kt-cli enhancement (#1834)

* [feat]: redesign kt run interactive configuration with i18n support

- 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

* [feat]: unify model selection UI and enable shared experts fusion by default

- Unify kt run model selection table with kt model list display
  * Add Total size, MoE Size, Repo, and SHA256 status columns
  * Use consistent formatting and styling
  * Improve user decision-making with more information

- Enable --disable-shared-experts-fusion by default
  * Change default value from False to True
  * Users can still override with --enable-shared-experts-fusion

* [feat]: improve kt chat with performance metrics and better CJK support

- Add performance metrics display after each response
  * Total time, TTFT (Time To First Token), TPOT (Time Per Output Token)
  * Accurate input/output token counts using model tokenizer
  * Fallback to estimation if tokenizer unavailable
  * Metrics shown in dim style (not prominent)

- Fix Chinese character input issues
  * Replace Prompt.ask() with console.input() for better CJK support
  * Fixes backspace deletion showing half-characters

- Suppress NumPy subnormal warnings
  * Filter "The value of the smallest subnormal" warnings
  * Cleaner CLI output on certain hardware environments

* [fix]: correct TTFT measurement in kt chat

- Move start_time initialization before API call
- Previously start_time was set when receiving first chunk, causing TTFT ≈ 0ms
- Now correctly measures time from request sent to first token received

* [docs]: 添加 Clawdbot 集成指南 - KTransformers 企业级 AI 助手部署方案

* [docs]: 强调推荐使用 Kimi K2.5 作为核心模型，突出企业级推理能力

* [docs]: 添加 Clawdbot 飞书接入教程链接

* [feat]: improve CLI table display, model verification, and chat experience

- Add sequence number (#) column to all model tables by default
- Filter kt edit to show only MoE GPU models (exclude AMX)
- Extend kt model verify to check *.json and *.py files in addition to weights
- Fix re-verification bug where repaired files caused false failures
- Suppress tokenizer debug output in kt chat token counting

* [fix]: fix cpu cores.

---------

Co-authored-by: skqliao <skqliao@gmail.com>

kt-kernel/python/cli/utils/run_configs.py

@@ -0,0 +1,111 @@
+"""
+Configuration save/load for kt run command.
+
+Manages saved run configurations bound to specific models.
+"""
+
+from pathlib import Path
+from typing import Dict, List, Optional, Any
+from datetime import datetime
+import yaml
+
+
+CONFIG_FILE = Path.home() / ".ktransformers" / "run_configs.yaml"
+
+
+class RunConfigManager:
+    """Manager for saved run configurations."""
+
+    def __init__(self):
+        self.config_file = CONFIG_FILE
+        self._ensure_config_file()
+
+    def _ensure_config_file(self):
+        """Ensure config file exists."""
+        if not self.config_file.exists():
+            self.config_file.parent.mkdir(parents=True, exist_ok=True)
+            self._save_data({"version": "1.0", "configs": {}})
+
+    def _load_data(self) -> Dict:
+        """Load raw config data."""
+        try:
+            with open(self.config_file, "r", encoding="utf-8") as f:
+                return yaml.safe_load(f) or {"version": "1.0", "configs": {}}
+        except Exception:
+            return {"version": "1.0", "configs": {}}
+
+    def _save_data(self, data: Dict):
+        """Save raw config data."""
+        with open(self.config_file, "w", encoding="utf-8") as f:
+            yaml.dump(data, f, allow_unicode=True, default_flow_style=False)
+
+    def list_configs(self, model_id: str) -> List[Dict[str, Any]]:
+        """List all saved configs for a model.
+
+        Returns:
+            List of config dicts with 'config_name' and other fields.
+        """
+        data = self._load_data()
+        configs = data.get("configs", {}).get(model_id, [])
+        return configs if isinstance(configs, list) else []
+
+    def save_config(self, model_id: str, config: Dict[str, Any]):
+        """Save a configuration for a model.
+
+        Args:
+            model_id: Model ID to bind config to
+            config: Configuration dict with all run parameters
+        """
+        data = self._load_data()
+
+        if "configs" not in data:
+            data["configs"] = {}
+
+        if model_id not in data["configs"]:
+            data["configs"][model_id] = []
+
+        # Add timestamp
+        config["created_at"] = datetime.now().isoformat()
+
+        # Append config
+        data["configs"][model_id].append(config)
+
+        self._save_data(data)
+
+    def delete_config(self, model_id: str, config_index: int) -> bool:
+        """Delete a saved configuration.
+
+        Args:
+            model_id: Model ID
+            config_index: Index of config to delete (0-based)
+
+        Returns:
+            True if deleted, False if not found
+        """
+        data = self._load_data()
+
+        if model_id not in data.get("configs", {}):
+            return False
+
+        configs = data["configs"][model_id]
+        if config_index < 0 or config_index >= len(configs):
+            return False
+
+        configs.pop(config_index)
+        self._save_data(data)
+        return True
+
+    def get_config(self, model_id: str, config_index: int) -> Optional[Dict[str, Any]]:
+        """Get a specific saved configuration.
+
+        Args:
+            model_id: Model ID
+            config_index: Index of config to get (0-based)
+
+        Returns:
+            Config dict or None if not found
+        """
+        configs = self.list_configs(model_id)
+        if config_index < 0 or config_index >= len(configs):
+            return None
+        return configs[config_index]