symbolic-cognition-pipeline.git

`
1. **Initialize git repo**
```bash
git init
```
This creates a new, empty git repository in your current directory.

2. **Stage all files**
```bash
git add .
```
Stages all files in your project directory for commit.

3. **Create your first commit**
```bash
git commit -m "Initial symbolic cognition pipeline"
```
Commits the staged files with the message "Initial symbolic cognition pipeline".

4. **Add the remote origin**
```bash
git remote add origin git@github.com:AmbassadorOv/symbolic-cognition-pipeline.git
```
Adds your GitHub repository as the remote called `origin`.
- Replace `your-username` with your actual GitHub username.

5. **Push to GitHub (main branch)**
```bash
git push -u origin main
```
Pushes your local `main` branch to GitHub and sets `origin/main` as the upstream branch for future pushes.

---

https://github.com/231/assets/81f9a8fd-daeb-478f-a972-14b6dccc3df6

import asyncio
import torch
import logging
from datetime import datetime, UTC
from typing import Union, List

# Context from input
CURRENT_UTC = "2025-06-18 08:17:03"
CURRENT_USER = "AmbassadorOv"

class AI231Processor:
def __init__(self):
self.gpu_available = torch.cuda.is_available()
self.device = "cuda" if self.gpu_available else "cpu"
self._setup_logging()

def _setup_logging(self):
logging.basicConfig(
level=logging.INFO,
format=f'%(asctime)s UTC - [{CURRENT_USER}] - %(levelname)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S'
)
self.logger = logging.getLogger('AI231')

async def check_gpu_load(self) -> float:
"""IF LOAD(GPU) > 70% THEN DISTRIBUTE(TASK, CPU)"""
if not self.gpu_available:
return 1.0
try:
load = torch.cuda.utilization() / 100.0
self.logger.info(f"GPU Load: {load*100:.1f}%")
return load
except Exception as e:
self.logger.warning(f"GPU monitoring failed: {e}")
return 1.0

async def ai231_task(self, text: str) -> str:
"""DEFINE GPT_TASK = CALL GPT(AI231)"""
try:
# Implement your exact pattern
return f"Processed: {text.upper()}"
except Exception as e:
self.logger.error(f"Task error: {e}")
raise

async def gpt_task_automation(text: Union[str, List[str]]) -> Union[str, List[str]]:
"""AUTOMATE GPT_TASK ON INPUT(TEXT)"""
processor = AI231Processor()

if isinstance(text, str):
gpu_load = await processor.check_gpu_load()
if gpu_load > 0.7:
processor.device = "cpu"
return await processor.ai231_task(text)
else:
return await asyncio.gather(*[processor.ai231_task(t) for t in text])

if __name__ == "__main__":
async def main():
processor = AI231Processor()
gpu_load = await processor.check_gpu_load()

if gpu_load > 0.7:
# Pattern 1
task = asyncio.ensure_future(gpt_task_automation("abc"))
result = await task
print(f"Pattern 1 result: {result}")
else:
# Pattern 2
result = await gpt_task_automation("abc")
print(f"Pattern 2 result: {result}")

# Pattern 3 (multiple tasks)
results = await asyncio.gather(
processor.ai231_task("abc"),
processor.ai231_task("def"),
processor.ai231_task("ghi")
)
print(f"Multiple tasks results: {results}")

# Run with your exact pattern
asyncio.run(main())