From 36dd009ffb99578e506dfe1a9d4343dfb9503ad1 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 6 Sep 2026 07:41:15 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: lldois/v46_v29_clean_user_evolution_lr5e7_ep045 Source: Original Platform --- .gitattributes | 36 + README.md | 58 + all_results.json | 8 + chat_template.jinja | 89 + config.json | 63 + experiment_recipe.json | 114 + generation_config.json | 12 + model.safetensors | 3 + ...36907.ubuntu-System-Product-Name.1408984.0 | 3 + tokenizer.json | 3 + tokenizer_config.json | 16 + train.log | 2148 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 7 + trainer_state.json | 85 + training_args.bin | 3 + training_loss.png | Bin 0 -> 39217 bytes 17 files changed, 2656 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 all_results.json create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 experiment_recipe.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 runs/Jul16_01-35-07_ubuntu-System-Product-Name/events.out.tfevents.1784136907.ubuntu-System-Product-Name.1408984.0 create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 train.log create mode 100644 train_results.json create mode 100644 trainer_log.jsonl create mode 100644 trainer_state.json create mode 100644 training_args.bin create mode 100644 training_loss.png diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs 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merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..73f1e06 --- /dev/null +++ b/README.md @@ -0,0 +1,58 @@ +--- +library_name: transformers +license: other +base_model: lldois/v29_v19_user_world_guard_lr8e7_ep018 +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: v46_v29_clean_user_evolution_lr5e7_ep045 + results: [] +--- + + + +# v46_v29_clean_user_evolution_lr5e7_ep045 + +This model is a fine-tuned version of [lldois/v29_v19_user_world_guard_lr8e7_ep018](https://huggingface.co/lldois/v29_v19_user_world_guard_lr8e7_ep018) on the exp_v46_clean_user_evolution dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 5e-07 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 202607196 +- gradient_accumulation_steps: 4 +- total_train_batch_size: 4 +- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments +- lr_scheduler_type: cosine +- lr_scheduler_warmup_steps: 0.03 +- num_epochs: 0.45 + +### Training results + + + +### Framework versions + +- Transformers 5.6.0 +- Pytorch 2.7.1+cu126 +- Datasets 4.0.0 +- Tokenizers 0.22.2 diff --git a/all_results.json b/all_results.json new file mode 100644 index 0000000..2b0d48c --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 0.4528301886792453, + "total_flos": 2.894445141093581e+16, + "train_loss": 1.7778411229451498, + "train_runtime": 516.0579, + "train_samples_per_second": 0.462, + "train_steps_per_second": 0.116 +} \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..01be9b3 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,89 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0].role == 'system' %} + {{- messages[0].content + '\n\n' }} + {%- endif %} + {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0].role == 'system' %} + {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} +{%- for message in messages[::-1] %} + {%- set index = (messages|length - 1) - loop.index0 %} + {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) %} + {%- set ns.multi_step_tool = false %} + {%- set ns.last_query_index = index %} + {%- endif %} +{%- endfor %} +{%- for message in messages %} + {%- if message.content is string %} + {%- set content = message.content %} + {%- else %} + {%- set content = '' %} + {%- endif %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} + {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {%- set reasoning_content = '' %} + {%- if message.reasoning_content is string %} + {%- set reasoning_content = message.reasoning_content %} + {%- else %} + {%- if '' in content %} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') %} + {%- set content = content.split('')[-1].lstrip('\n') %} + {%- endif %} + {%- endif %} + {%- if loop.index0 > ns.last_query_index %} + {%- if loop.last or (not loop.last and reasoning_content) %} + {{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') }} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- if message.tool_calls %} + {%- for tool_call in message.tool_calls %} + {%- if (loop.first and content) or (not loop.first) %} + {{- '\n' }} + {%- endif %} + {%- if tool_call.function %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {%- if tool_call.arguments is string %} + {{- tool_call.arguments }} + {%- else %} + {{- tool_call.arguments | tojson }} + {%- endif %} + {{- '}\n' }} + {%- endfor %} + {%- endif %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- content }} + {{- '\n' }} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} + {{- '<|im_end|>\n' }} + {%- endif %} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- '<|im_start|>assistant\n' }} + {%- if enable_thinking is defined and enable_thinking is false %} + {{- '\n\n\n\n' }} + {%- endif %} +{%- endif %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..c4eb20b --- /dev/null +++ b/config.json @@ -0,0 +1,63 @@ +{ + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} diff --git a/experiment_recipe.json b/experiment_recipe.json new file mode 100644 index 0000000..f096118 --- /dev/null +++ b/experiment_recipe.json @@ -0,0 +1,114 @@ +{ + "created_at": "2026-07-16 01:45:38", + "name": "v46_v29_clean_user_evolution_lr5e7_ep045", + "base": "/home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018", + "dataset": "v46_clean_user_evolution", + "dataset_manifest": { + "name": "v46_clean_user_evolution", + "path": "/home/ll/llm4rec/experiments/data/v46_clean_user_evolution.jsonl", + "records": 9250, + "bytes": 72444822, + "sha256": "44a179f71b7ecbe7f4d3df99088bbed4b249e7283fe0937448c63f628452907c", + "requested_components": { + "old_user_array_direct": 1200, + "old_user_logic_direct": 1100, + "old_user_logic_think": 450, + "old_rec_live_direct": 300, + "old_rec_live_think": 150, + "old_rec_ad_direct": 300, + "old_rec_ad_think": 150, + "old_rec_goods_direct": 300, + "old_rec_goods_think": 150, + "old_rec_video_direct": 300, + "old_rec_video_think": 150, + "old_item_goods_direct": 300, + "old_item_goods_think": 50, + "old_item_live_direct": 300, + "old_item_live_think": 50, + "old_item_ad_direct": 300, + "old_item_ad_think": 50, + "old_item_video_direct": 300, + "old_item_video_think": 50, + "r3_balanced_ad_direct": 250, + "r3_balanced_ad_think": 100, + "r3_balanced_live_direct": 350, + "r3_balanced_live_think": 450, + "r3_balanced_goods_direct": 150, + "r3_balanced_goods_think": 300, + "r3_balanced_video_direct": 250, + "r3_balanced_video_think": 250, + "general_cn_direct": 500, + "general_cn_think": 250, + "general_other_direct": 300, + "general_other_think": 150 + }, + "groups": { + "old_item_clean": 1400, + "old_rec_clean": 1800, + "r3_clean": 2100, + "old_user_clean": 2750, + "general_clean": 1200 + }, + "variants": { + "old_item_video_direct": 300, + "old_rec_video_direct": 300, + "strict_live_direct": 350, + "old_user_logic_direct": 1100, + "strict_single_turn_direct": 800, + "old_rec_ad_direct": 300, + "strict_single_turn_cot": 400, + "old_rec_goods_direct": 300, + "strict_live_cot": 450, + "old_item_live_direct": 300, + "old_user_array_direct": 1200, + "old_rec_ad_cot": 150, + "old_item_ad_direct": 300, + "old_rec_live_direct": 300, + "strict_video_cot": 250, + "old_user_logic_cot": 450, + "strict_video_direct": 250, + "strict_goods_cot": 300, + "old_rec_live_cot": 150, + "old_rec_goods_cot": 150, + "old_item_goods_direct": 300, + "strict_ad_direct": 250, + "old_item_goods_cot": 50, + "old_item_video_cot": 50, + "strict_goods_direct": 150, + "old_item_ad_cot": 50, + "old_rec_video_cot": 150, + "strict_ad_cot": 100, + "old_item_live_cot": 50 + }, + "routes": { + "no_think": 6500, + "think": 2750 + }, + "domains": { + "video": 1300, + "live": 1600, + "ad": 1150, + "goods": 1250 + }, + "canonical_duplicates": 0, + "output_chars_p50": 466, + "output_chars_p90": 1327, + "seed": 202607253 + }, + "learning_rate": "5.0e-7", + "epochs": 0.45, + "stages": null, + "note": "User/evolution specialist using parseable deduplicated JSON, retained evidence-bearing user CoT, strict R3 temporal examples, and balanced item/rec guards.", + "cot_policy": "Preserve meaningful CoT for /think and pure final outputs for /no_think.", + "checkpoint_policy": "save_strategy=no; only the final model is retained.", + "script": "/home/ll/llm4rec/experiments/run_experiments.py", + "script_sha256": "78d5f1619c271f19b4204ff4fa210ff4bbbadd81cdc0221e5f40cee201fc9877", + "data_builder": "/home/ll/llm4rec/experiments/source_data.py", + "data_builder_sha256": 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UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[transformers] warmup_ratio is deprecated and will be removed in v5.2. Use `warmup_steps` instead. +[transformers] `logging_dir` is deprecated and will be removed in v5.2. Please set `TENSORBOARD_LOGGING_DIR` instead. +[INFO|2026-07-16 01:34:44] llamafactory.hparams.parser:523 >> Process rank: 0, world size: 1, device: cuda:0, distributed training: False, compute dtype: torch.bfloat16 +[INFO|configuration_utils.py:769] 2026-07-16 01:34:44,788 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-16 01:34:44,792 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|configuration_utils.py:769] 2026-07-16 01:34:45,456 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-16 01:34:45,457 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|configuration_utils.py:769] 2026-07-16 01:34:45,460 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-16 01:34:45,460 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|2026-07-16 01:34:46] llamafactory.data.loader:144 >> Loading dataset /home/ll/llm4rec/experiments/data/v46_clean_user_evolution.jsonl... +Setting num_proc from 16 back to 1 for the train split to disable multiprocessing as it only contains one shard. + Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 9250 examples [00:00, 116321.56 examples/s] + Converting format of dataset (num_proc=16): 0%| | 0/9250 [00:00user +【用户交互历史】： +【2023-09-29】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-19】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-21】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-02】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-11】 + --:-- [商品-购买] <|prod_begin|> +【2024-01-01】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2024-01-07】 + --:-- [商品-购买] <|prod_begin|> +【2024-03-17】 + 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00:44 [广告-深度转化] <|ad_begin|> + 00:47 [广告-深度转化] <|ad_begin|> + 00:48 [广告-深度转化] <|ad_begin|> + 00:53 [广告-深度转化] <|ad_begin|> + 00:59 [广告-深度转化] <|ad_begin|> + 01:04 [广告-深度转化] <|ad_begin|> + 01:04 [广告-深度转化] <|ad_begin|> + 01:05 [广告-深度转化] <|ad_begin|> + 03:12 [广告-深度转化] <|ad_begin|> + 03:22 [广告-深度转化] <|ad_begin|> + 03:34 [广告-深度转化] <|ad_begin|> + 06:17 [视频-点赞/长播] <|video_begin|> + 06:28 [广告-深度转化] <|ad_begin|> + 06:32 [广告-深度转化] <|ad_begin|> + 06:39 [广告-深度转化] <|ad_begin|> + 06:40 [广告-深度转化] <|ad_begin|> + 07:01 [广告-深度转化] <|ad_begin|> + 09:40 [广告-深度转化] <|ad_begin|> + 11:47 [广告-深度转化] <|ad_begin|> + 11:53 [广告-深度转化] <|ad_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:07 [广告-深度转化] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 12:21 [广告-深度转化] <|ad_begin|> + 13:31 [广告-深度转化] <|ad_begin|> + 13:37 [广告-深度转化] <|ad_begin|> + 13:40 [广告-深度转化] <|ad_begin|> + 13:46 [广告-深度转化] <|ad_begin|> + 13:51 [广告-深度转化] <|ad_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 22:43 [视频-长播] <|video_begin|> + 22:43 [视频-长播] <|video_begin|> + 22:43 [视频-评论/点赞/长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:03 [广告-深度转化] <|ad_begin|> + 23:39 [广告-深度转化] <|ad_begin|> +【2026-02-05】 + 00:00 [广告-深度转化] <|ad_begin|> + 00:01 [广告-深度转化] <|ad_begin|> + 00:03 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 00:08 [广告-深度转化] <|ad_begin|> + 00:11 [广告-深度转化] <|ad_begin|> + 00:12 [广告-深度转化] <|ad_begin|> + 00:16 [广告-深度转化] <|ad_begin|> + 00:19 [广告-深度转化] <|ad_begin|> + 00:20 [广告-深度转化] <|ad_begin|> + 00:23 [广告-深度转化] <|ad_begin|> + 00:27 [广告-深度转化] <|ad_begin|> + 00:32 [广告-深度转化] <|ad_begin|> + 00:32 [广告-深度转化] <|ad_begin|> + 00:34 [广告-深度转化] <|ad_begin|> + 01:59 [视频-评论/长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-点赞/长播] <|video_begin|> + 02:13 [视频-评论/点赞/长播] <|video_begin|> + 02:23 [广告-深度转化] <|ad_begin|> + 02:28 [广告-深度转化] <|ad_begin|> + 02:33 [广告-深度转化] <|ad_begin|> + 02:34 [广告-深度转化] <|ad_begin|> + 02:36 [广告-深度转化] <|ad_begin|> + 02:54 [广告-点击] <|ad_begin|> + 02:55 [广告-点击] <|ad_begin|> + 02:56 [广告-点击] <|ad_begin|> + 02:56 [广告-点击] <|ad_begin|> + 02:57 [广告-点击] <|ad_begin|> + 03:03 [广告-深度转化] <|ad_begin|> + 03:03 [广告-点击] <|ad_begin|> + 03:06 [广告-点击] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 03:17 [广告-点击] <|ad_begin|> + 03:19 [广告-点击] <|ad_begin|> + 03:20 [广告-点击] <|ad_begin|> + 03:26 [广告-点击] <|ad_begin|> + 06:02 [广告-点击] <|ad_begin|> + 06:04 [广告-点击] <|ad_begin|> + 06:05 [广告-深度转化] <|ad_begin|> + 06:05 [广告-点击] <|ad_begin|> + 06:05 [广告-点击] <|ad_begin|> + 06:08 [广告-点击] <|ad_begin|> + 06:13 [广告-点击] <|ad_begin|> + 06:16 [广告-点击] <|ad_begin|> + 06:18 [广告-点击] <|ad_begin|> + 06:20 [广告-点击] <|ad_begin|> + 06:21 [广告-点击] <|ad_begin|> + 06:23 [广告-点击] <|ad_begin|> + 06:25 [广告-点击] <|ad_begin|> + 06:27 [广告-点击] <|ad_begin|> + 06:29 [广告-点击] <|ad_begin|> + 06:30 [广告-深度转化] <|ad_begin|> + 06:30 [广告-点击] <|ad_begin|> + 06:31 [广告-点击] <|ad_begin|> + 06:32 [广告-点击] <|ad_begin|> + 06:34 [广告-点击] <|ad_begin|> + 06:36 [广告-深度转化] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + 06:37 [广告-深度转化] <|ad_begin|> + 06:37 [广告-点击] <|ad_begin|> + 06:37 [广告-点击] <|ad_begin|> + 06:39 [广告-点击] <|ad_begin|> + 06:41 [广告-点击] <|ad_begin|> + 09:05 [广告-点击] <|ad_begin|> + 09:06 [广告-深度转化] <|ad_begin|> + 09:06 [广告-点击] <|ad_begin|> + 09:06 [广告-点击] <|ad_begin|> + 09:09 [广告-点击] <|ad_begin|> + 09:10 [广告-点击] <|ad_begin|> + 09:13 [广告-深度转化] <|ad_begin|> + 09:13 [广告-点击] <|ad_begin|> + 09:13 [广告-点击] <|ad_begin|> + 09:14 [广告-点击] <|ad_begin|> + 09:15 [广告-点击] <|ad_begin|> + 09:16 [广告-点击] <|ad_begin|> + 09:17 [广告-深度转化] <|ad_begin|> + 09:17 [广告-点击] <|ad_begin|> + 09:17 [广告-点击] <|ad_begin|> + 09:19 [广告-点击] <|ad_begin|> + 09:22 [广告-深度转化] <|ad_begin|> + 09:22 [广告-点击] <|ad_begin|> + 10:51 [广告-点击] <|ad_begin|> + 10:53 [广告-深度转化] <|ad_begin|> + 10:53 [广告-点击] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 10:55 [广告-点击] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 12:51 [广告-点击] <|ad_begin|> + 12:54 [广告-点击] <|ad_begin|> + 12:56 [广告-点击] <|ad_begin|> + 12:57 [广告-点击] <|ad_begin|> + 12:57 [广告-深度转化] <|ad_begin|> + 12:57 [广告-点击] <|ad_begin|> + 12:58 [广告-点击] <|ad_begin|> + 12:59 [广告-深度转化] <|ad_begin|> + 12:59 [广告-点击] <|ad_begin|> + 12:59 [广告-点击] <|ad_begin|> + 13:00 [广告-点击] <|ad_begin|> + 13:01 [广告-深度转化] <|ad_begin|> + 13:01 [广告-点击] <|ad_begin|> + 13:01 [广告-深度转化] <|ad_begin|> + 13:01 [广告-点击] <|ad_begin|> + 13:03 [广告-深度转化] <|ad_begin|> + 13:03 [广告-点击] <|ad_begin|> + 13:04 [广告-点击] <|ad_begin|> +【2026-02-06】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +角色任务：你是一个极端严苛的用户行为数据挖掘专家以及数据格式化专家，请根据以上用户交互历史，针对给定的主题，提取出具有行为递进逻辑和内在关联的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 搜索-搜索、视频-浏览、视频-长播、直播-关注、直播-首次打赏、商品-点击、商品-购买、广告-点击、广告-深度转化 +核心提取逻辑（递进性准则）： +按时间先后提取不超过 5 步的行为链，要求后项交互B必须对前项交互A形成场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是由 A 延展出来的需求，严禁提取任何品类平级、内容重复或仅因天气/促销造成的并列凑单行为。 +1.场景驱动协同：交互 B 与 交互 A 必须在同一生活场景、主题类目下具有极强的需求补完关系。 +2.兴趣因果递进：交互 B 必须与交互 A 构成因果递进关系，即 B 来源于 A 带来的副作用、新需求，或 A 是 B 的触发诱因。 +3.需求深度细化：在同一主题类目中，交互 B 相比交互 A 应体现出更具体、更详细的需求层次，但不得包含多次重复的购买、点击、搜索等行为，以避免重复节点内容。 +请面向以下主题提取行为逻辑链： +主题：从被动接收汽车信息到主动探索特定车型功能 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动接收汽车信息到主动探索特定车型功能", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/think<|im_end|> +<|im_start|>assistant + +好的，我来分析一下这位用户的行为。这项任务要求我基于用户的交互历史，挖掘出一条从被动接收汽车信息到主动探索特定车型功能的行为逻辑链。 我首先梳理了用户的整体行为时间线，发现他在2026年1月底之前，消费行为主要集中在茶叶、酒水、服饰以及一些生活用品上，例如购买了普洱茶 <|prod_begin|>、白兰地 和冲锋裤 <|prod_begin|>。他的直播关注内容也比较宽泛，从生活分享到二手车都有涉猎。 进入2026年1月下旬，我注意到用户的兴趣点开始出现一些新的变化。在1月26日，他观看了一个关于现代汽车豪华内饰和科技配置的视频 <|video_begin|>。这个视频内容比较泛化，主要展示了中控大屏、语音控制等通用性的高科技功能。我认为，这可以看作是用户对汽车领域兴趣的初步萌芽，他可能是在无意间被这类内容吸引，处于一个被动接收信息的阶段，对具体的品牌和车型还没有明确的概念。 紧接着，在短短三天后的1月29日，用户的行为出现了明显的递进。他观看了一个关于一汽丰田bZ5车型的视频 <|video_begin|>，并且进行了评论和点赞的深度互动。这与之前单纯的观看行为形成了鲜明对比。这次的视频内容不再是泛泛而谈的科技配置，而是聚焦于一个具体车型，并强调了其“精准操控”、“稳定性能”和“安全设计”等核心卖点。用户的点赞和评论行为表明，他不仅仅是看到了这条信息，更是对这些具体的功能点产生了认同或好奇，从而主动地表达了自己的态度。 我推测，从1月26日的泛化浏览到1月29日的深度互动，用户的兴趣已经完成了一次关键的收敛和升级。他不再满足于了解汽车有哪些酷炫的内饰，而是开始主动关注和评估特定车型的具体性能和安全特性。这个过程清晰地展现了他从一个对汽车内容被动接收的浏览者，转变为一个对特定车型功能有主动探索意愿的潜在消费者。 + +{"logic_chain":{"name":"从被动接收汽车信息到主动探索特定车型功能","events":[{"date":"2026-01-26","action":"[视频-长播] <|video_begin|>","logic":"初始阶段：被动接收关于汽车内饰、科技配置等泛化信息，兴趣尚处于发散状态。"},{"date":"2026-01-29","action":"[视频-评论/点赞/长播] <|video_begin|>","logic":"兴趣聚焦与深度交互：从泛化的汽车概念收敛至特定品牌型号“一汽丰田bZ5”，并对“精准操控”、“稳定性能”、“安全设计”等具体卖点产生了深度互动（评论/点赞），完成了从被动浏览到主动评估的认知升级。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-02-28】 + --:-- [直播-关注] <|living_begin|> +【2025-06-01】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-06-05】 + --:-- [直播-打赏] <|living_begin|> +【2025-06-10】 + --:-- [直播-关注/打赏] <|living_begin|> +【2025-06-14】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-06-22】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-26】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-08-13】 + --:-- [直播-打赏] <|living_begin|> +【2025-09-01】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-04】 + --:-- [直播-打赏] <|living_begin|> +【2025-09-21】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-09-25】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-09-26】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-10-03】 + --:-- [直播-打赏] <|living_begin|> +【2025-10-04】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-10-09】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-10-26】 + --:-- [直播-关注] <|living_begin|> +【2025-11-12】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-15】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-24】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-11-27】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-11-29】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-02】 + --:-- [直播-打赏] <|living_begin|> +【2025-12-10】 + 14:18 [广告-深度转化] <|ad_begin|> +【2025-12-11】 + 04:57 [广告-深度转化] <|ad_begin|> + 14:36 [广告-深度转化] <|ad_begin|> + 16:38 [广告-深度转化] <|ad_begin|> +【2025-12-12】 + 16:45 [广告-深度转化] <|ad_begin|> + 17:28 [广告-深度转化] <|ad_begin|> +【2025-12-13】 + 04:52 [广告-深度转化] <|ad_begin|> + 05:08 [广告-深度转化] <|ad_begin|> + 05:31 [广告-深度转化] <|ad_begin|> +【2025-12-14】 + 13:13 [广告-深度转化] <|ad_begin|> + 14:06 [广告-深度转化] <|ad_begin|> + 17:05 [广告-深度转化] <|ad_begin|> + 17:15 [广告-深度转化] <|ad_begin|> +【2025-12-15】 + 04:48 [广告-深度转化] <|ad_begin|> +【2025-12-16】 + 05:24 [广告-深度转化] <|ad_begin|> +【2025-12-17】 + 05:10 [广告-深度转化] <|ad_begin|> +【2025-12-18】 + 18:09 [广告-深度转化] <|ad_begin|> +【2025-12-20】 + 05:02 [广告-深度转化] <|ad_begin|> + 18:41 [广告-深度转化] <|ad_begin|> +【2025-12-21】 + 17:20 [广告-深度转化] <|ad_begin|> + 17:44 [广告-深度转化] <|ad_begin|> +【2025-12-22】 + 11:25 [广告-深度转化] <|ad_begin|> + 19:03 [广告-深度转化] <|ad_begin|> +【2025-12-23】 + 04:54 [广告-深度转化] <|ad_begin|> + 12:31 [广告-深度转化] <|ad_begin|> + 17:02 [广告-深度转化] <|ad_begin|> +【2025-12-24】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 04:33 [广告-深度转化] <|ad_begin|> + 18:27 [广告-深度转化] <|ad_begin|> +【2025-12-25】 + 11:19 [广告-深度转化] <|ad_begin|> + 13:16 [广告-深度转化] <|ad_begin|> +【2025-12-26】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 04:16 [广告-深度转化] <|ad_begin|> + 11:06 [广告-深度转化] <|ad_begin|> +【2025-12-27】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-29】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-30】 + --:-- [直播-首次打赏] <|living_begin|> + 11:36 [广告-深度转化] <|ad_begin|> + 12:29 [广告-深度转化] <|ad_begin|> +【2025-12-31】 + 05:25 [广告-深度转化] <|ad_begin|> +【2026-01-01】 + 05:12 [广告-深度转化] <|ad_begin|> +【2026-01-03】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 13:06 [广告-深度转化] <|ad_begin|> +【2026-01-04】 + 11:37 [广告-深度转化] <|ad_begin|> + 14:14 [广告-深度转化] <|ad_begin|> +【2026-01-05】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-06】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-07】 + --:-- [直播-关注] <|living_begin|> +【2026-01-08】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-10】 + --:-- [直播-首次打赏] <|living_begin|> +【2026-01-11】 + 02:45 [广告-点击] <|ad_begin|> + 02:46 [广告-点击] <|ad_begin|> + 02:49 [广告-点击] <|ad_begin|> + 09:33 [广告-深度转化] <|ad_begin|> + 09:33 [广告-点击] <|ad_begin|> + 09:53 [广告-深度转化] <|ad_begin|> + 09:53 [广告-点击] <|ad_begin|> + 10:53 [广告-深度转化] <|ad_begin|> + 10:53 [广告-点击] <|ad_begin|> +【2026-01-13】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 17:26 [广告-点击] <|ad_begin|> +【2026-01-14】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 10:19 [广告-点击] <|ad_begin|> + 10:51 [广告-点击] <|ad_begin|> + 11:50 [广告-深度转化] <|ad_begin|> + 11:50 [广告-点击] <|ad_begin|> +【2026-01-15】 + --:-- [直播-关注/打赏] <|living_begin|> + 11:57 [广告-深度转化] <|ad_begin|> + 11:57 [广告-点击] <|ad_begin|> + 12:53 [广告-点击] <|ad_begin|> +【2026-01-16】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:01 [广告-点击] <|ad_begin|> + 12:25 [广告-点击] <|ad_begin|> +【2026-01-18】 + 13:25 [广告-点击] <|ad_begin|> +【2026-01-19】 + --:-- [直播-关注] <|living_begin|> + 10:51 [广告-深度转化] <|ad_begin|> + 10:51 [广告-点击] <|ad_begin|> + 23:48 [广告-点击] <|ad_begin|> +【2026-01-20】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-21】 + --:-- [直播-首次打赏] <|living_begin|> + 05:34 [广告-点击] <|ad_begin|> + 05:39 [广告-点击] <|ad_begin|> + 06:35 [广告-点击] <|ad_begin|> +【2026-01-22】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 13:40 [广告-点击] <|ad_begin|> + 14:07 [视频-关注/收藏/点赞/长播] <|video_begin|> + 14:14 [视频-关注/点赞/长播] <|video_begin|> + 18:42 [视频-关注/收藏/点赞/长播] <|video_begin|> +【2026-01-23】 + 03:51 [广告-深度转化] <|ad_begin|> + 03:51 [广告-点击] <|ad_begin|> + 11:48 [视频-点赞/长播] <|video_begin|> + 12:17 [广告-深度转化] <|ad_begin|> + 12:17 [广告-点击] <|ad_begin|> + 12:39 [视频-收藏/点赞/长播] <|video_begin|> + 12:54 [视频-关注/点赞/长播] <|video_begin|> + 13:08 [视频-关注/点赞/长播] <|video_begin|> + 13:08 [视频-点赞/长播] <|video_begin|> + 13:08 [视频-收藏/点赞/长播] <|video_begin|> + 13:08 [视频-关注/收藏/长播] <|video_begin|> + 13:19 [视频-关注/点赞/长播] <|video_begin|> + 13:19 [视频-关注/点赞/长播] <|video_begin|> + 13:48 [视频-关注/点赞/长播] <|video_begin|> + 14:05 [广告-点击] <|ad_begin|> + 14:13 [视频-点赞/长播] <|video_begin|> + 14:13 [视频-点赞/长播] <|video_begin|> + 20:32 [视频-收藏/长播] <|video_begin|> +【2026-01-25】 + 05:55 [视频-关注/长播] <|video_begin|> + 18:08 [广告-点击] <|ad_begin|> + 23:48 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-26】 + 12:02 [广告-深度转化] <|ad_begin|> + 12:02 [广告-点击] <|ad_begin|> + 12:42 [广告-点击] <|ad_begin|> + 14:12 [视频-收藏/点赞/长播] <|video_begin|> + 14:22 [视频-评论/收藏/点赞/长播] <|video_begin|> + 18:05 [视频-关注/点赞/长播] <|video_begin|> + 18:05 [视频-点赞/长播] <|video_begin|> + 18:05 [视频-收藏/点赞/长播] <|video_begin|> + 18:11 [视频-评论/长播] <|video_begin|> + 20:41 [视频-评论/长播] <|video_begin|> + 23:49 [视频-点赞/长播] <|video_begin|> + 23:58 [广告-点击] <|ad_begin|> +【2026-01-27】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 11:55 [广告-点击] <|ad_begin|> + 12:11 [广告-点击] <|ad_begin|> + 13:15 [广告-深度转化] <|ad_begin|> + 13:15 [广告-点击] <|ad_begin|> + 13:44 [视频-关注/点赞/长播] <|video_begin|> + 13:59 [视频-关注/点赞/长播] <|video_begin|> + 14:22 [视频-关注/点赞/长播] <|video_begin|> + 14:22 [视频-点赞/长播] <|video_begin|> + 19:23 [视频-点赞/长播] <|video_begin|> + 22:32 [广告-深度转化] <|ad_begin|> + 22:32 [广告-点击] <|ad_begin|> + 22:37 [广告-点击] <|ad_begin|> + 22:46 [广告-点击] <|ad_begin|> +【2026-01-28】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 02:25 [视频-关注/收藏/点赞/长播] <|video_begin|> + 02:46 [广告-深度转化] <|ad_begin|> + 02:46 [广告-点击] <|ad_begin|> + 05:34 [广告-点击] <|ad_begin|> + 05:43 [广告-点击] <|ad_begin|> + 09:13 [视频-收藏/点赞/长播] <|video_begin|> + 10:18 [视频-关注/点赞/长播] <|video_begin|> + 10:18 [视频-收藏/点赞/长播] <|video_begin|> + 10:54 [广告-深度转化] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 11:43 [广告-深度转化] <|ad_begin|> + 11:43 [广告-点击] <|ad_begin|> + 12:28 [广告-深度转化] <|ad_begin|> + 12:28 [广告-点击] <|ad_begin|> + 13:22 [广告-点击] <|ad_begin|> + 13:23 [视频-关注/收藏/点赞/长播] <|video_begin|> + 17:09 [广告-点击] <|ad_begin|> + 17:23 [视频-关注/点赞/长播] <|video_begin|> + 17:26 [视频-关注/点赞/长播] <|video_begin|> + 17:26 [视频-关注/点赞/长播] <|video_begin|> + 17:26 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-29】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 00:04 [广告-深度转化] <|ad_begin|> + 00:04 [广告-点击] <|ad_begin|> + 18:50 [视频-点赞/长播] <|video_begin|> +【2026-01-30】 + --:-- [直播-打赏] <|living_begin|> + 04:25 [视频-点赞/长播] <|video_begin|> + 04:58 [广告-深度转化] <|ad_begin|> + 04:58 [广告-点击] <|ad_begin|> + 11:25 [广告-深度转化] <|ad_begin|> + 11:25 [广告-点击] <|ad_begin|> + 13:41 [广告-深度转化] <|ad_begin|> + 13:41 [广告-点击] <|ad_begin|> + 14:03 [视频-关注/点赞/长播] <|video_begin|> + 14:03 [视频-关注/点赞/长播] <|video_begin|> + 14:03 [视频-关注/点赞/长播] <|video_begin|> + 14:03 [视频-点赞/长播] <|video_begin|> + 14:32 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-31】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 02:09 [广告-点击] <|ad_begin|> + 02:24 [广告-深度转化] <|ad_begin|> + 02:24 [广告-点击] <|ad_begin|> + 03:10 [广告-深度转化] <|ad_begin|> + 03:10 [广告-点击] <|ad_begin|> + 05:22 [视频-关注/收藏/点赞/长播] <|video_begin|> + 05:22 [视频-收藏/点赞/长播] <|video_begin|> + 05:29 [视频-关注/点赞/长播] <|video_begin|> + 05:43 [视频-收藏/点赞/长播] <|video_begin|> + 05:51 [视频-关注/点赞/长播] <|video_begin|> + 05:57 [视频-关注/长播] <|video_begin|> + 05:58 [视频-点赞/长播] <|video_begin|> + 06:02 [视频-点赞/长播] <|video_begin|> + 17:58 [视频-关注/点赞/长播] <|video_begin|> + 18:20 [广告-深度转化] <|ad_begin|> + 18:20 [广告-点击] <|ad_begin|> +【2026-02-01】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 00:02 [广告-深度转化] <|ad_begin|> + 00:02 [广告-点击] <|ad_begin|> + 05:58 [广告-点击] <|ad_begin|> + 06:33 [视频-浏览] <|video_begin|> + 13:57 [广告-点击] <|ad_begin|> + 14:10 [广告-深度转化] <|ad_begin|> + 14:10 [广告-点击] <|ad_begin|> + 19:00 [广告-深度转化] <|ad_begin|> + 19:00 [广告-点击] <|ad_begin|> +【2026-02-02】 + 00:16 [视频-关注/收藏/点赞/长播] <|video_begin|> + 00:16 [视频-关注/点赞/长播] <|video_begin|> + 00:16 [视频-关注/点赞/长播] <|video_begin|> + 00:16 [视频-点赞/长播] <|video_begin|> + 00:16 [视频-收藏/点赞/长播] <|video_begin|> + 05:24 [视频-点赞/长播] <|video_begin|> + 12:23 [视频-关注/收藏/点赞/长播] <|video_begin|> + 12:23 [视频-点赞/长播] <|video_begin|> + 12:44 [广告-深度转化] <|ad_begin|> + 12:44 [广告-点击] <|ad_begin|> + 13:44 [广告-点击] <|ad_begin|> + 14:33 [视频-关注/点赞/长播] <|video_begin|> + 14:33 [视频-点赞/长播] <|video_begin|> + 20:54 [广告-深度转化] <|ad_begin|> + 20:54 [广告-点击] <|ad_begin|> + 21:00 [广告-点击] <|ad_begin|> + 21:20 [广告-点击] <|ad_begin|> + 21:22 [广告-点击] <|ad_begin|> + 21:25 [广告-点击] <|ad_begin|> + 23:10 [广告-点击] <|ad_begin|> +【2026-02-03】 + 05:05 [视频-收藏/点赞/长播] <|video_begin|> + 13:29 [广告-点击] <|ad_begin|> + 13:35 [广告-点击] <|ad_begin|> +【2026-02-04】 + 04:26 [广告-深度转化] <|ad_begin|> + 04:26 [广告-点击] <|ad_begin|> + 06:20 [广告-点击] <|ad_begin|> + 13:18 [广告-深度转化] <|ad_begin|> + 13:18 [广告-点击] <|ad_begin|> + 13:46 [视频-点赞/长播] <|video_begin|> + 13:46 [视频-点赞/长播] <|video_begin|> + 13:56 [视频-关注/点赞/长播] <|video_begin|> + 13:56 [视频-点赞/长播] <|video_begin|> + 14:25 [视频-点赞/长播] <|video_begin|> + 14:25 [视频-点赞/长播] <|video_begin|> + 14:25 [视频-点赞/长播] <|video_begin|> + 14:30 [视频-点赞/长播] <|video_begin|> + 14:30 [视频-点赞/长播] <|video_begin|> + 23:33 [视频-长播] <|video_begin|> + 23:48 [视频-长播] <|video_begin|> + 23:48 [视频-长播] <|video_begin|> +【2026-02-05】 + 00:06 [广告-深度转化] <|ad_begin|> + 00:06 [广告-点击] <|ad_begin|> + 04:56 [视频-长播] <|video_begin|> + 04:56 [视频-长播] <|video_begin|> + 04:56 [视频-长播] <|video_begin|> + 04:56 [视频-关注/收藏/点赞/长播] <|video_begin|> + 04:56 [视频-关注/点赞/长播] <|video_begin|> + 05:06 [视频-长播] <|video_begin|> + 05:06 [视频-关注/点赞/长播] <|video_begin|> + 05:06 [视频-点赞/长播] <|video_begin|> + 05:06 [视频-点赞/长播] <|video_begin|> + 05:06 [视频-点赞/长播] <|video_begin|> + 05:06 [视频-收藏/点赞/长播] <|video_begin|> + 05:17 [视频-长播] <|video_begin|> + 05:17 [视频-长播] <|video_begin|> + 05:17 [视频-长播] <|video_begin|> + 05:17 [视频-长播] <|video_begin|> + 05:26 [视频-长播] <|video_begin|> + 09:06 [视频-长播] <|video_begin|> + 09:11 [视频-长播] <|video_begin|> + 09:11 [视频-长播] <|video_begin|> + 09:11 [视频-长播] <|video_begin|> + 09:17 [视频-长播] <|video_begin|> + 09:17 [视频-长播] <|video_begin|> + 09:22 [视频-长播] <|video_begin|> + 09:24 [视频-长播] <|video_begin|> + 09:24 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:39 [广告-点击] <|ad_begin|> + 09:43 [视频-长播] <|video_begin|> + 09:43 [视频-长播] <|video_begin|> + 09:43 [视频-长播] <|video_begin|> + 09:43 [视频-长播] <|video_begin|> + 09:43 [视频-长播] <|video_begin|> + 09:46 [视频-长播] <|video_begin|> + 09:50 [视频-长播] <|video_begin|> + 09:52 [视频-长播] <|video_begin|> + 09:52 [视频-长播] <|video_begin|> + 10:01 [视频-长播] <|video_begin|> + 10:01 [视频-长播] <|video_begin|> + 10:05 [视频-长播] <|video_begin|> + 10:05 [视频-长播] <|video_begin|> + 10:05 [视频-长播] <|video_begin|> + 10:08 [视频-长播] <|video_begin|> + 10:08 [视频-长播] <|video_begin|> + 10:08 [视频-长播] <|video_begin|> + 10:14 [视频-长播] <|video_begin|> + 14:33 [视频-长播] <|video_begin|> + 14:33 [视频-长播] <|video_begin|> + 14:33 [视频-长播] <|video_begin|> + 14:33 [视频-长播] <|video_begin|> + 14:38 [视频-长播] <|video_begin|> + 14:38 [视频-长播] <|video_begin|> + 14:43 [视频-长播] <|video_begin|> + 14:43 [视频-长播] <|video_begin|> + 14:43 [视频-长播] <|video_begin|> +角色任务：你是一名极端严苛的用户行为数据挖掘专家和数据格式化专家，请基于以上用户交互历史，围绕指定主题提取具备行为递进关系与内在关联的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 直播-关注、直播-首次打赏、商品-点击、商品-购买、搜索-搜索、视频-浏览、视频-长播、广告-点击、广告-深度转化 +核心提取逻辑（递进性准则）： +按时间顺序提取 5 步以内的行为链，要求后项交互B必须是前项交互A的场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是因为 A 才产生的延伸需求，严禁提取任何品类平级、内容重复或仅因天气/促销产生的凑单并列行为。 +1.场景驱动协同：交互 B 与交互 A 必须同属一个生活场景及主题类目，并呈现极强的需求补完性。 +2.兴趣因果递进：交互 B 必须由交互 A 引发的副作用或新需求而产生，或者 A 本身就是 B 的诱因。 +3.需求深度细化：在同一主题类目下，交互 B 的需求必须比交互 A 更具体、更细化，但不包括重复出现的购买、点击、搜索等行为，避免节点内容重复。 +请针对以下主题提取行为逻辑链： +主题：从泛化动物兴趣到聚焦特定护农犬种的认知收敛 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化动物兴趣到聚焦特定护农犬种的认知收敛", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +{"logic_chain":{"name":"从泛化动物兴趣到聚焦特定护农犬种的认知收敛","events":[{"date":"2026-01-22","action":"[视频-关注/收藏/点赞/长播] <|video_begin|>","logic":"初始触发：被“西北刀客”这一IP下的护农、动物保护主题吸引，表现为对团队行为的泛化兴趣。"},{"date":"2026-01-23","action":"[视频-点赞/长播] <|video_begin|>","logic":"兴趣聚焦：从关注整个团队转向关注团队中的明星犬“青海”，认知从“团队护农”收敛至“特定犬只的成长史与能力”。"},{"date":"2026-01-23","action":"[视频-收藏/点赞/长播] <|video_begin|>","logic":"认知深化与扩展：兴趣从“青海”个体进一步扩展到其“后代”和“家族”概念，体现了从单一IP到家族谱系追踪的深度演化，认知增量为“繁衍”与“传承”。"},{"date":"2026-01-26","action":"[视频-评论/收藏/点赞/长播] <|video_begin|>","logic":"认知闭环与情感投射：通过评论行为，主动参与到对“护农犬家族”精神（如传承、牺牲）的讨论中，完成了从被动观看到主动建构情感认知的闭环。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2024-07-19】 + --:-- [商品-购买] <|prod_begin|> +【2024-07-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-25】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-02】 + --:-- [直播-关注] <|living_begin|> +【2025-11-12】 + --:-- [直播-关注] <|living_begin|> +【2025-11-13】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-15】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-16】 + --:-- [直播-关注] <|living_begin|> +【2025-12-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-07】 + --:-- [商品-加购] <|prod_begin|> +【2025-12-08】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> +【2025-12-11】 + --:-- [商品-加购] <|prod_begin|> +【2025-12-12】 + --:-- [商品-加购] <|prod_begin|> +【2025-12-17】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> +【2025-12-19】 + 03:37 [广告-深度转化] <|ad_begin|> +【2025-12-21】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 13:37 [广告-深度转化] <|ad_begin|> +【2025-12-23】 + --:-- [直播-首次打赏] <|living_begin|> + 03:47 [广告-深度转化] <|ad_begin|> + 03:49 [广告-深度转化] <|ad_begin|> + 10:19 [广告-深度转化] <|ad_begin|> + 10:24 [广告-深度转化] <|ad_begin|> + 10:40 [广告-深度转化] <|ad_begin|> + 11:00 [广告-深度转化] <|ad_begin|> + 14:19 [广告-深度转化] <|ad_begin|> +【2025-12-24】 + 05:04 [广告-深度转化] <|ad_begin|> + 10:55 [广告-深度转化] <|ad_begin|> + 15:43 [广告-深度转化] <|ad_begin|> +【2025-12-25】 + --:-- [直播-关注] <|living_begin|> +【2025-12-27】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-28】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-29】 + 15:24 [广告-深度转化] <|ad_begin|> +【2025-12-30】 + 04:16 [广告-深度转化] <|ad_begin|> + 05:39 [广告-深度转化] <|ad_begin|> + 14:48 [广告-深度转化] <|ad_begin|> +【2026-01-01】 + 05:38 [广告-深度转化] <|ad_begin|> + 09:27 [广告-深度转化] <|ad_begin|> + 09:57 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-02】 + 05:31 [广告-深度转化] <|ad_begin|> + 10:24 [广告-深度转化] <|ad_begin|> +【2026-01-04】 + 03:57 [广告-深度转化] <|ad_begin|> +【2026-01-06】 + 03:51 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-07】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-08】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-09】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-12】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-13】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-14】 + 03:59 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-16】 + 04:02 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-18】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-19】 + --:-- [直播-打赏] <|living_begin|> + 11:25 [广告-点击] <|ad_begin|> + 12:03 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-20】 + 03:56 [广告-点击] <|ad_begin|> + 10:11 [广告-点击] <|ad_begin|> + 15:08 [广告-点击] <|ad_begin|> +【2026-01-21】 + 03:39 [广告-点击] <|ad_begin|> + 05:52 [广告-点击] <|ad_begin|> + 13:37 [广告-点击] <|ad_begin|> + 13:58 [广告-点击] <|ad_begin|> + 16:01 [视频-收藏/点赞/长播] <|video_begin|> +【2026-01-22】 + 03:27 [视频-收藏/长播] <|video_begin|> + 03:27 [视频-收藏/长播] <|video_begin|> + 03:39 [视频-收藏/点赞/长播] <|video_begin|> + 03:40 [广告-点击] <|ad_begin|> + 14:09 [视频-收藏/长播] 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[广告-深度转化] <|ad_begin|> + 14:38 [广告-点击] <|ad_begin|> + 16:38 [视频-转发/收藏/长播] <|video_begin|> +【2026-01-25】 + 06:57 [视频-收藏/点赞/长播] <|video_begin|> + 07:27 [广告-深度转化] <|ad_begin|> + 07:27 [广告-点击] <|ad_begin|> + 08:37 [视频-点赞/长播] <|video_begin|> + 08:37 [视频-评论/长播] <|video_begin|> + 09:19 [广告-深度转化] <|ad_begin|> + 09:19 [广告-点击] <|ad_begin|> + 09:22 [广告-深度转化] <|ad_begin|> + 09:22 [广告-点击] <|ad_begin|> + 09:39 [广告-点击] <|ad_begin|> + 09:58 [广告-深度转化] <|ad_begin|> + 09:58 [广告-点击] <|ad_begin|> + 10:26 [广告-点击] <|ad_begin|> + 11:56 [视频-关注/长播] <|video_begin|> + 11:56 [视频-转发/收藏/长播] <|video_begin|> + 12:09 [视频-评论/长播] <|video_begin|> + 12:09 [视频-关注/收藏/点赞/长播] <|video_begin|> + 12:09 [视频-关注/评论/点赞/长播] <|video_begin|> + 15:54 [视频-收藏/长播] <|video_begin|> + 16:13 [广告-深度转化] <|ad_begin|> + 16:13 [广告-点击] <|ad_begin|> + 16:13 [广告-点击] <|ad_begin|> + 16:18 [广告-深度转化] <|ad_begin|> + 16:18 [广告-点击] <|ad_begin|> + 16:24 [广告-点击] <|ad_begin|> + 16:34 [视频-收藏/点赞/长播] <|video_begin|> + 16:41 [视频-点赞/长播] <|video_begin|> + 17:05 [视频-关注/转发/评论/点赞/长播] <|video_begin|> + 17:17 [视频-关注/评论/点赞/长播] <|video_begin|> + 20:05 [广告-点击] <|ad_begin|> +【2026-01-26】 + 03:42 [广告-点击] <|ad_begin|> + 03:45 [视频-转发/收藏/长播] <|video_begin|> + 04:35 [广告-点击] <|ad_begin|> + 04:39 [广告-点击] <|ad_begin|> + 11:59 [视频-收藏/点赞/长播] <|video_begin|> +【2026-01-27】 + 03:32 [视频-关注/点赞/长播] <|video_begin|> + 03:54 [广告-点击] <|ad_begin|> + 04:54 [广告-深度转化] <|ad_begin|> + 04:54 [广告-点击] <|ad_begin|> + 05:20 [广告-深度转化] <|ad_begin|> + 05:20 [广告-点击] <|ad_begin|> + 10:10 [视频-点赞/长播] <|video_begin|> + 10:27 [广告-深度转化] <|ad_begin|> + 10:27 [广告-点击] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> +【2026-01-28】 + 04:20 [广告-深度转化] <|ad_begin|> + 04:20 [广告-点击] <|ad_begin|> + 05:40 [视频-收藏/点赞/长播] <|video_begin|> + 05:40 [视频-评论/长播] <|video_begin|> + 12:32 [广告-点击] <|ad_begin|> + 14:39 [视频-点赞/长播] <|video_begin|> + 14:39 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-29】 + 03:29 [视频-收藏/长播] <|video_begin|> + 03:49 [视频-评论/长播] <|video_begin|> + 03:49 [视频-关注/收藏/点赞/长播] <|video_begin|> + 05:13 [广告-深度转化] <|ad_begin|> + 05:13 [广告-点击] <|ad_begin|> + 05:31 [视频-关注/点赞/长播] <|video_begin|> + 09:29 [视频-收藏/点赞/长播] <|video_begin|> + 09:29 [视频-关注/评论/点赞/长播] <|video_begin|> + 09:29 [视频-关注/评论/点赞/长播] <|video_begin|> + 09:44 [广告-深度转化] <|ad_begin|> + 09:44 [广告-点击] <|ad_begin|> + 10:09 [广告-点击] <|ad_begin|> + 15:48 [广告-深度转化] <|ad_begin|> + 15:48 [广告-点击] <|ad_begin|> + 15:50 [广告-深度转化] <|ad_begin|> + 15:50 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 16:11 [广告-点击] <|ad_begin|> +【2026-01-30】 + 03:59 [广告-深度转化] <|ad_begin|> + 03:59 [广告-点击] <|ad_begin|> + 04:10 [广告-点击] <|ad_begin|> + 04:21 [广告-点击] <|ad_begin|> + 05:17 [视频-点赞/长播] <|video_begin|> + 05:17 [视频-关注/点赞/长播] <|video_begin|> + 05:39 [广告-点击] <|ad_begin|> + 09:10 [视频-点赞/长播] <|video_begin|> + 09:32 [视频-点赞/长播] <|video_begin|> + 09:32 [视频-关注/点赞/长播] <|video_begin|> + 09:43 [广告-点击] <|ad_begin|> + 10:01 [广告-点击] <|ad_begin|> + 11:34 [视频-点赞/长播] <|video_begin|> + 13:07 [广告-深度转化] <|ad_begin|> + 13:07 [广告-点击] <|ad_begin|> + 14:20 [视频-点赞/长播] <|video_begin|> + 14:20 [视频-关注/评论/收藏/点赞/长播] <|video_begin|> + 14:29 [视频-点赞/长播] <|video_begin|> + 14:29 [视频-关注/收藏/点赞/长播] <|video_begin|> + 15:51 [视频-点赞/长播] <|video_begin|> + 15:53 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 16:08 [视频-关注/评论/点赞/长播] <|video_begin|> + 16:15 [视频-点赞/长播] <|video_begin|> + 16:15 [视频-关注/点赞/长播] <|video_begin|> + 16:15 [视频-关注/评论/点赞/长播] <|video_begin|> + 16:15 [视频-关注/评论/点赞/长播] <|video_begin|> + 16:22 [广告-点击] <|ad_begin|> + 16:24 [视频-点赞/长播] <|video_begin|> + 16:24 [视频-关注/点赞/长播] <|video_begin|> + 16:29 [视频-评论/收藏/长播] <|video_begin|> + 16:32 [视频-点赞/长播] <|video_begin|> + 16:32 [视频-点赞/长播] <|video_begin|> +【2026-01-31】 + 04:09 [视频-点赞/长播] <|video_begin|> + 04:09 [视频-点赞/长播] <|video_begin|> + 04:21 [视频-关注/点赞/长播] <|video_begin|> + 04:44 [广告-点击] <|ad_begin|> + 06:24 [广告-深度转化] <|ad_begin|> + 06:24 [广告-点击] <|ad_begin|> + 06:45 [广告-点击] <|ad_begin|> + 07:00 [视频-关注/收藏/点赞/长播] <|video_begin|> + 07:41 [广告-点击] <|ad_begin|> + 08:00 [视频-点赞/长播] <|video_begin|> + 08:03 [广告-点击] <|ad_begin|> + 08:44 [视频-点赞/长播] <|video_begin|> + 08:52 [广告-点击] <|ad_begin|> + 17:05 [视频-评论/点赞/长播] <|video_begin|> + 17:08 [视频-评论/长播] <|video_begin|> + 17:08 [视频-评论/点赞/长播] <|video_begin|> +【2026-02-01】 + 09:55 [广告-点击] <|ad_begin|> + 10:38 [视频-评论/收藏/点赞/长播] <|video_begin|> + 10:56 [视频-点赞/长播] <|video_begin|> + 10:56 [视频-关注/收藏/点赞/长播] <|video_begin|> + 11:03 [视频-评论/点赞/长播] <|video_begin|> + 15:07 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-02-02】 + 04:21 [视频-点赞/长播] <|video_begin|> + 04:21 [视频-关注/点赞/长播] <|video_begin|> + 05:12 [视频-点赞/长播] <|video_begin|> + 07:03 [视频-关注/点赞/长播] <|video_begin|> + 07:03 [视频-关注/点赞/长播] <|video_begin|> + 13:06 [视频-收藏/长播] <|video_begin|> + 13:06 [视频-点赞/长播] <|video_begin|> + 13:06 [视频-评论/长播] <|video_begin|> + 13:06 [视频-关注/收藏/点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 20:31 [广告-点击] <|ad_begin|> + 21:39 [视频-关注/长播] <|video_begin|> + 21:54 [广告-点击] <|ad_begin|> +【2026-02-03】 + 05:49 [广告-点击] <|ad_begin|> + 06:01 [广告-深度转化] <|ad_begin|> + 06:01 [广告-点击] <|ad_begin|> + 09:20 [视频-关注/评论/点赞/长播] <|video_begin|> + 13:30 [视频-长播] <|video_begin|> + 13:30 [视频-收藏/长播] <|video_begin|> + 13:47 [视频-长播] <|video_begin|> + 13:47 [视频-点赞/长播] <|video_begin|> + 13:47 [视频-点赞/长播] <|video_begin|> + 14:18 [广告-深度转化] <|ad_begin|> + 14:18 [广告-点击] <|ad_begin|> + 14:42 [视频-长播] <|video_begin|> + 14:42 [视频-点赞/长播] <|video_begin|> + 15:02 [视频-长播] <|video_begin|> + 15:55 [视频-长播] <|video_begin|> + 15:55 [视频-长播] <|video_begin|> + 15:55 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 16:14 [广告-点击] <|ad_begin|> + 16:47 [视频-长播] <|video_begin|> + 16:47 [视频-关注/点赞/长播] <|video_begin|> + 16:52 [视频-长播] <|video_begin|> + 16:52 [视频-长播] <|video_begin|> + 16:55 [广告-点击] <|ad_begin|> + 17:52 [视频-长播] <|video_begin|> + 17:52 [视频-点赞/长播] <|video_begin|> + 17:52 [视频-关注/点赞/长播] <|video_begin|> + 18:29 [视频-长播] <|video_begin|> + 18:29 [视频-长播] <|video_begin|> + 18:29 [视频-转发/收藏/长播] <|video_begin|> + 18:37 [广告-点击] <|ad_begin|> + 18:40 [视频-长播] <|video_begin|> + 18:40 [视频-长播] <|video_begin|> + 18:49 [视频-长播] <|video_begin|> + 18:49 [视频-长播] <|video_begin|> + 18:49 [视频-长播] <|video_begin|> + 18:49 [视频-长播] <|video_begin|> +【2026-02-04】 + 02:15 [视频-长播] <|video_begin|> + 02:40 [视频-长播] <|video_begin|> + 04:30 [视频-长播] <|video_begin|> + 04:30 [视频-长播] <|video_begin|> + 04:31 [视频-长播] <|video_begin|> + 04:31 [视频-长播] <|video_begin|> + 10:18 [视频-长播] <|video_begin|> + 10:18 [视频-长播] <|video_begin|> + 10:18 [视频-长播] <|video_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:23 [视频-收藏/长播] <|video_begin|> + 10:23 [视频-点赞/长播] <|video_begin|> + 11:01 [视频-长播] <|video_begin|> + 11:01 [视频-长播] <|video_begin|> + 11:01 [视频-长播] <|video_begin|> + 12:59 [视频-长播] <|video_begin|> + 13:25 [视频-长播] <|video_begin|> + 13:25 [视频-长播] <|video_begin|> + 13:25 [视频-点赞/长播] <|video_begin|> + 13:47 [广告-深度转化] <|ad_begin|> + 13:47 [广告-点击] <|ad_begin|> + 14:52 [视频-长播] <|video_begin|> + 14:52 [视频-收藏/长播] <|video_begin|> + 15:57 [视频-长播] <|video_begin|> + 16:40 [视频-长播] <|video_begin|> + 16:40 [视频-长播] <|video_begin|> + 16:40 [视频-长播] <|video_begin|> + 16:47 [视频-点赞/长播] <|video_begin|> + 16:57 [视频-长播] <|video_begin|> + 16:57 [视频-长播] <|video_begin|> + 17:03 [视频-长播] <|video_begin|> + 17:03 [视频-长播] <|video_begin|> + 17:03 [视频-长播] <|video_begin|> + 17:03 [视频-点赞/长播] <|video_begin|> + 17:08 [视频-关注/收藏/点赞/长播] <|video_begin|> + 17:08 [视频-转发/收藏/长播] <|video_begin|> + 17:24 [视频-长播] <|video_begin|> + 17:24 [视频-收藏/长播] <|video_begin|> + 17:24 [视频-点赞/长播] <|video_begin|> +【2026-02-05】 + 03:40 [广告-深度转化] <|ad_begin|> + 03:40 [广告-点击] <|ad_begin|> + 04:41 [视频-长播] <|video_begin|> + 05:05 [视频-长播] <|video_begin|> + 05:05 [视频-关注/点赞/长播] <|video_begin|> + 05:39 [视频-长播] <|video_begin|> + 05:39 [视频-长播] <|video_begin|> + 05:39 [视频-点赞/长播] <|video_begin|> + 14:28 [视频-点赞/长播] <|video_begin|> + 14:34 [视频-点赞/长播] <|video_begin|> + +角色任务：你需要以极端严苛的用户行为数据挖掘专家及数据格式化专家的身份，基于以上交互历史，针对给定主题筛选并提取出全部相关的历史交互行为。 + +主题：从被动游戏内容消费到主动探索游戏内虚拟资产交易 + +输出格式要求：请仅输出包含 SID 的 JSON 数组，严禁输出任何额外的解释、说明或 Markdown 标记。 + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +["<|living_begin|>","<|living_begin|>","<|living_begin|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|ad_begin|>","<|video_begin|>","<|ad_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>"]<|im_end|> +<|im_start|>user +【用户交互历史】： +【2023-09-29】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-19】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-21】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-02】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-11】 + --:-- [商品-购买] <|prod_begin|> +【2024-01-01】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2024-01-07】 + --:-- [商品-购买] <|prod_begin|> +【2024-03-17】 + --:-- [商品-购买] <|prod_begin|> +【2024-04-02】 + --:-- [商品-购买] <|prod_begin|> +【2024-04-04】 + --:-- [商品-购买] <|prod_begin|> +【2024-04-14】 + --:-- [商品-购买] <|prod_begin|> +【2024-04-27】 + --:-- [商品-购买] <|prod_begin|> +【2024-05-05】 + --:-- [商品-购买] <|prod_begin|> +【2024-07-14】 + --:-- [商品-购买] <|prod_begin|> +【2024-07-19】 + --:-- [商品-购买] <|prod_begin|> +【2024-09-02】 + --:-- [商品-购买] <|prod_begin|> +【2024-09-08】 + --:-- [商品-购买] <|prod_begin|> +【2024-10-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-14】 + --:-- [直播-关注] <|living_begin|> +【2025-06-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-03】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-23】 + --:-- [直播-关注] <|living_begin|> +【2025-06-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-31】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-02】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-30】 + --:-- [直播-关注] <|living_begin|> +【2025-11-04】 + --:-- [直播-关注] <|living_begin|> +【2025-12-01】 + --:-- [直播-关注] <|living_begin|> +【2025-12-02】 + --:-- [直播-关注] <|living_begin|> +【2025-12-09】 + --:-- [直播-关注] <|living_begin|> +【2025-12-17】 + --:-- [直播-关注] <|living_begin|> +【2025-12-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-31】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-01】 + --:-- [直播-关注] <|living_begin|> +【2026-01-02】 + --:-- [直播-关注] <|living_begin|> +【2026-01-03】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-07】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2026-01-08】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2026-01-09】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2026-01-12】 + --:-- [直播-关注] <|living_begin|> +【2026-01-13】 + --:-- [直播-关注] <|living_begin|> +【2026-01-19】 + --:-- [直播-关注] <|living_begin|> +【2026-01-21】 + --:-- [直播-关注] <|living_begin|> + 22:32 [视频-评论/长播] <|video_begin|> + 22:32 [视频-评论/长播] <|video_begin|> + 22:49 [视频-评论/长播] <|video_begin|> + 22:49 [视频-长播] <|video_begin|> + 22:49 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-22】 + 12:43 [视频-评论/长播] <|video_begin|> + 12:43 [视频-长播] <|video_begin|> + 12:43 [视频-点赞/长播] <|video_begin|> +【2026-01-23】 + 12:04 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-24】 + --:-- [直播-关注] <|living_begin|> + 01:44 [视频-评论/点赞/长播] <|video_begin|> + 13:31 [视频-长播] <|video_begin|> + 13:31 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-25】 + 00:20 [视频-长播] <|video_begin|> + 09:20 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-26】 + 04:12 [视频-长播] <|video_begin|> + 09:38 [视频-评论/长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 22:42 [视频-长播] <|video_begin|> +【2026-01-27】 + 12:10 [视频-长播] <|video_begin|> + 12:21 [视频-长播] <|video_begin|> + 23:05 [视频-长播] <|video_begin|> + 23:05 [视频-评论/点赞/长播] <|video_begin|> + 23:05 [视频-点赞/长播] <|video_begin|> +【2026-01-28】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 11:47 [视频-长播] <|video_begin|> + 11:47 [视频-点赞/长播] <|video_begin|> + 23:00 [视频-评论/长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-评论/点赞/长播] <|video_begin|> + 23:19 [视频-长播] <|video_begin|> + 23:19 [视频-长播] <|video_begin|> +【2026-01-29】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 00:52 [视频-长播] <|video_begin|> + 03:43 [视频-长播] <|video_begin|> + 08:29 [视频-长播] <|video_begin|> + 08:29 [视频-评论/点赞/长播] <|video_begin|> + 22:32 [视频-长播] <|video_begin|> + 22:32 [视频-评论/点赞/长播] <|video_begin|> + 22:32 [视频-点赞/长播] <|video_begin|> + 22:32 [视频-转发/长播] <|video_begin|> + 22:43 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-30】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 03:02 [视频-评论/点赞/长播] <|video_begin|> + 03:02 [视频-点赞/长播] <|video_begin|> + 22:49 [视频-评论/点赞/长播] <|video_begin|> + 22:49 [视频-转发/评论/长播] <|video_begin|> + 23:08 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-31】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:41 [视频-评论/长播] <|video_begin|> + 02:41 [视频-长播] <|video_begin|> + 02:41 [视频-评论/点赞/长播] <|video_begin|> + 02:41 [视频-点赞/长播] <|video_begin|> + 02:48 [视频-点赞/长播] <|video_begin|> + 08:05 [视频-评论/点赞/长播] <|video_begin|> + 08:05 [视频-评论/点赞/长播] <|video_begin|> + 08:05 [视频-点赞/长播] <|video_begin|> + 08:16 [视频-评论/长播] <|video_begin|> + 23:15 [视频-长播] <|video_begin|> +【2026-02-01】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:09 [视频-长播] <|video_begin|> + 02:09 [视频-长播] <|video_begin|> + 02:09 [视频-点赞/长播] <|video_begin|> + 02:17 [视频-长播] <|video_begin|> + 02:17 [视频-点赞/长播] <|video_begin|> + 23:32 [视频-评论/点赞/长播] <|video_begin|> + 23:32 [视频-评论/点赞/长播] <|video_begin|> + 23:39 [视频-点赞/长播] <|video_begin|> +【2026-02-02】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 06:34 [视频-评论/长播] <|video_begin|> + 06:34 [视频-长播] <|video_begin|> + 06:34 [视频-评论/点赞/长播] <|video_begin|> + 06:34 [视频-评论/点赞/长播] <|video_begin|> + 06:34 [视频-评论/点赞/长播] <|video_begin|> + 09:10 [视频-点赞/长播] <|video_begin|> + 12:13 [视频-评论/长播] <|video_begin|> + 12:13 [视频-评论/长播] <|video_begin|> + 12:26 [视频-评论/点赞/长播] <|video_begin|> + 22:36 [视频-评论/点赞/长播] <|video_begin|> +【2026-02-03】 + 01:45 [视频-点赞/长播] <|video_begin|> + 06:34 [视频-点赞/长播] <|video_begin|> + 22:30 [视频-长播] <|video_begin|> + 22:30 [视频-评论/点赞/长播] <|video_begin|> + 22:30 [视频-评论/点赞/长播] <|video_begin|> + 22:30 [视频-评论/点赞/长播] <|video_begin|> + 22:30 [视频-点赞/长播] <|video_begin|> + 22:48 [视频-长播] <|video_begin|> + 22:48 [视频-长播] <|video_begin|> + 22:48 [视频-长播] <|video_begin|> + 22:48 [视频-评论/点赞/长播] <|video_begin|> + 22:48 [视频-点赞/长播] <|video_begin|> + 22:58 [视频-长播] <|video_begin|> + 22:58 [视频-点赞/长播] <|video_begin|> +【2026-02-04】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 00:13 [广告-深度转化] <|ad_begin|> + 00:19 [广告-深度转化] <|ad_begin|> + 00:20 [广告-深度转化] <|ad_begin|> + 00:24 [广告-深度转化] <|ad_begin|> + 00:29 [广告-深度转化] <|ad_begin|> + 00:34 [广告-深度转化] <|ad_begin|> + 00:44 [广告-深度转化] <|ad_begin|> + 00:47 [广告-深度转化] <|ad_begin|> + 00:48 [广告-深度转化] <|ad_begin|> + 00:53 [广告-深度转化] <|ad_begin|> + 00:59 [广告-深度转化] <|ad_begin|> + 01:04 [广告-深度转化] <|ad_begin|> + 01:04 [广告-深度转化] <|ad_begin|> + 01:05 [广告-深度转化] <|ad_begin|> + 03:12 [广告-深度转化] <|ad_begin|> + 03:22 [广告-深度转化] <|ad_begin|> + 03:34 [广告-深度转化] <|ad_begin|> + 06:17 [视频-点赞/长播] <|video_begin|> + 06:28 [广告-深度转化] <|ad_begin|> + 06:32 [广告-深度转化] <|ad_begin|> + 06:39 [广告-深度转化] <|ad_begin|> + 06:40 [广告-深度转化] <|ad_begin|> + 07:01 [广告-深度转化] <|ad_begin|> + 09:40 [广告-深度转化] <|ad_begin|> + 11:47 [广告-深度转化] <|ad_begin|> + 11:53 [广告-深度转化] <|ad_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:07 [广告-深度转化] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 12:21 [广告-深度转化] <|ad_begin|> + 13:31 [广告-深度转化] <|ad_begin|> + 13:37 [广告-深度转化] <|ad_begin|> + 13:40 [广告-深度转化] <|ad_begin|> + 13:46 [广告-深度转化] <|ad_begin|> + 13:51 [广告-深度转化] <|ad_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 22:43 [视频-长播] <|video_begin|> + 22:43 [视频-长播] <|video_begin|> + 22:43 [视频-评论/点赞/长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> + 23:03 [广告-深度转化] <|ad_begin|> + 23:39 [广告-深度转化] <|ad_begin|> +【2026-02-05】 + 00:00 [广告-深度转化] <|ad_begin|> + 00:01 [广告-深度转化] <|ad_begin|> + 00:03 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 00:08 [广告-深度转化] <|ad_begin|> + 00:11 [广告-深度转化] <|ad_begin|> + 00:12 [广告-深度转化] <|ad_begin|> + 00:16 [广告-深度转化] <|ad_begin|> + 00:19 [广告-深度转化] <|ad_begin|> + 00:20 [广告-深度转化] <|ad_begin|> + 00:23 [广告-深度转化] <|ad_begin|> + 00:27 [广告-深度转化] <|ad_begin|> + 00:32 [广告-深度转化] <|ad_begin|> + 00:32 [广告-深度转化] <|ad_begin|> + 00:34 [广告-深度转化] <|ad_begin|> + 01:59 [视频-评论/长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-长播] <|video_begin|> + 01:59 [视频-点赞/长播] <|video_begin|> + 02:13 [视频-评论/点赞/长播] <|video_begin|> + 02:23 [广告-深度转化] <|ad_begin|> + 02:28 [广告-深度转化] <|ad_begin|> + 02:33 [广告-深度转化] <|ad_begin|> + 02:34 [广告-深度转化] <|ad_begin|> + 02:36 [广告-深度转化] <|ad_begin|> + 02:54 [广告-点击] <|ad_begin|> + 02:55 [广告-点击] <|ad_begin|> + 02:56 [广告-点击] <|ad_begin|> + 02:56 [广告-点击] <|ad_begin|> + 02:57 [广告-点击] <|ad_begin|> + 03:03 [广告-深度转化] <|ad_begin|> + 03:03 [广告-点击] <|ad_begin|> + 03:06 [广告-点击] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 03:17 [广告-点击] <|ad_begin|> + 03:19 [广告-点击] <|ad_begin|> + 03:20 [广告-点击] <|ad_begin|> + 03:26 [广告-点击] <|ad_begin|> + 06:02 [广告-点击] <|ad_begin|> + 06:04 [广告-点击] <|ad_begin|> + 06:05 [广告-深度转化] <|ad_begin|> + 06:05 [广告-点击] <|ad_begin|> + 06:05 [广告-点击] <|ad_begin|> + 06:08 [广告-点击] <|ad_begin|> + 06:13 [广告-点击] <|ad_begin|> + 06:16 [广告-点击] <|ad_begin|> + 06:18 [广告-点击] <|ad_begin|> + 06:20 [广告-点击] <|ad_begin|> + 06:21 [广告-点击] <|ad_begin|> + 06:23 [广告-点击] <|ad_begin|> + 06:25 [广告-点击] <|ad_begin|> + 06:27 [广告-点击] <|ad_begin|> + 06:29 [广告-点击] <|ad_begin|> + 06:30 [广告-深度转化] <|ad_begin|> + 06:30 [广告-点击] <|ad_begin|> + 06:31 [广告-点击] <|ad_begin|> + 06:32 [广告-点击] <|ad_begin|> + 06:34 [广告-点击] <|ad_begin|> + 06:36 [广告-深度转化] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + 06:37 [广告-深度转化] <|ad_begin|> + 06:37 [广告-点击] <|ad_begin|> + 06:37 [广告-点击] <|ad_begin|> + 06:39 [广告-点击] <|ad_begin|> + 06:41 [广告-点击] <|ad_begin|> + 09:05 [广告-点击] <|ad_begin|> + 09:06 [广告-深度转化] <|ad_begin|> + 09:06 [广告-点击] <|ad_begin|> + 09:06 [广告-点击] <|ad_begin|> + 09:09 [广告-点击] <|ad_begin|> + 09:10 [广告-点击] <|ad_begin|> + 09:13 [广告-深度转化] <|ad_begin|> + 09:13 [广告-点击] <|ad_begin|> + 09:13 [广告-点击] <|ad_begin|> + 09:14 [广告-点击] <|ad_begin|> + 09:15 [广告-点击] <|ad_begin|> + 09:16 [广告-点击] <|ad_begin|> + 09:17 [广告-深度转化] <|ad_begin|> + 09:17 [广告-点击] <|ad_begin|> + 09:17 [广告-点击] <|ad_begin|> + 09:19 [广告-点击] <|ad_begin|> + 09:22 [广告-深度转化] <|ad_begin|> + 09:22 [广告-点击] <|ad_begin|> + 10:51 [广告-点击] <|ad_begin|> + 10:53 [广告-深度转化] <|ad_begin|> + 10:53 [广告-点击] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 10:55 [广告-点击] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 12:51 [广告-点击] <|ad_begin|> + 12:54 [广告-点击] <|ad_begin|> + 12:56 [广告-点击] <|ad_begin|> + 12:57 [广告-点击] <|ad_begin|> + 12:57 [广告-深度转化] <|ad_begin|> + 12:57 [广告-点击] <|ad_begin|> + 12:58 [广告-点击] <|ad_begin|> + 12:59 [广告-深度转化] <|ad_begin|> + 12:59 [广告-点击] <|ad_begin|> + 12:59 [广告-点击] <|ad_begin|> + 13:00 [广告-点击] <|ad_begin|> + 13:01 [广告-深度转化] <|ad_begin|> + 13:01 [广告-点击] <|ad_begin|> + 13:01 [广告-深度转化] <|ad_begin|> + 13:01 [广告-点击] <|ad_begin|> + 13:03 [广告-深度转化] <|ad_begin|> + 13:03 [广告-点击] <|ad_begin|> + 13:04 [广告-点击] <|ad_begin|> +【2026-02-06】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +角色任务：你是一个极端严苛的用户行为数据挖掘专家以及数据格式化专家，请根据以上用户交互历史，针对给定的主题，提取出具有行为递进逻辑和内在关联的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 搜索-搜索、视频-浏览、视频-长播、直播-关注、直播-首次打赏、商品-点击、商品-购买、广告-点击、广告-深度转化 +核心提取逻辑（递进性准则）： +按时间先后提取不超过 5 步的行为链，要求后项交互B必须对前项交互A形成场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是由 A 延展出来的需求，严禁提取任何品类平级、内容重复或仅因天气/促销造成的并列凑单行为。 +1.场景驱动协同：交互 B 与 交互 A 必须在同一生活场景、主题类目下具有极强的需求补完关系。 +2.兴趣因果递进：交互 B 必须与交互 A 构成因果递进关系，即 B 来源于 A 带来的副作用、新需求，或 A 是 B 的触发诱因。 +3.需求深度细化：在同一主题类目中，交互 B 相比交互 A 应体现出更具体、更详细的需求层次，但不得包含多次重复的购买、点击、搜索等行为，以避免重复节点内容。 +请面向以下主题提取行为逻辑链： +主题：从被动接收汽车信息到主动探索特定车型功能 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动接收汽车信息到主动探索特定车型功能", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +{"logic_chain":{"name":"从被动接收汽车信息到主动探索特定车型功能","events":[{"date":"2026-01-26","action":"[视频-长播] <|video_begin|>","logic":"初始阶段：被动接收关于汽车内饰、科技配置等泛化信息，兴趣尚处于发散状态。"},{"date":"2026-01-29","action":"[视频-评论/点赞/长播] <|video_begin|>","logic":"兴趣聚焦与深度交互：从泛化的汽车概念收敛至特定品牌型号“一汽丰田bZ5”，并对“精准操控”、“稳定性能”、“安全设计”等具体卖点产生了深度互动（评论/点赞），完成了从被动浏览到主动评估的认知升级。"}]}}<|im_end|> +<|im_start|>user +你是推荐系统助手，需要基于多域时序行为进行证据充分、无目标泄漏的下一交互预测。 +用户多域历史行为（已按时间从早到晚排列）： +1. [较早][广告-转化] <|ad_begin|> +2. [较早][广告-转化] <|ad_begin|> +3. [中期][广告-深度转化/转化，累计2次] <|ad_begin|> +4. [中期][商品-点击，累计2次] <|prod_begin|> +5. [近期][商品-点击，累计3次] <|prod_begin|> +6. [近期][商品-点击，累计3次] <|prod_begin|> +7. [近期][商品-点击，累计2次] <|prod_begin|> +请推断用户接下来最可能交互的广告，最终只输出一个 itemic token。/think<|im_end|> +<|im_start|>assistant + +【画像抽象】历史呈现关于一款手机游戏“纯粹软件”的详、生活纪实偏好，其中<|ad_begin|>和<|ad_begin|>都产生了深度转化/转化/转化等主动信号。 +【兴趣展开】按时间连续性展开三个以内候选：“关于一款手机游戏“纯粹软件”的详”由<|ad_begin|>的深度转化/转化支持；“关于一款名为“治愈猫咪”的热门赚”由<|ad_begin|>的转化支持；“个人生活记录”由<|ad_begin|>的转化支持。 +【转移判断】比较近期程度、交互深度与跨条目复现后，“关于一款手机游戏“纯粹软件”的详”证据最完整；下一次广告选择应延续这一历史可见方向。 + +<|ad_begin|><|im_end|> +<|endoftext|> +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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我推测，从1月26日的泛化浏览到1月29日的深度互动，用户的兴趣已经完成了一次关键的收敛和升级。他不再满足于了解汽车有哪些酷炫的内饰，而是开始主动关注和评估特定车型的具体性能和安全特性。这个过程清晰地展现了他从一个对汽车内容被动接收的浏览者，转变为一个对特定车型功能有主动探索意愿的潜在消费者。 + +{"logic_chain":{"name":"从被动接收汽车信息到主动探索特定车型功能","events":[{"date":"2026-01-26","action":"[视频-长播] <|video_begin|>","logic":"初始阶段：被动接收关于汽车内饰、科技配置等泛化信息，兴趣尚处于发散状态。"},{"date":"2026-01-29","action":"[视频-评论/点赞/长播] <|video_begin|>","logic":"兴趣聚焦与深度交互：从泛化的汽车概念收敛至特定品牌型号“一汽丰田bZ5”，并对“精准操控”、“稳定性能”、“安全设计”等具体卖点产生了深度互动（评论/点赞），完成了从被动浏览到主动评估的认知升级。"}]}}<|im_end|> +{"logic_chain":{"name":"从泛化动物兴趣到聚焦特定护农犬种的认知收敛","events":[{"date":"2026-01-22","action":"[视频-关注/收藏/点赞/长播] <|video_begin|>","logic":"初始触发：被“西北刀客”这一IP下的护农、动物保护主题吸引，表现为对团队行为的泛化兴趣。"},{"date":"2026-01-23","action":"[视频-点赞/长播] <|video_begin|>","logic":"兴趣聚焦：从关注整个团队转向关注团队中的明星犬“青海”，认知从“团队护农”收敛至“特定犬只的成长史与能力”。"},{"date":"2026-01-23","action":"[视频-收藏/点赞/长播] <|video_begin|>","logic":"认知深化与扩展：兴趣从“青海”个体进一步扩展到其“后代”和“家族”概念，体现了从单一IP到家族谱系追踪的深度演化，认知增量为“繁衍”与“传承”。"},{"date":"2026-01-26","action":"[视频-评论/收藏/点赞/长播] <|video_begin|>","logic":"认知闭环与情感投射：通过评论行为，主动参与到对“护农犬家族”精神（如传承、牺牲）的讨论中，完成了从被动观看到主动建构情感认知的闭环。"}]}}<|im_end|> +["<|living_begin|>","<|living_begin|>","<|living_begin|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|ad_begin|>","<|video_begin|>","<|ad_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>"]<|im_end|> +{"logic_chain":{"name":"从被动接收汽车信息到主动探索特定车型功能","events":[{"date":"2026-01-26","action":"[视频-长播] <|video_begin|>","logic":"初始阶段：被动接收关于汽车内饰、科技配置等泛化信息，兴趣尚处于发散状态。"},{"date":"2026-01-29","action":"[视频-评论/点赞/长播] <|video_begin|>","logic":"兴趣聚焦与深度交互：从泛化的汽车概念收敛至特定品牌型号“一汽丰田bZ5”，并对“精准操控”、“稳定性能”、“安全设计”等具体卖点产生了深度互动（评论/点赞），完成了从被动浏览到主动评估的认知升级。"}]}}<|im_end|> + +【画像抽象】历史呈现关于一款手机游戏“纯粹软件”的详、生活纪实偏好，其中<|ad_begin|>和<|ad_begin|>都产生了深度转化/转化/转化等主动信号。 +【兴趣展开】按时间连续性展开三个以内候选：“关于一款手机游戏“纯粹软件”的详”由<|ad_begin|>的深度转化/转化支持；“关于一款名为“治愈猫咪”的热门赚”由<|ad_begin|>的转化支持；“个人生活记录”由<|ad_begin|>的转化支持。 +【转移判断】比较近期程度、交互深度与跨条目复现后，“关于一款手机游戏“纯粹软件”的详”证据最完整；下一次广告选择应延续这一历史可见方向。 + +<|ad_begin|><|im_end|> +[INFO|configuration_utils.py:769] 2026-07-16 01:35:06,190 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-16 01:35:06,191 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + + +[INFO|2026-07-16 01:35:06] llamafactory.model.model_utils.kv_cache:144 >> KV cache is disabled during training. +[INFO|2026-07-16 01:35:06] llamafactory.model.model_utils.liger_kernel:144 >> Liger kernel has been applied to the model. +[INFO|modeling_utils.py:748] 2026-07-16 01:35:06,608 >> loading weights file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/model.safetensors +[INFO|modeling_utils.py:821] 2026-07-16 01:35:06,608 >> Will use dtype=torch.bfloat16 as defined in model's config object +[INFO|configuration_utils.py:1027] 2026-07-16 01:35:06,658 >> Generate config GenerationConfig { + "eos_token_id": 151645, + "output_attentions": false, + "output_hidden_states": false, + "pad_token_id": 151643, + "use_cache": false +} + + Loading weights: 0%| | 0/311 [00:00> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/generation_config.json +[INFO|configuration_utils.py:1027] 2026-07-16 01:35:06,944 >> Generate config GenerationConfig { + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "temperature": 0.6, + "top_k": 20, + "top_p": 0.95 +} + +[INFO|dynamic_module_utils.py:406] 2026-07-16 01:35:06,944 >> Could not locate the custom_generate/generate.py inside /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018. +[INFO|2026-07-16 01:35:06] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled. +[INFO|2026-07-16 01:35:06] llamafactory.model.model_utils.attention:144 >> Using FlashAttention-2 for faster training and inference. +[INFO|2026-07-16 01:35:06] llamafactory.model.adapter:144 >> Pure bf16 / BAdam detected, remaining trainable params in half precision. +[INFO|2026-07-16 01:35:06] llamafactory.model.adapter:144 >> Fine-tuning method: Full +[INFO|2026-07-16 01:35:06] llamafactory.model.loader:144 >> trainable params: 801,433,600 || all params: 801,433,600 || trainable%: 100.0000 +[INFO|trainer.py:1469] 2026-07-16 01:35:07,072 >> ***** Running training ***** +[INFO|trainer.py:1470] 2026-07-16 01:35:07,072 >> Num examples = 530 +[INFO|trainer.py:1471] 2026-07-16 01:35:07,072 >> Num Epochs = 1 +[INFO|trainer.py:1472] 2026-07-16 01:35:07,072 >> Num update steps per epoch = 133 +[INFO|trainer.py:1473] 2026-07-16 01:35:07,072 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:1476] 2026-07-16 01:35:07,072 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:1477] 2026-07-16 01:35:07,072 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:1478] 2026-07-16 01:35:07,072 >> Total optimization steps = 60 +[INFO|trainer.py:1479] 2026-07-16 01:35:07,072 >> Number of trainable parameters = 801,433,600 + 0%| | 0/60 [00:00> `use_return_dict` is deprecated! 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Do not forget to share your model on huggingface.co/models =) + + + 100%|██████████| 60/60 [08:36<00:00, 8.25s/it] 100%|██████████| 60/60 [08:36<00:00, 8.60s/it] +[INFO|trainer.py:3815] 2026-07-16 01:43:43,131 >> Saving model checkpoint to /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045 +[INFO|configuration_utils.py:533] 2026-07-16 01:43:43,132 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/config.json +[INFO|configuration_utils.py:816] 2026-07-16 01:43:43,133 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/generation_config.json +{'loss': '1.778', 'grad_norm': '22.5', 'learning_rate': '4.822e-07', 'epoch': '0.07547'} +{'loss': '1.72', 'grad_norm': '6.906', 'learning_rate': '4.013e-07', 'epoch': '0.1509'} +{'loss': '1.737', 'grad_norm': '15.88', 'learning_rate': '2.77e-07', 'epoch': '0.2264'} +{'loss': '1.73', 'grad_norm': '9.062', 'learning_rate': '1.45e-07', 'epoch': '0.3019'} +{'loss': '1.787', 'grad_norm': '9.938', 'learning_rate': '4.308e-08', 'epoch': '0.3774'} +{'loss': '1.915', 'grad_norm': '20.88', 'learning_rate': '3.666e-10', 'epoch': '0.4528'} +{'train_runtime': '516.1', 'train_samples_per_second': '0.462', 'train_steps_per_second': '0.116', 'train_loss': '1.778', 'epoch': '0.4528'} + Writing model shards: 0%| | 0/1 [00:00> Model weights saved in /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/model.safetensors +[INFO|tokenization_utils_base.py:3278] 2026-07-16 01:43:44,096 >> chat template saved in /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/chat_template.jinja +[INFO|tokenization_utils_base.py:2111] 2026-07-16 01:43:44,117 >> tokenizer config file saved in /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/tokenizer_config.json +***** train metrics ***** + epoch = 0.4528 + total_flos = 26956621GF + train_loss = 1.7778 + train_runtime = 0:08:36.05 + train_samples_per_second = 0.462 + train_steps_per_second = 0.116 +Figure saved at: /home/ll/llm4rec/experiments/outputs/v46_v29_clean_user_evolution_lr5e7_ep045/training_loss.png +[WARNING|2026-07-16 01:43:44] llamafactory.extras.ploting:149 >> No metric eval_loss to plot. +[WARNING|2026-07-16 01:43:44] llamafactory.extras.ploting:149 >> No metric eval_accuracy to plot. +[INFO|modelcard.py:263] 2026-07-16 01:43:44,216 >> Dropping the following result as it does not have all the necessary fields: +{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}} diff --git a/train_results.json b/train_results.json new file mode 100644 index 0000000..2b0d48c --- /dev/null +++ b/train_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 0.4528301886792453, + "total_flos": 2.894445141093581e+16, + "train_loss": 1.7778411229451498, + "train_runtime": 516.0579, + "train_samples_per_second": 0.462, + "train_steps_per_second": 0.116 +} \ No newline at end of file diff --git a/trainer_log.jsonl b/trainer_log.jsonl new file mode 100644 index 0000000..c332a97 --- /dev/null +++ b/trainer_log.jsonl @@ -0,0 +1,7 @@ +{"current_steps": 10, "total_steps": 60, "loss": 1.7780149459838868, "lr": 4.822441799541978e-07, "epoch": 0.07547169811320754, "percentage": 16.67, "elapsed_time": "0:01:26", "remaining_time": "0:07:14"} +{"current_steps": 20, "total_steps": 60, "loss": 1.7199886322021485, "lr": 4.012935537984413e-07, "epoch": 0.1509433962264151, "percentage": 33.33, "elapsed_time": "0:02:54", "remaining_time": "0:05:49"} +{"current_steps": 30, "total_steps": 60, "loss": 1.736968994140625, "lr": 2.770297546059854e-07, "epoch": 0.22641509433962265, "percentage": 50.0, "elapsed_time": "0:04:21", "remaining_time": "0:04:21"} +{"current_steps": 40, "total_steps": 60, "loss": 1.7296815872192384, "lr": 1.4502772460993384e-07, "epoch": 0.3018867924528302, "percentage": 66.67, "elapsed_time": "0:05:46", "remaining_time": "0:02:53"} +{"current_steps": 50, 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