{ "add_bos_token": false, "add_prefix_space": false, "added_tokens_decoder": { "151643": { "content": "<|endoftext|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151644": { "content": "<|im_start|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151645": { "content": "<|im_end|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151646": { "content": "<|object_ref_start|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151647": { "content": "<|object_ref_end|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151648": { "content": "<|box_start|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151649": { "content": "<|box_end|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151650": { "content": "<|quad_start|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151651": { "content": "<|quad_end|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151652": { "content": "<|vision_start|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151653": { "content": "<|vision_end|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151654": { "content": "<|vision_pad|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151655": { "content": "<|image_pad|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151656": { "content": "<|video_pad|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true }, "151657": { "content": "", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151658": { "content": "", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151659": { "content": "<|fim_prefix|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151660": { "content": "<|fim_middle|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151661": { "content": "<|fim_suffix|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151662": { "content": "<|fim_pad|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151663": { "content": "<|repo_name|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151664": { "content": "<|file_sep|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": false }, "151665": { "content": "<|PAD_TOKEN|>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true } }, "additional_special_tokens": [ "<|im_start|>", "<|im_end|>", "<|object_ref_start|>", "<|object_ref_end|>", "<|box_start|>", "<|box_end|>", "<|quad_start|>", "<|quad_end|>", "<|vision_start|>", "<|vision_end|>", "<|vision_pad|>", "<|image_pad|>", "<|video_pad|>" ], "bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a Python expert.\nReturn ONLY the function implementation with no additional text or explanations.\n\nHere are some examples:\n\nex.1\n\n\nquery:\nwrite a function def analyze_nested_json(data, key_paths, value_types) to:\nAnalyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n\nThe function should output with:\ndict: A dictionary mapping types to lists of extracted values.\n\nYou should start with:\n\\`\\`\\`\nimport json\nimport defaultdict\nimport chain\nimport pandas as pd\nimport numpy as np\ndef analyze_nested_json(data, key_paths, value_types) \\`\\`\\`\n\n\nresponse:\nimport json\nfrom collections import defaultdict\nfrom itertools import chain\nimport pandas as pd\nimport numpy as np\n\ndef analyze_nested_json(data, key_paths, value_types):\n \"\"\"\n Analyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n \n Parameters:\n - data (dict): A nested JSON data structure.\n - key_paths (List[str]): Paths to keys in the JSON structure.\n - value_types (List[type]): Types to categorize the extracted values.\n \n Requirements:\n - json\n - collections\n - itertools\n - pandas\n - numpy\n \n Example:\n >>> data = {\n ... \"root\": {\n ... \"child1\": {\"name\": \"Alice\", \"age\": 30, \"is_student\": False},\n ... \"child2\": {\"name\": \"Bob\", \"age\": 25, \"is_student\": True},\n ... \"child3\": {\"name\": \"Charlie\", \"age\": 35, \"is_student\": False},\n ... \"child4\": {\"name\": \"David\", \"age\": 22, \"is_student\": True}\n ... }\n ... }\n >>> key_paths = [\"root.child1.age\", \"root.child2.is_student\", \"root.child3.name\"]\n >>> value_types = [int, bool, str]\n >>> result = analyze_nested_json(data, key_paths, value_types)\n >>> print(result)\n {\n \\'int\\': [30, 25, 35, 22],\n \\'bool\\': [False, True, False, True],\n \\'str\\': [\\'Alice\\', \\'Bob\\', \\'Charlie\\', \\'David\\']\n }\n \n Returns:\n dict: A dictionary mapping types to lists of extracted values.\n \"\"\"\n \n def get_value_from_path(data, path):\n keys = path.split(\\'.\\')\n value = data\n for key in keys:\n value = value.get(key)\n if value is None:\n return None\n return value\n \n categorized_values = defaultdict(list)\n \n for key_path, value_type in zip(key_paths, value_types):\n value = get_value_from_path(data, key_path)\n if isinstance(value, value_type):\n categorized_values[str(value_type)].append(value)\n \n return dict(categorized_values)\n\n' }}\n {%- endif %}\n {{- \"\\n\\n# 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\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a Python expert.\nReturn ONLY the function implementation with no additional text or explanations.\n\nHere are some examples:\n\nex.1\n\n\nquery:\nwrite a function def analyze_nested_json(data, key_paths, value_types) to:\nAnalyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n\nThe function should output with:\ndict: A dictionary mapping types to lists of extracted values.\n\nYou should start with:\n\\`\\`\\`\nimport json\nimport defaultdict\nimport chain\nimport pandas as pd\nimport numpy as np\ndef analyze_nested_json(data, key_paths, value_types) \\`\\`\\`\n\n\nresponse:\nimport json\nfrom collections import defaultdict\nfrom itertools import chain\nimport pandas as pd\nimport numpy as np\n\ndef analyze_nested_json(data, key_paths, value_types):\n \"\"\"\n Analyzes a nested JSON structure to extract values at specified keys and categorize them based on their types.\n \n Parameters:\n - data (dict): A nested JSON data structure.\n - key_paths (List[str]): Paths to keys in the JSON structure.\n - value_types (List[type]): Types to categorize the extracted values.\n \n Requirements:\n - json\n - collections\n - itertools\n - pandas\n - numpy\n \n Example:\n >>> data = {\n ... \"root\": {\n ... \"child1\": {\"name\": \"Alice\", \"age\": 30, \"is_student\": False},\n ... \"child2\": {\"name\": \"Bob\", \"age\": 25, \"is_student\": True},\n ... \"child3\": {\"name\": \"Charlie\", \"age\": 35, \"is_student\": False},\n ... \"child4\": {\"name\": \"David\", \"age\": 22, \"is_student\": True}\n ... }\n ... }\n >>> key_paths = [\"root.child1.age\", \"root.child2.is_student\", \"root.child3.name\"]\n >>> value_types = [int, bool, str]\n >>> result = analyze_nested_json(data, key_paths, value_types)\n >>> print(result)\n {\n \\'int\\': [30, 25, 35, 22],\n \\'bool\\': [False, True, False, True],\n \\'str\\': [\\'Alice\\', \\'Bob\\', \\'Charlie\\', \\'David\\']\n }\n \n Returns:\n dict: A dictionary mapping types to lists of extracted values.\n \"\"\"\n \n def get_value_from_path(data, path):\n keys = path.split(\\'.\\')\n value = data\n for key in keys:\n value = value.get(key)\n if value is None:\n return None\n return value\n \n categorized_values = defaultdict(list)\n \n for key_path, value_type in zip(key_paths, value_types):\n value = get_value_from_path(data, key_path)\n if isinstance(value, value_type):\n categorized_values[str(value_type)].append(value)\n \n return dict(categorized_values)\n\n<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n", "clean_up_tokenization_spaces": false, "eos_token": "<|im_end|>", "errors": "replace", "extra_special_tokens": {}, "model_max_length": 131072, "pad_token": "<|PAD_TOKEN|>", "padding_side": "left", "split_special_tokens": false, "tokenizer_class": "Qwen2Tokenizer", "unk_token": null }