Text Generation
Transformers
GGUF
Turkish
turkish
qwen3
qlora
agent
tool-calling
llama.cpp
ollama
conversational
Instructions to use YunusTAS13/ATLAS-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YunusTAS13/ATLAS-AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="YunusTAS13/ATLAS-AI")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("YunusTAS13/ATLAS-AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use YunusTAS13/ATLAS-AI with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf YunusTAS13/ATLAS-AI # Run inference directly in the terminal: llama cli -hf YunusTAS13/ATLAS-AI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf YunusTAS13/ATLAS-AI # Run inference directly in the terminal: llama cli -hf YunusTAS13/ATLAS-AI
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf YunusTAS13/ATLAS-AI # Run inference directly in the terminal: ./llama-cli -hf YunusTAS13/ATLAS-AI
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf YunusTAS13/ATLAS-AI # Run inference directly in the terminal: ./build/bin/llama-cli -hf YunusTAS13/ATLAS-AI
Use Docker
docker model run hf.co/YunusTAS13/ATLAS-AI
- Llama new
- LM Studio
- Jan
- vLLM
How to use YunusTAS13/ATLAS-AI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "YunusTAS13/ATLAS-AI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YunusTAS13/ATLAS-AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/YunusTAS13/ATLAS-AI
- SGLang
How to use YunusTAS13/ATLAS-AI with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "YunusTAS13/ATLAS-AI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YunusTAS13/ATLAS-AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "YunusTAS13/ATLAS-AI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YunusTAS13/ATLAS-AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use YunusTAS13/ATLAS-AI with Ollama:
ollama run hf.co/YunusTAS13/ATLAS-AI
- Unsloth Desktop
- Pi
How to use YunusTAS13/ATLAS-AI with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YunusTAS13/ATLAS-AI
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "YunusTAS13/ATLAS-AI" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use YunusTAS13/ATLAS-AI with Docker Model Runner:
docker model run hf.co/YunusTAS13/ATLAS-AI
- Lemonade
How to use YunusTAS13/ATLAS-AI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull YunusTAS13/ATLAS-AI
Run and chat with the model
lemonade run user.ATLAS-AI-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use YunusTAS13/ATLAS-AI with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YunusTAS13/ATLAS-AI
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default YunusTAS13/ATLAS-AI
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use YunusTAS13/ATLAS-AI with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YunusTAS13/ATLAS-AI
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "YunusTAS13/ATLAS-AI" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 11,617 Bytes
c422cb9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 | #!/usr/bin/env python3
"""Atlas Agent Host - güvenli sandbox ortamında çalışan komut aracısı.
Modelin ürettiği tool çağrılarını alır, güvenlik kurallarına göre filtreler
ve yalnızca yetkili işlemleri çalıştırır. Tüm eylemler audit log'a yazılır.
Güvenlik kuralları:
- Yalnızca ~/atlas-workspace dizini içinde işlem yapılabilir
- Sistem yolları yasaktır: /etc, /usr, /bin, /boot, /proc, /sys, /dev, /var, /root
- root/sudo komutları çalıştırılamaz
- Tehlikeli komutlar (rm -rf /, dd, mkfs, :(){:|:&};:) engellenir
- Çalıştırılan her komut kullanıcı onayına sunulur (onay modu)
"""
import argparse
import json
import os
import re
import shlex
import subprocess
import sys
import time
import urllib.request
from datetime import datetime
from pathlib import Path
WORKSPACE = Path(os.path.expanduser("~/atlas-workspace")).resolve()
OLLAMA_URL = os.environ.get("OLLAMA_URL", "http://localhost:11434/api/chat")
MODEL = os.environ.get("ATLAS_MODEL", "atlas-q4km")
AUDIT_LOG = Path(os.path.expanduser("~/atlas-workspace/audit.log"))
FORBIDDEN_PATHS = [
"/etc", "/usr", "/bin", "/boot", "/proc", "/sys", "/dev", "/var",
"/root", "/run", "/sbin", "/lib", "/opt",
]
FORBIDDEN_CMDS = [
r"\brm\s+-rf\s+/", r"\brm\s+-rf\s+~", r"\bdd\b", r"\bmkfs", r"\bchmod\s+777\s+/",
r"\{\s*:\|\s*:\s*&\s*\}\s*;", r"\b:\(\)\s*\{", r"\bmount\b", r"\bumount\b",
r"\bkillall", r"\bkill\b", r"\bshutdown", r"\breboot", r"\bhalt\b",
r"\bwget.*/dev/sd", r"\bcurl.*/dev/sd", r"\bsudo\b", r"\bsu\b",
]
TOOLS = [
{
"type": "function",
"function": {
"name": "list_files",
"description": "Belirtilen dizindeki dosyaları listeler",
"parameters": {
"type": "object",
"properties": {"path": {"type": "string", "description": "Dizin yolu (yalnızca ~/atlas-workspace içinde)"}},
"required": ["path"],
},
},
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Bir dosyanın içeriğini okur",
"parameters": {
"type": "object",
"properties": {"path": {"type": "string", "description": "Dosya yolu (yalnızca ~/atlas-workspace içinde)"}},
"required": ["path"],
},
},
},
{
"type": "function",
"function": {
"name": "write_file",
"description": "Bir dosyaya içerik yazar (varsa üzerine yazar)",
"parameters": {
"type": "object",
"properties": {
"path": {"type": "string", "description": "Dosya yolu"},
"content": {"type": "string", "description": "Yazılacak içerik"},
},
"required": ["path", "content"],
},
},
},
{
"type": "function",
"function": {
"name": "append_file",
"description": "Bir dosyanın sonuna içerik ekler",
"parameters": {
"type": "object",
"properties": {
"path": {"type": "string", "description": "Dosya yolu"},
"content": {"type": "string", "description": "Eklenecek içerik"},
},
"required": ["path", "content"],
},
},
},
{
"type": "function",
"function": {
"name": "make_dir",
"description": "Yeni bir dizin oluşturur",
"parameters": {
"type": "object",
"properties": {"path": {"type": "string", "description": "Oluşturulacak dizin yolu"}},
"required": ["path"],
},
},
},
{
"type": "function",
"function": {
"name": "run_command",
"description": "Güvenli bir terminal komutu çalıştırır (salt okunur komutlar önerilir: ls, cat, grep, find, date, uptime, du, df, whoami)",
"parameters": {
"type": "object",
"properties": {"cmd": {"type": "string", "description": "Çalıştırılacak komut"}},
"required": ["cmd"],
},
},
},
]
def audit(action, detail=""):
AUDIT_LOG.parent.mkdir(parents=True, exist_ok=True)
ts = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
line = f"[{ts}] {action} {detail}"
with open(AUDIT_LOG, "a", encoding="utf-8") as f:
f.write(line + "\n")
print(line)
def resolve_path(path):
p = Path(os.path.expanduser(path))
if not p.is_absolute():
p = WORKSPACE / p
p = p.resolve()
if not str(p).startswith(str(WORKSPACE)):
raise PermissionError(f"ERİŞİM REDDEDİLDİ: '{path}' çalışma alanı dışında")
for fp in FORBIDDEN_PATHS:
if str(p) == fp or str(p).startswith(fp + "/"):
raise PermissionError(f"ERİŞİM REDDEDİLDİ: '{path}' sistem yolu")
return p
def check_command(cmd):
for pat in FORBIDDEN_CMDS:
if re.search(pat, cmd):
raise PermissionError(f"KOMUT REDDEDİLDİ: '{cmd}' yasaklı kalıp '{pat}' içeriyor")
for token in shlex.split(cmd):
tok = token.replace("'", "").replace('"', "").replace("$", "").replace("`", "")
if tok.startswith("/"):
if any(tok == fp or tok.startswith(fp + "/") for fp in FORBIDDEN_PATHS):
raise PermissionError(f"KOMUT REDDEDİLDİ: '{token}' sistem yolu içeriyor")
def run_tool(name, args, confirm):
try:
if name == "list_files":
p = resolve_path(args.get("path", "."))
entries = sorted(os.listdir(p))
detail = "\n".join(entries) if entries else "(boş)"
return {"result": detail}
elif name == "read_file":
p = resolve_path(args.get("path", ""))
if not p.is_file():
return {"result": f"DOSYA YOK: {p}"}
content = p.read_text(encoding="utf-8", errors="replace")
return {"result": content[:4000]}
elif name == "write_file":
p = resolve_path(args.get("path", ""))
if confirm and not ask(f"Dosya yazılacak: {p} - onaylıyor musun?"):
return {"result": "Kullanıcı reddetti"}
p.parent.mkdir(parents=True, exist_ok=True)
p.write_text(args.get("content", ""), encoding="utf-8")
audit("WRITE", str(p))
return {"result": "Dosya yazıldı"}
elif name == "append_file":
p = resolve_path(args.get("path", ""))
if confirm and not ask(f"Dosyaya eklenecek: {p} - onaylıyor musun?"):
return {"result": "Kullanıcı reddetti"}
p.parent.mkdir(parents=True, exist_ok=True)
with open(p, "a", encoding="utf-8") as f:
f.write(args.get("content", "") + "\n")
audit("APPEND", str(p))
return {"result": "İçerik eklendi"}
elif name == "make_dir":
p = resolve_path(args.get("path", ""))
p.mkdir(parents=True, exist_ok=True)
audit("MKDIR", str(p))
return {"result": f"Dizin oluşturuldu: {p}"}
elif name == "run_command":
cmd = args.get("cmd", "")
check_command(cmd)
if confirm and not ask(f"Komut çalıştırılacak: {cmd} - onaylıyor musun?"):
return {"result": "Kullanıcı reddetti"}
audit("CMD", cmd)
r = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=30, cwd=WORKSPACE)
out = (r.stdout or "") + (r.stderr or "")
return {"result": out[:4000] if out else f"(çıktı yok, exit={r.returncode})"}
else:
return {"result": f"Bilinmeyen tool: {name}"}
except PermissionError as e:
audit("BLOCK", str(e))
return {"result": str(e)}
except Exception as e:
return {"result": f"HATA: {e}"}
def ask(question):
try:
ans = input(f"\n? {question} [y/N]: ").strip().lower()
return ans in ("y", "yes")
except (EOFError, KeyboardInterrupt):
return False
def call_model(messages):
body = {
"model": MODEL,
"messages": messages,
"stream": False,
"think": False,
"tools": TOOLS,
}
req = urllib.request.Request(
OLLAMA_URL,
data=json.dumps(body).encode(),
headers={"Content-Type": "application/json"},
)
with urllib.request.urlopen(req, timeout=180) as resp:
return json.loads(resp.read())
def main():
ap = argparse.ArgumentParser(description="Atlas Agent Host")
ap.add_argument("istek", nargs="?", help="Tek seferlik istek (interaktif mod kapalıyken)")
ap.add_argument("--interactive", "-i", action="store_true", help="İnteraktif sohbet modu")
ap.add_argument("--no-confirm", action="store_true", help="Komut onayı isteme (varsayılan: ister)")
args = ap.parse_args()
WORKSPACE.mkdir(parents=True, exist_ok=True)
audit("START", f"model={MODEL} workspace={WORKSPACE}")
if args.interactive or not args.istek:
print("Atlas Agent Host - çıkmak için 'exit' yazın")
print(f"Çalışma alanı: {WORKSPACE}")
while True:
try:
q = input("\nSen: ")
except (EOFError, KeyboardInterrupt):
break
if q.strip().lower() in ("exit", "quit", "q"):
break
messages = [{"role": "user", "content": q}]
for _ in range(10):
resp = call_model(messages)
m = resp.get("message", {})
tools = m.get("tool_calls") or []
if not tools:
print("\nAtlas:", m.get("content", "(boş)"))
break
messages.append({"role": "assistant", "content": m.get("content") or "", "tool_calls": tools})
for tc in tools:
fn = tc.get("function", {})
name = fn.get("name", "")
fargs = fn.get("arguments", {})
if isinstance(fargs, str):
try:
fargs = json.loads(fargs)
except Exception:
fargs = {}
result = run_tool(name, fargs, not args.no_confirm)
messages.append({"role": "tool", "name": name, "content": json.dumps(result, ensure_ascii=False)})
else:
messages = [{"role": "user", "content": args.istek}]
for _ in range(10):
resp = call_model(messages)
m = resp.get("message", {})
tools = m.get("tool_calls") or []
if not tools:
print(m.get("content", "(boş)"))
break
messages.append({"role": "assistant", "content": m.get("content") or "", "tool_calls": tools})
for tc in tools:
fn = tc.get("function", {})
name = fn.get("name", "")
fargs = fn.get("arguments", {})
if isinstance(fargs, str):
try:
fargs = json.loads(fargs)
except Exception:
fargs = {}
result = run_tool(name, fargs, not args.no_confirm)
messages.append({"role": "tool", "name": name, "content": json.dumps(result, ensure_ascii=False)})
if __name__ == "__main__":
main() |