From df882f613af83e8f9e4ff5268abfcedb9401657d Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 19 Jul 2026 01:58:10 +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/v42_v29_user_evolution_guard_lr5e7_ep10 Source: Original Platform --- .gitattributes | 36 + README.md | 58 + all_results.json | 8 + chat_template.jinja | 89 + config.json | 63 + experiment_recipe.json | 72 + generation_config.json | 12 + model.safetensors | 3 + ...65013.ubuntu-System-Product-Name.1385064.0 | 3 + tokenizer.json | 3 + tokenizer_config.json | 16 + train.log | 2291 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 66 + trainer_state.json | 498 ++++ training_args.bin | 3 + training_loss.png | Bin 0 -> 57729 bytes 17 files changed, 3229 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/Jul15_05-36-53_ubuntu-System-Product-Name/events.out.tfevents.1784065013.ubuntu-System-Product-Name.1385064.0 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..8e91f80 --- /dev/null +++ b/README.md @@ -0,0 +1,58 @@ +--- +library_name: transformers +license: other +base_model: lldois/v29_v19_user_world_guard_lr8e7_ep018 +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: v42_v29_user_evolution_guard_lr5e7_ep10 + results: [] +--- + + + +# v42_v29_user_evolution_guard_lr5e7_ep10 + +This model is a fine-tuned version of [lldois/v29_v19_user_world_guard_lr8e7_ep018](https://huggingface.co/lldois/v29_v19_user_world_guard_lr8e7_ep018) on the exp_v42_user_evolution dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 5e-07 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 202607192 +- gradient_accumulation_steps: 4 +- total_train_batch_size: 4 +- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments +- lr_scheduler_type: cosine +- lr_scheduler_warmup_steps: 0.03 +- num_epochs: 1.0 + +### 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..aa2c62f --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 1.0, + "total_flos": 3.143810179830989e+17, + "train_loss": 1.9069785443783536, + "train_runtime": 5405.3324, + "train_samples_per_second": 0.483, + "train_steps_per_second": 0.121 +} \ 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..ecead8d --- /dev/null +++ b/experiment_recipe.json @@ -0,0 +1,72 @@ +{ + "created_at": "2026-07-15 00:59:15", + "name": "v42_v29_user_evolution_guard_lr5e7_ep10", + "base": "/home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018", + "dataset": "v42_user_evolution", + "dataset_manifest": { + "name": "v42_user_evolution", + "path": "/home/ll/llm4rec/experiments/data/v42_user_evolution.jsonl", + "records": 75000, + "bytes": 381438256, + "sha256": "d4dcc5f06f9e32b0d781e29d2b6965ffc8683fc9b63e1d2533322535cfd73fde", + "requested_components": { + "general": 26000, + "r0": 6000, + "r3_think": 12000, + "r3_direct": 12000, + "old_rec": 5000, + "old_user": 9000, + "old_item": 5000 + }, + "groups": { + "general": 26000, + "r3": 24000, + "old_user": 9000, + "old_item": 5000, + "old_rec": 5000, + "r0": 6000 + }, + "variants": { + "official_general_cot": 13010, + "profile_video/video_cot": 3756, + "official_general_direct": 12990, + "original_competition": 8591, + "profile_goods_cot": 2593, + "profile_goods_direct": 2680, + "user_array_json_strict": 1530, + "item_no_think_direct_final": 883, + "rec_no_think_direct_final": 2473, + "profile_video/video_direct": 3677, + "sid_to_caption_cot": 1487, + "caption_to_sid_direct": 3020, + "profile_live_cot": 2827, + "user_strict_logic": 1274, + "user_strict_array": 1537, + "sid_to_caption_direct": 1493, + "profile_live_direct": 2850, + "profile_video/ad_direct": 2793, + "profile_video/ad_cot": 2824, + "item_short_think": 865, + "user_logic_json_strict": 1260, + "user_extra_no_think_logic": 587 + }, + "routes": { + "think": 33240, + "no_think": 41760 + }, + "target_leakage": 0, + "seed": 202607159 + }, + "learning_rate": "5.0e-7", + "epochs": 1.0, + "stages": null, + "note": "Protects structured user extraction/evolution formats while adding real-holdout R3 and general replay.", + "cot_policy": "Preserve meaningful CoT for /think and pure final outputs for /no_think.", + "checkpoint_policy": "save_strategy=no; only the final model is retained.", + "script": "/home/ll/llm4rec/experiments/run_v34_v43.py", + "script_sha256": "fbf01773c61579cf6159f64442fc0c8902714c84ed23b488bc9a6236a154f402", + "configs": [ + "/home/ll/llm4rec/experiments/configs/v42_v29_user_evolution_guard_lr5e7_ep10.yaml" + ], + "reproduce": "/home/ll/llm4rec/demo/LLaMA-Factory/.venv/bin/python /home/ll/llm4rec/experiments/run_v34_v43.py --single v42_v29_user_evolution_guard_lr5e7_ep10 --gpu " +} \ 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..a7a84dc --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ee2d14b407067abc7bbd66a60019472aaa976bf31bda9ddeb2b8a4fd25bfaeb9 +size 1602902832 diff --git a/runs/Jul15_05-36-53_ubuntu-System-Product-Name/events.out.tfevents.1784065013.ubuntu-System-Product-Name.1385064.0 b/runs/Jul15_05-36-53_ubuntu-System-Product-Name/events.out.tfevents.1784065013.ubuntu-System-Product-Name.1385064.0 new file mode 100644 index 0000000..d403510 --- /dev/null +++ b/runs/Jul15_05-36-53_ubuntu-System-Product-Name/events.out.tfevents.1784065013.ubuntu-System-Product-Name.1385064.0 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b9533e5971fd3539d92a32bbaaf774f8752e26ffbc9d2a89507de45d715d5dac +size 19983 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..9c08bcf --- /dev/null +++ b/train.log @@ -0,0 +1,2291 @@ +[2026-07-15 05:36:20] stage 1/1: /home/ll/llm4rec/experiments/configs/v42_v29_user_evolution_guard_lr5e7_ep10.yaml +/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|2026-07-15 05:36:23] 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] 2026-07-15 05:36:23,282 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-15 05:36:23,283 >> 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] 2026-07-15 05:36:23,947 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-15 05:36:23,948 >> 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] 2026-07-15 05:36:23,948 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-15 05:36:23,949 >> 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|2026-07-15 05:36:24] llamafactory.data.loader:144 >> Loading dataset /home/ll/llm4rec/experiments/data/v42_user_evolution.jsonl... +Setting num_proc from 16 back to 1 for the train split to disable multiprocessing as it only contains one shard. + Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 20747 examples [00:00, 188602.73 examples/s] Generating train split: 43406 examples [00:00, 204695.17 examples/s] Generating train split: 70124 examples [00:00, 218072.32 examples/s] Generating train split: 75000 examples [00:00, 215128.40 examples/s] + Converting format of dataset (num_proc=16): 0%| | 0/75000 [00:00user +【用户交互历史】： +【2025-03-26】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-04-02】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] 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<|video_begin|> + 01:08 [视频-评论/长播] <|video_begin|> + 01:18 [视频-浏览] <|video_begin|> + 01:23 [视频-长播] <|video_begin|> + 01:34 [视频-长播] <|video_begin|> + 01:34 [视频-点赞/长播] <|video_begin|> + 01:34 [视频-评论/长播] <|video_begin|> + 01:39 [视频-长播] <|video_begin|> + 01:39 [视频-长播] <|video_begin|> + 01:57 [广告-深度转化] <|ad_begin|> + 01:57 [广告-点击] <|ad_begin|> + 01:57 [广告-点击] <|ad_begin|> + 01:58 [广告-深度转化] <|ad_begin|> + 01:58 [广告-点击] <|ad_begin|> + 01:58 [广告-点击] <|ad_begin|> + 02:00 [广告-点击] <|ad_begin|> + 02:00 [广告-点击] <|ad_begin|> + 02:01 [广告-深度转化] <|ad_begin|> + 02:01 [广告-点击] <|ad_begin|> + 02:06 [广告-深度转化] <|ad_begin|> + 02:06 [广告-点击] <|ad_begin|> + 02:06 [广告-点击] <|ad_begin|> + 02:09 [广告-点击] <|ad_begin|> + 02:14 [广告-深度转化] <|ad_begin|> + 02:14 [广告-点击] <|ad_begin|> + 02:14 [广告-点击] <|ad_begin|> + 02:23 [广告-深度转化] <|ad_begin|> + 02:23 [广告-点击] <|ad_begin|> + 02:23 [广告-深度转化] <|ad_begin|> + 02:23 [广告-点击] <|ad_begin|> + 02:23 [广告-点击] <|ad_begin|> + 03:11 [广告-深度转化] <|ad_begin|> + 03:11 [广告-点击] <|ad_begin|> + 06:20 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[视频-点赞/长播] <|video_begin|> + 11:18 [广告-深度转化] <|ad_begin|> + 11:18 [广告-点击] <|ad_begin|> + 11:18 [广告-点击] <|ad_begin|> + 11:21 [广告-点击] <|ad_begin|> + 11:21 [广告-深度转化] <|ad_begin|> + 11:21 [广告-点击] <|ad_begin|> + 11:24 [广告-深度转化] <|ad_begin|> + 11:24 [广告-点击] <|ad_begin|> + 11:34 [广告-点击] <|ad_begin|> + 11:35 [广告-点击] <|ad_begin|> + 11:41 [广告-点击] <|ad_begin|> + 11:55 [广告-点击] <|ad_begin|> + 11:59 [广告-点击] <|ad_begin|> + 12:00 [广告-深度转化] <|ad_begin|> + 12:00 [广告-点击] <|ad_begin|> + 12:01 [广告-深度转化] <|ad_begin|> + 12:01 [广告-点击] <|ad_begin|> + 12:29 [广告-点击] <|ad_begin|> + 12:29 [广告-深度转化] <|ad_begin|> + 12:29 [广告-点击] <|ad_begin|> + 12:32 [广告-点击] <|ad_begin|> + 12:37 [广告-点击] <|ad_begin|> + 12:49 [广告-点击] <|ad_begin|> + 12:54 [广告-点击] <|ad_begin|> + 13:01 [广告-点击] <|ad_begin|> + 13:02 [广告-点击] <|ad_begin|> +【2026-02-05】 + 01:57 [视频-长播] <|video_begin|> + 01:57 [视频-长播] <|video_begin|> + 02:09 [视频-长播] <|video_begin|> + 02:27 [视频-长播] <|video_begin|> + 02:27 [视频-点赞/长播] <|video_begin|> + 02:28 [视频-点赞/长播] <|video_begin|> + 02:39 [视频-长播] <|video_begin|> + 02:39 [视频-评论/长播] <|video_begin|> + 02:46 [广告-深度转化] <|ad_begin|> + 02:46 [广告-点击] <|ad_begin|> + 02:46 [广告-点击] <|ad_begin|> + 02:48 [广告-深度转化] <|ad_begin|> + 02:48 [广告-点击] <|ad_begin|> + 03:09 [广告-深度转化] <|ad_begin|> + 03:09 [广告-点击] <|ad_begin|> + 03:17 [广告-点击] <|ad_begin|> + 03:18 [广告-深度转化] <|ad_begin|> + 03:18 [广告-点击] <|ad_begin|> + 03:25 [广告-深度转化] <|ad_begin|> + 03:25 [广告-点击] <|ad_begin|> + 03:25 [广告-点击] <|ad_begin|> + 04:21 [视频-评论/点赞/长播] <|video_begin|> + 04:33 [视频-评论/点赞/长播] <|video_begin|> + 04:33 [视频-评论/长播] <|video_begin|> + 12:22 [广告-深度转化] <|ad_begin|> + 12:22 [广告-点击] <|ad_begin|> + 12:22 [广告-点击] <|ad_begin|> + 12:24 [广告-点击] <|ad_begin|> + 12:34 [广告-点击] <|ad_begin|> + 12:38 [广告-深度转化] <|ad_begin|> + 12:38 [广告-点击] <|ad_begin|> + 12:39 [广告-点击] <|ad_begin|> + 12:46 [广告-深度转化] <|ad_begin|> + 12:46 [广告-点击] <|ad_begin|> + 13:04 [广告-深度转化] <|ad_begin|> + 13:04 [广告-点击] <|ad_begin|> + 13:05 [广告-深度转化] <|ad_begin|> + 13:05 [广告-点击] <|ad_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）： 搜索-搜索、视频-浏览、视频-长播、直播-关注、直播-首次打赏、商品-点击、商品-购买、广告-点击、广告-深度转化 +核心提取逻辑（递进性准则）： +按时间先后提取不超过 5 步的行为链，要求后项交互B必须对前项交互A形成场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是由 A 延展出来的需求，严禁提取任何品类平级、内容重复或仅因天气/促销造成的并列凑单行为。 +1.场景驱动协同：交互 B 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 需要体现为交互 A 之后衍生出的副作用需求或新需求，或者 A 是促使 B 出现的诱因。 +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。 +请针对以下主题提取行为逻辑链： +主题：从娱乐消遣到实用技能的兴趣转向 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从娱乐消遣到实用技能的兴趣转向", + "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":"从娱乐消遣到实用技能的兴趣转向","events":[{"date":"2025-04-02","action":"[直播-关注] <|living_begin|>","logic":"初始阶段：兴趣广泛，集中于高颜值、娱乐互动、情感陪伴类的泛娱乐主播，行为模式为发散性关注。"},{"date":"2025-04-18","action":"[直播-关注] <|living_begin|>","logic":"兴趣演化：首次出现明确的工具性、功利性诉求，关注内容从“娱乐”转向“教学”、“干货”，实现了从消遣到实用技能获取的认知跃迁。"},{"date":"2025-06-06","action":"[直播-关注] <|living_begin|>","logic":"认知深化与聚焦：在“极速版教学”的基础上，兴趣点进一步细化到“活跃值运营”、“标签转化”、“平台规则解读”等更深层次的运营技巧，表明用户已不满足于基础操作，开始探索更高阶的玩法和规则。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-01-01】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-05-26】 + --:-- [直播-关注] <|living_begin|> +【2025-06-17】 + --:-- [直播-关注] <|living_begin|> +【2025-06-30】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-02】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-08-02】 + --:-- [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|> +【2025-08-07】 + --:-- [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|> +【2025-08-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-09】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-13】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-15】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-22】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-30】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-31】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-05】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-14】 + --:-- [直播-关注] <|living_begin|> +【2025-09-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-09-16】 + --:-- [直播-关注] <|living_begin|> +【2025-09-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-09-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-19】 + --:-- [直播-关注] <|living_begin|> +【2025-09-26】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-29】 + --:-- [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|> +【2025-10-02】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-03】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-16】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-18】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-20】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-21】 + --:-- [直播-关注] <|living_begin|> +【2025-10-25】 + --:-- [直播-打赏] <|living_begin|> +【2025-10-26】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-01】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-02】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-11-03】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-04】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-05】 + --:-- [直播-打赏] <|living_begin|> +【2025-11-07】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-09】 + --:-- [直播-关注] <|living_begin|> +【2025-11-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-16】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-18】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-25】 + --:-- [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|> +【2025-11-26】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-17】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-22】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-23】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-12-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-27】 + --:-- [直播-关注] <|living_begin|> +【2025-12-30】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-04】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-12】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-14】 + 07:56 [广告-深度转化] <|ad_begin|> + 08:47 [广告-深度转化] <|ad_begin|> + 09:19 [广告-深度转化] <|ad_begin|> +【2026-01-15】 + 01:45 [广告-深度转化] <|ad_begin|> + 02:40 [广告-深度转化] <|ad_begin|> + 03:08 [广告-深度转化] <|ad_begin|> + 09:12 [广告-深度转化] <|ad_begin|> + 13:09 [广告-深度转化] <|ad_begin|> +【2026-01-16】 + 12:16 [广告-深度转化] <|ad_begin|> +【2026-01-17】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + 05:43 [广告-深度转化] <|ad_begin|> + 12:07 [广告-深度转化] <|ad_begin|> +【2026-01-18】 + --:-- [商品-购买] <|prod_begin|> + 02:32 [广告-深度转化] <|ad_begin|> +【2026-01-19】 + 01:03 [广告-深度转化] <|ad_begin|> + 01:14 [广告-深度转化] <|ad_begin|> + 08:45 [广告-深度转化] <|ad_begin|> + 10:50 [广告-深度转化] <|ad_begin|> +【2026-01-21】 + 05:03 [广告-深度转化] <|ad_begin|> + 11:02 [广告-深度转化] <|ad_begin|> + 23:38 [视频-点赞/长播] <|video_begin|> +【2026-01-22】 + 01:35 [视频-关注/长播] <|video_begin|> + 01:46 [视频-评论/长播] <|video_begin|> + 02:55 [视频-收藏/长播] <|video_begin|> + 02:58 [视频-收藏/长播] <|video_begin|> + 03:07 [视频-收藏/长播] <|video_begin|> + 05:27 [视频-点赞/长播] <|video_begin|> + 09:57 [广告-深度转化] <|ad_begin|> + 10:04 [广告-深度转化] <|ad_begin|> +【2026-01-23】 + 01:53 [广告-深度转化] <|ad_begin|> + 07:53 [视频-收藏/长播] <|video_begin|> + 11:55 [广告-深度转化] <|ad_begin|> + 13:18 [视频-评论/长播] <|video_begin|> + 13:52 [视频-评论/长播] <|video_begin|> +【2026-01-24】 + 04:32 [视频-点赞/长播] <|video_begin|> + 06:16 [视频-收藏/长播] <|video_begin|> + 07:21 [视频-点赞/长播] <|video_begin|> + 12:11 [广告-深度转化] <|ad_begin|> +【2026-01-25】 + 00:19 [广告-深度转化] <|ad_begin|> + 04:07 [视频-关注/长播] <|video_begin|> + 04:33 [广告-深度转化] <|ad_begin|> + 06:51 [视频-关注/长播] <|video_begin|> + 07:00 [视频-收藏/点赞/长播] <|video_begin|> + 07:14 [视频-收藏/长播] <|video_begin|> + 09:37 [广告-深度转化] <|ad_begin|> + 19:57 [广告-深度转化] <|ad_begin|> + 22:58 [广告-深度转化] <|ad_begin|> +【2026-01-26】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:35 [广告-深度转化] <|ad_begin|> + 10:42 [广告-深度转化] <|ad_begin|> + 14:18 [广告-深度转化] <|ad_begin|> + 21:58 [视频-评论/长播] <|video_begin|> + 22:26 [广告-深度转化] <|ad_begin|> +【2026-01-27】 + --:-- [商品-点击] <|prod_begin|> + 04:18 [广告-深度转化] <|ad_begin|> + 06:16 [广告-深度转化] <|ad_begin|> + 11:25 [广告-深度转化] <|ad_begin|> + 23:18 [广告-深度转化] <|ad_begin|> +【2026-01-29】 + --:-- [商品-点击] <|prod_begin|> + 02:45 [视频-点赞/长播] <|video_begin|> + 02:56 [视频-点赞/长播] <|video_begin|> + 03:15 [视频-点赞/长播] <|video_begin|> + 03:33 [视频-收藏/长播] <|video_begin|> + 12:10 [广告-深度转化] <|ad_begin|> + 12:15 [视频-点赞/长播] <|video_begin|> + 12:38 [视频-收藏/长播] <|video_begin|> +【2026-01-30】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:39 [视频-收藏/长播] <|video_begin|> + 06:03 [广告-深度转化] <|ad_begin|> + 06:17 [视频-收藏/长播] <|video_begin|> + 06:52 [视频-点赞/长播] <|video_begin|> + 07:15 [视频-收藏/长播] <|video_begin|> + 07:30 [视频-收藏/长播] <|video_begin|> + 07:36 [视频-评论/长播] <|video_begin|> + 07:36 [视频-收藏/长播] <|video_begin|> + 07:58 [视频-收藏/长播] <|video_begin|> + 08:01 [视频-收藏/长播] <|video_begin|> + 09:59 [广告-深度转化] <|ad_begin|> + 11:53 [广告-深度转化] <|ad_begin|> + 11:53 [广告-点击] <|ad_begin|> +【2026-01-31】 + --:-- [商品-点击] <|prod_begin|> + 04:27 [视频-评论/长播] <|video_begin|> + 04:44 [广告-深度转化] <|ad_begin|> + 04:44 [广告-点击] <|ad_begin|> + 05:17 [广告-深度转化] <|ad_begin|> + 05:17 [广告-点击] <|ad_begin|> + 08:05 [广告-点击] <|ad_begin|> + 08:09 [广告-点击] <|ad_begin|> + 08:24 [广告-深度转化] <|ad_begin|> + 08:24 [广告-点击] <|ad_begin|> + 08:34 [广告-点击] <|ad_begin|> + 08:50 [广告-点击] <|ad_begin|> + 08:51 [广告-点击] <|ad_begin|> + 09:00 [广告-点击] <|ad_begin|> + 14:46 [广告-深度转化] <|ad_begin|> + 14:46 [广告-点击] <|ad_begin|> + 22:04 [广告-点击] <|ad_begin|> + 22:07 [广告-点击] <|ad_begin|> + 22:17 [广告-深度转化] <|ad_begin|> + 22:17 [广告-点击] <|ad_begin|> + 22:35 [广告-点击] <|ad_begin|> +【2026-02-01】 + --:-- [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|> + 00:48 [广告-点击] <|ad_begin|> + 00:59 [广告-点击] <|ad_begin|> + 01:04 [广告-深度转化] <|ad_begin|> + 01:04 [广告-点击] <|ad_begin|> + 01:23 [广告-深度转化] <|ad_begin|> + 01:23 [广告-点击] <|ad_begin|> + 02:26 [广告-点击] <|ad_begin|> + 02:35 [广告-点击] <|ad_begin|> + 05:33 [广告-深度转化] <|ad_begin|> + 05:33 [广告-点击] <|ad_begin|> + 05:52 [广告-点击] <|ad_begin|> + 06:53 [视频-转发/长播] <|video_begin|> + 09:19 [广告-点击] <|ad_begin|> + 09:39 [广告-深度转化] <|ad_begin|> + 09:39 [广告-点击] <|ad_begin|> + 09:40 [广告-点击] <|ad_begin|> + 09:42 [广告-点击] <|ad_begin|> + 09:51 [广告-点击] <|ad_begin|> + 09:56 [广告-点击] <|ad_begin|> + 10:08 [广告-深度转化] <|ad_begin|> + 10:08 [广告-点击] <|ad_begin|> + 10:53 [广告-点击] <|ad_begin|> + 11:19 [广告-深度转化] <|ad_begin|> + 11:19 [广告-点击] <|ad_begin|> + 14:46 [广告-点击] <|ad_begin|> + 14:46 [广告-点击] <|ad_begin|> +【2026-02-02】 + 00:23 [视频-转发/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|> + 01:49 [广告-深度转化] <|ad_begin|> + 01:49 [广告-点击] <|ad_begin|> + 02:10 [广告-点击] <|ad_begin|> + 02:49 [广告-点击] <|ad_begin|> + 02:51 [广告-深度转化] <|ad_begin|> + 02:51 [广告-点击] <|ad_begin|> + 03:04 [广告-点击] <|ad_begin|> + 04:26 [广告-点击] <|ad_begin|> + 11:25 [视频-关注/长播] <|video_begin|> + 11:40 [视频-收藏/长播] <|video_begin|> + 13:38 [广告-点击] <|ad_begin|> + 14:25 [广告-点击] <|ad_begin|> + 14:27 [广告-深度转化] <|ad_begin|> + 14:27 [广告-点击] <|ad_begin|> + 16:42 [广告-点击] <|ad_begin|> + 22:53 [广告-深度转化] <|ad_begin|> + 22:53 [广告-点击] <|ad_begin|> +【2026-02-03】 + --:-- [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|> + 01:45 [广告-点击] <|ad_begin|> + 02:27 [广告-深度转化] <|ad_begin|> + 02:27 [广告-点击] <|ad_begin|> + 02:32 [广告-点击] <|ad_begin|> + 04:51 [广告-深度转化] <|ad_begin|> + 04:51 [广告-点击] <|ad_begin|> + 06:36 [广告-点击] <|ad_begin|> + 06:40 [视频-转发/长播] <|video_begin|> + 07:21 [广告-点击] <|ad_begin|> + 09:01 [广告-深度转化] <|ad_begin|> + 09:01 [广告-点击] <|ad_begin|> + 10:29 [广告-深度转化] <|ad_begin|> + 10:29 [广告-点击] <|ad_begin|> + 10:41 [广告-点击] <|ad_begin|> + 11:11 [广告-深度转化] <|ad_begin|> + 11:11 [广告-点击] <|ad_begin|> + 11:54 [广告-深度转化] <|ad_begin|> + 11:54 [广告-点击] <|ad_begin|> + 14:16 [广告-深度转化] <|ad_begin|> + 14:16 [广告-点击] <|ad_begin|> + 14:37 [广告-深度转化] <|ad_begin|> + 14:37 [广告-点击] <|ad_begin|> +【2026-02-04】 + 00:08 [广告-深度转化] <|ad_begin|> + 00:08 [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|> + 01:56 [广告-点击] <|ad_begin|> + 02:40 [广告-深度转化] <|ad_begin|> + 02:40 [广告-点击] <|ad_begin|> + 03:59 [广告-点击] <|ad_begin|> + 09:21 [视频-长播] <|video_begin|> + 09:42 [广告-点击] <|ad_begin|> + 09:56 [广告-深度转化] <|ad_begin|> + 09:56 [广告-点击] <|ad_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:42 [视频-长播] <|video_begin|> + 10:53 [视频-长播] <|video_begin|> + 10:53 [视频-长播] <|video_begin|> + 10:53 [视频-长播] <|video_begin|> + 16:36 [视频-长播] <|video_begin|> + 17:37 [广告-深度转化] <|ad_begin|> + 17:37 [广告-点击] <|ad_begin|> + 19:50 [广告-深度转化] <|ad_begin|> + 19:50 [广告-点击] <|ad_begin|> + 22:30 [视频-长播] <|video_begin|> + 22:30 [视频-长播] <|video_begin|> + 22:50 [广告-深度转化] <|ad_begin|> + 22:50 [广告-点击] <|ad_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|> + 02:26 [广告-深度转化] <|ad_begin|> + 02:26 [广告-点击] <|ad_begin|> + 03:37 [视频-长播] <|video_begin|> + 03:37 [视频-长播] <|video_begin|> + 03:39 [广告-点击] <|ad_begin|> + 03:43 [视频-长播] <|video_begin|> + 03:44 [视频-长播] <|video_begin|> + 03:44 [视频-长播] <|video_begin|> + 03:44 [视频-长播] <|video_begin|> + 03:46 [视频-长播] <|video_begin|> + 03:50 [视频-长播] <|video_begin|> + 03:50 [视频-长播] <|video_begin|> + 03:51 [视频-长播] <|video_begin|> + 03:51 [视频-长播] <|video_begin|> + 03:52 [视频-长播] <|video_begin|> + 03:52 [视频-长播] <|video_begin|> + 03:52 [视频-长播] <|video_begin|> + 03:52 [视频-转发/长播] <|video_begin|> + 03:53 [视频-长播] <|video_begin|> + 03:55 [视频-长播] <|video_begin|> + 04:03 [视频-长播] <|video_begin|> + 04:17 [视频-长播] <|video_begin|> + 04:32 [广告-点击] <|ad_begin|> + 05:21 [视频-长播] <|video_begin|> + 05:21 [视频-长播] <|video_begin|> + 05:21 [视频-长播] <|video_begin|> + 05:23 [视频-长播] <|video_begin|> + 05:23 [视频-长播] <|video_begin|> + 06:02 [视频-长播] <|video_begin|> + 06:02 [视频-长播] <|video_begin|> + 06:02 [视频-长播] <|video_begin|> + 06:26 [视频-长播] <|video_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|> + 06:27 [视频-长播] <|video_begin|> + 06:27 [视频-长播] <|video_begin|> + 06:29 [视频-收藏/长播] <|video_begin|> + 06:32 [视频-长播] <|video_begin|> + 06:32 [视频-长播] <|video_begin|> + 06:42 [视频-长播] <|video_begin|> + 06:42 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:45 [视频-长播] <|video_begin|> + 07:41 [视频-长播] <|video_begin|> +【2026-02-06】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_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：从泛化直播兴趣到聚焦“直播创业”的认知收敛 + +输出格式要求：请仅以包含 SID 的 JSON 数组形式返回结果，切勿输出任何额外的解释说明或无关字符。 + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +["<|living_begin|>","<|living_begin|>","<|living_begin|>","<|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|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>"]<|im_end|> +<|im_start|>user +【用户交互历史】： +【2024-12-15】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2024-12-29】 + --:-- [商品-购买] <|prod_begin|> +【2024-12-31】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-04】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-01-07】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-01-08】 + --:-- [直播-关注] <|living_begin|> +【2025-01-09】 + --:-- [直播-关注] <|living_begin|> +【2025-01-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-01-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-22】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-01-23】 + --:-- [直播-关注] <|living_begin|> +【2025-01-25】 + --:-- [直播-关注] <|living_begin|> +【2025-02-05】 + --:-- [直播-关注] <|living_begin|> +【2025-02-07】 + --:-- [直播-关注] <|living_begin|> +【2025-02-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-09】 + --:-- [直播-关注] <|living_begin|> +【2025-02-10】 + --:-- [直播-关注] <|living_begin|> +【2025-02-15】 + --:-- [直播-关注] <|living_begin|> +【2025-02-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-17】 + --:-- [直播-关注] <|living_begin|> +【2025-02-20】 + --:-- [直播-关注] <|living_begin|> +【2025-02-26】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-03-02】 + --:-- [直播-关注] <|living_begin|> +【2025-03-09】 + --:-- [直播-关注] <|living_begin|> +【2025-03-16】 + --:-- [直播-关注] <|living_begin|> +【2025-04-05】 + --:-- [直播-关注] <|living_begin|> +【2025-04-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-24】 + --:-- [直播-关注] <|living_begin|> +【2025-05-04】 + --:-- [直播-关注] <|living_begin|> +【2025-05-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-29】 + --:-- [直播-关注] <|living_begin|> +【2025-06-01】 + --:-- [直播-关注] <|living_begin|> +【2025-06-09】 + --:-- [直播-关注] <|living_begin|> +【2025-06-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-15】 + --:-- [直播-关注] <|living_begin|> +【2025-06-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-09】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-21】 + --:-- [直播-关注] <|living_begin|> +【2025-07-22】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-30】 + --:-- [直播-关注] <|living_begin|> +【2025-08-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-03】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-08-10】 + --:-- [直播-关注] <|living_begin|> +【2025-08-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-14】 + --:-- [直播-关注] <|living_begin|> +【2025-08-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-24】 + --:-- [直播-关注] <|living_begin|> +【2025-08-25】 + --:-- [直播-打赏] <|living_begin|> +【2025-09-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-17】 + --:-- [直播-关注] <|living_begin|> +【2025-10-19】 + --:-- [直播-关注] <|living_begin|> +【2025-10-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-21】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-11-22】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-11-27】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-02】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-09】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-11】 + --:-- [直播-关注] <|living_begin|> +【2025-12-14】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-16】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-19】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-23】 + 11:21 [广告-深度转化] <|ad_begin|> + 12:21 [广告-深度转化] <|ad_begin|> +【2025-12-24】 + --:-- [直播-关注] <|living_begin|> + 00:12 [广告-深度转化] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 11:07 [广告-深度转化] <|ad_begin|> + 21:00 [广告-深度转化] <|ad_begin|> + 22:19 [广告-深度转化] <|ad_begin|> +【2025-12-25】 + --:-- [商品-点击] <|prod_begin|> + 14:02 [广告-深度转化] <|ad_begin|> +【2025-12-26】 + 11:09 [广告-深度转化] <|ad_begin|> + 13:06 [广告-深度转化] <|ad_begin|> + 22:19 [广告-深度转化] <|ad_begin|> +【2025-12-27】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-28】 + 00:30 [广告-深度转化] <|ad_begin|> + 20:02 [广告-深度转化] <|ad_begin|> +【2025-12-29】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-30】 + --:-- [商品-点击] <|prod_begin|> + 14:55 [广告-深度转化] <|ad_begin|> + 17:23 [广告-深度转化] <|ad_begin|> +【2025-12-31】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 10:28 [广告-深度转化] <|ad_begin|> + 13:25 [广告-深度转化] <|ad_begin|> + 22:48 [广告-深度转化] <|ad_begin|> +【2026-01-01】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 09:57 [广告-深度转化] <|ad_begin|> + 20:57 [广告-点击] <|ad_begin|> + 21:02 [广告-点击] <|ad_begin|> +【2026-01-02】 + 07:41 [广告-深度转化] <|ad_begin|> + 07:41 [广告-点击] <|ad_begin|> + 08:02 [广告-深度转化] <|ad_begin|> + 08:02 [广告-点击] <|ad_begin|> + 11:45 [广告-点击] <|ad_begin|> + 14:26 [广告-深度转化] <|ad_begin|> + 14:26 [广告-点击] <|ad_begin|> +【2026-01-03】 + --:-- [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|> + 21:59 [广告-深度转化] <|ad_begin|> + 21:59 [广告-点击] <|ad_begin|> + 23:25 [广告-点击] <|ad_begin|> +【2026-01-04】 + 21:29 [广告-深度转化] <|ad_begin|> + 21:29 [广告-点击] <|ad_begin|> +【2026-01-05】 + --:-- [直播-关注] <|living_begin|> + 02:54 [广告-深度转化] <|ad_begin|> + 02:54 [广告-点击] <|ad_begin|> + 09:31 [广告-点击] <|ad_begin|> + 23:18 [广告-深度转化] <|ad_begin|> + 23:18 [广告-点击] <|ad_begin|> +【2026-01-06】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-07】 + 07:34 [广告-点击] <|ad_begin|> + 21:30 [广告-点击] <|ad_begin|> +【2026-01-08】 + 23:48 [广告-深度转化] <|ad_begin|> + 23:48 [广告-点击] <|ad_begin|> +【2026-01-09】 + --:-- [直播-关注] <|living_begin|> +【2026-01-10】 + 08:07 [广告-深度转化] <|ad_begin|> + 08:07 [广告-点击] <|ad_begin|> + 08:53 [广告-点击] <|ad_begin|> + 09:40 [广告-深度转化] <|ad_begin|> + 09:40 [广告-点击] <|ad_begin|> + 23:12 [广告-深度转化] <|ad_begin|> + 23:12 [广告-点击] <|ad_begin|> +【2026-01-11】 + --:-- [商品-点击] <|prod_begin|> + 11:01 [广告-深度转化] <|ad_begin|> + 11:01 [广告-点击] <|ad_begin|> + 13:28 [广告-深度转化] <|ad_begin|> + 13:28 [广告-点击] <|ad_begin|> +【2026-01-12】 + 03:07 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + 08:01 [广告-深度转化] <|ad_begin|> + 08:01 [广告-点击] <|ad_begin|> + 14:08 [广告-深度转化] <|ad_begin|> + 14:08 [广告-点击] <|ad_begin|> + 14:31 [广告-深度转化] <|ad_begin|> + 14:31 [广告-点击] <|ad_begin|> + 19:55 [广告-深度转化] <|ad_begin|> + 19:55 [广告-点击] <|ad_begin|> + 20:20 [广告-深度转化] <|ad_begin|> + 20:20 [广告-点击] <|ad_begin|> +【2026-01-13】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 21:34 [广告-深度转化] <|ad_begin|> + 21:34 [广告-点击] <|ad_begin|> +【2026-01-14】 + 03:24 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-15】 + 13:55 [广告-点击] <|ad_begin|> + 14:43 [广告-深度转化] <|ad_begin|> + 14:43 [广告-点击] <|ad_begin|> +【2026-01-16】 + --:-- [直播-关注] <|living_begin|> + 23:10 [广告-深度转化] <|ad_begin|> + 23:10 [广告-点击] <|ad_begin|> +【2026-01-18】 + 22:22 [广告-深度转化] <|ad_begin|> + 22:22 [广告-点击] <|ad_begin|> + 22:38 [广告-深度转化] <|ad_begin|> + 22:38 [广告-点击] <|ad_begin|> +【2026-01-19】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 21:12 [广告-点击] <|ad_begin|> + 21:35 [广告-深度转化] <|ad_begin|> + 21:35 [广告-点击] <|ad_begin|> +【2026-01-20】 + --:-- [商品-点击] <|prod_begin|> + 12:52 [广告-深度转化] <|ad_begin|> + 12:52 [广告-点击] <|ad_begin|> + 14:33 [广告-深度转化] <|ad_begin|> + 14:33 [广告-点击] <|ad_begin|> +【2026-01-21】 + --:-- [商品-点击] <|prod_begin|> + 22:15 [广告-深度转化] <|ad_begin|> + 22:15 [广告-点击] <|ad_begin|> +【2026-01-22】 + 00:34 [广告-深度转化] <|ad_begin|> + 00:34 [广告-点击] <|ad_begin|> + 09:37 [视频-浏览] <|video_begin|> + 09:57 [广告-深度转化] <|ad_begin|> + 09:57 [广告-点击] <|ad_begin|> + 11:49 [广告-点击] <|ad_begin|> + 21:07 [广告-深度转化] <|ad_begin|> + 21:07 [广告-点击] <|ad_begin|> + 22:58 [广告-深度转化] <|ad_begin|> + 22:58 [广告-点击] <|ad_begin|> +【2026-01-23】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 23:25 [广告-深度转化] <|ad_begin|> + 23:25 [广告-点击] <|ad_begin|> +【2026-01-24】 + 03:57 [广告-深度转化] <|ad_begin|> + 03:57 [广告-点击] <|ad_begin|> +【2026-01-25】 + 23:59 [广告-深度转化] <|ad_begin|> + 23:59 [广告-点击] <|ad_begin|> +【2026-01-27】 + 07:55 [视频-长播] <|video_begin|> + 07:55 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + 07:58 [视频-长播] <|video_begin|> + 07:58 [视频-长播] <|video_begin|> + 07:58 [视频-长播] <|video_begin|> + 22:55 [广告-深度转化] <|ad_begin|> + 22:55 [广告-点击] <|ad_begin|> +【2026-01-28】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 21:13 [视频-长播] <|video_begin|> + 21:13 [视频-长播] <|video_begin|> + 21:13 [视频-长播] <|video_begin|> +【2026-01-29】 + --:-- [商品-点击] <|prod_begin|> + 08:05 [视频-长播] <|video_begin|> + 08:05 [视频-长播] <|video_begin|> + 08:05 [视频-长播] <|video_begin|> + 08:18 [广告-深度转化] <|ad_begin|> + 08:18 [广告-点击] <|ad_begin|> + 21:03 [视频-长播] <|video_begin|> + 21:03 [视频-长播] <|video_begin|> + 21:18 [广告-深度转化] <|ad_begin|> + 21:18 [广告-点击] <|ad_begin|> + 22:26 [视频-长播] <|video_begin|> + 22:43 [广告-深度转化] <|ad_begin|> + 22:43 [广告-点击] <|ad_begin|> +【2026-01-30】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 15:09 [广告-深度转化] <|ad_begin|> + 15:09 [广告-点击] <|ad_begin|> + 21:56 [视频-长播] <|video_begin|> + 21:56 [视频-长播] <|video_begin|> + 21:56 [视频-长播] <|video_begin|> + 21:59 [广告-点击] <|ad_begin|> + 22:07 [视频-长播] <|video_begin|> + 22:12 [视频-长播] <|video_begin|> + 22:14 [视频-长播] <|video_begin|> + 22:14 [视频-长播] <|video_begin|> + 22:20 [视频-长播] <|video_begin|> +【2026-01-31】 + 22:05 [视频-长播] <|video_begin|> + 22:05 [视频-长播] <|video_begin|> + 23:11 [广告-深度转化] <|ad_begin|> + 23:11 [广告-点击] <|ad_begin|> +【2026-02-01】 + --:-- [商品-点击] <|prod_begin|> + 08:27 [视频-长播] <|video_begin|> + 08:27 [视频-长播] <|video_begin|> + 08:37 [广告-深度转化] <|ad_begin|> + 08:37 [广告-点击] <|ad_begin|> + 12:27 [广告-深度转化] <|ad_begin|> + 12:27 [广告-点击] <|ad_begin|> + 20:54 [视频-长播] <|video_begin|> + 20:57 [视频-长播] <|video_begin|> + 21:10 [视频-长播] <|video_begin|> + 21:10 [视频-长播] <|video_begin|> + 21:13 [视频-长播] <|video_begin|> + 21:20 [视频-长播] <|video_begin|> +【2026-02-02】 + 00:48 [视频-长播] <|video_begin|> + 00:48 [视频-长播] <|video_begin|> + 00:48 [视频-长播] <|video_begin|> + 07:43 [广告-点击] <|ad_begin|> + 20:56 [广告-深度转化] <|ad_begin|> + 20:56 [广告-点击] <|ad_begin|> + 23:07 [视频-长播] <|video_begin|> + 23:07 [视频-关注/长播] <|video_begin|> + 23:09 [广告-点击] <|ad_begin|> + 23:20 [广告-深度转化] <|ad_begin|> + 23:20 [广告-点击] <|ad_begin|> +【2026-02-03】 + --:-- [商品-点击] <|prod_begin|> + 10:27 [视频-长播] <|video_begin|> + 10:27 [视频-长播] <|video_begin|> + 10:50 [视频-长播] <|video_begin|> + 12:11 [广告-深度转化] <|ad_begin|> + 12:11 [广告-点击] <|ad_begin|> + 13:09 [视频-长播] <|video_begin|> + 13:09 [视频-收藏/长播] <|video_begin|> + 13:36 [广告-深度转化] <|ad_begin|> + 13:36 [广告-点击] <|ad_begin|> + 22:00 [广告-深度转化] <|ad_begin|> + 22:00 [广告-点击] <|ad_begin|> +【2026-02-04】 + 07:09 [广告-点击] <|ad_begin|> + 07:15 [广告-深度转化] <|ad_begin|> + 07:15 [广告-点击] <|ad_begin|> + 07:33 [视频-长播] <|video_begin|> + 07:43 [广告-深度转化] <|ad_begin|> + 07:43 [广告-点击] <|ad_begin|> + 21:12 [广告-深度转化] <|ad_begin|> + 21:12 [广告-点击] <|ad_begin|> +【2026-02-05】 + 00:07 [广告-深度转化] <|ad_begin|> + 00:07 [广告-点击] <|ad_begin|> + 00:42 [视频-长播] <|video_begin|> + 00:45 [视频-长播] <|video_begin|> + 00:45 [视频-长播] <|video_begin|> + 00:46 [视频-长播] <|video_begin|> + 00:48 [视频-长播] <|video_begin|> + 00:48 [视频-长播] <|video_begin|> + 00:48 [视频-长播] <|video_begin|> + 00:54 [视频-长播] <|video_begin|> + 01:00 [广告-深度转化] <|ad_begin|> + 01:00 [广告-点击] <|ad_begin|> + 07:05 [视频-长播] <|video_begin|> + 07:11 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_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：从被动接收到主动决策的二手车置换意图演化 + +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 +["<|ad_begin|>","<|video_begin|>","<|living_begin|>"]<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-01-09】 + --:-- [直播-关注] <|living_begin|> +【2025-01-22】 + --:-- [直播-关注] <|living_begin|> +【2025-02-17】 + --:-- [直播-关注] <|living_begin|> +【2025-04-13】 + --:-- [直播-关注] <|living_begin|> +【2025-04-28】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-05-10】 + --:-- [直播-关注] <|living_begin|> +【2025-06-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-29】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-13】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-09】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-10】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-27】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-30】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-25】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-19】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-24】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-01】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-02】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-03】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-05】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-16】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-17】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-19】 + --:-- [商品-购买] <|prod_begin|> +【2026-01-21】 + 05:48 [广告-深度转化] <|ad_begin|> + 08:19 [广告-深度转化] <|ad_begin|> + 08:43 [广告-深度转化] <|ad_begin|> + 10:10 [广告-深度转化] <|ad_begin|> + 10:49 [广告-深度转化] <|ad_begin|> + 11:33 [广告-深度转化] <|ad_begin|> + 11:38 [广告-深度转化] <|ad_begin|> + 12:06 [广告-深度转化] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 14:17 [广告-深度转化] <|ad_begin|> + 14:55 [广告-深度转化] <|ad_begin|> +【2026-01-22】 + 01:57 [广告-深度转化] <|ad_begin|> + 03:18 [广告-深度转化] <|ad_begin|> + 06:37 [广告-深度转化] <|ad_begin|> + 09:01 [视频-评论/点赞/长播] <|video_begin|> + 09:15 [广告-深度转化] <|ad_begin|> + 10:50 [广告-点击] <|ad_begin|> + 11:00 [广告-深度转化] <|ad_begin|> + 11:00 [广告-点击] <|ad_begin|> + 13:25 [视频-评论/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-23】 + 02:57 [广告-深度转化] <|ad_begin|> + 02:57 [广告-点击] <|ad_begin|> + 03:52 [广告-深度转化] <|ad_begin|> + 03:52 [广告-点击] <|ad_begin|> + 04:17 [广告-深度转化] <|ad_begin|> + 04:17 [广告-点击] <|ad_begin|> + 05:07 [广告-点击] <|ad_begin|> + 05:59 [广告-深度转化] <|ad_begin|> + 05:59 [广告-点击] <|ad_begin|> + 09:06 [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-购买] <|prod_begin|> +【2026-01-24】 + 01:16 [广告-深度转化] <|ad_begin|> + 01:16 [广告-点击] <|ad_begin|> + 02:51 [视频-点赞/长播] <|video_begin|> + 03:01 [广告-深度转化] <|ad_begin|> + 03:01 [广告-点击] <|ad_begin|> + 04:10 [视频-点赞/长播] <|video_begin|> + 04:49 [视频-浏览] <|video_begin|> + 05:21 [视频-评论/点赞/长播] <|video_begin|> + 05:28 [广告-深度转化] <|ad_begin|> + 05:28 [广告-点击] <|ad_begin|> + 05:44 [视频-评论/长播] <|video_begin|> + 06:15 [广告-深度转化] <|ad_begin|> + 06:15 [广告-点击] <|ad_begin|> + 07:54 [广告-点击] <|ad_begin|> + 08:27 [广告-深度转化] <|ad_begin|> + 08:27 [广告-点击] <|ad_begin|> + 09:07 [广告-点击] <|ad_begin|> + 09:30 [广告-深度转化] <|ad_begin|> + 09:30 [广告-点击] <|ad_begin|> + 09:42 [视频-评论/点赞/长播] <|video_begin|> + 09:53 [广告-深度转化] <|ad_begin|> + 09:53 [广告-点击] <|ad_begin|> + 11:15 [视频-浏览] <|video_begin|> + 12:31 [广告-深度转化] <|ad_begin|> + 12:31 [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|> +【2026-01-25】 + 01:27 [广告-点击] <|ad_begin|> + 02:40 [广告-深度转化] <|ad_begin|> + 02:40 [广告-点击] <|ad_begin|> + 03:07 [视频-点赞/长播] <|video_begin|> + 03:33 [广告-点击] <|ad_begin|> + 03:40 [广告-深度转化] <|ad_begin|> + 03:40 [广告-点击] <|ad_begin|> + 03:46 [广告-深度转化] <|ad_begin|> + 03:46 [广告-点击] <|ad_begin|> + 04:31 [广告-深度转化] <|ad_begin|> + 04:31 [广告-点击] <|ad_begin|> + 05:00 [广告-深度转化] <|ad_begin|> + 05:00 [广告-点击] <|ad_begin|> + 10:02 [视频-评论/点赞/长播] <|video_begin|> + 10:24 [广告-点击] <|ad_begin|> + 11:00 [视频-评论/长播] <|video_begin|> + 11:13 [广告-深度转化] <|ad_begin|> + 11:13 [广告-点击] <|ad_begin|> + 13:27 [视频-点赞/长播] <|video_begin|> + 22:01 [广告-深度转化] <|ad_begin|> + 22:01 [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-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 23:37 [广告-深度转化] <|ad_begin|> + 23:37 [广告-点击] <|ad_begin|> +【2026-01-26】 + 01:59 [广告-深度转化] <|ad_begin|> + 01:59 [广告-点击] <|ad_begin|> + 03:31 [广告-深度转化] <|ad_begin|> + 03:31 [广告-点击] <|ad_begin|> + 13:55 [视频-评论/点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-27】 + 00:36 [视频-点赞/长播] <|video_begin|> + 00:39 [广告-点击] <|ad_begin|> + 00:50 [广告-深度转化] <|ad_begin|> + 00:50 [广告-点击] <|ad_begin|> + 01:50 [视频-点赞/长播] <|video_begin|> + 02:05 [视频-评论/点赞/长播] <|video_begin|> + 02:16 [广告-深度转化] <|ad_begin|> + 02:16 [广告-点击] <|ad_begin|> + 02:52 [视频-点赞/长播] <|video_begin|> + 03:21 [广告-深度转化] <|ad_begin|> + 03:21 [广告-点击] <|ad_begin|> + 07:58 [广告-深度转化] <|ad_begin|> + 07:58 [广告-点击] <|ad_begin|> + 09:01 [广告-点击] <|ad_begin|> + 09:07 [视频-评论/点赞/长播] <|video_begin|> + 09:40 [广告-深度转化] <|ad_begin|> + 09:40 [广告-点击] <|ad_begin|> + 10:02 [广告-深度转化] <|ad_begin|> + 10:02 [广告-点击] <|ad_begin|> + 11:07 [广告-深度转化] <|ad_begin|> + 11:07 [广告-点击] <|ad_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|> +【2026-01-29】 + 03:14 [广告-深度转化] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> +【2026-01-30】 + 04:09 [广告-深度转化] <|ad_begin|> + 04:09 [广告-点击] <|ad_begin|> + 04:54 [广告-点击] <|ad_begin|> + 05:16 [广告-深度转化] <|ad_begin|> + 05:16 [广告-点击] <|ad_begin|> + 06:19 [视频-收藏/长播] <|video_begin|> + 08:03 [视频-评论/长播] <|video_begin|> + 08:09 [视频-评论/点赞/长播] <|video_begin|> + 09:12 [视频-浏览] <|video_begin|> + 09:16 [视频-浏览] <|video_begin|> + 09:40 [视频-关注/评论/点赞/长播] <|video_begin|> + 10:13 [视频-点赞/长播] <|video_begin|> + 10:55 [视频-评论/点赞/长播] <|video_begin|> + 11:07 [视频-点赞/长播] <|video_begin|> +【2026-01-31】 + 05:27 [视频-评论/点赞/长播] <|video_begin|> + 05:40 [广告-深度转化] <|ad_begin|> + 05:40 [广告-点击] <|ad_begin|> + 07:49 [视频-点赞/长播] <|video_begin|> + 07:59 [广告-深度转化] <|ad_begin|> + 07:59 [广告-点击] <|ad_begin|> + 09:25 [广告-深度转化] <|ad_begin|> + 09:25 [广告-点击] <|ad_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|> +【2026-02-01】 + 04:57 [广告-深度转化] <|ad_begin|> + 04:57 [广告-点击] <|ad_begin|> + 06:47 [广告-深度转化] <|ad_begin|> + 06:47 [广告-点击] <|ad_begin|> + 07:11 [广告-点击] <|ad_begin|> + 09:08 [视频-点赞/长播] <|video_begin|> + 09:57 [广告-深度转化] <|ad_begin|> + 09:57 [广告-点击] <|ad_begin|> + 09:59 [视频-关注/长播] <|video_begin|> + 23:07 [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-购买] <|prod_begin|> +【2026-02-02】 + 00:06 [广告-深度转化] <|ad_begin|> + 00:06 [广告-点击] <|ad_begin|> + 00:58 [广告-深度转化] <|ad_begin|> + 00:58 [广告-点击] <|ad_begin|> + 03:41 [广告-深度转化] <|ad_begin|> + 03:41 [广告-点击] <|ad_begin|> + 05:35 [广告-深度转化] <|ad_begin|> + 05:35 [广告-点击] <|ad_begin|> + 06:24 [视频-评论/长播] <|video_begin|> + 06:28 [视频-评论/长播] <|video_begin|> + 08:13 [广告-点击] <|ad_begin|> + 09:05 [视频-点赞/长播] <|video_begin|> + 11:02 [广告-深度转化] <|ad_begin|> + 11:02 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 23:40 [广告-点击] <|ad_begin|> + 23:54 [广告-深度转化] <|ad_begin|> + 23:54 [广告-点击] <|ad_begin|> +【2026-02-03】 + 03:44 [广告-点击] <|ad_begin|> + 06:49 [视频-评论/长播] <|video_begin|> + 07:32 [广告-深度转化] <|ad_begin|> + 07:32 [广告-点击] <|ad_begin|> + 08:25 [广告-深度转化] <|ad_begin|> + 08:25 [广告-点击] <|ad_begin|> +【2026-02-04】 + 00:10 [广告-深度转化] <|ad_begin|> + 00:10 [广告-点击] <|ad_begin|> + 01:24 [视频-评论/点赞/长播] <|video_begin|> + 02:22 [视频-浏览] <|video_begin|> + 07:54 [广告-深度转化] <|ad_begin|> + 07:54 [广告-点击] <|ad_begin|> + 10:33 [视频-浏览] <|video_begin|> + 11:13 [广告-深度转化] <|ad_begin|> + 11:13 [广告-点击] <|ad_begin|> + 13:26 [广告-深度转化] <|ad_begin|> + 13:26 [广告-点击] <|ad_begin|> + 23:23 [广告-深度转化] <|ad_begin|> + 23:23 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-02-05】 + 04:46 [广告-深度转化] <|ad_begin|> + 04:46 [广告-点击] <|ad_begin|> + 06:00 [视频-长播] <|video_begin|> + 06:00 [视频-长播] <|video_begin|> + 06:00 [视频-长播] <|video_begin|> + 06:57 [视频-长播] <|video_begin|> + 06:57 [视频-长播] <|video_begin|> + 06:58 [视频-长播] <|video_begin|> + 06:58 [视频-长播] <|video_begin|> + 06:58 [视频-长播] <|video_begin|> + 07:20 [广告-深度转化] <|ad_begin|> + 07:20 [广告-点击] <|ad_begin|> + 08:38 [视频-长播] <|video_begin|> + 08:38 [视频-长播] <|video_begin|> + 08:38 [视频-长播] <|video_begin|> + 08:38 [视频-长播] <|video_begin|> + 08:40 [视频-长播] <|video_begin|> + 08:46 [视频-长播] <|video_begin|> + 10:11 [广告-深度转化] <|ad_begin|> + 10:11 [广告-点击] <|ad_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:23 [视频-长播] <|video_begin|> + 10:26 [视频-长播] <|video_begin|> + 10:26 [视频-长播] <|video_begin|> + 10:26 [视频-长播] <|video_begin|> + 10:28 [视频-长播] <|video_begin|> + 10:33 [视频-长播] <|video_begin|> + 10:33 [视频-长播] <|video_begin|> + 10:33 [视频-长播] <|video_begin|> + 10:54 [视频-长播] <|video_begin|> + 10:54 [视频-长播] <|video_begin|> + 10:55 [视频-长播] <|video_begin|> + 10:55 [视频-长播] <|video_begin|> + 11:00 [视频-长播] <|video_begin|> + 11:00 [视频-长播] <|video_begin|> + 11:00 [视频-长播] <|video_begin|> + 11:12 [视频-长播] <|video_begin|> + 11:12 [视频-长播] <|video_begin|> + 11:14 [视频-长播] <|video_begin|> + 11:20 [视频-长播] <|video_begin|> + 11:20 [视频-长播] <|video_begin|> + 11:26 [视频-长播] <|video_begin|> + 11:50 [视频-长播] <|video_begin|> + 11:53 [视频-长播] <|video_begin|> + 11:53 [视频-长播] <|video_begin|> + 11:53 [视频-长播] <|video_begin|> + 11:53 [视频-长播] <|video_begin|> + 12:03 [视频-长播] <|video_begin|> + 12:03 [视频-长播] <|video_begin|> + 12:03 [视频-长播] <|video_begin|> + 12:03 [视频-长播] <|video_begin|> + 12:08 [视频-长播] <|video_begin|> + 12:08 [视频-长播] <|video_begin|> + 12:09 [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 +核心提取逻辑 (递进性准则)： +按时间顺序提取 5 步以内的行为链，要求后项交互B必须是前项交互A的场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是因为 A 才产生的延伸需求，严禁提取任何品类平级、内容重复或仅因天气/促销产生的凑单并列行为。 +1.场景驱动协同：交互 B 与交互 A 必须同属一个生活场景及主题类目，并呈现极强的需求补完性。 +2.兴趣因果递进：交互 B 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 的需求必须比交互 A 更具体、更细化，但不包括重复出现的购买、点击、搜索等行为，避免节点内容重复。 +请针对以下主题提取行为逻辑链： +主题：从泛化健康监测到聚焦特定功能产品的需求收敛 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化健康监测到聚焦特定功能产品的需求收敛", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/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":"从泛化健康监测到聚焦特定功能产品的需求收敛","events":[{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"初步探索：用户对“腕式血压仪”产生兴趣，开始点击浏览不同款式的同类产品，处于需求探索的泛化阶段。"},{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"同类对比：继续点击另一款腕式血压仪，表明用户仍在对基础的血压监测功能进行横向比较和筛选。"},{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"认知跃迁与需求聚焦：用户的关注点从单一的“血压”监测，跃迁至包含“无创血糖、尿酸、血脂”等多维监测功能的智能手表。这引入了全新的、更专业的健康监测变量，是典型的从发散到聚焦的认知收敛过程。"},{"date":"2026-01-25","action":"[商品-购买] <|prod_begin|>","logic":"决策落地：尽管探索了更高级的产品，但最终购买了基础款血压仪，可能基于价格、即时性或对新技术的不确定性等因素。然而，这不影响前序行为链所体现的认知升级过程，反而构成了“探索-评估-决策”的完整闭环。"}]}}<|im_end|> +<|im_start|>user +你是一位推荐系统分析助手，请阅读用户历史行为，并给出直播、电商、视频、广告场景的目标内容。 +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|>，首次打赏了 <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|>，对主播 <|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|>, <|living_begin|>, <|living_begin|> 有过关注/首次打赏行为，给主播 <|living_begin|>, <|living_begin|>, <|living_begin|>, <|living_begin|> 打赏过，对主播 <|living_begin|> 有过关注/打赏行为。 +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|> 有过收藏/长播行为，对视频 <|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|> 有过点赞/长播行为，对视频 <|video_begin|>, <|video_begin|>, <|video_begin|>, <|video_begin|> 有过转发/长播行为，对视频 <|video_begin|>, <|video_begin|>, <|video_begin|>, <|video_begin|>, <|video_begin|> 有过评论/长播行为，看过视频 <|video_begin|>, <|video_begin|>, <|video_begin|>，对视频 <|video_begin|> 有过评论/点赞/长播行为。 + +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 +好的，作为推荐系统分析助手，我将根据您提供的用户多域历史行为进行分析。 + +【兴趣归纳】： +根据用户的交互历史，可以归纳出以下核心兴趣类目： +1. **射击类游戏(以《和平精英》为主)**：这是用户当前最核心且活跃的兴趣。从2025年10月起，用户行为显著转向此类游戏，在直播域有多次关注与打赏行为如<|living_begin|>、<|living_begin|>，在视频域有更高频的点赞、收藏、评论等深度交互如<|video_begin|>、<|video_begin|>，并有多次主动搜索行为，表现出极高的粘性。 +2. **MOBA类游戏(以《王者荣耀》为主)**：这是用户的早期核心兴趣。在2025年6月至9月期间，用户的交互行为几乎全部集中于此，有大量的关注和首次打赏记录如<|living_begin|>、<|living_begin|>，显示出强烈的初始偏好。尽管近期交互减少，但仍是其重要的兴趣组成部分。 +3. **虚拟形象与外观美化**：该兴趣贯穿多个领域。用户对二次元、虚拟主播如<|living_begin|>、不露脸的游戏角色形象表现出持续关注和付费意愿。近期在视频域对假发、时尚穿搭如<|video_begin|>的集中浏览和收藏，以及多次对头像的搜索行为，表明其对虚拟及现实世界的个性化外观有浓厚兴趣。 +4. **情感与社交内容**：用户对情感共鸣类内容有稳定偏好。体现在对情感向主播的打赏如、对情感故事视频的转发<|video_begin|>，以及对情感状态、音乐和社交关系相关主题的搜索行为上。 + +【行为模式】： +用户的消费偏好明确，表现为在直播场景中有较高的付费意愿，对能提供陪伴感、互动性或高超技术的游戏主播(无论是否露脸)均有多次打赏行为。用户的行为模式呈现出明显的兴趣迁移路径，从MOBA游戏逐渐过渡到射击类游戏，并在后者上表现出更深度的内容消费(从看直播到主动搜索、观看教学视频)。 +跨域协同信号十分清晰：1)**搜索驱动消费**：用户会主动搜索游戏攻略、新版本内容，随后在视频域消费相关教学或展示视频。2)**兴趣泛化**：对游戏角色的喜爱延伸至对虚拟形象、二次元主播的关注，并进一步泛化到对现实中美妆、穿搭、头像等外观美化内容的探索。3)**内容主题一致性**：在游戏兴趣的主线下，用户同样关注游戏内的情侣互动、社交故事等情感化内容，与其在视频域消费情感类内容的行为形成呼应。 + +【预测总结】： +综合分析，用户接下来最可能感兴趣的内容有以下几类： +1. **《和平精英》相关深度内容**：鉴于这是用户当前最活跃的兴趣点，推送关于新赛季玩法解析、特定枪械或道具的进阶教学、游戏内浪漫打卡点或情侣互动故事等视频，有较大几率会获得用户的点击和深度交互。 +2. **虚拟形象与时尚穿搭**：用户近期对虚拟形象和外观美化的兴趣显著提升，可能会对二次元风格的虚拟主播直播、游戏角色的新皮肤展示、以及与“萌妹”、“甜妹”风格相关的时尚假发或穿搭推荐视频产生兴趣。 +3. **情感共鸣类音乐或短剧**：基于用户对情感内容的持续关注和相关搜索行为，一些带有伤感或治愈氛围的音乐分享、情感故事短视频或关于社交关系的探讨，或许能有效吸引其注意力。 +该用户最近喜欢的视频有: <|video_begin|><|im_end|> +<|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|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, 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<|living_begin|>","logic":"认知深化与聚焦：在“极速版教学”的基础上，兴趣点进一步细化到“活跃值运营”、“标签转化”、“平台规则解读”等更深层次的运营技巧，表明用户已不满足于基础操作，开始探索更高阶的玩法和规则。"}]}}<|im_end|> +["<|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|>","<|living_begin|>","<|prod_begin|>","<|living_begin|>","<|ad_begin|>","<|ad_begin|>","<|ad_begin|>"]<|im_end|> +["<|ad_begin|>","<|video_begin|>","<|living_begin|>"]<|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":"从泛化健康监测到聚焦特定功能产品的需求收敛","events":[{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"初步探索：用户对“腕式血压仪”产生兴趣，开始点击浏览不同款式的同类产品，处于需求探索的泛化阶段。"},{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"同类对比：继续点击另一款腕式血压仪，表明用户仍在对基础的血压监测功能进行横向比较和筛选。"},{"date":"2026-01-25","action":"[商品-点击] <|prod_begin|>","logic":"认知跃迁与需求聚焦：用户的关注点从单一的“血压”监测，跃迁至包含“无创血糖、尿酸、血脂”等多维监测功能的智能手表。这引入了全新的、更专业的健康监测变量，是典型的从发散到聚焦的认知收敛过程。"},{"date":"2026-01-25","action":"[商品-购买] <|prod_begin|>","logic":"决策落地：尽管探索了更高级的产品，但最终购买了基础款血压仪，可能基于价格、即时性或对新技术的不确定性等因素。然而，这不影响前序行为链所体现的认知升级过程，反而构成了“探索-评估-决策”的完整闭环。"}]}}<|im_end|> +好的，作为推荐系统分析助手，我将根据您提供的用户多域历史行为进行分析。 + +【兴趣归纳】： +根据用户的交互历史，可以归纳出以下核心兴趣类目： +1. **射击类游戏(以《和平精英》为主)**：这是用户当前最核心且活跃的兴趣。从2025年10月起，用户行为显著转向此类游戏，在直播域有多次关注与打赏行为如<|living_begin|>、<|living_begin|>，在视频域有更高频的点赞、收藏、评论等深度交互如<|video_begin|>、<|video_begin|>，并有多次主动搜索行为，表现出极高的粘性。 +2. **MOBA类游戏(以《王者荣耀》为主)**：这是用户的早期核心兴趣。在2025年6月至9月期间，用户的交互行为几乎全部集中于此，有大量的关注和首次打赏记录如<|living_begin|>、<|living_begin|>，显示出强烈的初始偏好。尽管近期交互减少，但仍是其重要的兴趣组成部分。 +3. **虚拟形象与外观美化**：该兴趣贯穿多个领域。用户对二次元、虚拟主播如<|living_begin|>、不露脸的游戏角色形象表现出持续关注和付费意愿。近期在视频域对假发、时尚穿搭如<|video_begin|>的集中浏览和收藏，以及多次对头像的搜索行为，表明其对虚拟及现实世界的个性化外观有浓厚兴趣。 +4. **情感与社交内容**：用户对情感共鸣类内容有稳定偏好。体现在对情感向主播的打赏如、对情感故事视频的转发<|video_begin|>，以及对情感状态、音乐和社交关系相关主题的搜索行为上。 + +【行为模式】： +用户的消费偏好明确，表现为在直播场景中有较高的付费意愿，对能提供陪伴感、互动性或高超技术的游戏主播(无论是否露脸)均有多次打赏行为。用户的行为模式呈现出明显的兴趣迁移路径，从MOBA游戏逐渐过渡到射击类游戏，并在后者上表现出更深度的内容消费(从看直播到主动搜索、观看教学视频)。 +跨域协同信号十分清晰：1)**搜索驱动消费**：用户会主动搜索游戏攻略、新版本内容，随后在视频域消费相关教学或展示视频。2)**兴趣泛化**：对游戏角色的喜爱延伸至对虚拟形象、二次元主播的关注，并进一步泛化到对现实中美妆、穿搭、头像等外观美化内容的探索。3)**内容主题一致性**：在游戏兴趣的主线下，用户同样关注游戏内的情侣互动、社交故事等情感化内容，与其在视频域消费情感类内容的行为形成呼应。 + +【预测总结】： +综合分析，用户接下来最可能感兴趣的内容有以下几类： +1. **《和平精英》相关深度内容**：鉴于这是用户当前最活跃的兴趣点，推送关于新赛季玩法解析、特定枪械或道具的进阶教学、游戏内浪漫打卡点或情侣互动故事等视频，有较大几率会获得用户的点击和深度交互。 +2. **虚拟形象与时尚穿搭**：用户近期对虚拟形象和外观美化的兴趣显著提升，可能会对二次元风格的虚拟主播直播、游戏角色的新皮肤展示、以及与“萌妹”、“甜妹”风格相关的时尚假发或穿搭推荐视频产生兴趣。 +3. **情感共鸣类音乐或短剧**：基于用户对情感内容的持续关注和相关搜索行为，一些带有伤感或治愈氛围的音乐分享、情感故事短视频或关于社交关系的探讨，或许能有效吸引其注意力。 +该用户最近喜欢的视频有: <|video_begin|><|im_end|> + +[INFO|configuration_utils.py:769] 2026-07-15 05:36:53,012 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/config.json +[INFO|configuration_utils.py:847] 2026-07-15 05:36:53,013 >> 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|2026-07-15 05:36:53] llamafactory.model.model_utils.kv_cache:144 >> KV cache is disabled during training. +[INFO|2026-07-15 05:36:53] llamafactory.model.model_utils.liger_kernel:144 >> Liger kernel has been applied to the model. +[INFO|modeling_utils.py:748] 2026-07-15 05:36:53,336 >> loading weights file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/model.safetensors +[INFO|modeling_utils.py:821] 2026-07-15 05:36:53,336 >> Will use dtype=torch.bfloat16 as defined in model's config object +[INFO|configuration_utils.py:1027] 2026-07-15 05:36:53,481 >> Generate config GenerationConfig { + "eos_token_id": 151645, + "output_attentions": false, + "output_hidden_states": false, + "pad_token_id": 151643, + "use_cache": false +} + + Loading weights: 0%| | 0/311 [00:00> loading configuration file /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018/generation_config.json +[INFO|configuration_utils.py:1027] 2026-07-15 05:36:53,782 >> 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] 2026-07-15 05:36:53,782 >> Could not locate the custom_generate/generate.py inside /home/ll/llm4rec/experiments/outputs/v29_v19_user_world_guard_lr8e7_ep018. +[INFO|2026-07-15 05:36:53] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled. +[INFO|2026-07-15 05:36:53] llamafactory.model.model_utils.attention:144 >> Using FlashAttention-2 for faster training and inference. +[INFO|2026-07-15 05:36:53] llamafactory.model.adapter:144 >> Pure bf16 / BAdam detected, remaining trainable params in half precision. +[INFO|2026-07-15 05:36:53] llamafactory.model.adapter:144 >> Fine-tuning method: Full +[INFO|2026-07-15 05:36:53] llamafactory.model.loader:144 >> trainable params: 801,433,600 || all params: 801,433,600 || trainable%: 100.0000 +[INFO|trainer.py:1469] 2026-07-15 05:36:53,908 >> ***** Running training ***** +[INFO|trainer.py:1470] 2026-07-15 05:36:53,908 >> Num examples = 2,611 +[INFO|trainer.py:1471] 2026-07-15 05:36:53,909 >> Num Epochs = 1 +[INFO|trainer.py:1472] 2026-07-15 05:36:53,909 >> Num update steps per epoch = 653 +[INFO|trainer.py:1473] 2026-07-15 05:36:53,909 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:1476] 2026-07-15 05:36:53,909 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:1477] 2026-07-15 05:36:53,909 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:1478] 2026-07-15 05:36:53,909 >> Total optimization steps = 653 +[INFO|trainer.py:1479] 2026-07-15 05:36:53,909 >> Number of trainable parameters = 801,433,600 + 0%| | 0/653 [00:00> `use_return_dict` is deprecated! 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Do not forget to share your model on huggingface.co/models =) + + + {'train_runtime': '5405', 'train_samples_per_second': '0.483', 'train_steps_per_second': '0.121', 'train_loss': '1.907', 'epoch': '1'} + 100%|██████████| 653/653 [1:30:05<00:00, 7.37s/it] 100%|██████████| 653/653 [1:30:05<00:00, 8.28s/it] +[INFO|trainer.py:3815] 2026-07-15 07:06:59,242 >> Saving model checkpoint to /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10 +[INFO|configuration_utils.py:533] 2026-07-15 07:06:59,244 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/config.json +[INFO|configuration_utils.py:816] 2026-07-15 07:06:59,244 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/generation_config.json + Writing model shards: 0%| | 0/1 [00:00> Model weights saved in /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/model.safetensors +[INFO|tokenization_utils_base.py:3278] 2026-07-15 07:07:00,208 >> chat template saved in /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/chat_template.jinja +[INFO|tokenization_utils_base.py:2111] 2026-07-15 07:07:00,231 >> tokenizer config file saved in /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/tokenizer_config.json +***** train metrics ***** + epoch = 1.0 + total_flos = 292790139GF + train_loss = 1.907 + train_runtime = 1:30:05.33 + train_samples_per_second = 0.483 + train_steps_per_second = 0.121 +Figure saved at: /home/ll/llm4rec/experiments/outputs/v42_v29_user_evolution_guard_lr5e7_ep10/training_loss.png +[WARNING|2026-07-15 07:07:00] llamafactory.extras.ploting:149 >> No metric eval_loss to plot. +[WARNING|2026-07-15 07:07:00] llamafactory.extras.ploting:149 >> No metric eval_accuracy to plot. +[INFO|modelcard.py:263] 2026-07-15 07:07:00,456 >> Dropping the following result as it does not have all the necessary fields: +{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}} diff --git a/train_results.json b/train_results.json new file mode 100644 index 0000000..aa2c62f --- /dev/null +++ b/train_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 1.0, + "total_flos": 3.143810179830989e+17, + "train_loss": 1.9069785443783536, + "train_runtime": 5405.3324, + "train_samples_per_second": 0.483, + "train_steps_per_second": 0.121 +} \ No newline at end of file diff --git a/trainer_log.jsonl b/trainer_log.jsonl new file mode 100644 index 0000000..d9e0046 --- /dev/null +++ b/trainer_log.jsonl @@ -0,0 +1,66 @@ +{"current_steps": 10, "total_steps": 653, "loss": 1.8881567001342774, "lr": 2.25e-07, "epoch": 0.015319800842589047, "percentage": 1.53, "elapsed_time": "0:01:21", "remaining_time": "1:27:47"} +{"current_steps": 20, "total_steps": 653, "loss": 2.0835521697998045, "lr": 4.7499999999999995e-07, "epoch": 0.030639601685178094, "percentage": 3.06, "elapsed_time": "0:02:42", 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