feat: v1.2.0 - 三项优化

1. 模型选择改为两步式：先搜索选择基模型，再选择量化版本
   - 自动选中默认量化版本(Q4_K_M)，后台可配置
   - 模型新增 base_model 字段，按基模型分组
   - 后台模型管理增加基模型字段

2. 参数搜索改为全局搜索
   - 搜索时跨所有分类显示匹配参数
   - 隐藏分类标签页，显示匹配数量

3. 自然语言支持 LLM 接口
   - 后台可配置 LLM API (URL/Key/Model/System Prompt)
   - 启用后优先调用 LLM 解析，失败自动回退正则解析
   - 兼容 OpenAI API 格式

app.py

@@ -7,6 +7,7 @@ import json
 import re
 import math
 import functools
+import urllib.request
 from flask import Flask, request, jsonify, send_from_directory, session, redirect
 from flask_cors import CORS
 from db import get_db, init_db, DB_PATH
@@ -600,16 +601,86 @@ def get_models():
     db.close()
     return jsonify(result)
 
+@app.route('/api/models/grouped')
+def get_models_grouped():
+    db = get_db()
+    models = db.execute('SELECT * FROM models ORDER BY base_model, sort_order, name').fetchall()
+    db.close()
+    grouped = {}
+    for m in models:
+        d = dict(m)
+        base = d['base_model']
+        if base not in grouped:
+            grouped[base] = []
+        grouped[base].append(d)
+    # Get default quant from settings
+    db2 = get_db()
+    dq = db2.execute("SELECT value FROM settings WHERE key = 'default_quant'").fetchone()
+    db2.close()
+    default_quant = dq['value'] if dq else 'Q4_K_M'
+    return jsonify({'models': grouped, 'default_quant': default_quant})
+
 
 # ----- Parse Natural Language -----
 @app.route('/api/parse-nl', methods=['POST'])
 def parse_nl():
     data = request.json
     text = data.get('text', '')
+    # Try LLM API first if enabled
+    db = get_db()
+    llm_enabled = db.execute("SELECT value FROM settings WHERE key = 'llm_enabled'").fetchone()
+    if llm_enabled and llm_enabled['value'] == 'true':
+        llm_url = db.execute("SELECT value FROM settings WHERE key = 'llm_api_url'").fetchone()
+        llm_key = db.execute("SELECT value FROM settings WHERE key = 'llm_api_key'").fetchone()
+        llm_model = db.execute("SELECT value FROM settings WHERE key = 'llm_api_model'").fetchone()
+        llm_prompt = db.execute("SELECT value FROM settings WHERE key = 'llm_system_prompt'").fetchone()
+        db.close()
+        url = llm_url['value'] if llm_url else ''
+        key = llm_key['value'] if llm_key else ''
+        model = llm_model['value'] if llm_model else ''
+        system_prompt = llm_prompt['value'] if llm_prompt else ''
+        if url:
+            try:
+                result = call_llm_for_parsing(url, key, model, system_prompt, text)
+                if result:
+                    return jsonify(result)
+            except Exception as e:
+                print(f'LLM parse failed: {e}', file=sys.stderr)
+    else:
+        db.close()
+    # Fallback to regex parsing
     result = parse_natural_language(text)
     return jsonify(result)
 
 
+def call_llm_for_parsing(url, key, model, system_prompt, user_text):
+    """Call LLM API to parse natural language into params."""
+    headers = {'Content-Type': 'application/json'}
+    if key:
+        headers['Authorization'] = f'Bearer {key}'
+    body = {
+        'model': model,
+        'messages': [
+            {'role': 'system', 'content': system_prompt},
+            {'role': 'user', 'content': user_text}
+        ],
+        'temperature': 0.1,
+        'max_tokens': 2000,
+    }
+    req = urllib.request.Request(url, data=json.dumps(body).encode('utf-8'), headers=headers, method='POST')
+    with urllib.request.urlopen(req, timeout=30) as resp:
+        data = json.loads(resp.read().decode('utf-8'))
+    # OpenAI-compatible response
+    content = data['choices'][0]['message']['content']
+    # Try to extract JSON from the response
+    content = content.strip()
+    if content.startswith('```'):
+        content = re.sub(r'^```\w*\n?', '', content)
+        content = re.sub(r'\n?```$', '', content)
+    result = json.loads(content)
+    return result
+
+
 # ==================== Admin API ====================
 
     # All admin routes below require login
@@ -800,9 +871,9 @@ def admin_add_model():
     data = request.json
     db = get_db()
     db.execute(
-        '''INSERT INTO models (name, size_gb, layers, embd, kv_heads, head_dim, attention_heads, quant, description, sort_order)
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
-        (data['name'], data['size_gb'], data['layers'], data['embd'],
+        '''INSERT INTO models (base_model, name, size_gb, layers, embd, kv_heads, head_dim, attention_heads, quant, description, sort_order)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
+        (data['base_model'], data['name'], data['size_gb'], data['layers'], data['embd'],
          data['kv_heads'], data['head_dim'], data['attention_heads'],
          data.get('quant', ''), data.get('description', ''), data.get('sort_order', 0))
     )
@@ -818,9 +889,9 @@ def admin_model_edit(mid):
     if request.method == 'PUT':
         data = request.json
         db.execute(
-            '''UPDATE models SET name=?, size_gb=?, layers=?, embd=?, kv_heads=?,
+            '''UPDATE models SET base_model=?, name=?, size_gb=?, layers=?, embd=?, kv_heads=?,
             head_dim=?, attention_heads=?, quant=?, description=?, sort_order=? WHERE id=?''',
-            (data['name'], data['size_gb'], data['layers'], data['embd'],
+            (data['base_model'], data['name'], data['size_gb'], data['layers'], data['embd'],
              data['kv_heads'], data['head_dim'], data['attention_heads'],
              data.get('quant', ''), data.get('description', ''), data.get('sort_order', 0), mid)
         )