yumoqing
9aa917bce5
- Add data_filter with 4 searchable fields (name LIKE, model LIKE, providerid, upappid) - Add filter_labels for search form display - Create llm_list.dspy with DBFilter support and LIKE wildcard handling - Create llm_create.dspy, llm_update.dspy, llm_delete.dspy - Create get_organizations.dspy and get_upapps.dspy for dropdown options - Add browserfields alters for providerid and upappid dropdowns - Add editable URLs for DataViewer CRUD operations
79 lines
2.7 KiB
Python
79 lines
2.7 KiB
Python
#!/usr/bin/env python3
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import json
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from sqlor.filter import DBFilter
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result = {'success': False, 'rows': [], 'total': 0}
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try:
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dbname = get_module_dbname('llmage')
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page = int(params_kw.get('page', 1))
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rows_per_page = int(params_kw.get('rows', 20))
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offset = (page - 1) * rows_per_page
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# Get data_filter JSON from frontend
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filterjson_str = params_kw.get('data_filter')
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filterjson = None
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if filterjson_str:
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try:
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filterjson = json.loads(filterjson_str)
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except (json.JSONDecodeError, TypeError):
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filterjson = None
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async with DBPools().sqlorContext(dbname) as sor:
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where_clause = ''
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filterdic = {}
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if filterjson:
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# Preprocess LIKE values: add wildcards if user didn't provide them
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ns = dict(params_kw)
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for key, val in ns.items():
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# Check if this var is used with LIKE op in filterjson
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if _is_like_var(filterjson, key) and val and '%' not in val:
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ns[key] = f'%{val}%'
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dbf = DBFilter(filterjson)
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conds = dbf.gen(ns)
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if conds:
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where_clause = f' WHERE {conds}'
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filterdic = ns
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# Total count
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count_sql = f"select count(*) as cnt from llm{where_clause}"
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count_rows = await sor.sqlExe(count_sql, filterdic)
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total = count_rows[0]['cnt'] if count_rows else 0
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# Paginated data
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data_sql = f"""
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select id, name, model, description, iconid, upappid, providerid,
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ownerid, enabled_date, expired_date, min_balance
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from llm{where_clause}
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order by model
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limit ${limit}$ offset ${offset}$
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"""
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rows = await sor.sqlExe(data_sql, {**filterdic, 'limit': rows_per_page, 'offset': offset})
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result['rows'] = [dict(r) for r in (rows or [])]
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result['total'] = total
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result['success'] = True
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except Exception as e:
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result['error'] = str(e)
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return json.dumps(result, ensure_ascii=False, default=str)
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def _is_like_var(filterjson, varname):
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"""Check if a var is used with LIKE operator in the filter tree."""
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if not filterjson:
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return False
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for key, val in filterjson.items():
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if key.upper() in ('AND', 'OR') and isinstance(val, list):
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for item in val:
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if _is_like_var(item, varname):
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return True
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elif key.upper() == 'NOT' and isinstance(val, dict):
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if _is_like_var(val, varname):
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return True
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elif isinstance(val, dict) and val.get('var') == varname:
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if val.get('op', '').upper() == 'LIKE':
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return True
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return False
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