A local-first private AI assistant for everyday use. Runs on-device models with encrypted P2P sync, and supports sharing chats publicly on ATProto.
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Merge pull request #111 from tilesprivacy/fix/qwen3.5-load-issue

fix: updated mlx related pkgs + end condition for stopping model request loop

authored by

Anandu Pavanan and committed by
GitHub
fdc886c4 d874af2d

+665 -777
+2 -2
modelfiles/qwen
··· 1 - FROM mlx-community/Qwen3.5-0.8B-8bit 1 + FROM mlx-community/Qwen3.5-4B-MLX-4bit 2 + #FROM mlx-community/Qwen3.5-0.8B-8bit 2 3 # FROM mlx-community/Qwen3.5-0.8B-MLX-8bit 3 - # FROM mlx-community/Qwen3.5-4B-MLX-4bit 4 4 # FROM mlx-community/Qwen3-0.6B-4bit
+6
pkg/scripts/preinstall
··· 1 + #!/bin/bash 2 + 3 + # So that we don't have multiple copies of python libs lying around 4 + # from previous installs 5 + 6 + rm -rf /usr/local/share/tiles/server
-7
server/api.py
··· 7 7 from pydantic import BaseModel, Field 8 8 9 9 from . import runtime 10 - from .hf_downloader import pull_model 11 10 from .mem_agent.engine import execute_sandboxed_code 12 11 from .mem_agent.utils import ( 13 12 create_memory_if_not_exists, ··· 35 34 @app.get("/ping") 36 35 async def ping(): 37 36 return {"message": "Badda-Bing Badda-Bang"} 38 - 39 - 40 - @app.post("/download") 41 - async def download(request: downloadRequest): 42 - """Download the model""" 43 - runtime.backend.download_model(request.model) 44 37 45 38 46 39 @app.post("/start")
-10
server/backend/mlx.py
··· 24 24 from ..reasoning_utils import ReasoningExtractor 25 25 26 26 from ..cache_utils import get_model_path 27 - from ..hf_downloader import pull_model 28 27 from ..schemas import ( 29 28 ChatCompletionRequest, 30 29 ChatMessage, 31 30 GenerationMetrics, 32 31 ResponsesRequest, 33 32 ResponsesResponse, 34 - downloadRequest, 35 33 ) 36 34 from .mlx_runner import MLXRunner 37 35 ··· 44 42 _current_model_path: Optional[str] = None 45 43 # Store generated responses for follow-up support (previous_response_id) 46 44 _responses: Dict[str, ResponsesResponse] = {} 47 - 48 - 49 - def download_model(model_name: str): 50 - """Download the model""" 51 - if pull_model(model_name): 52 - return {"message": "Model downloaded"} 53 - else: 54 - raise HTTPException(status_code=400, detail="Downloading model failed") 55 45 56 46 57 47 def get_or_load_model(
-145
server/hf_downloader.py
··· 1 - import json 2 - import os 3 - import subprocess 4 - import sys 5 - import tempfile 6 - 7 - try: 8 - from .cache_utils import ( 9 - MODEL_CACHE, 10 - hf_to_cache_dir, 11 - is_model_healthy, 12 - parse_model_spec, 13 - ) 14 - except ImportError: 15 - from pathlib import Path 16 - def parse_model_spec(x): return (x, None) 17 - def hf_to_cache_dir(x): return x 18 - if "HF_HOME" in os.environ: 19 - MODEL_CACHE = Path(os.environ["HF_HOME"]) / "hub" 20 - else: 21 - MODEL_CACHE = Path(os.path.expanduser("~/.cache/huggingface/hub")) 22 - def is_model_healthy(x): return False 23 - 24 - def describe_http_exception(exc): 25 - if hasattr(exc, "response") and exc.response is not None: 26 - status = getattr(exc.response, "status_code", None) 27 - url = getattr(exc.response, "url", None) 28 - if status == 401: 29 - return f"[ERROR] Unauthorized (401): Check your HuggingFace token or login.\nURL: {url}" 30 - elif status == 403: 31 - return f"[ERROR] Forbidden (403): Access denied.\nURL: {url}" 32 - elif status == 404: 33 - return f"[ERROR] Not Found (404): Resource does not exist.\nURL: {url}" 34 - elif status >= 500: 35 - return f"[ERROR] Server Error ({status}): Problem on HuggingFace's side.\nURL: {url}\nTry again later." 36 - else: 37 - return f"[ERROR] HTTP Error {status}: {exc}\nURL: {url}" 38 - return f"[ERROR] HTTP Error: {exc}" 39 - 40 - def configure_download_environment(): 41 - os.environ['HF_HUB_DOWNLOAD_THREADS'] = '1' 42 - os.environ['HF_HUB_DOWNLOAD_CHUNK_SIZE'] = '524288' # 512KB chunks for household-friendly downloads 43 - os.environ['HF_HUB_ENABLE_HF_TRANSFER'] = 'false' 44 - 45 - def pull_model(model_spec): 46 - original_spec = model_spec 47 - model_name, commit_hash = parse_model_spec(model_spec) 48 - 49 - # Validate HuggingFace Hub repository name length limit (Issue #6) 50 - if len(model_name) > 96: 51 - print(f"[ERROR] Repository name exceeds HuggingFace Hub limit: {len(model_name)}/96 characters") 52 - print("Repository names longer than 96 characters cannot exist on HuggingFace Hub.") 53 - print(f"Invalid name: '{model_name}'") 54 - return False 55 - 56 - if "/" not in original_spec.split("@")[0] and "/" in model_name: 57 - confirm = input(f"Download '{model_name}'? [Y/n] ") 58 - if confirm.lower() == "n": 59 - print("Download cancelled.") 60 - return False 61 - 62 - base_cache_dir = MODEL_CACHE / hf_to_cache_dir(model_name) 63 - if commit_hash: 64 - hash_dir = base_cache_dir / "snapshots" / commit_hash 65 - if hash_dir.exists() and is_model_healthy(f"{model_name}@{commit_hash}"): 66 - print("Model already exists") 67 - return True 68 - else: 69 - if base_cache_dir.exists() and is_model_healthy(model_name): 70 - print("Model already exists") 71 - return True 72 - 73 - print(f"Downloading {model_name}...") 74 - 75 - # Build kwargs dict for the worker 76 - kwargs_dict = { 77 - "repo_id": model_name, 78 - "local_dir_use_symlinks": False, 79 - "max_workers": 1 80 - } 81 - if commit_hash: 82 - kwargs_dict["revision"] = commit_hash 83 - # if "mlx-community" in model_name: 84 - kwargs_dict["allow_patterns"] = [ 85 - "*.json", "*.txt", "*.safetensors", "*.md", "*.gitattributes", "LICENSE" 86 - ] 87 - # if "mlx-community" not in model_name: 88 - # confirm = input(f"[WARNING] {model_name} is not an MLX model (may be >1GB). Continue? [y/N] ") 89 - # if confirm.lower() != "y": 90 - # print("Download cancelled.") 91 - # return 92 - 93 - kwargs_str = json.dumps(kwargs_dict, indent=2) 94 - with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f: 95 - f.write(kwargs_str) 96 - kwargs_file = f.name 97 - 98 - # Call the worker as subprocess with nice priority 99 - worker_path = os.path.join(os.path.dirname(__file__), "throttled_download_worker.py") 100 - try: 101 - result = subprocess.run( 102 - ['nice', '-n', '19', sys.executable, worker_path, kwargs_file], 103 - check=False 104 - ) 105 - if result.returncode == 0: 106 - print("Download completed successfully.") 107 - return True 108 - elif result.returncode in (10, 11, 12, 13, 14, 15): 109 - # Already handled in worker, do NOT retry fallback 110 - print("[WARNING] Fatal error encountered in throttled download, not attempting fallback.") 111 - return False 112 - else: 113 - print("[WARNING] Throttled download failed or was interrupted.") 114 - print("Attempting fallback download with standard throttling...") 115 - try: 116 - import requests 117 - from huggingface_hub import snapshot_download 118 - configure_download_environment() 119 - snapshot_download(**kwargs_dict) 120 - print("Download completed successfully.") 121 - return True 122 - except requests.exceptions.HTTPError as e: 123 - print(describe_http_exception(e)) 124 - return False 125 - except requests.exceptions.ConnectionError: 126 - print("[ERROR] Network connection error. Please check your internet connection and try again.") 127 - return False 128 - except requests.exceptions.Timeout: 129 - print("[ERROR] Download timed out. Please try again.") 130 - return False 131 - except KeyboardInterrupt: 132 - print("\n[WARNING] Download cancelled by user.") 133 - return False 134 - except Exception as e: 135 - print(f"[ERROR] Unexpected error during fallback download: {type(e).__name__}: {e}") 136 - return False 137 - except KeyboardInterrupt: 138 - print("\n[WARNING] Download cancelled by user.") 139 - return False 140 - except ImportError: 141 - print("huggingface-hub is not installed. Please install it with: pip install huggingface-hub") 142 - return False 143 - except Exception as e: 144 - print(f"[ERROR] Unexpected error: {type(e).__name__}: {e}") 145 - return False
+7 -5
server/pyproject.toml
··· 4 4 description = "Local MLX inference server for the Tiles CLI" 5 5 requires-python = "==3.13.*" 6 6 dependencies = [ 7 - "fastapi", 8 - "uvicorn", 9 - "mlx-lm", 10 - "black", 11 - "huggingface-hub>=0.34.0", 7 + "fastapi==0.119.0", 8 + "uvicorn==0.38.0", 9 + "mlx-lm==0.31.0", 10 + "black==25.9.0", 12 11 "openai-harmony==0.0.8", 13 12 "openresponses-types" 14 13 ] ··· 19 18 20 19 [tool.setuptools.packages.find] 21 20 exclude = ["backend", "backend.*"] 21 + 22 + [tool.uv] 23 + exclude-newer="10 days"
+19 -12
server/stack/requirements/app-server/packages-app-server.txt
··· 1 1 # Package summary for app-server 2 2 # Auto-generated by venvstacks (DO NOT EDIT) 3 + annotated-doc==0.0.4 3 4 annotated-types==0.7.0 4 - anyio==4.12.1 5 + anyio==4.13.0 5 6 black==25.9.0 6 7 certifi==2026.2.25 7 - charset-normalizer==3.4.6 8 8 click==8.3.1 9 9 fastapi==0.119.0 10 10 filelock==3.25.2 11 - fsspec==2026.2.0 11 + fsspec==2026.3.0 12 12 h11==0.16.0 13 13 hf-xet==1.4.2 14 - huggingface-hub==0.35.0 14 + httpcore==1.0.9 15 + httpx==0.28.1 16 + huggingface-hub==1.8.0 15 17 idna==3.11 16 18 jinja2==3.1.6 19 + markdown-it-py==4.0.0 17 20 markupsafe==3.0.3 18 - mlx-lm==0.28.3 21 + mdurl==0.1.2 22 + mlx-lm==0.31.0 19 23 mypy-extensions==1.1.0 20 - numpy==2.4.3 24 + numpy==2.4.4 21 25 openai-harmony==0.0.8 22 26 openresponses-types==2.3.0.post1 23 27 packaging==26.0 ··· 26 30 protobuf==7.34.1 27 31 pydantic==2.12.5 28 32 pydantic-core==2.41.5 33 + pygments==2.20.0 29 34 pytokens==0.4.1 30 35 pyyaml==6.0.3 31 - regex==2026.2.28 32 - requests==2.32.5 36 + regex==2026.3.32 37 + rich==14.3.3 33 38 safetensors==0.7.0 39 + sentencepiece==0.2.1 40 + shellingham==1.5.4 34 41 starlette==0.48.0 35 42 tokenizers==0.22.2 36 43 tqdm==4.67.3 37 - transformers==4.57.6 44 + transformers==5.4.0 45 + typer==0.24.1 38 46 typing-extensions==4.15.0 39 47 typing-inspection==0.4.2 40 - urllib3==2.6.3 41 48 uvicorn==0.38.0 42 49 43 50 # Shared packages inherited from other layers 44 - mlx-metal==0.29.3 ; platform_machine == 'arm64' and sys_platform == 'darwin' 45 - mlx==0.29.3 ; platform_machine == 'arm64' and sys_platform == 'darwin' 51 + mlx-metal==0.31.1 ; platform_machine == 'arm64' and sys_platform == 'darwin' 52 + mlx==0.31.1 ; platform_machine == 'arm64' and sys_platform == 'darwin'
+3 -3
server/stack/requirements/app-server/pylock.app-server.meta.json
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+256 -149
server/stack/requirements/app-server/pylock.app-server.toml
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+1 -2
server/stack/requirements/app-server/requirements-app-server.in
··· 2 2 # Relock layer dependencies to update. 3 3 fastapi==0.119.0 4 4 uvicorn==0.38.0 5 - mlx-lm==0.28.3 5 + mlx-lm==0.31.0 6 6 black==25.9.0 7 - huggingface-hub==0.35.0 8 7 openai-harmony==0.0.8 9 8 openresponses-types
+2 -2
server/stack/requirements/framework-mlx/packages-framework-mlx.txt
··· 1 1 # Package summary for framework-mlx 2 2 # Auto-generated by venvstacks (DO NOT EDIT) 3 - mlx==0.29.3 4 - mlx-metal==0.29.3 ; platform_machine == 'arm64' and sys_platform == 'darwin' 3 + mlx==0.31.1 4 + mlx-metal==0.31.1 ; platform_machine == 'arm64' and sys_platform == 'darwin'
+3 -3
server/stack/requirements/framework-mlx/pylock.framework-mlx.meta.json
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+30 -30
server/stack/requirements/framework-mlx/pylock.framework-mlx.toml
··· 7 7 8 8 [[packages]] 9 9 name = "mlx" 10 - version = "0.29.3" 10 + version = "0.31.1" 11 11 index = "https://pypi.org/simple" 12 12 13 13 [[packages.wheels]] 14 - url = "https://files.pythonhosted.org/packages/fe/a2/078152b45aa8a23949a1b09601d0044f8bb4ab85e909e4475a440c21aaea/mlx-0.29.3-cp313-cp313-macosx_13_0_arm64.whl" 15 - upload-time = 2025-10-17T19:17:01Z 16 - size = 549585 14 + url = "https://files.pythonhosted.org/packages/44/45/04465da443634b23fb11670bbd2f7538b1ed43ffc5e0de44a95b3c29e9c1/mlx-0.31.1-cp313-cp313-macosx_14_0_arm64.whl" 15 + upload-time = 2026-03-12T02:16:17Z 16 + size = 574268 17 17 18 18 [packages.wheels.hashes] 19 - sha256 = "d59eccf6a1e1e131becc5a3910504507862da3a4e9b7bd9e73a625515d767844" 19 + sha256 = "9a6d3410fc951bd28508fed9c1ab5d9903f6f6bb101c3a5d63d4191d49a384a1" 20 20 21 21 [[packages.wheels]] 22 - url = "https://files.pythonhosted.org/packages/ae/bb/869eaac4efaae033c13db5fddd6a8907b5d667d135a35a2e482b1af402ee/mlx-0.29.3-cp313-cp313-macosx_14_0_arm64.whl" 23 - 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+1 -1
server/stack/requirements/framework-mlx/requirements-framework-mlx.in
··· 1 1 # DO NOT EDIT. Automatically generated by venvstacks. 2 2 # Relock layer dependencies to update. 3 - mlx==0.29.3 3 + mlx==0.31.1
+2 -3
server/stack/venvstacks.toml
··· 14 14 linux_target = "glibc@2.35" 15 15 macosx_target = "14" 16 16 requirements = [ 17 - "mlx==0.29.3" 17 + "mlx==0.31.1" 18 18 ] 19 19 20 20 [[applications]] ··· 24 24 requirements = [ 25 25 "fastapi==0.119.0", 26 26 "uvicorn==0.38.0", 27 - "mlx-lm==0.28.3", 27 + "mlx-lm==0.31.0", 28 28 "black==25.9.0", 29 - "huggingface-hub==0.35.0", 30 29 "openai-harmony==0.0.8", 31 30 "openresponses-types" 32 31 ]
-163
server/throttled_download_worker.py
··· 1 - import json 2 - import os 3 - import signal 4 - import sys 5 - import time 6 - from typing import Any 7 - 8 - # Global tracking for accurate download rate 9 - _download_stats = { 10 - 'bytes_downloaded': 0, 11 - 'start_time': None, 12 - 'last_update': None, 13 - 'actual_download_time': 0.0 # Time spent actually downloading (without delays) 14 - } 15 - 16 - 17 - def signal_handler(signum: int, frame: Any) -> None: 18 - print("\n[WARNING] Download cancelled by user.") 19 - sys.exit(0) 20 - 21 - signal.signal(signal.SIGINT, signal_handler) 22 - signal.signal(signal.SIGTERM, signal_handler) 23 - 24 - os.environ["HF_HUB_DOWNLOAD_THREADS"] = "1" 25 - os.environ["HF_HUB_DOWNLOAD_CHUNK_SIZE"] = "524288" # 512KB chunks (half size) 26 - os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "false" 27 - 28 - try: 29 - import requests 30 - from huggingface_hub import snapshot_download 31 - except ImportError: 32 - print("[ERROR] huggingface_hub or requests not installed in worker environment!") 33 - sys.exit(2) 34 - 35 - # Throttle all HTTP(S) requests with adaptive delays 36 - original_get = requests.get 37 - original_post = requests.post 38 - 39 - def get_adaptive_delay(url: str, response: Any) -> float: 40 - """Calculate delay based on file type and size""" 41 - if not url: 42 - return 1.0 43 - 44 - # Check if this is a large model file download 45 - if any(ext in url.lower() for ext in ['.safetensors', '.bin', '.pth']): 46 - # For large model files, use more aggressive throttling 47 - content_length = response.headers.get('content-length') 48 - if content_length: 49 - size_mb = int(content_length) / (1024 * 1024) 50 - if size_mb > 100: # Files larger than 100MB 51 - return 3.0 # 3 second delay between chunks 52 - elif size_mb > 10: # Files larger than 10MB 53 - return 2.0 # 2 second delay 54 - return 2.0 # Default for model files 55 - 56 - # Regular files (config.json, tokenizer files, etc.) 57 - return 0.5 58 - 59 - def throttled_get(*args: Any, **kwargs: Any) -> Any: 60 - download_start = time.time() 61 - response = original_get(*args, **kwargs) 62 - download_end = time.time() 63 - 64 - # Track actual download time (without delays) 65 - actual_download_time = download_end - download_start 66 - _download_stats['actual_download_time'] += actual_download_time 67 - 68 - # Track bytes if we can determine them 69 - url = args[0] if args else kwargs.get('url', '') 70 - if hasattr(response, 'headers') and 'content-length' in response.headers: 71 - content_length = int(response.headers['content-length']) 72 - _download_stats['bytes_downloaded'] += content_length 73 - 74 - # Initialize timing if first download 75 - if _download_stats['start_time'] is None: 76 - _download_stats['start_time'] = download_start 77 - 78 - # Print accurate rate every ~5MB or every 10 seconds 79 - now = time.time() 80 - if (_download_stats['last_update'] is None or 81 - now - _download_stats['last_update'] > 10 or 82 - _download_stats['bytes_downloaded'] % (5 * 1024 * 1024) < content_length): 83 - 84 - if _download_stats['actual_download_time'] > 0: 85 - real_rate_mbps = (_download_stats['bytes_downloaded'] / _download_stats['actual_download_time']) / (1024 * 1024) 86 - total_mb = _download_stats['bytes_downloaded'] / (1024 * 1024) 87 - print(f"[THROTTLE] Downloaded {total_mb:.1f}MB at real rate: {real_rate_mbps:.1f}MB/s (excluding delays)") 88 - _download_stats['last_update'] = now 89 - 90 - delay = get_adaptive_delay(url, response) 91 - time.sleep(delay) 92 - return response 93 - 94 - def throttled_post(*args: Any, **kwargs: Any) -> Any: 95 - response = original_post(*args, **kwargs) 96 - time.sleep(0.5) 97 - return response 98 - 99 - requests.get = throttled_get 100 - requests.post = throttled_post 101 - 102 - def main() -> None: 103 - if len(sys.argv) != 2: 104 - print("Usage: python throttled_download_worker.py <kwargs_file.json>") 105 - sys.exit(1) 106 - 107 - kwargs_file = sys.argv[1] 108 - try: 109 - with open(kwargs_file) as f: 110 - kwargs_dict = json.load(f) 111 - except Exception as e: 112 - print(f"[ERROR] Could not read worker kwargs: {e}") 113 - sys.exit(1) 114 - 115 - try: 116 - snapshot_download(**kwargs_dict) 117 - except requests.exceptions.HTTPError as e: 118 - status = getattr(e.response, "status_code", None) 119 - url = getattr(e.response, "url", None) 120 - if status == 401: 121 - print(f"[ERROR] Unauthorized (401): Check your HuggingFace token or login.\nURL: {url}") 122 - sys.exit(10) 123 - elif status == 403: 124 - print(f"[ERROR] Forbidden (403): Access denied.\nURL: {url}") 125 - sys.exit(11) 126 - elif status == 404: 127 - print(f"[ERROR] Not Found (404): Resource does not exist.\nURL: {url}") 128 - sys.exit(12) 129 - else: 130 - print(f"[ERROR] HTTP Error: {e}") 131 - sys.exit(2) 132 - except requests.exceptions.ConnectionError: 133 - print("[ERROR] Network connection error. Please check your internet connection and try again.") 134 - sys.exit(20) 135 - except PermissionError as e: 136 - print(f"[ERROR] Permission denied: {e.filename if hasattr(e, 'filename') else 'check file permissions'}") 137 - print(" Ensure you have write access to the cache directory.") 138 - sys.exit(13) 139 - except OSError as e: 140 - import errno 141 - if e.errno == errno.ENOSPC: 142 - print("[ERROR] No space left on device. Please free up disk space and try again.") 143 - sys.exit(14) 144 - elif e.errno == errno.EACCES: 145 - print(f"[ERROR] Access denied: {e.filename if hasattr(e, 'filename') else 'check permissions'}") 146 - sys.exit(13) 147 - else: 148 - print(f"[ERROR] OS Error during download: {e}") 149 - sys.exit(15) 150 - except Exception as e: 151 - print(f"[ERROR] Unexpected error during download: {type(e).__name__}: {e}") 152 - sys.exit(2) 153 - finally: 154 - try: 155 - os.unlink(kwargs_file) 156 - except Exception: 157 - pass 158 - 159 - sys.exit(0) 160 - 161 - if __name__ == "__main__": 162 - main() 163 -
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+14 -8
tiles/src/main.rs
··· 185 185 } 186 186 #[tokio::main] 187 187 pub async fn main() -> Result<(), Box<dyn Error>> { 188 - env_logger::try_init()?; 188 + build_logger(); 189 189 let cli = Cli::parse(); 190 190 let runtime = build_runtime(); 191 191 match cli.command { ··· 280 280 Ok(()) 281 281 } 282 282 283 - // fn build_logger() -> Result<(), SetLoggerError> { 284 - // let mut env_builder = env_logger::Builder::new(); 285 - // if !cfg!(debug_assertions) { 286 - // env_builder.filter_module("iroh", log::LevelFilter::Off); 287 - // } 288 - // env_builder.try_init() 289 - // } 283 + fn build_logger() { 284 + if cfg!(debug_assertions) { 285 + env_logger::Builder::from_env( 286 + env_logger::Env::default().default_filter_or("info,iroh=error,tracing=off"), 287 + ) 288 + .init() 289 + } else { 290 + env_logger::Builder::from_env( 291 + env_logger::Env::default().default_filter_or("error,iroh=off"), 292 + ) 293 + .init() 294 + } 295 + }
+2
tiles/src/runtime/mlx.rs
··· 553 553 if !memory_mode && content.contains("**[Answer]**") { 554 554 let list_a = content.split("**[Answer]**").collect::<Vec<&str>>(); 555 555 list_a[1].to_owned() 556 + } else if !memory_mode { 557 + content.to_owned() 556 558 } else if content.contains("<reply>") && content.contains("</reply>") { 557 559 let list_a = content.split("<reply>").collect::<Vec<&str>>(); 558 560 let list_b = list_a[1].split("</reply>").collect::<Vec<&str>>();