mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-10-23 02:00:23 +08:00
skqliao
a052fc3809
- Redesign kt run with 8-step interactive flow (model selection, inference method, NUMA/CPU, GPU experts, KV cache, GPU/TP selection, parsers, host/port) - Add configuration save/load system (~/.ktransformers/run_configs.yaml) - Add i18n support for kt chat (en/zh translations) - Add universal input validators with auto-retry and Chinese comma support - Add port availability checker with auto-suggestion - Add parser configuration (--tool-call-parser, --reasoning-parser) - Remove tuna command and clean up redundant files - Fix: variable reference bug in run.py, filter to show only MoE models
112 lines
3.3 KiB
Python
112 lines
3.3 KiB
Python
"""
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Configuration save/load for kt run command.
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Manages saved run configurations bound to specific models.
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"""
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from pathlib import Path
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from typing import Dict, List, Optional, Any
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from datetime import datetime
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import yaml
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CONFIG_FILE = Path.home() / ".ktransformers" / "run_configs.yaml"
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class RunConfigManager:
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"""Manager for saved run configurations."""
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def __init__(self):
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self.config_file = CONFIG_FILE
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self._ensure_config_file()
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def _ensure_config_file(self):
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"""Ensure config file exists."""
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if not self.config_file.exists():
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self.config_file.parent.mkdir(parents=True, exist_ok=True)
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self._save_data({"version": "1.0", "configs": {}})
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def _load_data(self) -> Dict:
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"""Load raw config data."""
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try:
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with open(self.config_file, "r", encoding="utf-8") as f:
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return yaml.safe_load(f) or {"version": "1.0", "configs": {}}
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except Exception:
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return {"version": "1.0", "configs": {}}
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def _save_data(self, data: Dict):
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"""Save raw config data."""
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with open(self.config_file, "w", encoding="utf-8") as f:
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yaml.dump(data, f, allow_unicode=True, default_flow_style=False)
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def list_configs(self, model_id: str) -> List[Dict[str, Any]]:
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"""List all saved configs for a model.
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Returns:
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List of config dicts with 'config_name' and other fields.
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"""
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data = self._load_data()
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configs = data.get("configs", {}).get(model_id, [])
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return configs if isinstance(configs, list) else []
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def save_config(self, model_id: str, config: Dict[str, Any]):
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"""Save a configuration for a model.
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Args:
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model_id: Model ID to bind config to
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config: Configuration dict with all run parameters
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"""
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data = self._load_data()
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if "configs" not in data:
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data["configs"] = {}
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if model_id not in data["configs"]:
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data["configs"][model_id] = []
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# Add timestamp
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config["created_at"] = datetime.now().isoformat()
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# Append config
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data["configs"][model_id].append(config)
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self._save_data(data)
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def delete_config(self, model_id: str, config_index: int) -> bool:
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"""Delete a saved configuration.
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Args:
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model_id: Model ID
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config_index: Index of config to delete (0-based)
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Returns:
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True if deleted, False if not found
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"""
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data = self._load_data()
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if model_id not in data.get("configs", {}):
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return False
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configs = data["configs"][model_id]
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if config_index < 0 or config_index >= len(configs):
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return False
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configs.pop(config_index)
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self._save_data(data)
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return True
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def get_config(self, model_id: str, config_index: int) -> Optional[Dict[str, Any]]:
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"""Get a specific saved configuration.
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Args:
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model_id: Model ID
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config_index: Index of config to get (0-based)
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Returns:
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Config dict or None if not found
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"""
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configs = self.list_configs(model_id)
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if config_index < 0 or config_index >= len(configs):
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return None
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return configs[config_index]
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