From c3bdd76b11a97622da9da1af3d1e598b1990e07d Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Wed, 19 Aug 2026 05:59:17 +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/v26_v21_product_rec_rebalance_lr22e6_ep032 Source: Original Platform --- .gitattributes | 36 + README.md | 58 + all_results.json | 8 + chat_template.jinja | 89 + config.json | 63 + experiment_recipe.json | 62 + generation_config.json | 12 + model.safetensors | 3 + ...98359.ubuntu-System-Product-Name.3126867.0 | 3 + tokenizer.json | 3 + tokenizer_config.json | 16 + train.log | 2255 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 22 + trainer_state.json | 190 ++ training_args.bin | 3 + training_loss.png | Bin 0 -> 51577 bytes 17 files changed, 2831 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_23-45-59_ubuntu-System-Product-Name/events.out.tfevents.1783698359.ubuntu-System-Product-Name.3126867.0 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 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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..ab11eb2 --- /dev/null +++ b/README.md @@ -0,0 +1,58 @@ +--- +library_name: transformers +license: other +base_model: lldois/v21_v15_user_repair_rec_fast_lr4e6_ep055 +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: v26_v21_product_rec_rebalance_lr22e6_ep032 + results: [] +--- + + + +# v26_v21_product_rec_rebalance_lr22e6_ep032 + +This model is a fine-tuned version of [lldois/v21_v15_user_repair_rec_fast_lr4e6_ep055](https://huggingface.co/lldois/v21_v15_user_repair_rec_fast_lr4e6_ep055) on the exp_v21_product_rec_rebalance 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: 2.2e-06 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 202607261 +- 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: 0.32 + +### 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..db42250 --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 0.3204837490551776, + "total_flos": 5.064451518240154e+16, + "train_loss": 0.745630294084549, + "train_runtime": 819.7494, + "train_samples_per_second": 0.516, + "train_steps_per_second": 0.129 +} \ 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..e7dc195 --- /dev/null +++ b/experiment_recipe.json @@ -0,0 +1,62 @@ +{ + "created_at": "2026-07-10 23:45:28", + "run": { + "name": "v26_v21_product_rec_rebalance_lr22e6_ep032", + "dataset": "v21_product_rec_rebalance", + "model_path": "/home/ll/llm4rec/experiments/outputs/v21_v15_user_repair_rec_fast_lr4e6_ep055", + "lr": "2.2e-6", + "epochs": 0.32, + "warmup": 0.02, + "scheduler": "cosine", + "seed": 202607261, + "note": "v21 continuation. Rec rebalance from the best user1 checkpoint: heavier product/video rec route supervision, item replay, and only light user replay. Goal: preserve user1 while raising rec1/rec2.", + "config": "/home/ll/llm4rec/experiments/configs/v26_v21_product_rec_rebalance_lr22e6_ep032.yaml" + }, + "dataset_manifest": { + "name": "v21_product_rec_rebalance", + "path": "/home/ll/llm4rec/experiments/data/v21_product_rec_rebalance.jsonl", + "records": 37594, + "groups": { + "rec": 24000, + "item": 11194, + "user": 2400 + }, + "variants": { + "rec_short_think_final": 9600, + "item_no_think_direct_final": 2805, + "rec_no_think_direct_final": 14400, + "user_strict_logic": 904, + "user_strict_array": 1094, + "item_short_think": 2792, + "item_compact_cot": 5597, + "user_extra_no_think_logic": 402 + }, + "sha256": "5b58f82b4dfaed0a3bee1dc5ae24ee4406ae40c70038e6bca271ca61b8fe50fa", + "seed": 202607112 + }, + "dataset_recipe": "v21 continuation: heavier product/video rec repair, full item replay, and light user replay. Tests whether highest-user checkpoint can recover recommendation metrics.", + "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/v26_v21_product_rec_rebalance_lr22e6_ep032.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..56b90fa --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d62b80611c55e38f996606a87abf1760fd7dd44aceebbd130c2f4023b374c657 +size 1602902832 diff --git a/runs/Jul10_23-45-59_ubuntu-System-Product-Name/events.out.tfevents.1783698359.ubuntu-System-Product-Name.3126867.0 b/runs/Jul10_23-45-59_ubuntu-System-Product-Name/events.out.tfevents.1783698359.ubuntu-System-Product-Name.3126867.0 new file mode 100644 index 0000000..30ec736 --- /dev/null +++ b/runs/Jul10_23-45-59_ubuntu-System-Product-Name/events.out.tfevents.1783698359.ubuntu-System-Product-Name.3126867.0 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ce2c6dc40a6d1425d8bf419c655fbcb25f2e99ecdc25476909a09b19649b6003 +size 10665 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..c9897af --- /dev/null +++ b/train.log @@ -0,0 +1,2255 @@ +/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 23:45:31,431 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v21_v15_user_repair_rec_fast_lr4e6_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/v21_v15_user_repair_rec_fast_lr4e6_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/v21_v15_user_repair_rec_fast_lr4e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:32,123 >> 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/v21_product_rec_rebalance.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: 14866 examples [00:00, 135892.83 examples/s] Generating train split: 35890 examples [00:00, 164865.30 examples/s] Generating train split: 37594 examples [00:00, 160968.12 examples/s] + Converting format of dataset (num_proc=16): 0%| | 0/37594 [00:00user +【用户交互历史】： +【2025-01-10】 + --:-- [直播-关注] <|living_begin|> +【2025-01-27】 + --:-- [直播-关注] <|living_begin|> +【2025-02-12】 + --:-- [直播-关注] <|living_begin|> +【2025-02-21】 + --:-- [直播-关注] <|living_begin|> +【2025-02-28】 + --:-- [直播-关注] <|living_begin|> +【2025-03-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-03-30】 + --:-- [直播-关注] <|living_begin|> +【2025-04-04】 + --:-- [直播-关注] <|living_begin|> +【2025-04-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-04-19】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-21】 + --:-- [直播-关注] <|living_begin|> +【2025-05-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-06】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-05-07】 + --:-- [直播-关注] <|living_begin|> +【2025-05-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-09】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-19】 + --:-- [直播-关注] <|living_begin|> +【2025-06-30】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-07】 + --:-- [直播-关注] <|living_begin|> +【2025-07-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-22】 + --:-- [直播-关注] <|living_begin|> +【2025-07-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-08-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-23】 + --:-- [直播-关注] <|living_begin|> +【2025-08-30】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-31】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-10】 + --:-- [直播-关注] <|living_begin|> +【2025-09-11】 + --:-- [直播-打赏] <|living_begin|> +【2025-09-22】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-30】 + --:-- [直播-打赏] <|living_begin|> +【2025-10-02】 + --:-- [直播-关注] <|living_begin|> +【2025-10-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-18】 + --:-- [直播-关注] <|living_begin|> +【2025-10-19】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-21】 + --:-- [直播-关注] <|living_begin|> +【2025-11-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-27】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-02】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-08】 + --:-- [直播-关注] <|living_begin|> + 13:12 [广告-深度转化] <|ad_begin|> + 13:38 [广告-深度转化] <|ad_begin|> +【2025-12-09】 + --:-- [直播-打赏] <|living_begin|> + 11:55 [广告-深度转化] <|ad_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|> + 23:04 [广告-深度转化] <|ad_begin|> +【2025-12-10】 + 09:32 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + 14:47 [广告-深度转化] <|ad_begin|> + 23:04 [广告-深度转化] <|ad_begin|> +【2025-12-12】 + --:-- [商品-购买] <|prod_begin|> + 22:56 [广告-深度转化] <|ad_begin|> +【2025-12-14】 + 01:47 [广告-深度转化] <|ad_begin|> + 22:46 [广告-深度转化] <|ad_begin|> +【2025-12-15】 + --:-- [商品-购买] <|prod_begin|> + 22:00 [广告-深度转化] <|ad_begin|> + 23:52 [广告-深度转化] <|ad_begin|> +【2025-12-16】 + 00:02 [广告-深度转化] <|ad_begin|> + 08:16 [广告-深度转化] <|ad_begin|> + 08:24 [广告-深度转化] <|ad_begin|> +【2025-12-19】 + 22:56 [广告-深度转化] <|ad_begin|> +【2025-12-20】 + 23:01 [广告-深度转化] <|ad_begin|> +【2025-12-21】 + 00:17 [广告-深度转化] <|ad_begin|> +【2025-12-23】 + --:-- [直播-关注] <|living_begin|> + 09:19 [广告-深度转化] <|ad_begin|> +【2025-12-27】 + 01:11 [广告-深度转化] <|ad_begin|> +【2025-12-28】 + 07:42 [广告-深度转化] <|ad_begin|> +【2025-12-29】 + 08:53 [广告-深度转化] <|ad_begin|> + 09:45 [广告-深度转化] <|ad_begin|> + 12:12 [广告-深度转化] <|ad_begin|> +【2025-12-30】 + 08:53 [广告-深度转化] <|ad_begin|> +【2025-12-31】 + 08:27 [广告-深度转化] <|ad_begin|> + 13:24 [广告-深度转化] <|ad_begin|> +【2026-01-02】 + 13:37 [广告-深度转化] <|ad_begin|> +【2026-01-03】 + 08:09 [广告-深度转化] <|ad_begin|> + 08:09 [广告-点击] <|ad_begin|> + 21:54 [广告-点击] <|ad_begin|> +【2026-01-04】 + 08:28 [广告-深度转化] <|ad_begin|> + 08:28 [广告-点击] <|ad_begin|> + 12:43 [广告-深度转化] <|ad_begin|> + 12:43 [广告-点击] <|ad_begin|> + 22:56 [广告-深度转化] <|ad_begin|> + 22:56 [广告-点击] <|ad_begin|> + 23:06 [广告-深度转化] <|ad_begin|> + 23:06 [广告-点击] <|ad_begin|> +【2026-01-05】 + 14:09 [广告-点击] <|ad_begin|> +【2026-01-06】 + 11:43 [广告-深度转化] <|ad_begin|> + 11:43 [广告-点击] <|ad_begin|> +【2026-01-07】 + 10:50 [广告-深度转化] <|ad_begin|> + 10:50 [广告-点击] <|ad_begin|> +【2026-01-08】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 23:39 [广告-点击] <|ad_begin|> +【2026-01-09】 + 05:59 [广告-点击] <|ad_begin|> + 06:01 [广告-点击] <|ad_begin|> + 06:03 [广告-点击] <|ad_begin|> + 09:34 [广告-深度转化] <|ad_begin|> + 09:34 [广告-点击] <|ad_begin|> + 13:47 [广告-深度转化] <|ad_begin|> + 13:47 [广告-点击] <|ad_begin|> +【2026-01-10】 + 12:11 [广告-深度转化] <|ad_begin|> + 12:11 [广告-点击] <|ad_begin|> +【2026-01-11】 + 00:48 [广告-深度转化] <|ad_begin|> + 00:48 [广告-点击] <|ad_begin|> + 23:53 [广告-点击] <|ad_begin|> +【2026-01-12】 + 08:00 [广告-点击] <|ad_begin|> + 08:02 [广告-点击] <|ad_begin|> + 08:02 [广告-点击] <|ad_begin|> + 08:04 [广告-点击] <|ad_begin|> + 08:05 [广告-点击] <|ad_begin|> + 08:09 [广告-点击] <|ad_begin|> +【2026-01-13】 + 22:12 [广告-点击] <|ad_begin|> + 22:14 [广告-点击] <|ad_begin|> +【2026-01-14】 + --:-- [直播-关注] <|living_begin|> +【2026-01-15】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 13:11 [广告-深度转化] <|ad_begin|> + 13:11 [广告-点击] <|ad_begin|> +【2026-01-16】 + --:-- [直播-关注] <|living_begin|> + 05:54 [广告-深度转化] <|ad_begin|> + 05:54 [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|> + 23:33 [广告-深度转化] <|ad_begin|> + 23:33 [广告-点击] <|ad_begin|> +【2026-01-17】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-18】 + 10:23 [广告-深度转化] <|ad_begin|> + 10:23 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 13:12 [广告-深度转化] <|ad_begin|> + 13:12 [广告-点击] <|ad_begin|> + 22:21 [广告-点击] <|ad_begin|> +【2026-01-19】 + 10:02 [广告-深度转化] <|ad_begin|> + 10:02 [广告-点击] <|ad_begin|> + 11:40 [广告-深度转化] <|ad_begin|> + 11:40 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-20】 + 00:19 [广告-深度转化] <|ad_begin|> + 00:19 [广告-点击] <|ad_begin|> + 00:53 [广告-深度转化] <|ad_begin|> + 00:53 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-21】 + 03:14 [广告-深度转化] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 04:27 [广告-深度转化] <|ad_begin|> + 04:27 [广告-点击] <|ad_begin|> + 07:46 [广告-点击] <|ad_begin|> + 07:47 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-22】 + 05:51 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 22:38 [广告-点击] <|ad_begin|> +【2026-01-23】 + 01:36 [广告-点击] <|ad_begin|> + 01:42 [广告-深度转化] <|ad_begin|> + 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[视频-点赞/长播] <|video_begin|> + 23:12 [视频-点赞/长播] <|video_begin|> + 23:12 [视频-点赞/长播] <|video_begin|> + 23:17 [视频-点赞/长播] <|video_begin|> +【2026-01-27】 + 03:18 [视频-点赞/长播] <|video_begin|> + 03:18 [视频-点赞/长播] <|video_begin|> + 03:38 [广告-深度转化] <|ad_begin|> + 03:38 [广告-点击] <|ad_begin|> + 11:21 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 22:35 [广告-深度转化] <|ad_begin|> + 22:35 [广告-点击] <|ad_begin|> +【2026-01-28】 + 00:40 [广告-点击] <|ad_begin|> + 09:18 [视频-点赞/长播] <|video_begin|> + 09:18 [视频-点赞/长播] <|video_begin|> + 09:18 [视频-点赞/长播] <|video_begin|> + 09:26 [视频-点赞/长播] <|video_begin|> + 09:26 [视频-点赞/长播] <|video_begin|> + 09:44 [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|> + 14:00 [视频-点赞/长播] <|video_begin|> + 23:04 [广告-深度转化] <|ad_begin|> + 23:04 [广告-点击] <|ad_begin|> +【2026-01-29】 + 00:20 [广告-深度转化] <|ad_begin|> + 00:20 [广告-点击] <|ad_begin|> + 06:50 [广告-深度转化] <|ad_begin|> + 06:50 [广告-点击] <|ad_begin|> + 10:54 [视频-点赞/长播] <|video_begin|> + --:-- [商品-购买] <|prod_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:18 [视频-长播] <|video_begin|> + 13:18 [视频-长播] <|video_begin|> + 13:18 [视频-点赞/长播] <|video_begin|> + 13:22 [视频-长播] <|video_begin|> + 13:22 [视频-长播] <|video_begin|> + 13:22 [视频-点赞/长播] <|video_begin|> + 13:22 [视频-点赞/长播] <|video_begin|> + 13:57 [广告-深度转化] <|ad_begin|> + 13:57 [广告-点击] <|ad_begin|> + 23:07 [视频-点赞/长播] <|video_begin|> + 23:50 [广告-点击] <|ad_begin|> + 23:51 [广告-点击] <|ad_begin|> + 23:53 [广告-点击] <|ad_begin|> +【2026-01-30】 + 00:03 [视频-长播] <|video_begin|> + 00:03 [视频-长播] <|video_begin|> + 04:58 [视频-长播] <|video_begin|> + 05:00 [视频-长播] <|video_begin|> + 22:03 [视频-长播] <|video_begin|> + 22:03 [视频-点赞/长播] <|video_begin|> + 22:04 [视频-长播] <|video_begin|> + 22:30 [视频-长播] <|video_begin|> +【2026-01-31】 + 06:56 [视频-长播] <|video_begin|> + 10:34 [视频-长播] <|video_begin|> + 10:34 [视频-长播] <|video_begin|> + 10:34 [视频-点赞/长播] <|video_begin|> + 10:38 [广告-点击] <|ad_begin|> + 10:52 [视频-长播] <|video_begin|> + 10:52 [视频-长播] <|video_begin|> + 10:55 [视频-长播] <|video_begin|> +【2026-02-01】 + 13:34 [视频-点赞/长播] <|video_begin|> + 13:42 [视频-长播] <|video_begin|> + 13:42 [视频-收藏/长播] <|video_begin|> +【2026-02-02】 + 10:05 [视频-长播] <|video_begin|> + 10:53 [视频-长播] <|video_begin|> + 10:53 [视频-点赞/长播] <|video_begin|> + 10:53 [视频-点赞/长播] <|video_begin|> + 11:05 [视频-长播] <|video_begin|> + 11:08 [视频-长播] <|video_begin|> + 11:08 [视频-长播] <|video_begin|> + 11:13 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 23:41 [视频-长播] <|video_begin|> + 23:41 [视频-长播] <|video_begin|> +【2026-02-03】 + 00:24 [广告-深度转化] <|ad_begin|> + 00:24 [广告-点击] <|ad_begin|> + 00:53 [广告-点击] <|ad_begin|> + 07:43 [视频-长播] <|video_begin|> + 08:34 [视频-点赞/长播] <|video_begin|> + 08:36 [视频-长播] <|video_begin|> + 08:36 [视频-点赞/长播] <|video_begin|> + 08:43 [视频-长播] <|video_begin|> + 08:56 [广告-深度转化] <|ad_begin|> + 08:56 [广告-点击] <|ad_begin|> + 09:22 [视频-长播] <|video_begin|> + 09:22 [视频-点赞/长播] <|video_begin|> + 09:31 [视频-长播] <|video_begin|> + 09:31 [视频-点赞/长播] <|video_begin|> + 09:31 [视频-点赞/长播] <|video_begin|> + 09:41 [视频-点赞/长播] <|video_begin|> + 09:41 [视频-点赞/长播] <|video_begin|> + 09:46 [视频-长播] <|video_begin|> + 12:53 [视频-长播] <|video_begin|> + 12:53 [视频-长播] <|video_begin|> + 12:57 [视频-长播] <|video_begin|> + 12:57 [视频-长播] <|video_begin|> + 13:06 [视频-长播] <|video_begin|> + 22:13 [视频-点赞/长播] <|video_begin|> + 22:35 [广告-深度转化] <|ad_begin|> + 22:35 [广告-点击] <|ad_begin|> + 22:56 [广告-深度转化] <|ad_begin|> + 22:56 [广告-点击] <|ad_begin|> +【2026-02-04】 + 14:38 [视频-长播] <|video_begin|> + 14:38 [视频-长播] <|video_begin|> + 22:55 [视频-长播] <|video_begin|> + 22:56 [视频-点赞/长播] <|video_begin|> + 23:30 [广告-深度转化] <|ad_begin|> + 23:30 [广告-点击] <|ad_begin|> +【2026-02-05】 + 00:21 [视频-点赞/长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:32 [视频-点赞/长播] <|video_begin|> + 00:37 [视频-点赞/长播] <|video_begin|> + 00:44 [视频-长播] <|video_begin|> + 00:44 [视频-点赞/长播] <|video_begin|> + 00:47 [视频-点赞/长播] <|video_begin|> + 00:50 [视频-长播] <|video_begin|> + 00:53 [视频-长播] <|video_begin|> + 00:55 [视频-长播] <|video_begin|> + 00:56 [视频-点赞/长播] <|video_begin|> + 13:59 [视频-点赞/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）： 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）： +请按时间顺序提取 5 步以内的行为链，且后项交互B必须构成前项交互A在场景需求上的协同补充、副作用诱因或兴趣细化升级——即 B 必须源于 A 所延伸出的需求，严禁提取任何品类平级、内容重复或仅由天气/促销触发的并列凑单行为。 +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 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：在同一主题类目下,交互 B 的需求比 交互 A 更具体详细, 但不包括多次重复的购买、点击、搜索等行为，避免重复节点内容。 +请针对以下主题提取行为逻辑链： +主题：从被动信息吸收到主动利用AI工具的认知跃迁 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动信息吸收到主动利用AI工具的认知跃迁", + "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":"从被动信息吸收到主动利用AI工具的认知跃迁","events":[{"date":"2026-01-26","action":"[视频-收藏/长播] <|video_begin|>","logic":"信息积累与痛点形成：用户通过大量观看财经、科技、时政类视频，积累了海量信息，并收藏了关于“投资策略与心理学”的深度分析视频，表明其在信息处理和决策上可能遇到了瓶颈，产生了对更高效工具的需求。"},{"date":"2026-01-29","action":"[广告-点击] <|ad_begin|>","logic":"兴趣转向与工具探索：用户开始主动点击“免费人工智能课程”广告，标志着其兴趣从被动接收信息转向主动学习和了解能提升信息处理效率的AI工具，行为模式发生显著变化。"},{"date":"2026-02-01","action":"[视频-收藏/长播] <|video_begin|>","logic":"认知深化与效率追求：用户收藏了关于“手机实用功能”以提升操作效率的视频。这一行为与探索AI工具的逻辑一致，共同指向其核心诉求——利用工具提升个人效率，进一步佐证了其从“信息消费”到“工具赋能”的认知转变。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-02-02】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-02-03】 + --:-- [直播-关注] <|living_begin|> +【2025-02-04】 + --:-- [直播-关注] <|living_begin|> +【2025-03-04】 + --:-- [直播-关注] <|living_begin|> +【2025-03-08】 + --:-- [直播-关注] <|living_begin|> +【2025-03-09】 + --:-- [直播-关注] <|living_begin|> +【2025-03-19】 + --:-- [直播-关注] <|living_begin|> +【2025-03-26】 + --:-- [直播-关注] <|living_begin|> +【2025-04-24】 + --:-- [直播-关注] <|living_begin|> +【2025-04-25】 + --:-- [直播-打赏] <|living_begin|> +【2025-05-09】 + --:-- [直播-关注] <|living_begin|> +【2025-05-13】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-05-16】 + --:-- [直播-打赏] <|living_begin|> +【2025-05-17】 + --:-- [直播-关注] <|living_begin|> +【2025-05-22】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-23】 + --:-- [直播-关注] <|living_begin|> +【2025-05-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-10】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-11】 + --:-- [直播-打赏] <|living_begin|> +【2025-06-13】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-06-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-22】 + --:-- [直播-关注] <|living_begin|> +【2025-06-23】 + --:-- [直播-关注] <|living_begin|> +【2025-06-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-07】 + --:-- [直播-关注] <|living_begin|> +【2025-07-10】 + --:-- [直播-关注] <|living_begin|> +【2025-07-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-23】 + --:-- [直播-关注] <|living_begin|> +【2025-07-26】 + --:-- [直播-关注] <|living_begin|> +【2025-07-31】 + --:-- [直播-关注] <|living_begin|> +【2025-08-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-18】 + --:-- [直播-关注] <|living_begin|> +【2025-08-22】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-08-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-27】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-03】 + --:-- [直播-关注] <|living_begin|> +【2025-09-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-07】 + --:-- [直播-关注] <|living_begin|> +【2025-09-18】 + --:-- [直播-关注] <|living_begin|> +【2025-09-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-21】 + --:-- [直播-关注] <|living_begin|> +【2025-09-24】 + --:-- [直播-关注] <|living_begin|> +【2025-09-26】 + --:-- [直播-关注] <|living_begin|> +【2025-10-02】 + --:-- [直播-关注] <|living_begin|> +【2025-10-03】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-05】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-07】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-09】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-14】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-15】 + --:-- [直播-关注] <|living_begin|> +【2025-10-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-28】 + --:-- [直播-关注] <|living_begin|> +【2025-11-16】 + --:-- [直播-关注] <|living_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-27】 + --:-- [直播-关注] <|living_begin|> +【2025-12-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-15】 + --:-- [直播-关注] <|living_begin|> +【2025-12-27】 + --:-- [直播-关注] <|living_begin|> +【2025-12-31】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-02】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-03】 + 14:58 [广告-深度转化] <|ad_begin|> + 16:17 [广告-深度转化] <|ad_begin|> +【2026-01-04】 + 11:49 [广告-深度转化] <|ad_begin|> + 14:53 [广告-深度转化] <|ad_begin|> +【2026-01-05】 + 03:51 [广告-深度转化] <|ad_begin|> + 05:37 [广告-深度转化] <|ad_begin|> + 12:35 [广告-深度转化] <|ad_begin|> +【2026-01-06】 + 05:22 [广告-深度转化] <|ad_begin|> + 06:29 [广告-深度转化] <|ad_begin|> +【2026-01-07】 + 14:56 [广告-深度转化] <|ad_begin|> + 15:41 [广告-深度转化] <|ad_begin|> +【2026-01-08】 + 10:31 [广告-深度转化] <|ad_begin|> + 14:13 [广告-深度转化] <|ad_begin|> +【2026-01-09】 + --:-- [商品-购买] <|prod_begin|> + 14:55 [广告-深度转化] <|ad_begin|> +【2026-01-10】 + 02:56 [广告-深度转化] <|ad_begin|> + 13:44 [广告-深度转化] <|ad_begin|> +【2026-01-11】 + --:-- [直播-关注] <|living_begin|> + 06:53 [广告-深度转化] <|ad_begin|> +【2026-01-12】 + 15:20 [广告-深度转化] <|ad_begin|> +【2026-01-14】 + 13:29 [广告-深度转化] <|ad_begin|> + 13:46 [广告-深度转化] <|ad_begin|> + 15:48 [广告-深度转化] <|ad_begin|> +【2026-01-15】 + --:-- [商品-购买] <|prod_begin|> + 05:55 [广告-深度转化] <|ad_begin|> + 11:48 [广告-深度转化] <|ad_begin|> + 12:57 [广告-深度转化] <|ad_begin|> + 13:52 [广告-深度转化] <|ad_begin|> +【2026-01-16】 + 06:22 [广告-深度转化] <|ad_begin|> + 10:25 [广告-深度转化] <|ad_begin|> + 14:57 [广告-深度转化] <|ad_begin|> + 23:02 [广告-深度转化] <|ad_begin|> +【2026-01-17】 + 10:42 [广告-深度转化] <|ad_begin|> + 13:29 [广告-深度转化] <|ad_begin|> +【2026-01-18】 + --:-- [商品-购买] <|prod_begin|> + 03:43 [广告-深度转化] <|ad_begin|> + 03:43 [广告-点击] <|ad_begin|> + 12:51 [广告-点击] <|ad_begin|> +【2026-01-20】 + 12:14 [广告-点击] <|ad_begin|> + 12:29 [广告-点击] <|ad_begin|> + 12:40 [广告-深度转化] <|ad_begin|> + 12:40 [广告-点击] <|ad_begin|> + 13:09 [广告-深度转化] <|ad_begin|> + 13:09 [广告-点击] <|ad_begin|> + 15:12 [广告-深度转化] <|ad_begin|> + 15:12 [广告-点击] <|ad_begin|> +【2026-01-21】 + 01:37 [广告-点击] <|ad_begin|> + 01:37 [广告-点击] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + 06:27 [广告-点击] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 13:11 [广告-点击] <|ad_begin|> + 13:16 [广告-深度转化] <|ad_begin|> + 13:16 [广告-点击] <|ad_begin|> + 14:25 [广告-深度转化] <|ad_begin|> + 14:25 [广告-点击] <|ad_begin|> +【2026-01-22】 + --:-- [商品-购买] <|prod_begin|> + 05:14 [视频-点赞/长播] <|video_begin|> + 05:25 [广告-深度转化] <|ad_begin|> + 05:25 [广告-点击] <|ad_begin|> + 05:42 [广告-深度转化] <|ad_begin|> + 05:42 [广告-点击] <|ad_begin|> + 06:31 [广告-深度转化] <|ad_begin|> + 06:31 [广告-点击] <|ad_begin|> +【2026-01-23】 + --:-- [商品-购买] <|prod_begin|> + 06:23 [视频-关注/点赞/长播] <|video_begin|> + 06:37 [广告-深度转化] <|ad_begin|> + 06:37 [广告-点击] <|ad_begin|> + 09:20 [广告-点击] <|ad_begin|> + 12:27 [广告-深度转化] <|ad_begin|> + 12:27 [广告-点击] <|ad_begin|> + 14:18 [广告-深度转化] <|ad_begin|> + 14:18 [广告-点击] <|ad_begin|> +【2026-01-24】 + 01:39 [广告-深度转化] <|ad_begin|> + 01:39 [广告-点击] <|ad_begin|> + 11:03 [视频-点赞/长播] <|video_begin|> + 14:28 [广告-深度转化] <|ad_begin|> + 14:28 [广告-点击] <|ad_begin|> + 14:36 [广告-深度转化] <|ad_begin|> + 14:36 [广告-点击] <|ad_begin|> +【2026-01-25】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-26】 + 06:53 [视频-点赞/长播] <|video_begin|> + 13:15 [视频-评论/点赞/长播] <|video_begin|> + 14:48 [广告-深度转化] <|ad_begin|> + 14:48 [广告-点击] <|ad_begin|> +【2026-01-27】 + --:-- [直播-关注] <|living_begin|> + 05:18 [广告-点击] <|ad_begin|> + 06:28 [广告-点击] <|ad_begin|> + 12:31 [视频-长播] <|video_begin|> + 12:31 [视频-长播] <|video_begin|> + 12:31 [视频-长播] <|video_begin|> + 12:36 [视频-长播] <|video_begin|> + 14:13 [广告-深度转化] <|ad_begin|> + 14:13 [广告-点击] <|ad_begin|> +【2026-01-28】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 03:08 [广告-深度转化] <|ad_begin|> + 03:08 [广告-点击] <|ad_begin|> + 08:07 [广告-点击] <|ad_begin|> + 10:31 [广告-深度转化] <|ad_begin|> + 10:31 [广告-点击] <|ad_begin|> + 11:14 [视频-长播] <|video_begin|> + 11:14 [视频-长播] <|video_begin|> + 11:14 [视频-长播] <|video_begin|> + 11:34 [广告-深度转化] <|ad_begin|> + 11:34 [广告-点击] <|ad_begin|> + 11:35 [广告-点击] <|ad_begin|> + 13:09 [广告-点击] <|ad_begin|> + 13:15 [广告-点击] <|ad_begin|> + 13:17 [广告-点击] <|ad_begin|> + 13:18 [广告-深度转化] <|ad_begin|> + 13:18 [广告-点击] <|ad_begin|> + 13:19 [视频-长播] <|video_begin|> + 13:56 [广告-点击] <|ad_begin|> +【2026-01-29】 + --:-- [商品-购买] <|prod_begin|> + 05:19 [广告-深度转化] <|ad_begin|> + 05:19 [广告-点击] <|ad_begin|> + 07:10 [广告-深度转化] <|ad_begin|> + 07:10 [广告-点击] <|ad_begin|> + 10:21 [广告-深度转化] <|ad_begin|> + 10:21 [广告-点击] <|ad_begin|> + 11:20 [视频-点赞/长播] <|video_begin|> + 11:27 [视频-长播] <|video_begin|> + 11:27 [视频-长播] <|video_begin|> + 11:38 [视频-长播] <|video_begin|> + 11:56 [广告-深度转化] <|ad_begin|> + 11:56 [广告-点击] <|ad_begin|> + 14:50 [广告-深度转化] <|ad_begin|> + 14:50 [广告-点击] <|ad_begin|> + 15:09 [视频-点赞/长播] <|video_begin|> + 15:09 [视频-长播] <|video_begin|> + 15:16 [视频-长播] <|video_begin|> + 15:21 [广告-点击] <|ad_begin|> + 15:22 [视频-长播] <|video_begin|> + 15:22 [视频-长播] <|video_begin|> + 15:25 [视频-点赞/长播] <|video_begin|> + 15:25 [视频-点赞/长播] <|video_begin|> + 15:25 [视频-长播] <|video_begin|> + 15:52 [视频-长播] <|video_begin|> +【2026-01-30】 + 01:01 [视频-长播] <|video_begin|> + 01:11 [广告-点击] <|ad_begin|> + 03:54 [广告-深度转化] <|ad_begin|> + 03:54 [广告-点击] <|ad_begin|> + 06:07 [视频-长播] <|video_begin|> + 06:07 [视频-长播] <|video_begin|> + 13:59 [广告-深度转化] <|ad_begin|> + 13:59 [广告-点击] <|ad_begin|> + 14:47 [广告-深度转化] <|ad_begin|> + 14:47 [广告-点击] <|ad_begin|> + 15:26 [视频-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|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 05:00 [视频-点赞/长播] <|video_begin|> + 05:02 [视频-长播] <|video_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:01 [广告-点击] <|ad_begin|> + 12:22 [广告-点击] <|ad_begin|> + 12:25 [广告-深度转化] <|ad_begin|> + 12:25 [广告-点击] <|ad_begin|> + 12:38 [广告-点击] <|ad_begin|> + 12:56 [视频-点赞/长播] <|video_begin|> + 12:56 [视频-关注/点赞/长播] <|video_begin|> + 13:42 [广告-深度转化] <|ad_begin|> + 13:42 [广告-点击] <|ad_begin|> +【2026-02-01】 + 01:30 [广告-点击] <|ad_begin|> + 01:34 [广告-点击] <|ad_begin|> + 01:35 [视频-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-购买] <|prod_begin|> + 03:51 [广告-深度转化] <|ad_begin|> + 03:51 [广告-点击] <|ad_begin|> + 05:19 [广告-点击] <|ad_begin|> + 11:13 [视频-长播] <|video_begin|> + 11:30 [广告-点击] <|ad_begin|> + 11:53 [广告-深度转化] <|ad_begin|> + 11:53 [广告-点击] <|ad_begin|> + 13:00 [广告-深度转化] <|ad_begin|> + 13:00 [广告-点击] <|ad_begin|> + 15:02 [广告-点击] <|ad_begin|> + 15:03 [视频-长播] <|video_begin|> + 15:03 [视频-长播] <|video_begin|> + 15:15 [视频-长播] <|video_begin|> + 15:19 [广告-点击] <|ad_begin|> +【2026-02-02】 + 00:48 [视频-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-购买] <|prod_begin|> + 04:22 [视频-点赞/长播] <|video_begin|> + 04:22 [视频-长播] <|video_begin|> + 04:56 [广告-深度转化] <|ad_begin|> + 04:56 [广告-点击] <|ad_begin|> + 11:15 [广告-深度转化] <|ad_begin|> + 11:15 [广告-点击] <|ad_begin|> +【2026-02-03】 + 00:38 [视频-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-购买] <|prod_begin|> + 05:54 [广告-点击] <|ad_begin|> + 07:40 [视频-长播] <|video_begin|> + 12:09 [视频-长播] <|video_begin|> + 12:15 [视频-点赞/长播] <|video_begin|> + 15:04 [视频-长播] <|video_begin|> + 15:59 [视频-长播] <|video_begin|> + 16:01 [广告-点击] <|ad_begin|> + 23:22 [视频-长播] <|video_begin|> + 23:22 [视频-长播] <|video_begin|> + 23:32 [视频-点赞/长播] <|video_begin|> + 23:34 [视频-长播] <|video_begin|> + 23:34 [视频-长播] <|video_begin|> +【2026-02-04】 + 01:01 [视频-长播] <|video_begin|> + 01:10 [视频-关注/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|> + 06:44 [视频-长播] <|video_begin|> + 06:47 [视频-长播] <|video_begin|> + 08:51 [视频-长播] <|video_begin|> + 08:56 [视频-评论/点赞/长播] <|video_begin|> + 11:42 [视频-长播] <|video_begin|> + 13:25 [视频-长播] <|video_begin|> + 14:20 [广告-深度转化] <|ad_begin|> + 14:20 [广告-点击] <|ad_begin|> + 23:34 [视频-长播] <|video_begin|> + 23:34 [视频-长播] <|video_begin|> +【2026-02-05】 + --:-- [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|> + 07:21 [视频-长播] <|video_begin|> + 07:24 [视频-长播] <|video_begin|> + 11:27 [视频-长播] <|video_begin|> + 12:11 [广告-深度转化] <|ad_begin|> + 12:11 [广告-点击] <|ad_begin|> + 13:52 [广告-点击] <|ad_begin|> + 15:05 [视频-长播] <|video_begin|> + 15:07 [广告-点击] <|ad_begin|> +角色任务：你作为极端严苛的用户行为数据挖掘专家和数据格式化专家，需要根据以上用户交互历史，围绕给定主题抽取存在行为递进逻辑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）： 广告-点击、广告-深度转化、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 +核心判定逻辑（递进性准则）： +请按时间顺序提取 5 步以内的行为链，且后项交互B必须构成前项交互A在场景需求上的协同补充、副作用诱因或兴趣细化升级——即 B 必须源于 A 所延伸出的需求，严禁提取任何品类平级、内容重复或仅由天气/促销触发的并列凑单行为。 +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：在同一主题类目下，交互 B 需要比交互 A 表达得更具体详细，但不纳入重复性的购买、点击、搜索等行为，避免形成重复节点。 +请针对以下主题提取行为逻辑链： +主题：从被动观赏到主动实践的节日装饰决策链 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动观赏到主动实践的节日装饰决策链", + "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":"从被动观赏到主动实践的节日装饰决策链","events":[{"date":"2026-02-04","action":"[视频-关注/长播] <|video_begin|>","logic":"兴趣触发：被动接收到关于“灯笼制作”的视频内容，对节日装饰产生初步兴趣，但认知停留在成品外观层面。"},{"date":"2026-01-29","action":"[商品-购买] <|prod_begin|>","logic":"认知收敛与行动转化：从对灯笼成品的笼统兴趣，聚焦到实现其发光效果的核心组件“无线遥控LED灯芯”上，并完成购买。这表明用户已从欣赏转向实践，并对装饰方案的技术细节（无线、遥控）产生了明确的功能性需求，是典型的认知增量和行为深化。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-04-19】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-24】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-05-25】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-26】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-03】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-29】 + --:-- [直播-关注] <|living_begin|> +【2025-08-31】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-02】 + --:-- [直播-关注] <|living_begin|> +【2025-09-03】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-04】 + --:-- [直播-关注] <|living_begin|> +【2025-09-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-20】 + --:-- [直播-关注] <|living_begin|> +【2025-10-10】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-19】 + --:-- [直播-关注] <|living_begin|> +【2025-10-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-25】 + --:-- [直播-关注] <|living_begin|> +【2025-10-27】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-30】 + --:-- [直播-关注] <|living_begin|> +【2025-11-02】 + --:-- [直播-关注] <|living_begin|> +【2025-11-03】 + --:-- [直播-关注] <|living_begin|> +【2025-11-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-10】 + --:-- [直播-关注] <|living_begin|> +【2025-11-11】 + --:-- [直播-关注] <|living_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|> +【2025-11-14】 + --:-- [直播-关注] <|living_begin|> +【2025-11-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-16】 + --:-- [直播-关注] <|living_begin|> +【2025-11-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-18】 + --:-- [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] <|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|> +【2025-11-19】 + --:-- [直播-关注] <|living_begin|> +【2025-11-20】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-21】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-26】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-27】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-28】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-11-29】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-11-30】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-04】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-06】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-08】 + --:-- [直播-打赏] <|living_begin|> +【2025-12-11】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-12】 + --:-- [直播-打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-14】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-16】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-17】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-20】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-21】 + --:-- [直播-关注/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|> +【2025-12-22】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-23】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-24】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-26】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-27】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-29】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-12-31】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-01】 + --:-- [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|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-02】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-06】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-07】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-08】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-09】 + --:-- [直播-首次打赏] <|living_begin|> +【2026-01-10】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-11】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2026-01-12】 + 02:42 [广告-深度转化] <|ad_begin|> + 05:11 [广告-深度转化] <|ad_begin|> + 07:37 [广告-深度转化] <|ad_begin|> + 17:27 [广告-深度转化] <|ad_begin|> + 23:54 [广告-深度转化] <|ad_begin|> +【2026-01-13】 + 03:28 [广告-深度转化] <|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|> + 16:21 [广告-深度转化] <|ad_begin|> + 19:21 [广告-深度转化] <|ad_begin|> +【2026-01-14】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> + 17:06 [广告-深度转化] <|ad_begin|> +【2026-01-15】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 01:03 [广告-深度转化] <|ad_begin|> + 03:15 [广告-深度转化] <|ad_begin|> +【2026-01-16】 + 04:54 [广告-深度转化] <|ad_begin|> + 05:58 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 11:21 [广告-深度转化] <|ad_begin|> +【2026-01-17】 + 07:07 [广告-深度转化] <|ad_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|> + 08:14 [广告-深度转化] <|ad_begin|> + 14:53 [广告-深度转化] <|ad_begin|> + 23:38 [广告-深度转化] <|ad_begin|> +【2026-01-18】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 02:29 [广告-深度转化] <|ad_begin|> +【2026-01-19】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-关注/打赏] <|living_begin|> + 02:39 [广告-深度转化] <|ad_begin|> + 03:38 [广告-深度转化] <|ad_begin|> + 06:39 [广告-深度转化] <|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-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-20】 + 09:39 [广告-深度转化] <|ad_begin|> + 15:37 [广告-深度转化] <|ad_begin|> + 23:01 [广告-深度转化] <|ad_begin|> +【2026-01-21】 + 09:09 [广告-深度转化] <|ad_begin|> + 15:29 [广告-深度转化] <|ad_begin|> + 21:38 [视频-转发/点赞/长播] <|video_begin|> + 22:08 [广告-深度转化] <|ad_begin|> +【2026-01-22】 + 04:44 [广告-深度转化] <|ad_begin|> +【2026-01-23】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 06:48 [广告-深度转化] <|ad_begin|> +【2026-01-24】 + 01:08 [广告-深度转化] <|ad_begin|> + 03:04 [视频-转发/点赞/长播] <|video_begin|> + 04:54 [广告-深度转化] <|ad_begin|> + 22:54 [视频-转发/点赞/长播] <|video_begin|> +【2026-01-25】 + 03:07 [广告-深度转化] <|ad_begin|> + 08:30 [广告-深度转化] <|ad_begin|> +【2026-01-26】 + 00:23 [视频-转发/评论/收藏/点赞/长播] <|video_begin|> + 02:09 [视频-转发/点赞/长播] <|video_begin|> + 05:14 [广告-深度转化] <|ad_begin|> + 05:48 [广告-深度转化] <|ad_begin|> +【2026-01-27】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + 08:10 [广告-深度转化] <|ad_begin|> + 08:11 [广告-深度转化] <|ad_begin|> + 09:16 [广告-深度转化] <|ad_begin|> + 09:27 [广告-深度转化] <|ad_begin|> + 12:58 [广告-深度转化] <|ad_begin|> +【2026-01-28】 + 13:41 [广告-深度转化] <|ad_begin|> + 16:16 [广告-深度转化] <|ad_begin|> +【2026-01-29】 + 04:42 [广告-深度转化] <|ad_begin|> + 04:42 [广告-点击] <|ad_begin|> + 06:36 [广告-深度转化] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 07:43 [广告-深度转化] <|ad_begin|> + 07:43 [广告-点击] <|ad_begin|> + 13:06 [广告-点击] <|ad_begin|> + 13:22 [广告-点击] <|ad_begin|> + 15:27 [广告-点击] <|ad_begin|> + 23:14 [视频-转发/评论/点赞/长播] <|video_begin|> +【2026-01-30】 + 01:44 [广告-点击] <|ad_begin|> + 02:23 [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-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 10:07 [广告-点击] <|ad_begin|> + 10:15 [广告-点击] <|ad_begin|> + 10:17 [广告-点击] <|ad_begin|> + 10:23 [广告-点击] <|ad_begin|> + 20:57 [广告-点击] <|ad_begin|> +【2026-01-31】 + --:-- [直播-打赏] <|living_begin|> + 01:14 [广告-点击] <|ad_begin|> + 04:51 [广告-深度转化] <|ad_begin|> + 04:51 [广告-点击] <|ad_begin|> + 07:51 [广告-深度转化] <|ad_begin|> + 07:51 [广告-点击] <|ad_begin|> + 15:22 [广告-点击] <|ad_begin|> + 15:28 [广告-点击] <|ad_begin|> + 15:31 [广告-点击] <|ad_begin|> + 16:18 [广告-深度转化] <|ad_begin|> + 16:18 [广告-点击] <|ad_begin|> + 23:09 [广告-点击] <|ad_begin|> + 23:13 [广告-点击] <|ad_begin|> + 23:15 [广告-点击] <|ad_begin|> + 23:16 [广告-点击] <|ad_begin|> + 23:47 [视频-转发/评论/点赞/长播] <|video_begin|> +【2026-02-01】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + 02:46 [广告-点击] <|ad_begin|> + 02:56 [广告-点击] <|ad_begin|> + 06:57 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 08:16 [广告-点击] <|ad_begin|> + 08:26 [广告-点击] <|ad_begin|> + 08:38 [广告-点击] <|ad_begin|> + 10:42 [视频-转发/点赞/长播] <|video_begin|> + 11:28 [视频-长播] <|video_begin|> + 11:28 [视频-点赞/长播] <|video_begin|> + 16:07 [广告-点击] <|ad_begin|> + 17:49 [广告-深度转化] <|ad_begin|> + 17:49 [广告-点击] <|ad_begin|> + 19:51 [广告-点击] <|ad_begin|> + 19:55 [广告-深度转化] <|ad_begin|> + 19:55 [广告-点击] <|ad_begin|> + 23:30 [广告-深度转化] <|ad_begin|> + 23:30 [广告-点击] <|ad_begin|> + 23:36 [广告-点击] <|ad_begin|> + 23:37 [广告-点击] <|ad_begin|> + 23:40 [广告-点击] <|ad_begin|> + 23:45 [广告-深度转化] <|ad_begin|> + 23:45 [广告-点击] <|ad_begin|> +【2026-02-02】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 04:44 [广告-点击] <|ad_begin|> + 04:47 [广告-点击] <|ad_begin|> + 04:52 [广告-点击] <|ad_begin|> + 04:59 [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|> + 07:57 [广告-深度转化] <|ad_begin|> + 07:57 [广告-点击] <|ad_begin|> + 08:54 [广告-深度转化] <|ad_begin|> + 08:54 [广告-点击] <|ad_begin|> + 10:06 [广告-深度转化] <|ad_begin|> + 10:06 [广告-点击] <|ad_begin|> + 10:32 [广告-点击] <|ad_begin|> + 11:19 [广告-深度转化] <|ad_begin|> + 11:19 [广告-点击] <|ad_begin|> + 16:14 [广告-深度转化] <|ad_begin|> + 16:14 [广告-点击] <|ad_begin|> + 16:16 [广告-深度转化] <|ad_begin|> + 16:16 [广告-点击] <|ad_begin|> +【2026-02-03】 + 01:48 [广告-深度转化] <|ad_begin|> + 01:48 [广告-点击] <|ad_begin|> + 02:11 [广告-点击] <|ad_begin|> + 02:24 [广告-深度转化] <|ad_begin|> + 02:24 [广告-点击] <|ad_begin|> + 11:38 [广告-深度转化] <|ad_begin|> + 11:38 [广告-点击] <|ad_begin|> +【2026-02-04】 + 01:02 [广告-深度转化] <|ad_begin|> + 01:02 [广告-点击] <|ad_begin|> + 06:10 [广告-深度转化] <|ad_begin|> + 06:10 [广告-点击] <|ad_begin|> + 07:32 [广告-深度转化] <|ad_begin|> + 07:32 [广告-点击] <|ad_begin|> + 08:19 [广告-点击] <|ad_begin|> + 08:43 [广告-深度转化] <|ad_begin|> + 08:43 [广告-点击] <|ad_begin|> + 11:52 [广告-深度转化] <|ad_begin|> + 11:52 [广告-点击] <|ad_begin|> + 14:27 [广告-深度转化] <|ad_begin|> + 14:27 [广告-点击] <|ad_begin|> + 18:42 [广告-点击] <|ad_begin|> + 23:38 [视频-转发/点赞/长播] <|video_begin|> +【2026-02-05】 + 00:59 [广告-点击] <|ad_begin|> + 06:19 [广告-点击] <|ad_begin|> + 06:31 [广告-深度转化] <|ad_begin|> + 06:31 [广告-点击] <|ad_begin|> + 08:48 [广告-点击] <|ad_begin|> + 09:07 [广告-深度转化] <|ad_begin|> + 09:07 [广告-点击] <|ad_begin|> + 13:56 [广告-点击] <|ad_begin|> + 14:32 [广告-点击] <|ad_begin|> + 15:21 [广告-点击] <|ad_begin|> +角色任务：你是一名极端严苛的用户行为数据挖掘专家，同时具备数据格式化能力，请根据以上用户交互历史，针对指定主题提取具有行为递进逻辑及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）： 广告-点击、广告-深度转化、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 +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 和交互 A 必须落在同一生活场景、同一主题类目中，且存在很强的需求补完关系。 +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：在相同主题类目下，交互 B 的需求应较交互 A 更加具体和细致，但不包含多次重复的购买、点击、搜索等行为，以避免节点内容重复。 +请围绕以下主题提取行为逻辑链： +主题：从被动娱乐到主动探索：对赛车游戏兴趣的具象化过程 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动娱乐到主动探索：对赛车游戏兴趣的具象化过程", + "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":"从被动娱乐到主动探索：对赛车游戏兴趣的具象化过程","events":[{"date":"2026-01-26","action":"[视频-转发/评论/收藏/点赞/长播] <|video_begin|>","logic":"兴趣触发：通过深度互动（转发/评论/收藏/点赞/长播）一个赛车游戏视频，表现出对该品类的初步兴趣。"},{"date":"2026-01-26","action":"[视频-转发/点赞/长播] <|video_begin|>","logic":"兴趣聚焦：在同一天，用户的兴趣从泛化的赛车游戏，聚焦到了一款具体游戏《和平精英》中的赛车玩法，并进行了深度互动，体现了兴趣的快速收敛。"},{"date":"2026-01-29","action":"[视频-转发/评论/点赞/长播] <|video_begin|>","logic":"对比与拓展：在聚焦《和平精英》后，用户又深度互动了另一款经典赛车游戏《极品飞车》，表明其正在对不同赛车游戏进行横向对比和体验拓展，认知从单一游戏玩法扩展到品类比较。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-01-04】 + --:-- [直播-关注] <|living_begin|> +【2025-02-01】 + --:-- [直播-关注] <|living_begin|> +【2025-02-04】 + --:-- [直播-关注] <|living_begin|> +【2025-04-22】 + --:-- [直播-关注] <|living_begin|> +【2025-07-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-22】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-25】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-09】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-29】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-09】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-22】 + 09:45 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-23】 + 05:04 [广告-深度转化] <|ad_begin|> +【2025-12-24】 + 11:56 [广告-深度转化] <|ad_begin|> +【2025-12-25】 + 09:02 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-27】 + 14:21 [广告-深度转化] <|ad_begin|> +【2025-12-29】 + 11:50 [广告-深度转化] <|ad_begin|> +【2025-12-30】 + 05:03 [广告-深度转化] <|ad_begin|> +【2025-12-31】 + 06:28 [广告-深度转化] <|ad_begin|> +【2026-01-01】 + 02:52 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + 23:29 [广告-深度转化] <|ad_begin|> +【2026-01-02】 + 02:02 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-03】 + 08:54 [广告-深度转化] <|ad_begin|> + 12:32 [广告-深度转化] <|ad_begin|> +【2026-01-04】 + 03:14 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 13:50 [广告-深度转化] <|ad_begin|> + 13:50 [广告-深度转化] <|ad_begin|> +【2026-01-05】 + 02:52 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-09】 + 03:52 [广告-深度转化] <|ad_begin|> +【2026-01-10】 + --:-- [直播-关注] <|living_begin|> + 08:59 [广告-深度转化] <|ad_begin|> + 19:15 [广告-深度转化] <|ad_begin|> +【2026-01-11】 + 06:05 [广告-深度转化] <|ad_begin|> +【2026-01-12】 + 06:03 [广告-深度转化] <|ad_begin|> +【2026-01-13】 + 05:29 [广告-深度转化] <|ad_begin|> + 08:27 [广告-深度转化] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> + 11:44 [广告-深度转化] <|ad_begin|> + 13:07 [广告-深度转化] <|ad_begin|> +【2026-01-14】 + 13:52 [广告-深度转化] <|ad_begin|> +【2026-01-15】 + 09:35 [广告-深度转化] <|ad_begin|> + 09:35 [广告-点击] <|ad_begin|> + 10:01 [广告-深度转化] <|ad_begin|> + 10:01 [广告-点击] <|ad_begin|> + 22:07 [广告-深度转化] <|ad_begin|> + 22:07 [广告-点击] <|ad_begin|> + 22:34 [广告-点击] <|ad_begin|> +【2026-01-16】 + 05:43 [广告-深度转化] <|ad_begin|> + 05:43 [广告-点击] <|ad_begin|> + 08:05 [广告-点击] <|ad_begin|> + 08:15 [广告-深度转化] <|ad_begin|> + 08:15 [广告-点击] <|ad_begin|> + 12:48 [广告-点击] <|ad_begin|> +【2026-01-17】 + 02:29 [广告-深度转化] <|ad_begin|> + 02:29 [广告-点击] <|ad_begin|> + 06:08 [广告-深度转化] <|ad_begin|> + 06:08 [广告-点击] <|ad_begin|> + 15:37 [广告-深度转化] <|ad_begin|> + 15:37 [广告-点击] <|ad_begin|> +【2026-01-19】 + 01:11 [广告-点击] <|ad_begin|> + 07:35 [广告-点击] <|ad_begin|> + 08:30 [广告-点击] <|ad_begin|> +【2026-01-20】 + 06:17 [广告-深度转化] <|ad_begin|> + 06:17 [广告-点击] <|ad_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-22】 + 05:42 [视频-点赞/长播] <|video_begin|> + 07:03 [广告-点击] <|ad_begin|> + 09:04 [视频-关注/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|> + 20:38 [视频-关注/长播] <|video_begin|> + 21:47 [广告-点击] <|ad_begin|> +【2026-01-23】 + 03:12 [广告-深度转化] <|ad_begin|> + 03:12 [广告-点击] <|ad_begin|> + 05:39 [广告-深度转化] <|ad_begin|> + 05:39 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 11:20 [广告-深度转化] <|ad_begin|> + 11:20 [广告-点击] <|ad_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 13:55 [广告-点击] <|ad_begin|> + 21:09 [视频-关注/点赞/长播] <|video_begin|> + 21:34 [视频-关注/长播] <|video_begin|> + 21:44 [视频-关注/点赞/长播] <|video_begin|> + 23:32 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-24】 + 02:25 [广告-深度转化] <|ad_begin|> + 02:25 [广告-点击] <|ad_begin|> + 05:31 [广告-深度转化] <|ad_begin|> + 05:31 [广告-点击] <|ad_begin|> + 06:27 [视频-点赞/长播] <|video_begin|> + 06:27 [视频-关注/点赞/长播] <|video_begin|> + 09:19 [广告-深度转化] <|ad_begin|> + 09:19 [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|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 11:56 [广告-点击] <|ad_begin|> + 12:09 [广告-点击] <|ad_begin|> + 12:18 [广告-点击] <|ad_begin|> + 13:16 [广告-深度转化] <|ad_begin|> + 13:16 [广告-点击] <|ad_begin|> + 13:26 [广告-点击] <|ad_begin|> +【2026-01-25】 + 01:08 [广告-深度转化] <|ad_begin|> + 01:08 [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|> + --:-- [商品-点击] <|prod_begin|> + 10:47 [广告-点击] <|ad_begin|> + 14:09 [广告-点击] <|ad_begin|> +【2026-01-26】 + 03:28 [广告-深度转化] <|ad_begin|> + 03:28 [广告-点击] <|ad_begin|> + 05:52 [广告-点击] <|ad_begin|> + 06:33 [广告-深度转化] <|ad_begin|> + 06:33 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 12:51 [广告-深度转化] <|ad_begin|> + 12:51 [广告-点击] <|ad_begin|> +【2026-01-27】 + 10:21 [视频-关注/长播] <|video_begin|> + 12:06 [广告-点击] <|ad_begin|> + 12:27 [视频-关注/点赞/长播] <|video_begin|> + 12:40 [视频-关注/点赞/长播] <|video_begin|> + 13:01 [视频-关注/长播] <|video_begin|> + 13:05 [视频-关注/点赞/长播] <|video_begin|> + 13:05 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-28】 + 00:52 [视频-点赞/长播] <|video_begin|> + 01:10 [视频-关注/点赞/长播] <|video_begin|> + 01:27 [视频-点赞/长播] <|video_begin|> + 03:21 [视频-关注/点赞/长播] <|video_begin|> + 04:10 [广告-深度转化] <|ad_begin|> + 04:10 [广告-点击] <|ad_begin|> + 07:28 [广告-深度转化] <|ad_begin|> + 07:28 [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-购买] <|prod_begin|> + 11:24 [视频-点赞/长播] <|video_begin|> + 12:19 [视频-点赞/长播] <|video_begin|> + 13:21 [视频-点赞/长播] <|video_begin|> +【2026-01-29】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 10:42 [视频-点赞/长播] <|video_begin|> + 11:06 [广告-深度转化] <|ad_begin|> + 11:06 [广告-点击] <|ad_begin|> + 12:58 [广告-点击] <|ad_begin|> + 13:25 [视频-点赞/长播] <|video_begin|> + 21:36 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-30】 + 00:19 [广告-深度转化] <|ad_begin|> + 00:19 [广告-点击] <|ad_begin|> + 01:40 [广告-深度转化] <|ad_begin|> + 01:40 [广告-点击] <|ad_begin|> + 03:16 [广告-点击] <|ad_begin|> + 06:21 [广告-深度转化] <|ad_begin|> + 06:21 [广告-点击] <|ad_begin|> + 07:41 [广告-深度转化] <|ad_begin|> + 07:41 [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-购买] <|prod_begin|> + 11:45 [视频-收藏/长播] <|video_begin|> +【2026-01-31】 + 00:23 [视频-关注/点赞/长播] <|video_begin|> + 00:51 [视频-关注/点赞/长播] <|video_begin|> + 01:38 [广告-深度转化] <|ad_begin|> + 01:38 [广告-点击] <|ad_begin|> + 06:01 [广告-深度转化] <|ad_begin|> + 06:01 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 12:59 [广告-深度转化] <|ad_begin|> + 12:59 [广告-点击] <|ad_begin|> +【2026-02-01】 + 09:19 [广告-点击] <|ad_begin|> + 13:16 [广告-深度转化] <|ad_begin|> + 13:16 [广告-点击] <|ad_begin|> +【2026-02-02】 + 01:11 [视频-关注/点赞/长播] <|video_begin|> + 01:40 [视频-关注/点赞/长播] <|video_begin|> + 01:55 [广告-点击] <|ad_begin|> + 02:22 [广告-深度转化] <|ad_begin|> + 02:22 [广告-点击] <|ad_begin|> + 03:50 [广告-深度转化] <|ad_begin|> + 03:50 [广告-点击] <|ad_begin|> + 06:39 [广告-点击] <|ad_begin|> + 07:51 [广告-深度转化] <|ad_begin|> + 07:51 [广告-点击] <|ad_begin|> + 23:10 [广告-深度转化] <|ad_begin|> + 23:10 [广告-点击] <|ad_begin|> +【2026-02-03】 + 03:19 [视频-点赞/长播] <|video_begin|> + 03:44 [广告-深度转化] <|ad_begin|> + 03:44 [广告-点击] <|ad_begin|> + 06:30 [视频-长播] <|video_begin|> + 06:30 [视频-关注/收藏/点赞/长播] <|video_begin|> + 06:58 [视频-长播] <|video_begin|> + 06:58 [视频-长播] <|video_begin|> + 10:08 [广告-点击] <|ad_begin|> + 10:33 [视频-长播] <|video_begin|> + 10:33 [视频-点赞/长播] <|video_begin|> + 11:56 [广告-深度转化] <|ad_begin|> + 11:56 [广告-点击] <|ad_begin|> + 14:26 [视频-长播] <|video_begin|> + 14:32 [视频-长播] <|video_begin|> + 23:00 [视频-长播] <|video_begin|> +【2026-02-04】 + 07:38 [视频-长播] <|video_begin|> + 07:38 [视频-长播] <|video_begin|> + 07:38 [视频-长播] <|video_begin|> + 08:31 [视频-长播] <|video_begin|> + 09:51 [视频-长播] <|video_begin|> + 10:19 [视频-长播] <|video_begin|> + 10:19 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 10:30 [视频-长播] <|video_begin|> + 10:30 [视频-长播] <|video_begin|> + 10:30 [视频-长播] <|video_begin|> + 10:34 [视频-长播] <|video_begin|> + 11:00 [广告-深度转化] <|ad_begin|> + 11:00 [广告-点击] <|ad_begin|> + 12:42 [视频-长播] <|video_begin|> + 12:57 [视频-长播] <|video_begin|> + 13:00 [视频-关注/点赞/长播] <|video_begin|> + 13:53 [视频-长播] <|video_begin|> + 13:53 [视频-长播] <|video_begin|> + 22:33 [视频-长播] <|video_begin|> + 22:51 [视频-长播] <|video_begin|> + 23:03 [视频-长播] <|video_begin|> + 23:03 [视频-长播] <|video_begin|> + 23:22 [广告-深度转化] <|ad_begin|> + 23:22 [广告-点击] <|ad_begin|> + 23:52 [视频-长播] <|video_begin|> + 23:52 [视频-长播] <|video_begin|> + 23:55 [视频-长播] <|video_begin|> + 23:55 [视频-长播] <|video_begin|> + 23:55 [视频-长播] <|video_begin|> +【2026-02-05】 + 00:09 [视频-关注/点赞/长播] <|video_begin|> + 00:14 [广告-点击] <|ad_begin|> + 00:20 [视频-长播] <|video_begin|> + 00:20 [视频-长播] <|video_begin|> + 00:25 [视频-长播] <|video_begin|> + 00:25 [视频-长播] <|video_begin|> + 00:32 [视频-长播] <|video_begin|> + 00:39 [视频-长播] <|video_begin|> + 00:39 [视频-长播] <|video_begin|> + 01:00 [视频-长播] <|video_begin|> + 01:25 [视频-浏览] <|video_begin|> + 01:28 [视频-长播] <|video_begin|> + 02:16 [广告-点击] <|ad_begin|> + 02:50 [视频-长播] <|video_begin|> + 02:54 [视频-长播] <|video_begin|> + 03:28 [视频-长播] <|video_begin|> + 03:43 [广告-深度转化] <|ad_begin|> + 03:43 [广告-点击] <|ad_begin|> + 05:26 [视频-长播] <|video_begin|> + 06:08 [视频-长播] <|video_begin|> + 06:08 [视频-长播] <|video_begin|> + 06:13 [视频-长播] <|video_begin|> + 06:13 [视频-长播] <|video_begin|> + 06:13 [视频-长播] <|video_begin|> + 09:05 [广告-深度转化] <|ad_begin|> + 09:05 [广告-点击] <|ad_begin|> + 10:09 [视频-长播] <|video_begin|> + 10:50 [广告-点击] <|ad_begin|> + 14:04 [广告-点击] <|ad_begin|> + 14:12 [广告-深度转化] <|ad_begin|> + 14:12 [广告-点击] <|ad_begin|> + 15:23 [广告-点击] <|ad_begin|> +角色任务：你是一名极端严苛的用户行为数据挖掘专家，同时具备数据格式化能力，请根据以上用户交互历史，针对指定主题提取具有行为递进逻辑及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 +核心判定逻辑（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。 +请根据以下主题提取行为逻辑链： +主题：从被动娱乐到主动寻求情感慰藉的路径探索 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动娱乐到主动寻求情感慰藉的路径探索", + "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":"从被动娱乐到主动寻求情感慰藉的路径探索","events":[{"date":"2025-12-22","action":"[广告-深度转化] <|ad_begin|>","logic":"初始阶段：用户被动接收并深度转化了大量以“家庭关系”、“情感纠葛”、“逆袭”为主题的短剧广告，表明其对该类内容存在初步兴趣。"},{"date":"2026-01-22","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"兴趣深化与行为转变：用户从观看虚构的短剧，转向主动关注、点赞并长时观看真实社会事件中关于“家庭责任”与“牺牲”的纪实内容。行为从被动接收广告转为主动深度互动，兴趣点从“戏剧冲突”深化为“真实情感共鸣”。"},{"date":"2026-01-29","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"主题聚焦与认知确认：用户再次主动关注并深度互动另一则关于“家庭责任”与“孝道”的真实感人故事。这确认了其兴趣已从宽泛的“情感纠葛”收敛至更具正能量和社会价值的“亲情奉献”主题，完成了从消遣娱乐到寻求情感慰藉和正向价值认同的认知跃迁。"}]}}<|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|>，对主播 <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|> 有过关注/首次打赏行为。 +用户购物行为: 浏览了商品 <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>，购买了 <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_begin|>, <|prod_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|>。 +广告行为: 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|>。 + +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 + +先按近期、高频、深度互动和跨域重复信号归纳用户兴趣，再筛掉与历史语义弱相关的候选；最终只输出最可能命中的视频 itemic 结果。 + +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, 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-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, 151667, 198, 60726, 59879, 104352, 5373, 114427, 5373, 102217, 104199, 33108, 99960, 99390, 105444, 104757, 112543, 20002, 100565, 3837, 87256, 101737, 100373, 57218, 100022, 72881, 64559, 99932, 105470, 111015, 24968, 103941, 91680, 66017, 31235, 87267, 50509, 101047, 87140, 1509, 292, 89254, 27773, 8997, 151668, 198, 75882, 20002, 104044, 99729, 9370, 87140, 18830, 25, 220, 176245, 156191, 162715, 173952, 151645, 198, -100][INFO|configuration_utils.py:769] 2026-07-10 23:45:56,712 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v21_v15_user_repair_rec_fast_lr4e6_ep055/config.json +[INFO|configuration_utils.py:847] 2026-07-10 23:45:56,713 >> 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":"从被动信息吸收到主动利用AI工具的认知跃迁","events":[{"date":"2026-01-26","action":"[视频-收藏/长播] <|video_begin|>","logic":"信息积累与痛点形成：用户通过大量观看财经、科技、时政类视频，积累了海量信息，并收藏了关于“投资策略与心理学”的深度分析视频，表明其在信息处理和决策上可能遇到了瓶颈，产生了对更高效工具的需求。"},{"date":"2026-01-29","action":"[广告-点击] <|ad_begin|>","logic":"兴趣转向与工具探索：用户开始主动点击“免费人工智能课程”广告，标志着其兴趣从被动接收信息转向主动学习和了解能提升信息处理效率的AI工具，行为模式发生显著变化。"},{"date":"2026-02-01","action":"[视频-收藏/长播] <|video_begin|>","logic":"认知深化与效率追求：用户收藏了关于“手机实用功能”以提升操作效率的视频。这一行为与探索AI工具的逻辑一致，共同指向其核心诉求——利用工具提升个人效率，进一步佐证了其从“信息消费”到“工具赋能”的认知转变。"}]}}<|im_end|> +{"logic_chain":{"name":"从被动观赏到主动实践的节日装饰决策链","events":[{"date":"2026-02-04","action":"[视频-关注/长播] <|video_begin|>","logic":"兴趣触发：被动接收到关于“灯笼制作”的视频内容，对节日装饰产生初步兴趣，但认知停留在成品外观层面。"},{"date":"2026-01-29","action":"[商品-购买] <|prod_begin|>","logic":"认知收敛与行动转化：从对灯笼成品的笼统兴趣，聚焦到实现其发光效果的核心组件“无线遥控LED灯芯”上，并完成购买。这表明用户已从欣赏转向实践，并对装饰方案的技术细节（无线、遥控）产生了明确的功能性需求，是典型的认知增量和行为深化。"}]}}<|im_end|> + +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":"从被动娱乐到主动探索：对赛车游戏兴趣的具象化过程","events":[{"date":"2026-01-26","action":"[视频-转发/评论/收藏/点赞/长播] <|video_begin|>","logic":"兴趣触发：通过深度互动（转发/评论/收藏/点赞/长播）一个赛车游戏视频，表现出对该品类的初步兴趣。"},{"date":"2026-01-26","action":"[视频-转发/点赞/长播] <|video_begin|>","logic":"兴趣聚焦：在同一天，用户的兴趣从泛化的赛车游戏，聚焦到了一款具体游戏《和平精英》中的赛车玩法，并进行了深度互动，体现了兴趣的快速收敛。"},{"date":"2026-01-29","action":"[视频-转发/评论/点赞/长播] <|video_begin|>","logic":"对比与拓展：在聚焦《和平精英》后，用户又深度互动了另一款经典赛车游戏《极品飞车》，表明其正在对不同赛车游戏进行横向对比和体验拓展，认知从单一游戏玩法扩展到品类比较。"}]}}<|im_end|> +{"logic_chain":{"name":"从被动娱乐到主动寻求情感慰藉的路径探索","events":[{"date":"2025-12-22","action":"[广告-深度转化] <|ad_begin|>","logic":"初始阶段：用户被动接收并深度转化了大量以“家庭关系”、“情感纠葛”、“逆袭”为主题的短剧广告，表明其对该类内容存在初步兴趣。"},{"date":"2026-01-22","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"兴趣深化与行为转变：用户从观看虚构的短剧，转向主动关注、点赞并长时观看真实社会事件中关于“家庭责任”与“牺牲”的纪实内容。行为从被动接收广告转为主动深度互动，兴趣点从“戏剧冲突”深化为“真实情感共鸣”。"},{"date":"2026-01-29","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"主题聚焦与认知确认：用户再次主动关注并深度互动另一则关于“家庭责任”与“孝道”的真实感人故事。这确认了其兴趣已从宽泛的“情感纠葛”收敛至更具正能量和社会价值的“亲情奉献”主题，完成了从消遣娱乐到寻求情感慰藉和正向价值认同的认知跃迁。"}]}}<|im_end|> + +先按近期、高频、深度互动和跨域重复信号归纳用户兴趣，再筛掉与历史语义弱相关的候选；最终只输出最可能命中的视频 itemic 结果。 + +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 23:45:57,034 >> loading weights file /home/ll/llm4rec/experiments/outputs/v21_v15_user_repair_rec_fast_lr4e6_ep055/model.safetensors +[INFO|modeling_utils.py:821] 2026-07-10 23:45:57,034 >> Will use dtype=torch.bfloat16 as defined in model's config object +[INFO|configuration_utils.py:1027] 2026-07-10 23:45:57,188 >> 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/v21_v15_user_repair_rec_fast_lr4e6_ep055/generation_config.json +[INFO|configuration_utils.py:1027] 2026-07-10 23:45:59,210 >> 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 23:45:59,211 >> Could not locate the custom_generate/generate.py inside /home/ll/llm4rec/experiments/outputs/v21_v15_user_repair_rec_fast_lr4e6_ep055. +[INFO|2026-07-10 23:45:59] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled. +[INFO|2026-07-10 23:45:59] llamafactory.model.model_utils.attention:144 >> Using FlashAttention-2 for faster training and inference. +[INFO|2026-07-10 23:45:59] llamafactory.model.adapter:144 >> Pure bf16 / BAdam detected, remaining trainable params in half precision. +[INFO|2026-07-10 23:45:59] llamafactory.model.adapter:144 >> Fine-tuning method: Full +[INFO|2026-07-10 23:45:59] llamafactory.model.loader:144 >> trainable params: 801,433,600 || all params: 801,433,600 || trainable%: 100.0000 +[INFO|trainer.py:1469] 2026-07-10 23:45:59,357 >> ***** Running training ***** +[INFO|trainer.py:1470] 2026-07-10 23:45:59,357 >> Num examples = 1,323 +[INFO|trainer.py:1471] 2026-07-10 23:45:59,357 >> Num Epochs = 1 +[INFO|trainer.py:1472] 2026-07-10 23:45:59,357 >> Num update steps per epoch = 331 +[INFO|trainer.py:1473] 2026-07-10 23:45:59,357 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:1476] 2026-07-10 23:45:59,357 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:1477] 2026-07-10 23:45:59,357 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:1478] 2026-07-10 23:45:59,357 >> Total optimization steps = 106 +[INFO|trainer.py:1479] 2026-07-10 23:45:59,358 >> Number of trainable parameters = 801,433,600 + 0%| | 0/106 [00:00> `use_return_dict` is deprecated! 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Do not forget to share your model on huggingface.co/models =) + + + 100%|██████████| 106/106 [13:39<00:00, 8.02s/it] 100%|██████████| 106/106 [13:39<00:00, 7.73s/it] +[INFO|trainer.py:3815] 2026-07-10 23:59:39,108 >> Saving model checkpoint to /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032 +[INFO|configuration_utils.py:533] 2026-07-10 23:59:39,109 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/config.json +[INFO|configuration_utils.py:816] 2026-07-10 23:59:39,110 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/generation_config.json +{'loss': '0.9166', 'grad_norm': '38.25', 'learning_rate': '2.199e-06', 'epoch': '0.01512'} +{'loss': '0.8236', 'grad_norm': '40.5', 'learning_rate': '2.182e-06', 'epoch': '0.03023'} +{'loss': '0.8143', 'grad_norm': '40.25', 'learning_rate': '2.139e-06', 'epoch': '0.04535'} +{'loss': '0.619', 'grad_norm': '4.906', 'learning_rate': '2.072e-06', 'epoch': '0.06047'} +{'loss': '0.7871', 'grad_norm': '38.75', 'learning_rate': '1.982e-06', 'epoch': '0.07559'} +{'loss': '0.6626', 'grad_norm': '4.625', 'learning_rate': '1.872e-06', 'epoch': '0.0907'} +{'loss': '0.63', 'grad_norm': '4.312', 'learning_rate': '1.744e-06', 'epoch': '0.1058'} +{'loss': '0.6887', 'grad_norm': '4.375', 'learning_rate': '1.601e-06', 'epoch': '0.1209'} +{'loss': '0.7747', 'grad_norm': '4.531', 'learning_rate': '1.446e-06', 'epoch': '0.1361'} +{'loss': '0.6845', 'grad_norm': '4.5', 'learning_rate': '1.284e-06', 'epoch': '0.1512'} +{'loss': '0.7352', 'grad_norm': '36.75', 'learning_rate': '1.117e-06', 'epoch': '0.1663'} +{'loss': '0.7789', 'grad_norm': '30.38', 'learning_rate': '9.495e-07', 'epoch': '0.1814'} +{'loss': '0.7242', 'grad_norm': '3.656', 'learning_rate': '7.857e-07', 'epoch': '0.1965'} +{'loss': '0.8204', 'grad_norm': '31.88', 'learning_rate': '6.292e-07', 'epoch': '0.2116'} +{'loss': '0.7025', 'grad_norm': '5.844', 'learning_rate': '4.837e-07', 'epoch': '0.2268'} +{'loss': '0.6883', 'grad_norm': '4.906', 'learning_rate': '3.524e-07', 'epoch': '0.2419'} +{'loss': '0.7953', 'grad_norm': '5.375', 'learning_rate': '2.385e-07', 'epoch': '0.257'} +{'loss': '0.7164', 'grad_norm': '14.5', 'learning_rate': '1.446e-07', 'epoch': '0.2721'} +{'loss': '0.6571', 'grad_norm': '4.781', 'learning_rate': '7.286e-08', 'epoch': '0.2872'} +{'loss': '0.8478', 'grad_norm': '29.88', 'learning_rate': '2.498e-08', 'epoch': '0.3023'} +{'loss': '0.8161', 'grad_norm': '5.469', 'learning_rate': '2.046e-09', 'epoch': '0.3175'} +{'train_runtime': '819.7', 'train_samples_per_second': '0.516', 'train_steps_per_second': '0.129', 'train_loss': '0.7456', 'epoch': '0.3205'} + Writing model shards: 0%| | 0/1 [00:00> Model weights saved in /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/model.safetensors +[INFO|tokenization_utils_base.py:3278] 2026-07-10 23:59:40,058 >> chat template saved in /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/chat_template.jinja +[INFO|tokenization_utils_base.py:2111] 2026-07-10 23:59:40,080 >> tokenizer config file saved in /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/tokenizer_config.json +***** train metrics ***** + epoch = 0.3205 + total_flos = 47166380GF + train_loss = 0.7456 + train_runtime = 0:13:39.74 + train_samples_per_second = 0.516 + train_steps_per_second = 0.129 +Figure saved at: /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/training_loss.png +[WARNING|2026-07-10 23:59:40] llamafactory.extras.ploting:149 >> No metric eval_loss to plot. +[WARNING|2026-07-10 23:59:40] llamafactory.extras.ploting:149 >> No metric eval_accuracy to plot. +[INFO|modelcard.py:263] 2026-07-10 23:59:40,177 >> Dropping the following result as it does not have all the necessary fields: +{'task': {'name': 'Causal Language Modeling', 'type': 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