++

generated_alpha/2026/01/03/162703.txt

@@ -0,0 +1,39 @@
+multiply(ts_delta(divide(fn_treasury_stock_shares_a, ts_mean(fn_treasury_stock_shares_a, 60)), 10), ts_rank(ts_zscore(nws12_allz_result2, 20), 100))
+
+subtract(group_rank(ts_mean(fnd2_a_frtandfixturesg, 30), pv13_h_min2_focused_sector), rank(ts_delta(nws12_mainz_tonhigh, 5)))
+
+multiply(ts_av_diff(fn_def_tax_assets_liab_net_q, 40), power(ts_corr(fn_liab_fair_val_a, nws12_afterhsz_tonhigh, 20), 2))
+
+add(ts_scale(ts_sum(news_max_up_amt, 10), 5), reverse(ts_regression(fn_comp_not_rec_stock_options_q, fscore_bfl_total, 30, 0, 0)))
+
+if_else(ts_arg_min(fn_def_tax_liab_a, 15) > 5, ts_backfill(multi_factor_acceleration_score_derivative, 8), ts_delay(nws18_sse, 3))
+
+group_neutralize(ts_rank(ts_decay_linear(rp_nip_ratings, 10), pv13_h_min52_1k_sector), pv13_h_min24_500_sector)
+
+multiply(sign(ts_delta(anl4_netdebt_flag, 8)), sqrt(ts_count_nans(fn_comp_not_rec_stock_options_a, 25)))
+
+subtract(ts_mean(group_zscore(fnd2_a_frtandfixturesg, pv13_h_min22_1000_sector), 20), ts_quantile(news_max_up_amt, 15))
+
+add(ts_step(1), multiply(ts_covariance(nws12_allz_result2, fn_treasury_stock_shares_a, 30), hump(ts_std_dev(fscore_bfl_total, 10))))
+
+if_else(ts_breakout(fn_def_tax_assets_liab_net_q, 8) > 0.15, reverse(ts_zscore(fn_liab_fair_val_a, 20)), ts_mean(rp_nip_ratings, 10))
+
+multiply(ts_backfill(fn_comp_not_rec_stock_options_q, 5), power(ts_rank(ts_delay(nws18_sse, 2), 50), ts_arg_max(fn_def_tax_liab_a, 12)))
+
+group_scale(ts_sum(ts_av_diff(multi_factor_acceleration_score_derivative, 15), pv13_h_min2_1k_sector), pv13_h_min2_focused_sector)
+
+subtract(ts_product(ts_delta(anl4_netdebt_flag, 6), 10), rank(ts_corr(nws12_mainz_tonhigh, news_max_up_amt, 25)))
+
+add(zscore(ts_mean(fnd2_a_frtandfixturesg, 40)), ts_scale(ts_rank(ts_decay_linear(fscore_bfl_total, 8), 60), 2))
+
+multiply(signed_power(ts_regression(fn_treasury_stock_shares_a, nws12_afterhsz_tonhigh, 20, 0, 1), 0.5), group_mean(ts_zscore(rp_nip_ratings, 15), 1, pv13_h_min24_500_sector))
+
+if_else(ts_count_nans(fn_liab_fair_val_a, 10) < 5, ts_sum(ts_delta(fn_comp_not_rec_stock_options_a, 4), 8), reverse(ts_mean(nws12_allz_result2, 15)))
+
+subtract(ts_rank(ts_std_dev(multi_factor_acceleration_score_derivative, 20), 30), quantile(ts_backfill(anl4_netdebt_flag, 12)))
+
+multiply(ts_delay(ts_covariance(fn_def_tax_assets_liab_net_q, nws18_sse, 18), 2), sqrt(ts_scale(ts_sum(fnd2_a_frtandfixturesg, 10), 3)))
+
+add(group_zscore(ts_mean(fn_treasury_stock_shares_a, 25), pv13_h_min52_1k_sector), power(ts_av_diff(rp_nip_ratings, 12), 2))
+
+subtract(ts_quantile(ts_delta(news_max_up_amt, 6), 15), rank(ts_breakout(fn_comp_not_rec_stock_options_q, 8)))

generated_alpha/2026/01/03/162729.txt

@@ -0,0 +1,39 @@
+ts_delta(divide(fn_def_tax_assets_liab_net_q, add(fn_def_tax_assets_liab_net_q, fn_def_tax_liab_a)), 8)
+
+ts_rank(ts_delta(fn_liab_fair_val_a, 4), 20)
+
+group_zscore(ts_sum(fn_comp_not_rec_stock_options_a, 12), pv13_h_min2_focused_sector)
+
+ts_mean(ts_delta(fn_treasury_stock_shares_a, 4), 8)
+
+ts_corr(ts_delay(fn_def_tax_liab_a, 4), ts_delta(fn_def_tax_assets_liab_net_q, 4), 12)
+
+ts_scale(ts_delta(fn_comp_not_rec_stock_options_q, 8), 16)
+
+group_neutralize(ts_zscore(fn_liab_fair_val_a, 20), pv13_h_min52_1k_sector)
+
+ts_regression(fn_def_tax_assets_liab_net_q, ts_delay(fn_def_tax_liab_a, 4), 12, 0, 0)
+
+ts_av_diff(ts_delay(fn_comp_not_rec_stock_options_a, 2), 8)
+
+ts_quantile(ts_delta(fn_treasury_stock_shares_a, 4), 12, "uniform")
+
+ts_std_dev(ts_delta(fn_def_tax_assets_liab_net_q, 4), 8)
+
+group_rank(ts_sum(fn_liab_fair_val_a, 4), pv13_h_min24_500_sector)
+
+ts_decay_linear(ts_delta(fn_def_tax_liab_a, 4), 12, false)
+
+ts_product(ts_arg_max(fn_comp_not_rec_stock_options_q, 12), 4)
+
+ts_count_nans(ts_delta(fn_treasury_stock_shares_a, 4), 8)
+
+ts_covariance(fn_def_tax_assets_liab_net_q, fn_def_tax_liab_a, 12)
+
+ts_step(1)
+
+ts_backfill(ts_delta(fn_liab_fair_val_a, 4), 8, 1, "NAN")
+
+ts_rank(ts_mean(ts_delta(fn_comp_not_rec_stock_options_a, 4), 4), 20)
+
+group_scale(ts_delta(fn_def_tax_assets_liab_net_q, 8), pv13_h_min22_1000_sector)

generated_alpha/2026/01/04/093236.txt

@@ -0,0 +1,25 @@
+reverse(ts_delta(customer_acquisition_cost, 63))
+multiply(ts_delta(customer_acquisition_cost, 63), reverse(ts_mean(customer_acquisition_cost, 126)))
+divide(ts_delta(customer_acquisition_cost, 63), ts_std_dev(customer_acquisition_cost, 126))
+subtract(ts_delta(customer_acquisition_cost, 63), ts_mean(customer_acquisition_cost, 252))
+
+if_else(ts_delta(customer_acquisition_cost, 63) > multiply(ts_mean(customer_acquisition_cost, 126), 1.2), -1, ts_delta(customer_acquisition_cost, 63))
+multiply(ts_delta(customer_acquisition_cost, 63), sign(subtract(ts_delta(customer_acquisition_cost, 63), ts_mean(customer_acquisition_cost, 252))))
+
+ts_zscore(ts_delta(customer_acquisition_cost, 63), 126)
+multiply(ts_rank(customer_acquisition_cost, 63), reverse(ts_delta(customer_acquisition_cost, 63)))
+add(ts_delta(customer_acquisition_cost, 63), multiply(ts_mean(customer_acquisition_cost, 126), -1))
+
+power(ts_delta(customer_acquisition_cost, 63), 0.5)
+multiply(ts_delta(customer_acquisition_cost, 63), log(ts_mean(customer_acquisition_cost, 126)))
+divide(ts_delta(customer_acquisition_cost, 63), ts_sum(customer_acquisition_cost, 126))
+subtract(ts_delta(customer_acquisition_cost, 63), ts_min(customer_acquisition_cost, 252))
+
+multiply(ts_delta(customer_acquisition_cost, 63), if_else(ts_delta(customer_acquisition_cost, 63) > 0, -1, 1))
+ts_scale(ts_delta(customer_acquisition_cost, 63), 126)
+multiply(ts_delta(customer_acquisition_cost, 63), reverse(ts_zscore(customer_acquisition_cost, 126)))
+
+add(ts_delta(customer_acquisition_cost, 63), multiply(ts_std_dev(customer_acquisition_cost, 126), -1))
+divide(ts_delta(customer_acquisition_cost, 63), ts_max(customer_acquisition_cost, 252))
+multiply(ts_delta(customer_acquisition_cost, 63), sqrt(ts_mean(customer_acquisition_cost, 126)))
+reverse(ts_sum(ts_delta(customer_acquisition_cost, 21), 3))

generated_alpha/2026/01/04/093304.txt

@@ -0,0 +1,39 @@
+ts_delta(customer_acquisition_cost, 63)
+
+ts_delta(customer_acquisition_cost, 63) > ts_mean(ts_delta(customer_acquisition_cost, 63), 189) * 1.2
+
+-1 * if_else(ts_delta(customer_acquisition_cost, 63) > ts_mean(ts_delta(customer_acquisition_cost, 63), 189) * 1.2, 1, 0)
+
+bucket(rank(customer_acquisition_cost), buckets="2,5,6,7,10")
+
+group_zscore(ts_delta(customer_acquisition_cost, 63), market_penetration_group)
+
+group_rank(ts_delta(customer_acquisition_cost, 63), market_penetration_group)
+
+group_scale(ts_delta(customer_acquisition_cost, 63), market_penetration_group)
+
+ts_zscore(ts_delta(customer_acquisition_cost, 63), 189)
+
+ts_rank(ts_delta(customer_acquisition_cost, 63), 189)
+
+ts_scale(ts_delta(customer_acquisition_cost, 63), 189)
+
+group_neutralize(ts_delta(customer_acquisition_cost, 63), market_penetration_group)
+
+multiply(ts_delta(customer_acquisition_cost, 63), -1, filter=true)
+
+ts_av_diff(customer_acquisition_cost, 189)
+
+divide(ts_delta(customer_acquisition_cost, 63), ts_mean(customer_acquisition_cost, 189))
+
+ts_std_dev(ts_delta(customer_acquisition_cost, 63), 189)
+
+ts_corr(ts_delta(customer_acquisition_cost, 63), ts_delta(forward_price_120, 63), 189)
+
+ts_regression(ts_delta(customer_acquisition_cost, 63), ts_delta(forward_price_120, 63), 189, rettype=0)
+
+ts_decay_linear(ts_delta(customer_acquisition_cost, 63), 189, dense=false)
+
+group_backfill(ts_delta(customer_acquisition_cost, 63), market_penetration_group, 189)
+
+ts_quantile(ts_delta(customer_acquisition_cost, 63), 189, driver="gaussian")

generated_alpha/2026/01/04/153654.txt

@@ -0,0 +1,20 @@
+ts_backfill(fnd6_newa2v1300_oiadp, 60)
+multiply(ts_delta(fnd6_newqeventv110_cipenq, 5), ts_rank(ts_zscore(fnd6_newqv1300_cipenq, 30), 10))
+group_neutralize(ts_mean(fscore_total, 20), vec_avg(multi_factor_acceleration_score_derivative))
+subtract(ts_av_diff(nws12_afterhsz_tonhigh, 10), ts_av_diff(nws12_allz_result2, 10))
+divide(ts_sum(nws12_mainz_tonhigh, 15), ts_std_dev(rp_nip_ratings, 15))
+add(power(fn_comp_not_rec_a, 0.5), sqrt(abs(fn_comp_not_rec_stock_options_a)))
+max(ts_delay(fn_comp_not_rec_stock_options_q, 3), ts_delay(fn_def_tax_assets_liab_net_q, 3))
+if_else(ts_rank(fn_entity_common_stock_shares_out_a, 20) > 0.5, fn_entity_common_stock_shares_out_q, 0)
+ts_corr(fn_liab_fair_val_a, fn_liab_fair_val_l1_a, 30)
+min(ts_product(fn_liab_fair_val_l1_q, 5), ts_product(fn_liab_fair_val_l2_a, 5))
+reverse(ts_regression(fn_liab_fair_val_l2_q, fn_oth_income_loss_fx_transaction_and_tax_translation_adj_q, 20, 0, 1))
+signed_power(ts_delta(fn_treasury_stock_shares_a, 10), ts_scale(fnd2_a_fedstyitxrt, 10))
+group_zscore(ts_backfill(forward_price_120, 30), bucket(rank(ts_mean(fscore_total, 20)), range="0,1,0.2"))
+ts_decay_linear(multi_factor_acceleration_score_derivative, 10, true)
+quantile(ts_covariance(nws12_afterhsz_tonhigh, nws12_allz_result2, 15), "gaussian", 1.0)
+trade_when(ts_step(1) > 5, ts_arg_max(nws12_mainz_tonhigh, 10), rp_nip_ratings)
+vec_sum(kth_element(fn_comp_not_rec_a, 5, 2))
+hump(ts_count_nans(fn_comp_not_rec_stock_options_a, 20), 0.01)
+winsorize(days_from_last_change(fn_comp_not_rec_stock_options_q), 3)
+last_diff_value(fn_def_tax_assets_liab_net_q, 7)

generated_alpha/2026/01/04/153729.txt

@@ -0,0 +1,39 @@
+ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN")
+
+divide(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), group_mean(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), sector))
+
+ts_delta(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 20)
+
+group_zscore(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), industry)
+
+ts_rank(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 126)
+
+ts_zscore(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 63)
+
+group_scale(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), industry)
+
+ts_decay_linear(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 90, dense=false)
+
+ts_mean(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 60)
+
+ts_std_dev(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 120)
+
+ts_corr(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), forward_price_120, 90)
+
+ts_quantile(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 252, driver="gaussian")
+
+ts_arg_max(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 180)
+
+ts_arg_min(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 180)
+
+ts_scale(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 252, constant=0)
+
+group_neutralize(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), subindustry)
+
+ts_av_diff(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 90)
+
+hump(ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), hump=0.01)
+
+ts_regression(forward_price_120, ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN"), 120, lag=0, rettype=0)
+
+multi_factor_acceleration_score_derivative * ts_backfill(digital_supply_chain_index, lookback=252, k=1, ignore="NAN")

generated_alpha/2026/01/04/161557.txt

@@ -0,0 +1,39 @@
+ts_backfill(fnd6_newa2v1300_oiadp, 250, 1)
+ts_backfill(fn_entity_common_stock_shares_out_q, 250, 1)
+ts_backfill(fn_treasury_stock_shares_a, 250, 1)
+
+divide(ts_backfill(fnd6_newa2v1300_oiadp, 250, 1), group_mean(ts_backfill(fnd6_newa2v1300_oiadp, 250, 1), 1, bucket(fn_comp_not_rec_a, buckets = "2,5,6,7,10")))
+
+ts_delta(ts_backfill(fn_liab_fair_val_l1_q, 250, 1), 60)
+
+ts_rank(divide(fn_comp_not_rec_stock_options_a, fn_entity_common_stock_shares_out_q), 120, 0)
+
+group_zscore(ts_backfill(fn_def_tax_assets_liab_net_q, 250, 1), bucket(ts_backfill(fn_treasury_stock_shares_a, 250, 1), buckets = "2,5,6,7,10"))
+
+ts_corr(ts_backfill(fn_liab_fair_val_l2_a, 250, 1), ts_backfill(fn_liab_fair_val_l1_a, 250, 1), 60)
+
+multiply(sign(ts_delta(ts_backfill(fnd6_newqv1300_cipenq, 250, 1), 30)), ts_std_dev(ts_backfill(fn_comp_not_rec_stock_options_q, 250, 1), 60))
+
+if_else(ts_backfill(fscore_total, 250, 1) > group_mean(ts_backfill(fscore_total, 250, 1), 1, bucket(fn_comp_not_rec_a, buckets = "2,5,6,7,10")), ts_sum(ts_backfill(multi_factor_acceleration_score_derivative, 250, 1), 30), reverse(ts_sum(ts_backfill(multi_factor_acceleration_score_derivative, 250, 1), 30)))
+
+subtract(ts_mean(ts_backfill(nws12_afterhsz_tonhigh, 250, 1), 60), ts_mean(ts_backfill(nws12_mainz_tonhigh, 250, 1), 60))
+
+ts_av_diff(ts_backfill(rp_nip_ratings, 250, 1), 30)
+
+add(ts_backfill(fn_oth_income_loss_fx_transaction_and_tax_translation_adj_q, 250, 1), ts_backfill(fnd2_a_fedstyitxrt, 250, 1))
+
+power(divide(ts_backfill(fn_entity_common_stock_shares_out_a, 250, 1), ts_backfill(fn_treasury_stock_shares_a, 250, 1)), 0.5)
+
+ts_zscore(ts_backfill(fn_liab_fair_val_a, 250, 1), 120)
+
+group_neutralize(ts_backfill(forward_price_120, 250, 1), bucket(ts_backfill(fn_comp_not_rec_stock_options_a, 250, 1), buckets = "2,5,6,7,10"))
+
+ts_regression(ts_backfill(fnd6_newa2v1300_oiadp, 250, 1), ts_backfill(fn_entity_common_stock_shares_out_q, 250, 1), 60, 0, 1)
+
+log(divide(ts_backfill(fn_def_tax_assets_liab_net_q, 250, 1), ts_backfill(fn_comp_not_rec_a, 250, 1)))
+
+ts_scale(ts_backfill(nws12_allz_result2, 250, 1), 60, 0.01)
+
+signed_power(ts_delta(ts_backfill(fscore_total, 250, 1), 30), 2)
+
+inverse(ts_mean(ts_backfill(fn_liab_fair_val_l2_q, 250, 1), 60))

generated_alpha/2026/01/04/161726.txt

@@ -0,0 +1,39 @@
+ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1)
+
+divide(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), ts_mean(fnd6_newa2v1300_oiadp, 60))
+
+ts_delta(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 5)
+
+ts_rank(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 60)
+
+ts_zscore(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 30)
+
+group_mean(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), sector, industry)
+
+group_neutralize(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), industry)
+
+group_scale(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), sector)
+
+group_zscore(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), industry)
+
+ts_decay_linear(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 10)
+
+ts_corr(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), ts_delay(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 1), 20)
+
+ts_quantile(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 60, driver="gaussian")
+
+ts_scale(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 30)
+
+ts_std_dev(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 20)
+
+ts_sum(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 10)
+
+ts_av_diff(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 20)
+
+ts_arg_max(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 30)
+
+ts_arg_min(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 30)
+
+ts_regression(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), ts_delay(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), 1), 20, rettype=0)
+
+group_backfill(ts_backfill(fnd6_newa2v1300_oiadp, lookback=20, k=1), industry, 20, std=4)

main.py

@@ -22,7 +22,7 @@ SILICONFLOW_BASE_URL = "https://api.siliconflow.cn/v1"
 MODELS = [
     'Pro/deepseek-ai/DeepSeek-V3.1-Terminus',
     # 'deepseek-ai/DeepSeek-V3.2-Exp',
-    # 'Qwen/Qwen3-VL-235B-A22B-Instruct',
+    'Qwen/Qwen3-VL-235B-A22B-Instruct',
     # 'MiniMaxAI/MiniMax-M2',
     # 'zai-org/GLM-4.6',
     # 'inclusionAI/Ring-flash-2.0',
@@ -31,12 +31,13 @@ MODELS = [
     # 'inclusionAI/Ring-flash-2.0',
 ]
 
+
 def process_text(text):
     filter_list = ['\n', '\t', '\r', '\b', '\f', '\v', '：', '的', '或', '10', '天', '了', '可', '是', '该', '，', ' ', '、', '让', '和', '集',
-                   '/', '日', '在', '（', '_', '-', ')', '(', '上', '距', '与', '比', '下', '及', '）', '...', '；', '%', '&', '+', ',', '.', 
+                   '/', '日', '在', '（', '_', '-', ')', '(', '上', '距', '与', '比', '下', '及', '）', '...', '；', '%', '&', '+', ',', '.',
                    ':', ';', '<', '=', '>', '?', '[', ']', '|', '—', '。'
-    ]
-    
+                   ]
+
     text_list = jieba.lcut(text)
     results = []
     for tl in text_list:
@@ -53,6 +54,7 @@ def process_text(text):
     else:
         return None
 
+
 def load_keys_text():
     if not os.path.exists(KEYS_TEXT):
         print(f"文件不存在: {KEYS_TEXT}")
@@ -69,6 +71,7 @@ def load_keys_text():
 
         return result_str
 
+
 def txtFileLoader(file_path):
     if not os.path.exists(file_path):
         print(f"文件不存在: {file_path}")
@@ -81,9 +84,9 @@ def csvFileLoader(file_path, keys_text):
     if not os.path.exists(file_path):
         print(f"文件不存在: {file_path}")
         exit(1)
-    
+
     data_dict = {}  # 使用字典来存储，以id为键
-    
+
     with open(file_path, 'r', encoding='utf-8') as f:
         reader = csv.reader(f)
         for row in reader:
@@ -98,7 +101,7 @@ def csvFileLoader(file_path, keys_text):
                             'description': row[2],
                             'description_cn': row[11],
                         }
-    
+
     # 将字典的值转换为列表
     return list(data_dict.values())
 
@@ -131,7 +134,20 @@ def create_result_folder():
     folder_name = "generated_alpha"
     if not os.path.exists(folder_name):
         os.makedirs(folder_name)
-    return folder_name
+
+    now = datetime.now()
+    year_folder = os.path.join(folder_name, str(now.year))
+    month_folder = os.path.join(year_folder, f"{now.month:02d}")
+    day_folder = os.path.join(month_folder, f"{now.day:02d}")
+
+    if not os.path.exists(year_folder):
+        os.makedirs(year_folder)
+    if not os.path.exists(month_folder):
+        os.makedirs(month_folder)
+    if not os.path.exists(day_folder):
+        os.makedirs(day_folder)
+
+    return day_folder
 
 
 def call_siliconflow(prompt, model):
@@ -161,16 +177,10 @@ def call_siliconflow(prompt, model):
 
 def save_result(result, folder):
     now = datetime.now()
-    date_folder = now.strftime("%Y-%m-%d")
     time_filename = now.strftime("%H%M%S")
-    full_folder_path = os.path.join(folder, date_folder)
-
-    if not os.path.exists(full_folder_path):
-        os.makedirs(full_folder_path)
-        print(f"创建文件夹: {full_folder_path}")
 
     filename = f"{time_filename}.txt"
-    filepath = os.path.join(full_folder_path, filename)
+    filepath = os.path.join(folder, filename)
 
     with open(filepath, 'w', encoding='utf-8') as f:
         f.write(result)
@@ -193,12 +203,22 @@ def manual_prompt(prompt):
 
     if not os.path.exists(manual_prompt_path):
         os.makedirs(manual_prompt_path)
-        print(f"创建文件夹: {manual_prompt_path}")
 
-    # 文件名后添加保存时间
     now = datetime.now()
+    year_folder = os.path.join(manual_prompt_path, str(now.year))
+    month_folder = os.path.join(year_folder, f"{now.month:02d}")
+    day_folder = os.path.join(month_folder, f"{now.day:02d}")
+
+    if not os.path.exists(year_folder):
+        os.makedirs(year_folder)
+    if not os.path.exists(month_folder):
+        os.makedirs(month_folder)
+    if not os.path.exists(day_folder):
+        os.makedirs(day_folder)
+
+    # 文件名后添加保存时间
     filename = f"manual_prompt_{now.strftime('%Y%m%d%H%M%S')}.txt"
-    filepath = os.path.join(manual_prompt_path, filename)
+    filepath = os.path.join(day_folder, filename)
 
     with open(filepath, 'w', encoding='utf-8') as f:
         f.write(prompt)
@@ -264,7 +284,6 @@ def main():
         print(f'搜索数据集为空, 程序退出')
         exit(1)
 
-
     data_sets = 0
     print(f'从数据集中提取了 {len(result_data_sets)} 条数据')
     if len(result_data_sets) > 500:
@@ -272,7 +291,6 @@ def main():
     else:
         data_sets = result_data_sets
 
-
     # 组合提示词
     prompt = prepare_prompt(data_sets)