via n1n.ai API)              |  |
|  +---------------------------+---------------------------+  |
|                              |                              |
|                              v                              |
|  +---------------------------+---------------------------+  |
|  |                     2. Sandboxed Runner               |  |
|  |                 (Executes code via Subprocess)        |  |
|  +---------------------------+---------------------------+  |
|                              |                              |
|                              v                              |
|  +---------------------------+---------------------------+  |
|  |                     3. Evaluator                      |  |
|  |               (Checks exit codes & stdout/stderr)     |  |
|  +---------------------------+---------------------------+  |
|                              |                              |
|                              v                              |
|  +---------------------------+---------------------------+  |
|  |                     4. Self-Correction                |  |
|  |       (Feeds error logs back to LLM if failure)       |  |
|  +-------------------------------------------------------+  |
+------------------------------+------------------------------+
                               |
                               v
+------------------------------+------------------------------+
|                        Final Output                         |
+-------------------------------------------------------------+

pip install requests

import json
import os
import subprocess
import requests

# Configure API access via n1n.ai
API_KEY = os.getenv("N1N_API_KEY", "your_n1n_api_key_here")
API_URL = "https://api.n1n.ai/v1/chat/completions"

def call_llm(prompt: str, system_instruction: str, model: str = "claude-3-5-sonnet") -> str:
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    payload = {
        "model": model,
        "messages": [
            {"role": "system", "content": system_instruction},
            {"role": "user", "content": prompt}
        ],
        "temperature": 0.2
    }

    response = requests.post(API_URL, json=payload, headers=headers)
    if response.status_code != 200:
        raise Exception(f"API Error: {response.status_code} - {response.text}")

    result = response.json()
    return result["choices"][0]["message"]["content"]

def extract_code(llm_output: str) -> str:
    # Simple parser to extract code from markdown code blocks
    if "```python" in llm_output:
        parts = llm_output.split("```python")
        code = parts[1].split("```")[0]
        return code.strip()
    elif "```" in llm_output:
        parts = llm_output.split("```")
        code = parts[1].split("```")[0]
        return code.strip()
    return llm_output.strip()

def execute_code(code: str, filename: str = "temp_agent_code.py") -> tuple[bool, str]:
    with open(filename, "w", encoding="utf-8") as f:
        f.write(code)

    try:
        # Run the code inside a subprocess with a timeout
        result = subprocess.run(
            ["python", filename],
            capture_output=True,
            text=True,
            timeout=10
        )
        if result.returncode == 0:
            return True, result.stdout
        else:
            return False, result.stderr
    except subprocess.TimeoutExpired:
        return False, "Execution timed out after 10 seconds."
    finally:
        if os.path.exists(filename):
            os.remove(filename)

def self_healing_coder(task_description: str, max_iterations: int = 5) -> str:
    system_instruction = (
        "You are an expert Python developer. Write only clean, functional Python code. "
        "Do not include explanations, intro text, or outro text. Always wrap your code "
        "in a ```python block."
    )

    current_prompt = f"Write a Python script that completes the following task: \{task_description\}"

    for iteration in range(1, max_iterations + 1):
        print(f"\n--- Iteration \{iteration\} ---")
        print("Generating code...")

        llm_response = call_llm(current_prompt, system_instruction, model="deepseek-v3")
        code = extract_code(llm_response)

        print("Generated Code Preview:")
        print("\n".join(code.split("\n")[:10]))  # Print first 10 lines
        print("...")

        print("Executing code...")
        success, output = execute_code(code)

        if success:
            print("Success! Execution Output:")
            print(output)
            return code
        else:
            print("Execution failed. Error:")
            print(output)
            # Update prompt with the failing code and the error message to trigger self-healing
            current_prompt = (
                f"The previously generated code failed execution.\n\n"
                f"### Code:\n\{code\}\n\n"
                f"### Error Output:\n\{output\}\n\n"
                f"Please analyze the error, fix the bug, and write the corrected Python code."
            )

    raise Exception("Failed to generate working code within the iteration limit.")

if __name__ == "__main__":
    # Task requiring data processing and exception handling
    task = "Parse a JSON string containing user profiles, filter out users under 18, and calculate average age."
    try:
        successful_code = self_healing_coder(task)
        print("\nFinal Working Code:")
        print(successful_code)
    except Exception as e:
        print(f"Agent failed: \{e\}")