Instructions to use Raiff1982/Gruntcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raiff1982/Gruntcoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Raiff1982/Gruntcoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from fastapi import FastAPI, HTTPException | |
| from pydantic import BaseModel | |
| import asyncio | |
| from ai_core import AICore | |
| app = FastAPI() | |
| # Initialize the AI core | |
| ai_core = AICore() | |
| class QueryRequest(BaseModel): | |
| query: str | |
| class QueryResponse(BaseModel): | |
| insights: list | |
| response: str | |
| security_level: int | |
| safety_checks: dict | |
| health_status: dict | |
| encrypted_query: str | |
| async def handle_query(request: QueryRequest): | |
| try: | |
| response = await ai_core.generate_response(request.query) | |
| return QueryResponse(**response) | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) | |
| async def shutdown_event(): | |
| await ai_core.shutdown() | |
| if __name__ == "__main__": | |
| import uvicorn | |
| uvicorn.run(app, host="0.0.0.0", port=7860) |