From 016c3bb08130b103fbbdff4a0b1a70da705b579b Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 2 Aug 2026 11:27:17 +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/v25_v19_product_world_guard_lr18e6_ep028 Source: Original Platform --- .gitattributes | 36 + README.md | 58 + all_results.json | 8 + chat_template.jinja | 89 + config.json | 63 + experiment_recipe.json | 63 + generation_config.json | 12 + model.safetensors | 3 + ...98358.ubuntu-System-Product-Name.3126868.0 | 3 + tokenizer.json | 3 + tokenizer_config.json | 16 + train.log | 2211 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 15 + trainer_state.json | 141 ++ training_args.bin | 3 + training_loss.png | Bin 0 -> 48053 bytes 17 files changed, 2732 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/Jul10_23-45-58_ubuntu-System-Product-Name/events.out.tfevents.1783698358.ubuntu-System-Product-Name.3126868.0 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 diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs 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..d58e573 --- /dev/null +++ b/README.md @@ -0,0 +1,58 @@ +--- +library_name: transformers +license: other +base_model: lldois/v19_v15_dualmode_fast_lr5e6_ep055 +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: v25_v19_product_world_guard_lr18e6_ep028 + results: [] +--- + + + +# v25_v19_product_world_guard_lr18e6_ep028 + +This model is a fine-tuned version of [lldois/v19_v15_dualmode_fast_lr5e6_ep055](https://huggingface.co/lldois/v19_v15_dualmode_fast_lr5e6_ep055) on the exp_v19_product_world_guard 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: 1.8e-06 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 202607251 +- 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: 0.02 +- num_epochs: 0.28 + +### 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..8e38edb --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 0.2819047619047619, + "total_flos": 3.606259359855821e+16, + "train_loss": 1.335793836696728, + "train_runtime": 616.3408, + "train_samples_per_second": 0.477, + "train_steps_per_second": 0.12 +} \ 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..5a27515 --- /dev/null +++ b/experiment_recipe.json @@ -0,0 +1,63 @@ +{ + "created_at": "2026-07-10 23:45:28", + "run": { + "name": "v25_v19_product_world_guard_lr18e6_ep028", + "dataset": "v19_product_world_guard", + "model_path": "/home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055", + "lr": "1.8e-6", + "epochs": 0.28, + "warmup": 0.02, + "scheduler": "cosine", + "seed": 202607251, + "note": "v19 continuation. Ultra-light product-rec repair with item replay and small user guard. Goal: keep v19 fast/item/user1 behavior while recovering product recommendation and avoiding further world-score erosion.", + "config": "/home/ll/llm4rec/experiments/configs/v25_v19_product_world_guard_lr18e6_ep028.yaml" + }, + "dataset_manifest": { + "name": "v19_product_world_guard", + "path": "/home/ll/llm4rec/experiments/data/v19_product_world_guard.jsonl", + "records": 27772, + "groups": { + "rec": 13378, + "item": 11194, + "user": 3200 + }, + "variants": { + "rec_cot_pattern_clean": 2400, + "item_short_think": 2792, + "item_compact_cot": 5597, + "rec_no_think_direct_final": 6289, + "user_strict_logic": 1208, + "rec_short_think_final": 4689, + "item_no_think_direct_final": 2805, + "user_extra_no_think_logic": 550, + "user_strict_array": 1442 + }, + "sha256": "6e45bc1b371e8ca509768327592079c144491f55adf772007ca24b1859acd29a", + "seed": 202607111 + }, + "dataset_recipe": "v19 continuation: route-balanced rec replay plus extra product rec /no_think and /think, small cleaned CoT, full item replay, and small user guard. Low LR/short epoch because v19 is already near best.", + "cot_policy": "Preserve /think reasoning supervision and do not use v7_final_only as a CoT training base. For /no_think prompts, train pure final answers without generated tags. This is route-specific behavior, not global CoT removal.", + "raw_counts": { + "rec": 19204, + "item": 10384, + "user": 2892 + }, + "eval_observations": { + "v07": "best local score so far: total=0.8978, eval_time≈47.3min; fast final outputs likely help.", + "v15": "best CoT-preserving score so far: total=0.8778, eval_time≈70.1min; logs show repeated tokens, JSON shell errors, prompt leakage, and verbose /no_think outputs.", + "v19": "best CoT-native continuation so far: total=0.8855, eval_time≈48.1min; user1 and rec4 improved but world dropped.", + "v20": "v7 final-only continuation with CoT restore failed as a CoT route: total=0.8527, item fell to 0.1840; do not use v7 as future CoT base.", + "v22": "scratch official-base 3 epoch clean CoT underperformed: total=0.8217; item/world preserved but user and rec2 are weak.", + "v23": "scratch official-base 5 epoch low-LR guard failed badly: total=0.6990; item/user collapse suggests long scratch SFT is not viable with current data mix.", + "v24": "v15 light repair is best among v22-v24 but still only total=0.8364; user2 improves but rec/world do not recover.", + "v16": "CoT pattern rewrite failed: total=0.7912; logs show malformed user JSON and fragmented recommendation reasoning.", + "v18": "low-LR mixed replay from v12 failed: total=0.8340; item/world dropped and rec outputs mixed text/itemic/think tags." + }, + "script": "/home/ll/llm4rec/experiments/run_experiments.py", + "script_sha256": "f752ec011aae9158402c880ebe487650272242b5b35d45bd4a6d9ec1c7dc33d5", + "deadline": "2026-07-11 09:00:00 +0800", + "reproduce": { + "prepare_command": "EXPERIMENT_PREPARE_ONLY=1 python3 experiments/run_experiments.py", + "train_command": "CUDA_VISIBLE_DEVICES= bash -lc 'source /home/ll/llm4rec/demo/LLaMA-Factory/.venv/bin/activate && llamafactory-cli train /home/ll/llm4rec/experiments/configs/v25_v19_product_world_guard_lr18e6_ep028.yaml'" + } +} \ No newline at end of file diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..cf5bf49 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,12 @@ +{ + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "temperature": 0.6, + "top_k": 20, + "top_p": 0.95, + "transformers_version": "5.6.0" +} diff --git a/model.safetensors b/model.safetensors new file mode 100644 index 0000000..10ea774 --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ceda855c11d7ed93c9dcbc56b7350ef3b7cbe482b160f8e4de2577ad2ce806a3 +size 1602902832 diff --git a/runs/Jul10_23-45-58_ubuntu-System-Product-Name/events.out.tfevents.1783698358.ubuntu-System-Product-Name.3126868.0 b/runs/Jul10_23-45-58_ubuntu-System-Product-Name/events.out.tfevents.1783698358.ubuntu-System-Product-Name.3126868.0 new file mode 100644 index 0000000..7f6e234 --- /dev/null +++ b/runs/Jul10_23-45-58_ubuntu-System-Product-Name/events.out.tfevents.1783698358.ubuntu-System-Product-Name.3126868.0 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cd77403b89a4ad1d691763c8022dbe01ac08896df6efdc5464fbcc2b02ef048e +size 9212 diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..8aee134 --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cd4d15f596979aecbc11ba12668cb21c9fb8452ce1235cd9d7878cc950170421 +size 16016554 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..35d445f --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,16 @@ +{ + "add_prefix_space": false, + "backend": "tokenizers", + "bos_token": null, + "clean_up_tokenization_spaces": false, + "eos_token": "<|im_end|>", + "errors": "replace", + "is_local": true, + "local_files_only": false, + "model_max_length": 131072, + "pad_token": "<|endoftext|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "Qwen2Tokenizer", + "unk_token": null +} diff --git a/train.log b/train.log new file mode 100644 index 0000000..39cc4c2 --- /dev/null +++ b/train.log @@ -0,0 +1,2211 @@ +/home/ll/llm4rec/demo/LLaMA-Factory/.venv/lib/python3.11/site-packages/jieba/_compat.py:18: 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|2026-07-10 23:45:31] 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] 2026-07-10 23:45:31,429 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:31,433 >> 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] 2026-07-10 23:45:32,121 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:32,122 >> 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] 2026-07-10 23:45:32,122 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:32,122 >> 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|2026-07-10 23:45:32] llamafactory.data.loader:144 >> Loading dataset /home/ll/llm4rec/experiments/data/v19_product_world_guard.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: 14319 examples [00:00, 127278.17 examples/s] Generating train split: 27772 examples [00:00, 134710.39 examples/s] + Converting format of dataset (num_proc=16): 0%| | 0/27772 [00:00user +【用户交互历史】： +【2025-04-06】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-14】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-02】 + --:-- [直播-关注] <|living_begin|> +【2025-10-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-02】 + --:-- [直播-关注] <|living_begin|> +【2025-10-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-06】 + --:-- [直播-关注] <|living_begin|> +【2025-10-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-09】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-13】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-22】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-23】 + --:-- [直播-关注] <|living_begin|> +【2025-11-01】 + --:-- [直播-关注] <|living_begin|> +【2025-11-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-10】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-13】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-29】 + --:-- [直播-关注] <|living_begin|> + --:-- [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|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-30】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-06】 + --:-- [直播-关注] <|living_begin|> +【2025-12-07】 + --:-- [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|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-08】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> +【2025-12-12】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-14】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-15】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-16】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> +【2025-12-18】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-19】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-20】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-22】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-23】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-03】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2026-01-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> +【2026-01-06】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2026-01-11】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-12】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-13】 + --:-- [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|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-14】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> +【2026-01-16】 + --:-- [直播-关注] <|living_begin|> + --:-- [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|> + --:-- [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|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> +【2026-01-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-19】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 19:08 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 19:53 [广告-深度转化] <|ad_begin|> +【2026-01-20】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [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-购买] <|prod_begin|> +【2026-01-21】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-22】 + 03:37 [视频-点赞/长播] <|video_begin|> + 12:02 [广告-深度转化] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 12:45 [广告-深度转化] <|ad_begin|> + 15:20 [视频-长播] <|video_begin|> + 15:20 [视频-长播] <|video_begin|> + 15:20 [视频-长播] <|video_begin|> + 16:28 [广告-深度转化] <|ad_begin|> + 18:51 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 21:27 [广告-深度转化] <|ad_begin|> + 23:42 [视频-长播] <|video_begin|> +【2026-01-23】 + 11:38 [视频-长播] <|video_begin|> + 12:14 [广告-深度转化] <|ad_begin|> + 12:32 [广告-深度转化] <|ad_begin|> + 13:05 [广告-深度转化] <|ad_begin|> + 13:30 [广告-深度转化] <|ad_begin|> + 14:33 [广告-深度转化] <|ad_begin|> + 18:01 [广告-深度转化] <|ad_begin|> + 21:04 [广告-深度转化] <|ad_begin|> +【2026-01-24】 + 08:51 [广告-深度转化] <|ad_begin|> + 08:59 [广告-深度转化] <|ad_begin|> + 11:40 [广告-深度转化] <|ad_begin|> + 12:00 [广告-深度转化] <|ad_begin|> + 12:23 [视频-长播] <|video_begin|> + 12:23 [视频-长播] <|video_begin|> + 12:37 [视频-长播] <|video_begin|> + 12:37 [视频-长播] <|video_begin|> + 12:37 [视频-长播] <|video_begin|> + 12:41 [视频-长播] <|video_begin|> + 12:52 [视频-长播] <|video_begin|> + 16:33 [广告-深度转化] <|ad_begin|> + 17:14 [广告-深度转化] <|ad_begin|> + 18:02 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 20:20 [广告-深度转化] <|ad_begin|> +【2026-01-25】 + 02:13 [广告-深度转化] <|ad_begin|> + 02:14 [视频-长播] <|video_begin|> + 02:35 [广告-深度转化] <|ad_begin|> + 04:44 [广告-深度转化] <|ad_begin|> + 05:08 [广告-深度转化] <|ad_begin|> + 07:37 [广告-深度转化] <|ad_begin|> + 12:19 [广告-深度转化] <|ad_begin|> + 12:40 [广告-深度转化] <|ad_begin|> + 13:07 [广告-深度转化] <|ad_begin|> + 14:49 [广告-深度转化] <|ad_begin|> + 15:24 [广告-深度转化] <|ad_begin|> + 18:04 [广告-深度转化] <|ad_begin|> +【2026-01-26】 + 06:44 [广告-深度转化] <|ad_begin|> + 07:09 [广告-深度转化] <|ad_begin|> + 09:28 [广告-深度转化] <|ad_begin|> + 10:58 [广告-深度转化] <|ad_begin|> + 21:05 [广告-深度转化] <|ad_begin|> + 22:32 [广告-深度转化] <|ad_begin|> +【2026-01-27】 + --:-- [直播-关注] <|living_begin|> + 04:25 [视频-长播] <|video_begin|> + 04:25 [视频-长播] <|video_begin|> + 04:28 [视频-长播] <|video_begin|> + 04:28 [视频-长播] <|video_begin|> + 06:38 [广告-深度转化] <|ad_begin|> + 08:41 [广告-深度转化] <|ad_begin|> + 09:34 [广告-深度转化] <|ad_begin|> + 12:37 [广告-深度转化] <|ad_begin|> + 12:43 [广告-深度转化] <|ad_begin|> + 13:28 [广告-深度转化] <|ad_begin|> + 16:29 [广告-深度转化] <|ad_begin|> + 16:48 [广告-深度转化] <|ad_begin|> + 16:53 [广告-深度转化] <|ad_begin|> +【2026-01-28】 + 03:39 [广告-深度转化] <|ad_begin|> + 04:27 [视频-长播] <|video_begin|> + 04:27 [视频-长播] <|video_begin|> + 04:27 [视频-长播] <|video_begin|> + 04:27 [视频-长播] <|video_begin|> + 04:31 [视频-长播] <|video_begin|> + 04:31 [视频-长播] <|video_begin|> + 06:48 [视频-长播] <|video_begin|> + 06:48 [视频-长播] <|video_begin|> + 06:48 [视频-长播] <|video_begin|> + 06:48 [视频-长播] <|video_begin|> + 06:56 [视频-长播] <|video_begin|> + 11:58 [广告-深度转化] <|ad_begin|> + 12:09 [广告-深度转化] <|ad_begin|> + 13:02 [广告-深度转化] <|ad_begin|> + 13:37 [广告-深度转化] <|ad_begin|> + 15:27 [广告-深度转化] <|ad_begin|> + 16:28 [广告-深度转化] <|ad_begin|> + 17:44 [广告-深度转化] <|ad_begin|> + 18:50 [广告-深度转化] <|ad_begin|> + 19:24 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 20:01 [广告-深度转化] <|ad_begin|> + 20:18 [广告-深度转化] <|ad_begin|> + 22:15 [广告-深度转化] <|ad_begin|> + 22:57 [视频-长播] <|video_begin|> + 22:57 [视频-关注/长播] <|video_begin|> +【2026-01-29】 + 01:01 [广告-深度转化] <|ad_begin|> + 03:05 [广告-点击] <|ad_begin|> + 12:28 [广告-点击] <|ad_begin|> + 13:06 [广告-点击] <|ad_begin|> + 13:12 [广告-点击] <|ad_begin|> + 13:19 [广告-点击] <|ad_begin|> + 13:35 [广告-深度转化] <|ad_begin|> + 13:35 [广告-点击] <|ad_begin|> + 14:23 [广告-点击] <|ad_begin|> + 16:04 [广告-点击] <|ad_begin|> + 16:04 [广告-点击] <|ad_begin|> + 16:15 [广告-点击] <|ad_begin|> + 17:29 [广告-深度转化] <|ad_begin|> + 17:29 [广告-点击] <|ad_begin|> + 17:43 [广告-点击] <|ad_begin|> + 17:56 [广告-点击] <|ad_begin|> + 18:01 [广告-点击] <|ad_begin|> + 18:25 [广告-点击] <|ad_begin|> + 18:25 [广告-点击] <|ad_begin|> + 18:32 [广告-点击] <|ad_begin|> + 18:37 [视频-长播] <|video_begin|> + 18:39 [视频-长播] <|video_begin|> + 18:39 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-30】 + 03:33 [广告-点击] <|ad_begin|> + 10:36 [广告-深度转化] <|ad_begin|> + 10:36 [广告-点击] <|ad_begin|> + 13:25 [广告-点击] <|ad_begin|> + 15:06 [广告-点击] <|ad_begin|> + 15:17 [广告-点击] <|ad_begin|> + 15:19 [广告-点击] <|ad_begin|> + 15:22 [广告-点击] <|ad_begin|> + 15:23 [广告-点击] <|ad_begin|> + 15:42 [广告-深度转化] <|ad_begin|> + 15:42 [广告-点击] <|ad_begin|> + 16:12 [视频-转发/长播] <|video_begin|> + 16:45 [广告-深度转化] <|ad_begin|> + 16:45 [广告-点击] <|ad_begin|> + 16:49 [视频-长播] <|video_begin|> + 17:06 [广告-点击] <|ad_begin|> + 17:11 [视频-长播] <|video_begin|> + 17:11 [视频-长播] <|video_begin|> + 17:14 [视频-长播] <|video_begin|> + 17:56 [广告-点击] <|ad_begin|> + 17:58 [广告-点击] <|ad_begin|> + 18:50 [广告-点击] <|ad_begin|> + 19:19 [视频-转发/长播] <|video_begin|> + --:-- [商品-购买] <|prod_begin|> + 19:41 [视频-长播] <|video_begin|> +【2026-01-31】 + 04:46 [广告-点击] <|ad_begin|> + 05:59 [视频-长播] <|video_begin|> + 05:59 [视频-长播] <|video_begin|> + 05:59 [视频-长播] <|video_begin|> + 13:55 [广告-点击] <|ad_begin|> + 14:03 [广告-深度转化] <|ad_begin|> + 14:03 [广告-点击] <|ad_begin|> + 14:30 [广告-点击] <|ad_begin|> +【2026-02-01】 + --:-- [直播-关注] <|living_begin|> + 04:07 [广告-点击] <|ad_begin|> + 05:54 [视频-长播] <|video_begin|> + 05:54 [视频-长播] <|video_begin|> + 06:49 [视频-长播] <|video_begin|> + 07:33 [广告-点击] <|ad_begin|> + 07:59 [广告-点击] <|ad_begin|> + 08:02 [广告-点击] <|ad_begin|> + 08:06 [视频-长播] <|video_begin|> + 08:10 [视频-长播] <|video_begin|> + 09:59 [广告-点击] <|ad_begin|> + 11:44 [广告-点击] <|ad_begin|> + 13:06 [广告-点击] <|ad_begin|> + 13:41 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-02-02】 + 02:01 [广告-点击] <|ad_begin|> + 02:04 [广告-深度转化] <|ad_begin|> + 02:04 [广告-点击] <|ad_begin|> + 02:07 [广告-点击] <|ad_begin|> + 02:09 [广告-点击] <|ad_begin|> + 02:13 [广告-点击] <|ad_begin|> + 02:19 [广告-点击] <|ad_begin|> + 02:20 [广告-点击] <|ad_begin|> + 02:23 [广告-点击] <|ad_begin|> + 02:26 [广告-点击] <|ad_begin|> + 02:29 [视频-长播] <|video_begin|> + 02:50 [广告-点击] <|ad_begin|> + 07:46 [视频-长播] <|video_begin|> + 07:46 [视频-长播] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 09:22 [广告-点击] <|ad_begin|> + 15:13 [广告-点击] <|ad_begin|> + 15:38 [广告-点击] <|ad_begin|> + 15:40 [广告-点击] <|ad_begin|> + 15:44 [广告-点击] <|ad_begin|> + 15:53 [广告-点击] <|ad_begin|> + 16:04 [广告-点击] <|ad_begin|> + 16:11 [广告-点击] <|ad_begin|> + 16:14 [广告-点击] <|ad_begin|> + 16:21 [广告-点击] <|ad_begin|> + 16:22 [广告-点击] <|ad_begin|> + 16:41 [广告-点击] <|ad_begin|> + 23:25 [广告-点击] <|ad_begin|> +【2026-02-03】 + 15:26 [广告-点击] <|ad_begin|> +【2026-02-04】 + 09:15 [广告-点击] <|ad_begin|> + 09:17 [广告-点击] <|ad_begin|> + 15:27 [广告-点击] <|ad_begin|> +角色任务：你是极端严苛的用户行为数据挖掘专家，同时也是数据格式化专家，请结合以上用户交互历史，面向给定主题提取带有递进行为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）： 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 必须处于同一生活场景和主题类目下，并具备极强的需求补完关系。 +2.兴趣因果递进：交互 B 是因为 交互 A 产生的副作用或新需求，或者 A 是 B 的诱因。 +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：从泛化祈福到特定化、功能化的玄学消费演进 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化祈福到特定化、功能化的玄学消费演进", + "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 + +按时间顺序筛选关键交互，抽取兴趣变化和行为转化链路，最终只返回合法 JSON。 + +{"logic_chain":{"name":"从泛化祈福到特定化、功能化的玄学消费演进","events":[{"date":"2025-10-09","action":"[商品-购买] <|prod_begin|>","logic":"初始触发：购买泛化的、带有普适性祝福寓意（天官赐福）的玄学商品，作为兴趣起点。"},{"date":"2025-11-10","action":"[商品-购买] <|prod_begin|>","logic":"兴趣强化与时效性认知：从通用款转向具有明确年份（2026马年）指向的同类商品，并带有“老师推荐”标签，表明用户开始接受特定圈层的引导，认知从“随意买”向“跟着买”演进。"},{"date":"2025-12-15","action":"[商品-购买] <|prod_begin|>","logic":"认知分化与深度探索：兴趣从汉地主流的“天官赐福”体系，首次转向具有明确地域和文化符号（布宫、藏粉）的藏传佛教体系，实现了文化圈层的跨越，是显著的认知增量。"},{"date":"2025-12-18","action":"[商品-点击] <|prod_begin|>","logic":"需求聚焦与功能收敛：在经历了泛化祈福和文化体系探索后，用户的兴趣收敛到具有明确“招财”功能的“五路貔貅”上。这标志着用户的需求从“保平安”的模糊概念，聚焦到了“求财”这一具体目标，完成了从发散到聚焦的认知闭环。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-05-20】 + --:-- [直播-关注] <|living_begin|> +【2025-07-03】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-04】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-06】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-11-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-11】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-10】 + 22:33 [广告-深度转化] <|ad_begin|> +【2025-12-11】 + 09:05 [广告-深度转化] <|ad_begin|> + 09:46 [广告-深度转化] <|ad_begin|> + 12:05 [广告-深度转化] <|ad_begin|> + 13:09 [广告-深度转化] <|ad_begin|> +【2025-12-12】 + 15:38 [广告-深度转化] <|ad_begin|> +【2025-12-13】 + 09:20 [广告-深度转化] <|ad_begin|> + 09:37 [广告-深度转化] <|ad_begin|> + 10:38 [广告-深度转化] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 14:50 [广告-深度转化] <|ad_begin|> +【2025-12-14】 + 06:45 [广告-深度转化] <|ad_begin|> + 07:23 [广告-深度转化] <|ad_begin|> + 11:20 [广告-深度转化] <|ad_begin|> + 17:01 [广告-深度转化] <|ad_begin|> +【2025-12-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-16】 + 08:29 [广告-深度转化] <|ad_begin|> + 11:39 [广告-深度转化] <|ad_begin|> + 11:39 [广告-点击] <|ad_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:01 [广告-点击] <|ad_begin|> + 13:32 [广告-深度转化] <|ad_begin|> + 13:32 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 16:37 [广告-深度转化] <|ad_begin|> + 16:37 [广告-点击] <|ad_begin|> + 16:37 [广告-深度转化] <|ad_begin|> + 16:37 [广告-点击] <|ad_begin|> +【2025-12-17】 + 04:53 [广告-深度转化] <|ad_begin|> + 04:53 [广告-点击] <|ad_begin|> + 05:36 [广告-深度转化] <|ad_begin|> + 05:36 [广告-点击] <|ad_begin|> + 12:18 [广告-点击] <|ad_begin|> + 14:55 [广告-深度转化] <|ad_begin|> + 14:55 [广告-点击] <|ad_begin|> + 15:02 [广告-点击] <|ad_begin|> +【2025-12-19】 + 14:23 [广告-深度转化] <|ad_begin|> + 14:23 [广告-点击] <|ad_begin|> + 15:45 [广告-深度转化] <|ad_begin|> + 15:45 [广告-点击] <|ad_begin|> + 16:22 [广告-深度转化] <|ad_begin|> + 16:22 [广告-点击] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + 16:37 [广告-深度转化] <|ad_begin|> + 16:37 [广告-点击] <|ad_begin|> + 18:12 [广告-深度转化] <|ad_begin|> + 18:12 [广告-点击] <|ad_begin|> +【2025-12-20】 + 03:14 [广告-深度转化] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 03:36 [广告-深度转化] <|ad_begin|> + 03:36 [广告-点击] <|ad_begin|> + 03:36 [广告-深度转化] <|ad_begin|> + 03:36 [广告-点击] <|ad_begin|> + 04:37 [广告-深度转化] <|ad_begin|> + 04:37 [广告-点击] <|ad_begin|> + 04:54 [广告-深度转化] <|ad_begin|> + 04:54 [广告-点击] <|ad_begin|> + 05:11 [广告-深度转化] <|ad_begin|> + 05:11 [广告-点击] <|ad_begin|> + 05:38 [广告-深度转化] <|ad_begin|> + 05:38 [广告-点击] <|ad_begin|> + 05:43 [广告-深度转化] <|ad_begin|> + 05:43 [广告-点击] <|ad_begin|> + 06:27 [广告-深度转化] <|ad_begin|> + 06:27 [广告-点击] <|ad_begin|> + 07:34 [广告-深度转化] <|ad_begin|> + 07:34 [广告-点击] <|ad_begin|> + 10:21 [广告-深度转化] <|ad_begin|> + 10:21 [广告-点击] <|ad_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 13:55 [广告-点击] <|ad_begin|> + 18:02 [广告-深度转化] <|ad_begin|> + 18:02 [广告-点击] <|ad_begin|> +【2025-12-21】 + 09:38 [广告-深度转化] <|ad_begin|> + 09:38 [广告-点击] <|ad_begin|> + 10:54 [广告-深度转化] <|ad_begin|> + 10:54 [广告-点击] <|ad_begin|> + 14:06 [广告-深度转化] <|ad_begin|> + 14:06 [广告-点击] <|ad_begin|> + 14:30 [广告-点击] <|ad_begin|> + 14:43 [广告-点击] <|ad_begin|> +【2025-12-27】 + 13:19 [广告-深度转化] <|ad_begin|> + 13:19 [广告-点击] <|ad_begin|> +【2025-12-28】 + 08:58 [广告-深度转化] <|ad_begin|> + 08:58 [广告-点击] <|ad_begin|> + 10:42 [广告-深度转化] <|ad_begin|> + 10:42 [广告-点击] <|ad_begin|> +【2025-12-30】 + 14:38 [广告-深度转化] <|ad_begin|> + 14:38 [广告-点击] <|ad_begin|> +【2025-12-31】 + 01:24 [广告-深度转化] <|ad_begin|> + 01:24 [广告-点击] <|ad_begin|> + 05:57 [广告-深度转化] <|ad_begin|> + 05:57 [广告-点击] <|ad_begin|> + 08:46 [广告-点击] <|ad_begin|> + 08:47 [广告-深度转化] <|ad_begin|> + 08:47 [广告-点击] <|ad_begin|> +【2026-01-01】 + 15:10 [广告-点击] <|ad_begin|> +【2026-01-05】 + 13:27 [广告-点击] <|ad_begin|> +【2026-01-06】 + 03:33 [广告-点击] <|ad_begin|> +【2026-01-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-10】 + 08:50 [广告-深度转化] <|ad_begin|> + 08:50 [广告-点击] <|ad_begin|> +【2026-01-11】 + 02:59 [广告-深度转化] <|ad_begin|> + 02:59 [广告-点击] <|ad_begin|> + 03:04 [广告-深度转化] <|ad_begin|> + 03:04 [广告-点击] <|ad_begin|> +【2026-01-12】 + 05:36 [广告-点击] <|ad_begin|> +【2026-01-13】 + 14:02 [广告-深度转化] <|ad_begin|> + 14:02 [广告-点击] <|ad_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|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-14】 + 01:46 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-15】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-16】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-17】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-18】 + --:-- [商品-加购] <|prod_begin|> +【2026-01-19】 + 04:41 [广告-深度转化] <|ad_begin|> + 04:41 [广告-点击] <|ad_begin|> + 14:45 [广告-深度转化] <|ad_begin|> + 14:45 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-21】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-22】 + 14:40 [视频-评论/点赞/长播] <|video_begin|> + 15:25 [视频-评论/长播] <|video_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> +【2026-01-23】 + 04:22 [视频-评论/点赞/长播] <|video_begin|> + 05:04 [视频-评论/长播] <|video_begin|> + 05:42 [视频-评论/点赞/长播] <|video_begin|> + 15:05 [视频-评论/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-24】 + 05:54 [视频-收藏/长播] <|video_begin|> + 07:04 [视频-评论/长播] <|video_begin|> + 07:12 [视频-评论/长播] <|video_begin|> + 07:12 [视频-转发/收藏/长播] <|video_begin|> + 09:09 [视频-转发/长播] <|video_begin|> + 09:11 [视频-关注/点赞/长播] <|video_begin|> + 12:04 [视频-关注/收藏/长播] <|video_begin|> + 12:24 [视频-评论/长播] <|video_begin|> + 13:16 [视频-评论/长播] <|video_begin|> +【2026-01-25】 + 07:35 [视频-评论/长播] <|video_begin|> +【2026-01-26】 + 02:13 [视频-点赞/长播] <|video_begin|> + 03:01 [视频-点赞/长播] <|video_begin|> + 03:39 [视频-转发/点赞/长播] <|video_begin|> + 09:09 [视频-点赞/长播] <|video_begin|> + 09:09 [视频-点赞/长播] <|video_begin|> + 12:30 [视频-评论/长播] <|video_begin|> + 13:58 [视频-点赞/长播] <|video_begin|> + 14:26 [广告-深度转化] <|ad_begin|> + 14:26 [广告-点击] <|ad_begin|> + 14:43 [视频-点赞/长播] <|video_begin|> + 14:43 [视频-点赞/长播] <|video_begin|> +【2026-01-27】 + 03:33 [广告-深度转化] <|ad_begin|> + 03:33 [广告-点击] <|ad_begin|> + 03:43 [视频-点赞/长播] <|video_begin|> + 04:00 [视频-点赞/长播] <|video_begin|> + 04:35 [视频-评论/长播] <|video_begin|> + 08:49 [广告-深度转化] <|ad_begin|> + 08:49 [广告-点击] <|ad_begin|> + 09:53 [广告-深度转化] <|ad_begin|> + 09:53 [广告-点击] <|ad_begin|> + 10:15 [视频-评论/长播] <|video_begin|> + 12:39 [视频-关注/点赞/长播] <|video_begin|> + 12:56 [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-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-28】 + 02:29 [视频-评论/长播] <|video_begin|> + 02:29 [视频-评论/长播] <|video_begin|> + 02:30 [广告-深度转化] <|ad_begin|> + 02:30 [广告-点击] <|ad_begin|> + 03:11 [视频-点赞/长播] <|video_begin|> + 03:14 [视频-点赞/长播] <|video_begin|> + 03:57 [视频-点赞/长播] <|video_begin|> + 04:46 [视频-评论/长播] <|video_begin|> + 04:54 [视频-点赞/长播] <|video_begin|> + 05:04 [视频-点赞/长播] <|video_begin|> + 05:06 [视频-点赞/长播] <|video_begin|> + 05:09 [视频-点赞/长播] <|video_begin|> + 10:14 [视频-点赞/长播] <|video_begin|> + 10:14 [视频-评论/长播] <|video_begin|> + 12:23 [视频-转发/长播] <|video_begin|> + 12:36 [视频-转发/长播] <|video_begin|> + 12:36 [视频-转发/长播] <|video_begin|> + 12:39 [视频-转发/长播] <|video_begin|> + 12:40 [视频-转发/长播] <|video_begin|> + 12:49 [视频-转发/长播] <|video_begin|> + 14:47 [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-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|> + --:-- [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|> + --:-- [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-加购] <|prod_begin|> + 16:39 [视频-点赞/长播] <|video_begin|> + 17:18 [视频-点赞/长播] <|video_begin|> +【2026-01-29】 + 04:17 [视频-点赞/长播] <|video_begin|> + 04:57 [视频-评论/长播] <|video_begin|> + 05:32 [视频-点赞/长播] <|video_begin|> + 05:32 [视频-点赞/长播] <|video_begin|> + 05:34 [视频-评论/长播] <|video_begin|> + 05:34 [视频-评论/长播] <|video_begin|> + 06:06 [视频-点赞/长播] <|video_begin|> + 06:06 [视频-点赞/长播] <|video_begin|> + 11:19 [广告-深度转化] <|ad_begin|> + 11:19 [广告-点击] <|ad_begin|> + 11:37 [视频-评论/长播] <|video_begin|> + 11:37 [视频-转发/长播] <|video_begin|> + 12:36 [视频-评论/长播] <|video_begin|> + 16:52 [视频-转发/长播] <|video_begin|> +【2026-01-30】 + 04:44 [视频-评论/点赞/长播] <|video_begin|> + 05:37 [视频-点赞/长播] <|video_begin|> + 13:52 [视频-评论/长播] <|video_begin|> + 16:17 [视频-收藏/长播] <|video_begin|> + 16:17 [视频-转发/长播] <|video_begin|> + 16:37 [视频-点赞/长播] <|video_begin|> +【2026-01-31】 + 03:38 [视频-点赞/长播] <|video_begin|> + 03:57 [视频-点赞/长播] <|video_begin|> + 03:59 [视频-点赞/长播] <|video_begin|> + 08:20 [视频-转发/长播] <|video_begin|> + 08:32 [视频-评论/长播] <|video_begin|> + 08:38 [视频-转发/长播] <|video_begin|> + 10:04 [视频-点赞/长播] <|video_begin|> + 10:04 [视频-评论/长播] <|video_begin|> + 11:14 [视频-点赞/长播] <|video_begin|> + 11:14 [视频-点赞/长播] <|video_begin|> + 11:16 [视频-点赞/长播] <|video_begin|> + 13:17 [广告-点击] <|ad_begin|> + 18:34 [视频-转发/长播] <|video_begin|> + 19:00 [视频-点赞/长播] <|video_begin|> +【2026-02-01】 + 03:07 [视频-点赞/长播] <|video_begin|> + 03:35 [视频-点赞/长播] <|video_begin|> + 04:56 [视频-点赞/长播] <|video_begin|> + 04:56 [视频-评论/长播] <|video_begin|> + 05:20 [广告-点击] <|ad_begin|> + 07:43 [广告-点击] <|ad_begin|> + 08:32 [广告-深度转化] <|ad_begin|> + 08:32 [广告-点击] <|ad_begin|> + 08:51 [视频-点赞/长播] <|video_begin|> + 09:20 [视频-点赞/长播] <|video_begin|> + 15:27 [视频-评论/长播] <|video_begin|> +【2026-02-02】 + 06:21 [视频-收藏/点赞/长播] <|video_begin|> + 06:43 [广告-点击] <|ad_begin|> + 07:25 [视频-点赞/长播] <|video_begin|> + 12:56 [广告-深度转化] <|ad_begin|> + 12:56 [广告-点击] <|ad_begin|> + 16:02 [视频-转发/长播] <|video_begin|> + 16:24 [视频-点赞/长播] <|video_begin|> + 16:54 [广告-深度转化] <|ad_begin|> + 16:54 [广告-点击] <|ad_begin|> + 18:36 [视频-评论/长播] <|video_begin|> +【2026-02-03】 + 03:53 [广告-深度转化] <|ad_begin|> + 03:53 [广告-点击] <|ad_begin|> + 04:02 [视频-评论/点赞/长播] <|video_begin|> + 05:10 [视频-点赞/长播] <|video_begin|> + 08:39 [广告-深度转化] <|ad_begin|> + 08:39 [广告-点击] <|ad_begin|> + 08:46 [视频-评论/长播] <|video_begin|> + 14:30 [视频-点赞/长播] <|video_begin|> + 14:30 [视频-点赞/长播] <|video_begin|> + 14:30 [视频-转发/长播] <|video_begin|> + 15:50 [视频-评论/长播] <|video_begin|> +【2026-02-04】 + 08:29 [视频-点赞/长播] <|video_begin|> + 08:53 [视频-转发/长播] <|video_begin|> + 09:29 [视频-长播] <|video_begin|> + 09:29 [视频-长播] <|video_begin|> + 09:29 [视频-长播] <|video_begin|> + 09:55 [视频-长播] <|video_begin|> + 09:58 [视频-长播] <|video_begin|> + 09:58 [视频-长播] <|video_begin|> + 11:23 [视频-长播] <|video_begin|> + 11:23 [视频-长播] <|video_begin|> + 11:23 [视频-评论/长播] <|video_begin|> + 11:27 [视频-长播] <|video_begin|> + 11:27 [视频-长播] <|video_begin|> + 11:33 [视频-长播] <|video_begin|> + 11:35 [视频-长播] <|video_begin|> + 13:39 [视频-长播] <|video_begin|> + 13:39 [视频-长播] <|video_begin|> + 13:39 [视频-长播] <|video_begin|> + 16:18 [视频-长播] <|video_begin|> + 16:18 [视频-点赞/长播] <|video_begin|> + 16:22 [视频-长播] <|video_begin|> + 16:22 [视频-长播] <|video_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:25 [视频-长播] <|video_begin|> + 16:35 [广告-点击] <|ad_begin|> + 17:01 [视频-长播] <|video_begin|> + 17:01 [视频-长播] <|video_begin|> + 17:01 [视频-长播] <|video_begin|> + 17:33 [视频-长播] <|video_begin|> + 17:33 [视频-长播] <|video_begin|> + 18:53 [视频-长播] <|video_begin|> + 18:53 [视频-长播] <|video_begin|> +【2026-02-05】 + 03:31 [视频-收藏/点赞/长播] <|video_begin|> + 03:57 [视频-长播] <|video_begin|> + 03:57 [视频-点赞/长播] <|video_begin|> + 03:57 [广告-深度转化] <|ad_begin|> + 03:57 [广告-点击] <|ad_begin|> + 08:47 [视频-长播] <|video_begin|> + 08:51 [视频-长播] <|video_begin|> + 08:58 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:12 [视频-评论/长播] <|video_begin|> + 09:12 [视频-点赞/长播] <|video_begin|> + 11:47 [视频-长播] <|video_begin|> + 11:58 [视频-长播] <|video_begin|> + 11:58 [视频-长播] <|video_begin|> + 11:59 [视频-长播] <|video_begin|> + 12:05 [视频-长播] <|video_begin|> + 12:05 [视频-长播] <|video_begin|> + 12:09 [视频-长播] <|video_begin|> + 12:15 [视频-长播] <|video_begin|> + 12:15 [视频-长播] <|video_begin|> + 12:15 [视频-长播] <|video_begin|> + 12:37 [视频-长播] <|video_begin|> + 13:43 [视频-长播] <|video_begin|> + 13:43 [视频-长播] <|video_begin|> + 13:55 [视频-长播] <|video_begin|> + 13:55 [视频-长播] <|video_begin|> + 14:33 [视频-长播] <|video_begin|> + +角色任务：你将作为一个极端严苛的用户行为数据挖掘专家和数据格式化专家，依据以上用户交互历史，围绕目标主题，精确提取出所有相关的历史交互信息。 + +主题：从被动接收到主动探索：DIY礼物兴趣的具象化过程 + +输出格式要求：输出必须且仅为包含 SID 的 JSON 数组，绝对不要输出任何额外的解释、提示或格式化外的文字。 + +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 +["<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|ad_begin|>","<|ad_begin|>","<|prod_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|ad_begin|>"]<|im_end|> +<|im_start|>user +【用户交互历史】： +【2023-09-23】 + --:-- [商品-购买] <|prod_begin|> +【2023-09-29】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-02】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-11】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-01】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2023-11-03】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-22】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-23】 + --:-- [商品-购买] <|prod_begin|> +【2023-12-06】 + --:-- [商品-购买] <|prod_begin|> +【2023-12-24】 + --:-- [商品-购买] <|prod_begin|> +【2024-04-01】 + --:-- [商品-购买] <|prod_begin|> +【2024-09-08】 + --:-- [商品-购买] <|prod_begin|> +【2024-09-26】 + --:-- [商品-购买] <|prod_begin|> +【2024-10-15】 + --:-- [商品-购买] <|prod_begin|> +【2024-11-02】 + --:-- [商品-购买] <|prod_begin|> +【2024-11-25】 + --:-- [商品-购买] <|prod_begin|> +【2024-12-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-02】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-01-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-06】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-01-15】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-02】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-05-05】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-05-06】 + --:-- [直播-打赏] <|living_begin|> +【2025-05-14】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-06-22】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-21】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-07-25】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-08-07】 + --:-- [直播-打赏] <|living_begin|> +【2025-08-12】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-08-17】 + --:-- [直播-打赏] <|living_begin|> +【2025-08-28】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-08-30】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-08-31】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-09-07】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-10】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-11】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-29】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-01】 + --:-- [直播-打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-24】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-31】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-22】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-09】 + 04:43 [广告-点击] <|ad_begin|> +【2025-12-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-19】 + 14:46 [广告-深度转化] <|ad_begin|> + 14:46 [广告-点击] <|ad_begin|> + 16:27 [广告-点击] <|ad_begin|> +【2025-12-20】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-22】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-24】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 16:11 [广告-深度转化] <|ad_begin|> + 16:11 [广告-点击] <|ad_begin|> +【2025-12-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-12-27】 + 08:09 [广告-深度转化] <|ad_begin|> + 08:09 [广告-点击] <|ad_begin|> +【2025-12-28】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-30】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 12:05 [广告-深度转化] <|ad_begin|> + 12:05 [广告-点击] <|ad_begin|> + 12:52 [广告-深度转化] <|ad_begin|> + 12:52 [广告-点击] <|ad_begin|> +【2025-12-31】 + --:-- [直播-关注] <|living_begin|> + 14:59 [广告-深度转化] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> +【2026-01-02】 + 15:05 [广告-点击] <|ad_begin|> +【2026-01-03】 + 00:30 [广告-点击] <|ad_begin|> +【2026-01-04】 + 09:02 [广告-点击] <|ad_begin|> +【2026-01-05】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2026-01-06】 + --:-- [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|> + --:-- [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|> + --:-- [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|> + 16:56 [广告-深度转化] <|ad_begin|> + 16:56 [广告-点击] <|ad_begin|> +【2026-01-07】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-08】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-10】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 00:12 [广告-深度转化] <|ad_begin|> + 00:12 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 13:55 [广告-点击] <|ad_begin|> +【2026-01-12】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-13】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-14】 + 06:51 [广告-深度转化] <|ad_begin|> + 06:51 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-15】 + 00:10 [广告-深度转化] <|ad_begin|> + 00:10 [广告-点击] <|ad_begin|> +【2026-01-19】 + 03:49 [广告-深度转化] <|ad_begin|> + 03:49 [广告-点击] <|ad_begin|> +【2026-01-20】 + 02:47 [广告-深度转化] <|ad_begin|> + 02:47 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-21】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 01:18 [广告-深度转化] <|ad_begin|> + 01:18 [广告-点击] <|ad_begin|> + 23:49 [广告-点击] <|ad_begin|> +【2026-01-22】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 02:54 [视频-点赞/长播] <|video_begin|> + 03:12 [广告-深度转化] <|ad_begin|> + 03:12 [广告-点击] <|ad_begin|> +【2026-01-23】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 00:26 [视频-关注/长播] <|video_begin|> + 00:44 [视频-关注/长播] <|video_begin|> + 01:47 [视频-关注/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 08:16 [广告-深度转化] <|ad_begin|> + 08:16 [广告-点击] <|ad_begin|> + 08:19 [广告-深度转化] <|ad_begin|> + 08:19 [广告-点击] <|ad_begin|> + 08:23 [视频-关注/长播] <|video_begin|> +【2026-01-24】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 08:40 [广告-深度转化] <|ad_begin|> + 08:40 [广告-点击] <|ad_begin|> + 11:23 [视频-关注/长播] <|video_begin|> + 21:41 [广告-深度转化] <|ad_begin|> + 21:41 [广告-点击] <|ad_begin|> +【2026-01-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 23:48 [视频-关注/长播] <|video_begin|> + 23:55 [视频-关注/长播] <|video_begin|> +【2026-01-26】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 01:25 [广告-深度转化] <|ad_begin|> + 01:25 [广告-点击] <|ad_begin|> + 09:15 [广告-深度转化] <|ad_begin|> + 09:15 [广告-点击] <|ad_begin|> + 23:25 [广告-深度转化] <|ad_begin|> + 23:25 [广告-点击] <|ad_begin|> +【2026-01-27】 + 01:16 [视频-关注/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 08:18 [视频-关注/长播] <|video_begin|> + 08:46 [视频-关注/长播] <|video_begin|> + 09:38 [广告-深度转化] <|ad_begin|> + 09:38 [广告-点击] <|ad_begin|> + 13:40 [广告-点击] <|ad_begin|> + 13:51 [视频-关注/长播] <|video_begin|> + 14:04 [视频-关注/长播] <|video_begin|> + 14:43 [广告-深度转化] <|ad_begin|> + 14:43 [广告-点击] <|ad_begin|> + 16:35 [广告-深度转化] <|ad_begin|> + 16:35 [广告-点击] <|ad_begin|> + 23:43 [视频-关注/长播] <|video_begin|> +【2026-01-28】 + --:-- [直播-关注] <|living_begin|> + 06:58 [广告-深度转化] <|ad_begin|> + 06:58 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 15:29 [广告-深度转化] <|ad_begin|> + 15:29 [广告-点击] <|ad_begin|> +【2026-01-29】 + --:-- [直播-关注] <|living_begin|> + 09:54 [视频-关注/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|> + 16:40 [视频-关注/长播] <|video_begin|> + 17:14 [广告-深度转化] <|ad_begin|> + 17:14 [广告-点击] <|ad_begin|> +【2026-01-31】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 01:24 [广告-深度转化] <|ad_begin|> + 01:24 [广告-点击] <|ad_begin|> +【2026-02-01】 + 09:35 [广告-深度转化] <|ad_begin|> + 09:35 [广告-点击] <|ad_begin|> + 15:12 [广告-深度转化] <|ad_begin|> + 15:12 [广告-点击] <|ad_begin|> + 16:47 [广告-深度转化] <|ad_begin|> + 16:47 [广告-点击] <|ad_begin|> + 18:29 [广告-点击] <|ad_begin|> +【2026-02-02】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 01:33 [视频-长播] <|video_begin|> + 01:33 [视频-长播] <|video_begin|> + 01:55 [广告-深度转化] <|ad_begin|> + 01:55 [广告-点击] <|ad_begin|> + 03:06 [视频-长播] <|video_begin|> + 03:06 [视频-长播] <|video_begin|> + 03:08 [视频-长播] <|video_begin|> + 03:08 [视频-长播] <|video_begin|> + 04:00 [视频-长播] <|video_begin|> + 04:00 [视频-长播] <|video_begin|> + 06:15 [视频-长播] <|video_begin|> + 06:46 [视频-长播] <|video_begin|> + 06:46 [视频-长播] <|video_begin|> + 06:46 [视频-浏览] <|video_begin|> + 08:35 [视频-长播] <|video_begin|> + 08:35 [视频-长播] <|video_begin|> + 08:35 [视频-长播] <|video_begin|> + 09:24 [广告-深度转化] <|ad_begin|> + 09:24 [广告-点击] <|ad_begin|> + 22:27 [视频-长播] <|video_begin|> + 22:27 [视频-长播] <|video_begin|> +【2026-02-03】 + 01:26 [视频-关注/长播] <|video_begin|> + 01:31 [视频-长播] <|video_begin|> + 02:40 [广告-深度转化] <|ad_begin|> + 02:40 [广告-点击] <|ad_begin|> + 02:51 [视频-长播] <|video_begin|> + 03:07 [视频-长播] <|video_begin|> + 03:07 [视频-长播] <|video_begin|> + 03:17 [视频-长播] <|video_begin|> + 03:19 [视频-长播] <|video_begin|> + 03:19 [视频-长播] <|video_begin|> + 03:21 [视频-长播] <|video_begin|> + 03:21 [视频-长播] <|video_begin|> + 03:25 [视频-长播] <|video_begin|> + 03:25 [视频-长播] <|video_begin|> + 04:56 [视频-长播] <|video_begin|> + 09:35 [视频-长播] <|video_begin|> + 09:35 [视频-长播] <|video_begin|> + 09:35 [视频-长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 09:38 [视频-关注/长播] <|video_begin|> +【2026-02-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-关注/长播] <|video_begin|> + 00:40 [视频-长播] <|video_begin|> + 00:40 [视频-长播] <|video_begin|> + 00:40 [视频-长播] <|video_begin|> + 00:40 [视频-长播] <|video_begin|> + 00:44 [视频-长播] <|video_begin|> + 00:44 [视频-长播] <|video_begin|> + 00:44 [视频-长播] <|video_begin|> + 00:54 [视频-长播] <|video_begin|> + 04:08 [视频-长播] <|video_begin|> + 04:08 [视频-长播] <|video_begin|> + 07:32 [视频-长播] <|video_begin|> + 07:32 [视频-长播] <|video_begin|> + 07:32 [视频-长播] <|video_begin|> + 07:38 [视频-长播] <|video_begin|> + 23:37 [视频-关注/长播] <|video_begin|> +【2026-02-05】 + 00:38 [广告-深度转化] <|ad_begin|> + 00:38 [广告-点击] <|ad_begin|> + 05:22 [广告-深度转化] <|ad_begin|> + 05:22 [广告-点击] <|ad_begin|> + 06:34 [视频-长播] <|video_begin|> + 06:34 [视频-长播] <|video_begin|> +角色任务：你需要扮演极端严苛的用户行为数据挖掘专家以及数据格式化专家，基于以上用户交互历史，针对给定主题识别并提取具有递进逻辑和内在联系的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 视频-浏览、视频-长播、搜索-搜索、商品-点击、商品-购买、直播-关注、直播-首次打赏、广告-点击、广告-深度转化 +核心判定逻辑（递进性准则）： +按照时间顺序抽取 5 步以内的行为链，要求后续交互B必须是前序交互A在场景需求协同补充、副作用诱发或兴趣细化升级上的延伸——也就是说，B 必须因 A 而产生，严禁提取任何品类平级、内容重复或仅受天气/促销影响形成的并列凑单行为。 +1.场景驱动协同：交互 B 相对于交互 A，必须在同一生活场景与主题类目下形成强需求补完关系。 +2.兴趣因果递进：交互 B 应是交互 A 带来的副作用需求或新增需求的结果，或者 A 对 B 具有明确诱发作用。 +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。 +请面向以下主题提取行为逻辑链： +主题：从泛化健康焦虑到具体问题解决方案的探索 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化健康焦虑到具体问题解决方案的探索", + "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":"从泛化健康焦虑到具体问题解决方案的探索","events":[{"date":"2024-04-01","action":"[商品-购买] <|prod_begin|>","logic":"初始触发：首次出现明确的健康焦虑信号，聚焦于“防脱”这一普遍的男性形象问题。"},{"date":"2025-09-11","action":"[商品-购买] <|prod_begin|>","logic":"问题持续：时隔一年多再次购买防脱产品，表明该问题持续存在且未得到满意解决，强化了健康焦虑的背景。"},{"date":"2025-09-11","action":"[商品-购买] <|prod_begin|>","logic":"认知跃迁与问题深化：在解决“防脱”问题的同一天，行为首次从外部形象问题（脱发）转向了更核心、更私密的男科健康问题（私处不适），实现了从泛化焦虑到具体病症的认知聚焦。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-03-13】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-04-23】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-04-24】 + --:-- [直播-关注] <|living_begin|> +【2025-04-25】 + --:-- [直播-关注] <|living_begin|> +【2025-04-26】 + --:-- [直播-关注] <|living_begin|> +【2025-04-27】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-04-29】 + --:-- [直播-关注] <|living_begin|> +【2025-05-08】 + --:-- [直播-关注] <|living_begin|> +【2025-05-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-05-12】 + --:-- [直播-关注] <|living_begin|> +【2025-05-14】 + --:-- [直播-关注] <|living_begin|> +【2025-05-15】 + --:-- [直播-关注] <|living_begin|> +【2025-05-19】 + --:-- [直播-关注] <|living_begin|> +【2025-05-23】 + --:-- [直播-关注] <|living_begin|> +【2025-05-25】 + --:-- [直播-关注] <|living_begin|> +【2025-05-28】 + --:-- [直播-关注] <|living_begin|> +【2025-05-30】 + --:-- [直播-关注] <|living_begin|> +【2025-05-31】 + --:-- [直播-关注] <|living_begin|> +【2025-06-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-06-06】 + --:-- [直播-关注] <|living_begin|> +【2025-06-07】 + --:-- [直播-关注] <|living_begin|> +【2025-06-08】 + --:-- [直播-关注] <|living_begin|> +【2025-06-11】 + --:-- [直播-关注] <|living_begin|> +【2025-06-13】 + --:-- [直播-关注] <|living_begin|> +【2025-06-15】 + --:-- [直播-关注] <|living_begin|> +【2025-06-25】 + --:-- [直播-关注] <|living_begin|> +【2025-06-26】 + --:-- [直播-关注] <|living_begin|> +【2025-06-27】 + --:-- [直播-关注] <|living_begin|> +【2025-06-28】 + --:-- [直播-关注] <|living_begin|> +【2025-07-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-07-02】 + --:-- [直播-关注] <|living_begin|> +【2025-07-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-27】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-11】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-14】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-16】 + --:-- [直播-关注] <|living_begin|> +【2025-08-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-28】 + --:-- [直播-关注] <|living_begin|> +【2025-08-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-31】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-08】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-13】 + --:-- [直播-关注] <|living_begin|> +【2025-09-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-22】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-25】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-27】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-02】 + --:-- [直播-关注] <|living_begin|> +【2025-10-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-18】 + --:-- [直播-关注] <|living_begin|> +【2025-10-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-05】 + --:-- [直播-关注] <|living_begin|> +【2025-11-11】 + --:-- [直播-关注] <|living_begin|> +【2025-11-13】 + --:-- [直播-关注] <|living_begin|> +【2025-11-15】 + --:-- [直播-关注] <|living_begin|> +【2025-11-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-17】 + --:-- [直播-关注] <|living_begin|> +【2025-12-26】 + --:-- [直播-关注] <|living_begin|> +【2025-12-27】 + --:-- [直播-关注] <|living_begin|> +【2026-01-01】 + --:-- [直播-关注] <|living_begin|> +【2026-01-07】 + --:-- [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|> +【2026-01-08】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-09】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-10】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-11】 + --:-- [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|> +【2026-01-12】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-15】 + --:-- [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|> +【2026-01-16】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-18】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-19】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-20】 + --:-- [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|> +【2026-01-22】 + 07:47 [视频-转发/长播] <|video_begin|> + 07:47 [视频-点赞/长播] <|video_begin|> +【2026-01-23】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-25】 + 22:30 [视频-转发/收藏/长播] <|video_begin|> +【2026-01-26】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-30】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-31】 + 13:15 [广告-深度转化] <|ad_begin|> + 21:17 [广告-深度转化] <|ad_begin|> + 21:18 [广告-深度转化] <|ad_begin|> + 21:23 [广告-深度转化] <|ad_begin|> + 21:33 [广告-深度转化] <|ad_begin|> + 21:36 [广告-深度转化] <|ad_begin|> + 21:38 [广告-深度转化] <|ad_begin|> + 21:43 [广告-深度转化] <|ad_begin|> + 22:07 [广告-深度转化] <|ad_begin|> +【2026-02-01】 + 00:10 [广告-深度转化] <|ad_begin|> + 01:27 [广告-深度转化] <|ad_begin|> + 01:30 [广告-深度转化] <|ad_begin|> + 04:04 [广告-深度转化] <|ad_begin|> + 04:09 [广告-深度转化] <|ad_begin|> + 04:45 [广告-深度转化] <|ad_begin|> + 08:36 [广告-深度转化] <|ad_begin|> + 08:41 [广告-深度转化] <|ad_begin|> + 11:40 [广告-深度转化] <|ad_begin|> + 11:57 [广告-深度转化] <|ad_begin|> + 21:13 [广告-深度转化] <|ad_begin|> + 21:13 [广告-深度转化] <|ad_begin|> + 21:15 [广告-深度转化] <|ad_begin|> + 21:35 [广告-深度转化] <|ad_begin|> + 22:09 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 22:52 [视频-长播] <|video_begin|> + 23:25 [广告-深度转化] <|ad_begin|> + 23:29 [视频-长播] <|video_begin|> + 23:29 [视频-长播] <|video_begin|> +【2026-02-02】 + 00:03 [广告-深度转化] <|ad_begin|> + 01:42 [广告-深度转化] <|ad_begin|> + 01:43 [广告-深度转化] <|ad_begin|> + 02:20 [视频-长播] <|video_begin|> + 02:26 [视频-长播] <|video_begin|> + 04:04 [广告-深度转化] <|ad_begin|> + 04:07 [广告-深度转化] <|ad_begin|> + 04:11 [广告-深度转化] <|ad_begin|> + 04:42 [广告-深度转化] <|ad_begin|> + 04:45 [广告-深度转化] <|ad_begin|> + 04:46 [广告-深度转化] <|ad_begin|> + 06:19 [视频-长播] <|video_begin|> + 07:15 [广告-深度转化] <|ad_begin|> + 07:17 [广告-深度转化] <|ad_begin|> + 07:18 [广告-深度转化] <|ad_begin|> + 08:25 [视频-长播] <|video_begin|> + 10:01 [视频-长播] <|video_begin|> + 10:01 [视频-长播] <|video_begin|> + 11:22 [视频-长播] <|video_begin|> + 21:53 [广告-深度转化] <|ad_begin|> + 22:37 [视频-长播] <|video_begin|> + 22:37 [视频-长播] <|video_begin|> + 23:05 [视频-长播] <|video_begin|> + 23:53 [视频-长播] <|video_begin|> +【2026-02-03】 + 03:19 [视频-长播] <|video_begin|> + 03:19 [视频-浏览] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 08:43 [广告-深度转化] <|ad_begin|> + 11:25 [视频-长播] <|video_begin|> + 21:30 [视频-长播] <|video_begin|> + 21:58 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 22:29 [视频-长播] <|video_begin|> + 23:25 [视频-长播] <|video_begin|> + 23:59 [视频-长播] <|video_begin|> + 23:59 [视频-长播] <|video_begin|> +【2026-02-04】 + 00:05 [视频-长播] <|video_begin|> + 00:05 [视频-长播] <|video_begin|> + 00:12 [视频-长播] <|video_begin|> + 00:20 [广告-深度转化] <|ad_begin|> + 00:36 [视频-长播] <|video_begin|> + 00:46 [广告-深度转化] <|ad_begin|> + 01:16 [广告-深度转化] <|ad_begin|> + 01:16 [广告-深度转化] <|ad_begin|> + 01:24 [广告-深度转化] <|ad_begin|> + 01:25 [广告-深度转化] <|ad_begin|> + 01:26 [广告-深度转化] <|ad_begin|> + 01:31 [视频-长播] <|video_begin|> + 02:42 [视频-长播] <|video_begin|> + 03:14 [广告-深度转化] <|ad_begin|> + 04:34 [视频-长播] <|video_begin|> + 04:43 [广告-深度转化] <|ad_begin|> + 05:56 [广告-深度转化] <|ad_begin|> + 06:27 [视频-长播] <|video_begin|> + 06:27 [视频-长播] <|video_begin|> + 06:27 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:32 [视频-长播] <|video_begin|> + 09:56 [广告-深度转化] <|ad_begin|> + 12:03 [广告-深度转化] <|ad_begin|> + 21:56 [广告-深度转化] <|ad_begin|> + 22:10 [广告-点击] <|ad_begin|> + 22:11 [广告-点击] <|ad_begin|> + 22:17 [广告-点击] <|ad_begin|> + 22:21 [广告-深度转化] <|ad_begin|> + 22:21 [广告-点击] <|ad_begin|> + 22:22 [广告-深度转化] <|ad_begin|> + 22:22 [广告-点击] <|ad_begin|> + 22:27 [广告-点击] <|ad_begin|> + 22:27 [广告-点击] <|ad_begin|> + 22:28 [广告-点击] <|ad_begin|> + 22:28 [广告-点击] <|ad_begin|> + 22:29 [广告-点击] <|ad_begin|> + 22:29 [广告-点击] <|ad_begin|> + 22:30 [广告-点击] <|ad_begin|> + 22:30 [广告-点击] <|ad_begin|> + 22:30 [广告-点击] <|ad_begin|> + 22:31 [广告-点击] <|ad_begin|> + 23:16 [广告-点击] <|ad_begin|> + 23:16 [广告-点击] <|ad_begin|> + 23:16 [广告-点击] <|ad_begin|> + 23:45 [视频-长播] <|video_begin|> +【2026-02-05】 + 00:13 [视频-长播] <|video_begin|> + 00:30 [广告-点击] <|ad_begin|> + 00:30 [广告-点击] <|ad_begin|> + 00:43 [广告-点击] <|ad_begin|> + 01:19 [广告-点击] <|ad_begin|> + 01:22 [广告-点击] <|ad_begin|> + 01:24 [广告-点击] <|ad_begin|> + 01:25 [广告-深度转化] <|ad_begin|> + 01:25 [广告-点击] <|ad_begin|> + 01:25 [广告-点击] <|ad_begin|> + 01:26 [广告-深度转化] <|ad_begin|> + 01:26 [广告-点击] <|ad_begin|> + 01:27 [广告-深度转化] <|ad_begin|> + 01:27 [广告-点击] <|ad_begin|> + 01:28 [广告-深度转化] <|ad_begin|> + 01:28 [广告-点击] <|ad_begin|> + 01:29 [广告-深度转化] <|ad_begin|> + 01:29 [广告-点击] <|ad_begin|> + 01:30 [广告-深度转化] <|ad_begin|> + 01:30 [广告-点击] <|ad_begin|> + 02:16 [视频-长播] <|video_begin|> + 02:16 [视频-长播] <|video_begin|> + 02:16 [视频-长播] <|video_begin|> + 03:03 [广告-点击] <|ad_begin|> + 03:04 [广告-点击] <|ad_begin|> + 03:05 [广告-点击] <|ad_begin|> + 03:06 [广告-点击] <|ad_begin|> + 03:07 [广告-点击] <|ad_begin|> + 03:08 [广告-点击] <|ad_begin|> + 03:09 [广告-点击] <|ad_begin|> + 03:10 [广告-点击] <|ad_begin|> + 03:11 [广告-点击] <|ad_begin|> + 03:11 [广告-点击] <|ad_begin|> + 03:12 [广告-点击] <|ad_begin|> + 03:13 [广告-点击] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 03:15 [广告-点击] <|ad_begin|> + 03:16 [广告-深度转化] <|ad_begin|> + 03:16 [广告-点击] <|ad_begin|> + 03:17 [广告-深度转化] <|ad_begin|> + 03:17 [广告-点击] <|ad_begin|> + 03:18 [广告-点击] <|ad_begin|> + 04:41 [广告-点击] <|ad_begin|> + 06:04 [视频-长播] <|video_begin|> + 06:12 [视频-长播] <|video_begin|> + 06:12 [视频-长播] <|video_begin|> + 06:12 [视频-长播] <|video_begin|> + 06:12 [视频-长播] <|video_begin|> + 06:40 [视频-长播] <|video_begin|> + 06:47 [广告-点击] <|ad_begin|> + 06:48 [广告-点击] <|ad_begin|> + 08:16 [广告-点击] <|ad_begin|> + 09:01 [广告-深度转化] <|ad_begin|> + 09:01 [广告-点击] <|ad_begin|> + 10:26 [广告-点击] <|ad_begin|> + 10:30 [广告-点击] <|ad_begin|> + 10:30 [广告-点击] <|ad_begin|> + 10:32 [广告-点击] <|ad_begin|> + 11:32 [广告-深度转化] <|ad_begin|> + 11:32 [广告-点击] <|ad_begin|> + 11:33 [广告-深度转化] <|ad_begin|> + 11:33 [广告-点击] <|ad_begin|> + 11:34 [广告-点击] <|ad_begin|> + 11:37 [广告-点击] <|ad_begin|> + 11:38 [广告-点击] <|ad_begin|> + 11:39 [广告-点击] <|ad_begin|> + 11:41 [广告-深度转化] <|ad_begin|> + 11:41 [广告-点击] <|ad_begin|> + 11:42 [广告-点击] <|ad_begin|> + 11:43 [广告-深度转化] <|ad_begin|> + 11:43 [广告-点击] <|ad_begin|> + 11:43 [广告-点击] <|ad_begin|> + 11:43 [广告-深度转化] <|ad_begin|> + 11:43 [广告-点击] <|ad_begin|> + 11:50 [广告-点击] <|ad_begin|> + 12:47 [广告-深度转化] <|ad_begin|> + 12:47 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_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：从娱乐消遣到社会纪实内容的深度探索 + +输出格式要求：请务必仅返回一个包含 SID 的 JSON 数组，不要附带任何额外的文字解释或冗余内容。 + +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 +["<|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 +你负责根据用户多域行为理解用户兴趣偏好，并输出该用户在各场景中的目标内容。 +以下是一个用户的多域历史行为信息： +用户在直播域: 关注了主播 <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>。 +用户视频行为: 深度观看了 <|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|>, <|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|>，对视频 <|video_begin|>, <|video_begin|>, <|video_begin|>, <|video_begin|> 有过点赞/长播行为，看过视频 <|video_begin|>，对视频 <|video_begin|> 有过转发/长播行为。 +广告行为: 对广告 <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|> 完成过深度转化，点击过广告 <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>, <|ad_begin|>。 + +请根据以上信息，给出该用户在直播、电商、视频、广告场景中的目标内容。/think<|im_end|> +<|im_start|>assistant + +【兴趣归纳】根据用户的交互历史，可以归纳出以下几个核心兴趣类目： 1. 时政与军事资讯：这是用户最稳定且深入的核心兴趣。用户通过`直播-关注` (<|living_begin|>, 3660056176, 1131031528, 3738042564) 多次关注军事、国际局势和两岸关系领域的博主，并在近期通过`视频-长播`及`视频-转发/长播` (<|video_begin|>, 183611343351) 等高意向行为，持续消费相关内容，表现出极高的关注度和粘性。 2. 健康与养生：该兴趣贯穿用户的行为历史，且近期表现出极强的需求信号。早期以关注养生带货主播为主 <|living_begin|>，近期则涌现出大量`广告-点击`和`广告-深度转化`行为，内容高度集中于特定健康问题(尤其是男性健康)及本地化医疗服务。交互频次极高，表明用户正处于该领域信息的主动获取阶段。 3. 乡土与生活纪实：用户对展现真实、接地气的生活内容有持续偏好。 +【行为证据】用户的消费偏好呈现出明显的“务实”和“接地气”特征。在内容风格上，他偏爱`口语化讲解`、`实在诚信`、`接地气唠嗑`风格的主播，而非过度包装的内容。这种偏好也体现在广告互动上，他关注的汽车、家装等广告多以性价比和实用性为卖点。 跨域协同信号非常显著： * 地域关联性强：用户早期关注的`甘肃白银主播`与其近期大量点击的位于甘肃定西、兰州、临夏等地的医疗服务广告高度相关，表明其线上行为与现实地理位置及生活需求紧密绑定。 * 兴趣驱动转化：在直播域建立的“健康养生”兴趣，直接映射到广告域中对医疗健康类广告的大量点击和转化行为，形成了清晰的“内容兴趣 → 现实需求 → 广告转化”路径。 +【预测总结】基于用户近期的行为密度和兴趣演变，预测用户接下来可能会对以下内容表现出较高兴趣： 1. 时事深度解读类视频：鉴于用户对时政军事的持续高度关注，他很可能会点击由专业人士或风格通俗的创作者制作的，关于国内外热点事件、军事动态或区域局势分析的短视频或中长视频。 2. 本地化生活服务信息：由于用户对本地医疗广告的高频互动，推测他可能也会关注本地新闻、民生政策(如养老金 <|video_begin|>)、社区活动等实用信息流内容，这些内容满足了他务实和贴近生活的需求。 + +该用户最近喜欢的视频有: <|video_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, 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configuration file /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:56,436 >> 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 +} + + +labels: + +按时间顺序筛选关键交互，抽取兴趣变化和行为转化链路，最终只返回合法 JSON。 + +{"logic_chain":{"name":"从泛化祈福到特定化、功能化的玄学消费演进","events":[{"date":"2025-10-09","action":"[商品-购买] <|prod_begin|>","logic":"初始触发：购买泛化的、带有普适性祝福寓意（天官赐福）的玄学商品，作为兴趣起点。"},{"date":"2025-11-10","action":"[商品-购买] <|prod_begin|>","logic":"兴趣强化与时效性认知：从通用款转向具有明确年份（2026马年）指向的同类商品，并带有“老师推荐”标签，表明用户开始接受特定圈层的引导，认知从“随意买”向“跟着买”演进。"},{"date":"2025-12-15","action":"[商品-购买] <|prod_begin|>","logic":"认知分化与深度探索：兴趣从汉地主流的“天官赐福”体系，首次转向具有明确地域和文化符号（布宫、藏粉）的藏传佛教体系，实现了文化圈层的跨越，是显著的认知增量。"},{"date":"2025-12-18","action":"[商品-点击] <|prod_begin|>","logic":"需求聚焦与功能收敛：在经历了泛化祈福和文化体系探索后，用户的兴趣收敛到具有明确“招财”功能的“五路貔貅”上。这标志着用户的需求从“保平安”的模糊概念，聚焦到了“求财”这一具体目标，完成了从发散到聚焦的认知闭环。"}]}}<|im_end|> +["<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|ad_begin|>","<|ad_begin|>","<|prod_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|ad_begin|>"]<|im_end|> +{"logic_chain":{"name":"从泛化健康焦虑到具体问题解决方案的探索","events":[{"date":"2024-04-01","action":"[商品-购买] <|prod_begin|>","logic":"初始触发：首次出现明确的健康焦虑信号，聚焦于“防脱”这一普遍的男性形象问题。"},{"date":"2025-09-11","action":"[商品-购买] <|prod_begin|>","logic":"问题持续：时隔一年多再次购买防脱产品，表明该问题持续存在且未得到满意解决，强化了健康焦虑的背景。"},{"date":"2025-09-11","action":"[商品-购买] <|prod_begin|>","logic":"认知跃迁与问题深化：在解决“防脱”问题的同一天，行为首次从外部形象问题（脱发）转向了更核心、更私密的男科健康问题（私处不适），实现了从泛化焦虑到具体病症的认知聚焦。"}]}}<|im_end|> +["<|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|> + +【兴趣归纳】根据用户的交互历史，可以归纳出以下几个核心兴趣类目： 1. 时政与军事资讯：这是用户最稳定且深入的核心兴趣。用户通过`直播-关注` (<|living_begin|>, 3660056176, 1131031528, 3738042564) 多次关注军事、国际局势和两岸关系领域的博主，并在近期通过`视频-长播`及`视频-转发/长播` (<|video_begin|>, 183611343351) 等高意向行为，持续消费相关内容，表现出极高的关注度和粘性。 2. 健康与养生：该兴趣贯穿用户的行为历史，且近期表现出极强的需求信号。早期以关注养生带货主播为主 <|living_begin|>，近期则涌现出大量`广告-点击`和`广告-深度转化`行为，内容高度集中于特定健康问题(尤其是男性健康)及本地化医疗服务。交互频次极高，表明用户正处于该领域信息的主动获取阶段。 3. 乡土与生活纪实：用户对展现真实、接地气的生活内容有持续偏好。 +【行为证据】用户的消费偏好呈现出明显的“务实”和“接地气”特征。在内容风格上，他偏爱`口语化讲解`、`实在诚信`、`接地气唠嗑`风格的主播，而非过度包装的内容。这种偏好也体现在广告互动上，他关注的汽车、家装等广告多以性价比和实用性为卖点。 跨域协同信号非常显著： * 地域关联性强：用户早期关注的`甘肃白银主播`与其近期大量点击的位于甘肃定西、兰州、临夏等地的医疗服务广告高度相关，表明其线上行为与现实地理位置及生活需求紧密绑定。 * 兴趣驱动转化：在直播域建立的“健康养生”兴趣，直接映射到广告域中对医疗健康类广告的大量点击和转化行为，形成了清晰的“内容兴趣 → 现实需求 → 广告转化”路径。 +【预测总结】基于用户近期的行为密度和兴趣演变，预测用户接下来可能会对以下内容表现出较高兴趣： 1. 时事深度解读类视频：鉴于用户对时政军事的持续高度关注，他很可能会点击由专业人士或风格通俗的创作者制作的，关于国内外热点事件、军事动态或区域局势分析的短视频或中长视频。 2. 本地化生活服务信息：由于用户对本地医疗广告的高频互动，推测他可能也会关注本地新闻、民生政策(如养老金 <|video_begin|>)、社区活动等实用信息流内容，这些内容满足了他务实和贴近生活的需求。 + +该用户最近喜欢的视频有: <|video_begin|><|im_end|> + +[INFO|2026-07-10 23:45:56] llamafactory.model.model_utils.kv_cache:144 >> KV cache is disabled during training. +[INFO|2026-07-10 23:45:56] llamafactory.model.model_utils.liger_kernel:144 >> Liger kernel has been applied to the model. +[INFO|modeling_utils.py:748] 2026-07-10 23:45:56,764 >> loading weights file /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055/model.safetensors +[INFO|modeling_utils.py:821] 2026-07-10 23:45:56,764 >> Will use dtype=torch.bfloat16 as defined in model's config object +[INFO|configuration_utils.py:1027] 2026-07-10 23:45:56,908 >> 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/v19_v15_dualmode_fast_lr5e6_ep055/generation_config.json +[INFO|configuration_utils.py:1027] 2026-07-10 23:45:58,844 >> 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] 2026-07-10 23:45:58,844 >> Could not locate the custom_generate/generate.py inside /home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055. +[INFO|2026-07-10 23:45:58] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled. +[INFO|2026-07-10 23:45:58] llamafactory.model.model_utils.attention:144 >> Using FlashAttention-2 for faster training and inference. +[INFO|2026-07-10 23:45:58] llamafactory.model.adapter:144 >> Pure bf16 / BAdam detected, remaining trainable params in half precision. +[INFO|2026-07-10 23:45:58] llamafactory.model.adapter:144 >> Fine-tuning method: Full +[INFO|2026-07-10 23:45:58] llamafactory.model.loader:144 >> trainable params: 801,433,600 || all params: 801,433,600 || trainable%: 100.0000 +[INFO|trainer.py:1469] 2026-07-10 23:45:58,995 >> ***** Running training ***** +[INFO|trainer.py:1470] 2026-07-10 23:45:58,995 >> Num examples = 1,050 +[INFO|trainer.py:1471] 2026-07-10 23:45:58,995 >> Num Epochs = 1 +[INFO|trainer.py:1472] 2026-07-10 23:45:58,995 >> Num update steps per epoch = 263 +[INFO|trainer.py:1473] 2026-07-10 23:45:58,995 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:1476] 2026-07-10 23:45:58,995 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:1477] 2026-07-10 23:45:58,995 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:1478] 2026-07-10 23:45:58,995 >> Total optimization steps = 74 +[INFO|trainer.py:1479] 2026-07-10 23:45:58,996 >> Number of trainable parameters = 801,433,600 + 0%| | 0/74 [00:00> `use_return_dict` is deprecated! 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Do not forget to share your model on huggingface.co/models =) + + + 100%|██████████| 74/74 [10:16<00:00, 8.33s/it] 100%|██████████| 74/74 [10:16<00:00, 8.33s/it] +[INFO|trainer.py:3815] 2026-07-10 23:56:15,337 >> Saving model checkpoint to /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028 +[INFO|configuration_utils.py:533] 2026-07-10 23:56:15,339 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/config.json +[INFO|configuration_utils.py:816] 2026-07-10 23:56:15,339 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/generation_config.json +{'loss': '1.334', 'grad_norm': '71.5', 'learning_rate': '1.797e-06', 'epoch': '0.01905'} +{'loss': '1.362', 'grad_norm': '7.812', 'learning_rate': '1.758e-06', 'epoch': '0.0381'} +{'loss': '1.369', 'grad_norm': '13', 'learning_rate': '1.679e-06', 'epoch': '0.05714'} +{'loss': '1.242', 'grad_norm': '10.06', 'learning_rate': '1.564e-06', 'epoch': '0.07619'} +{'loss': '1.433', 'grad_norm': '8.562', 'learning_rate': '1.416e-06', 'epoch': '0.09524'} +{'loss': '1.272', 'grad_norm': '28.25', 'learning_rate': '1.244e-06', 'epoch': '0.1143'} +{'loss': '1.272', 'grad_norm': '7.062', 'learning_rate': '1.056e-06', 'epoch': '0.1333'} +{'loss': '1.195', 'grad_norm': '52.5', 'learning_rate': '8.607e-07', 'epoch': '0.1524'} +{'loss': '1.331', 'grad_norm': '7.25', 'learning_rate': '6.671e-07', 'epoch': '0.1714'} +{'loss': '1.384', 'grad_norm': '9.188', 'learning_rate': '4.844e-07', 'epoch': '0.1905'} +{'loss': '1.289', 'grad_norm': '38.5', 'learning_rate': '3.215e-07', 'epoch': '0.2095'} +{'loss': '1.292', 'grad_norm': '35.75', 'learning_rate': '1.86e-07', 'epoch': '0.2286'} +{'loss': '1.357', 'grad_norm': '9.25', 'learning_rate': '8.432e-08', 'epoch': '0.2476'} +{'loss': '1.478', 'grad_norm': '8.75', 'learning_rate': '2.133e-08', 'epoch': '0.2667'} +{'train_runtime': '616.3', 'train_samples_per_second': '0.477', 'train_steps_per_second': '0.12', 'train_loss': '1.336', 'epoch': '0.2819'} + Writing model shards: 0%| | 0/1 [00:00> Model weights saved in /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/model.safetensors +[INFO|tokenization_utils_base.py:3278] 2026-07-10 23:56:16,294 >> chat template saved in /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/chat_template.jinja +[INFO|tokenization_utils_base.py:2111] 2026-07-10 23:56:16,317 >> tokenizer config file saved in /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/tokenizer_config.json +***** train metrics ***** + epoch = 0.2819 + total_flos = 33585907GF + train_loss = 1.3358 + train_runtime = 0:10:16.34 + train_samples_per_second = 0.477 + train_steps_per_second = 0.12 +Figure saved at: /home/ll/llm4rec/experiments/outputs/v25_v19_product_world_guard_lr18e6_ep028/training_loss.png +[WARNING|2026-07-10 23:56:16] llamafactory.extras.ploting:149 >> 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