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breadability: filename=breadability-0.1.20-py2.py3-none-any.whl size=21695 sha256=b0d5fc8371eb48d8d9e53ecf146e64ea7d1de9db6d81429a2b7cad6c7219d418\n","  Stored in directory: /root/.cache/pip/wheels/32/99/64/59305409cacd03aa03e7bddf31a9db34b1fa7033bd41972662\n","  Building wheel for docopt (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for docopt: filename=docopt-0.6.2-py2.py3-none-any.whl size=13706 sha256=2ecac7e1b3eecc6655b326be94aa55c213599daaba56e0c605b77aa1660b7811\n","  Stored in directory: /root/.cache/pip/wheels/1a/bf/a1/4cee4f7678c68c5875ca89eaccf460593539805c3906722228\n","Successfully built breadability docopt\n","Installing collected packages: docopt, pycountry, breadability, sumy\n","Successfully installed breadability-0.1.20 docopt-0.6.2 pycountry-24.6.1 sumy-0.11.0\n"]}],"source":["pip install sumy transformers torch"]},{"cell_type":"markdown","source":[],"metadata":{"id":"DkprxexWamFt"}},{"cell_type":"code","source":["import nltk\n","nltk.download('punkt_tab')\n","from sumy.nlp.tokenizers import Tokenizer\n","from sumy.parsers.plaintext import PlaintextParser\n","from sumy.summarizers.lex_rank import LexRankSummarizer\n","from transformers import pipeline"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"z1wA5jTNaxl9","executionInfo":{"status":"ok","timestamp":1758818481664,"user_tz":-330,"elapsed":43240,"user":{"displayName":"YOGESH SAHU","userId":"09036209155327710676"}},"outputId":"cc225df1-b076-4a37-f0aa-b6c848dc7e23"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["[nltk_data] Downloading package punkt_tab to /root/nltk_data...\n","[nltk_data]   Unzipping tokenizers/punkt_tab.zip.\n"]}]},{"cell_type":"code","source":["text=\"Are you feeling overwhelmed by the rapid changes in content publishing? You’re not alone. The industry is transforming quickly, and AI-powered platforms are at the heart of this revolution. While these tools promise efficiency and innovation, they also bring challenges like maintaining content quality and managing data privacy. It’s easy to feel daunted by the prospect of adapting to these new technologies.\""],"metadata":{"id":"jekqWi3Ha0Pl"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Extractive Summarization\n","def extractive_summary(text, num_sentences=3):\n","    parser = PlaintextParser.from_string(text, Tokenizer(\"english\"))\n","    summarizer = LexRankSummarizer()\n","    summary = summarizer(parser.document, num_sentences)\n","    return \" \".join(str(sentence) for sentence in summary)"],"metadata":{"id":"bK3k-ZArbdes"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Abstractive Summarization\n","def abstractive_summary(text):\n","    summarizer = pipeline(\"summarization\")\n","    summary = summarizer(text, max_length=100, min_length=25, do_sample=False)\n","    return summary[0]['summary_text']"],"metadata":{"id":"byi911igbfe8"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Run both summarizations\n","print(\"===== Abstractive Summary =====\")\n","print(abstractive_summary(text))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":437,"referenced_widgets":["aa06720b37004be0963d33a08fa1988d","4c9aceb291594eb0878aa59770590411","26e3fd6067e84f3e9151b811cb2835be","5385d647aca5494382cde940ae83f670","f5b888bbedda4f109def6b0ee20f20a8","d9c2336333ab485b98a4345fe9e89537","bae5a5b876584b998518967c6a492c98","731faa83a51a49a39a55ebc0de89704c","b10ab3eceef246f7b62d89a37b67d25a","c009167265a749ebae7e30ceb3680ba2","1f5b3c2988f94f96afda1232958f46fc","78a3744a54924d999e0dbf6747037a7c","3a98404b430f49d8b3383991434f4977","daf35d243e694d23a95067655a905225","6b91d76017844ff5a3958d0f616ef954","5294d3df84f64ac1a9df57eab3c5db4f","30a56a2c0baf45d1afbb2088d470d250","31c77f6a56834f80bff27fef5afc305a","ff6177968dcf468f9132ca8d0da83bc0","bb88ec7d601b46a39e6f77d0762e8438","31900db1342843a18e7b14964f64140e","1f7b420dad92412aa5d0d65959a32182","df7f295186a344e0b7a21e89ec57cdc0","b86f76a5dd2249e9ad4e8cc7ecbec0ca","914be3d06b29475a8564b9fc1ee6a792","9b5c2e3319204c969c2da9c57714491a","fec1a2b27e0e429c9af13c97873b82fa","3db251fe2fd948ca8b96d238be4ab2d4","fd3dbcd94295451dbc9d79cdcf95e0a0","e12bc51633ca4236a99471b0996b91b4","94b51df26c0f4feaac25d488bec3f95d","3b1f8f738df947ffb4237d326207be19","f39a5e6727af47eba6b568e24f595ed1","16eb903813c649299bf04c239b1579a6","b623f1cf54984b60a904981e3cb1ab02","7f01bc3b7e75492e9be15d2bf2dc3d67","adcadba8be864d1fa82387f597a3bb82","0d055b10c9f441318978655a81c63729","1933cc438f404484a71b63e40542aabc","56f7cbf452e34736a59df7ada92fedc3","a97907a37852499f8cc4caffe6535e20","5350e809ccd9471eb2a821485607bef6","0e47717ceab64721a3e72dad84fe6028","935d99c4e50c4af8b0ae68e706262237","9c9c0000b78f4b22b63becf63468f66b","7be8e95624614a19b65c670db9f1f3c3","ef9f0d8e9f314f2cb58d9b19955c80cd","6c51ba191a6b4e20b1ed0a6160e86285","938a31db6f8044bea4760524009dee79","970e730b64154edf919d4c09f8e77b02","c2938308f52e4ab6b648e30239d9ce68","465df3fdb7a8463aa0e40b83898a68b0","dd88dcb383814bdab405d71986b8e4ac","6e7b66cb57d34d7490964ed306e550b2","63b2d33bfb094d01a77bb23b4c372b0d","0872ddbca8e14f92b534a5503bea9e39","e01ae9d6d4c642d5830b8e62f481cf52","81ce7b61dd124173999553330a5b3054","d0a7a11761464b148fe7bd0e7a5cd70c","60d3f08618a74e8c9ef033eaf21cc164","274730c3b274424c98dea2672ce2d33f","e244ed2ae15a4946a6d03c57ce75cfb0","a193614c5750494e96cd2787865bd396","e3e87b83bfee45d5973a2e414a546344","dfbdf6a38abd4e3098566136f0b96ae1","c56371ba15874399b73e568dfc047b10"]},"id":"uC0xXc1ObhJL","executionInfo":{"status":"ok","timestamp":1758818565376,"user_tz":-330,"elapsed":41131,"user":{"displayName":"YOGESH SAHU","userId":"09036209155327710676"}},"outputId":"a7edd3b7-b72d-4510-ed6c-978c4dd43cb5"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["No model was supplied, defaulted to sshleifer/distilbart-cnn-12-6 and revision a4f8f3e (https://huggingface.co/sshleifer/distilbart-cnn-12-6).\n","Using a pipeline without specifying a model name and revision in production is not recommended.\n"]},{"output_type":"stream","name":"stdout","text":["===== Abstractive Summary =====\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n","The secret `HF_TOKEN` does not exist in your Colab secrets.\n","To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n","You will be able to reuse this secret in all of your notebooks.\n","Please note that authentication is recommended but still optional to access public models or datasets.\n","  warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["config.json: 0.00B [00:00, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"aa06720b37004be0963d33a08fa1988d"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["pytorch_model.bin:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"78a3744a54924d999e0dbf6747037a7c"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"df7f295186a344e0b7a21e89ec57cdc0"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"16eb903813c649299bf04c239b1579a6"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.json: 0.00B [00:00, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"9c9c0000b78f4b22b63becf63468f66b"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["merges.txt: 0.00B [00:00, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"0872ddbca8e14f92b534a5503bea9e39"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Device set to use cpu\n","Your max_length is set to 100, but your input_length is only 80. Since this is a summarization task, where outputs shorter than the input are typically wanted, you might consider decreasing max_length manually, e.g. summarizer('...', max_length=40)\n"]},{"output_type":"stream","name":"stdout","text":[" AI-powered platforms are at the heart of this revolution in content publishing . While these tools promise efficiency and innovation, they also bring challenges like maintaining content quality .\n"]}]},{"cell_type":"code","source":["print(\"\\n===== Extractive Summary =====\")\n","print(extractive_summary(text))"],"metadata":{"id":"56FP3nBIbjPs","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1758818569514,"user_tz":-330,"elapsed":155,"user":{"displayName":"YOGESH SAHU","userId":"09036209155327710676"}},"outputId":"ef5351f0-7923-4c6b-994f-65dca9f909f4"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","===== Extractive Summary =====\n","Are you feeling overwhelmed by the rapid changes in content publishing? You’re not alone. The industry is transforming quickly, and AI-powered platforms are at the heart of this revolution.\n"]}]},{"cell_type":"code","source":["# Install necessary packages (for Jupyter/Colab)\n","!pip install sumy transformers torch\n","\n","import nltk\n","nltk.download('punkt_tab')\n","from sumy.parsers.plaintext import PlaintextParser\n","from sumy.nlp.tokenizers import Tokenizer\n","from sumy.summarizers.lex_rank import LexRankSummarizer\n","from transformers import pipeline\n","\n","# Sample text\n","text = \"\"\" Artificial intelligence (AI) is the technology that allows machines to simulate human intelligence, enabling them\n","to learn, reason, problem-solve, and make decisions. AI systems achieve this by analyzing vast amounts of data to identify patterns,\n","understand language, and recognize objects, similar to how humans think and behave. Key applications of AI include natural language processing,\n","computer vision, and autonomous systems, impacting various industries by automating tasks and improving decision-making.\n","The four common types of Artificial Intelligence (AI), based on their functionality, are: Reactive Machines, Limited Memory,\n","Theory of Mind, and Self-aware AI. Reactive machines, like the IBM Deep Blue chess program, act on the present situation but don't store memories.\n"," Limited Memory AI, such as self-driving cars, can use past data to inform current decisions. Theory of Mind and Self-aware AI are currently conceptual stages\n"," of AI that would possess human-like understanding of emotions and consciousness, respectively.\n","\"\"\"\n","\n","# Extractive Summarization\n","def extractive_summary(text, num_sentences=3):\n","    parser = PlaintextParser.from_string(text, Tokenizer(\"english\"))\n","    summarizer = LexRankSummarizer()\n","    summary = summarizer(parser.document, num_sentences)\n","    return ' '.join(str(sentence) for sentence in summary)\n","\n","# Abstractive Summarization\n","def abstractive_summary(text):\n","    summarizer = pipeline(\"summarization\")\n","    summary = summarizer(text, max_length=100, min_length=25, do_sample=False)\n","    return summary[0]['summary_text']\n","\n","# Run both summarizations\n","print(\"===== Abstractive Summary =====\")\n","print(abstractive_summary(text))\n","\n","print(\"\\n===== Extractive Summary =====\")\n","print(extractive_summary(text))\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["189d524fb2094108bbd6de7f3c1852e6","1a342a9422dd4dd29e4aa1a3921dfc93","c35dfca8469a4b6fa84b8a48fe267192","5b874bad0c5f43ff9c0dbee0a7e38f95","b6bd73818b694027a1b47d8c1bb22d24","382290aba7fe45f2a03f0d1e44efcb94","901e3ef156724de89dd1165b43bbf621","484554e8109d4e39b8962cebecfb23a7","da042f053cf34c2e9c3b5b072f5b23ed","dea74c927b954b96b2ae8828d0cb3f39","565d0be76600476183087d177ef185e0","a2e7a0f8cbbf41ceadec1a584069ac8d","58b87e2847b342e1a03ab3f9ca87fb79","3e17516fda284271bfe19ff74830540f","1e62495fdd69433ca4d2772195e35617","9d8e3e8d0dd04b39b64b9c3b208a5bd5","29d18a761593422f9599a0c3f18fec4f","9afcebf2f4ad4e079831354ed490cbbd","c14dac769e844733877a45f4760bf5d9","35660d9c985344dbbe49c61afaf8635c","b404c9dde0d047a0abd25f082bf9804e","1f398fe87428439bb9787121dc970dab","5bd5f4edb473477fb589ea1817c78cac","0af3273dfd6840beb9e12a25c1514827","d2987f1ef62f4a418cb99ffe4a2f7720","cf211cc6ef6446768736fed4f48e53ff","8d0238daa0264f2995f12b3a1d8e1749","daad762ceb67478582231a3c5db2ef69","30e6b3b757124032b92ff95a16e59c15","640cbedd03ad45afa23a60772c4fb990","74c75ac3fdf143fc95d5a54db79f4ee7","78600613e893401684148cd3267439aa","43ce7ff26d46490ea868ee8b80458ddd","985e43d4cd3d4d40958b9a7d4c142a69","60e06fe57d804508ab97f46c3f1d03ab","5e55020699e3458abdc6a5163753e769","a48a1b503c22433a89b47d0462c2e6e8","149b7e6e55ba48d2889d07b8514ce5b8","5776c948d24542b2b3b14fcf01d0d800","0bffd5cfddff46a996049d1f6c53391c","dfaec2c1e43a4b9ea556f4c3ad586159","8f25e2c9a9764a2ebfd16b2fcd698738","71e84650a9684a2ab60dbce5adb5ec4a","a176c822a33a4d3f9dc53c19bd231bbf","7cbda543566249d2b22ec00aca45e15b","c2990051176d484f94aa83d5bbc4ebef","44e0e2a0496f421c8d50cc9d14f67faf","039a8954f843476d9f0daa718cf35899","55bfb158bf01484a85b21fa382a0817e","0b2ee52e7a814558909e499422ea532c","f2cc967d0e844883a2a1763716cd6c89","ee1e6ee45ff24f6f88272daaebf1fce9","44a811ee0ec941ceac9d2820eeaade4a","fbcaec1d3da049ddb2097cfe490315b9","d8128c9bf2204760b91ffcaee52b9977","2982746cce9645c1a5b5f2694a551bd4","b18f1d85520e4f7b9481475666543f23","6add46edd1d64883b1130c25d97011e5","e8924fbac4464b63a93ddbd22ddb4f3f","211400fe65a94a959034d52a4d6b8a79","1dc257bcc2a64cdd85d581ace4497584","a865713b5684424eb1691ad613b705ef","ff05a375d374400b889c9c536e64e292","fbd474b17ce74b21a52679b25825beb7","0ca25e3ca05346d7827cba1e992b7283","c46fd3843d0444d98af13825034b8d00"]},"id":"-Y3MRdpyTT0F","executionInfo":{"status":"ok","timestamp":1759599638312,"user_tz":-330,"elapsed":108282,"user":{"displayName":"YOGESH SAHU","userId":"09036209155327710676"}},"outputId":"3b72ff58-c107-4f1a-fb87-347154b7acbb"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting sumy\n","  Downloading sumy-0.11.0-py2.py3-none-any.whl.metadata (7.5 kB)\n","Requirement already satisfied: transformers in /usr/local/lib/python3.12/dist-packages (4.56.2)\n","Requirement already satisfied: torch in /usr/local/lib/python3.12/dist-packages (2.8.0+cu126)\n","Collecting docopt<0.7,>=0.6.1 (from sumy)\n","  Downloading docopt-0.6.2.tar.gz (25 kB)\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Collecting breadability>=0.1.20 (from sumy)\n","  Downloading breadability-0.1.20.tar.gz (32 kB)\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: requests>=2.7.0 in /usr/local/lib/python3.12/dist-packages (from sumy) (2.32.4)\n","Collecting pycountry>=18.2.23 (from sumy)\n","  Downloading 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Unzipping tokenizers/punkt_tab.zip.\n","No model was supplied, defaulted to sshleifer/distilbart-cnn-12-6 and revision a4f8f3e (https://huggingface.co/sshleifer/distilbart-cnn-12-6).\n","Using a pipeline without specifying a model name and revision in production is not recommended.\n"]},{"output_type":"stream","name":"stdout","text":["===== Abstractive Summary =====\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n","The secret `HF_TOKEN` does not exist in your Colab secrets.\n","To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n","You will be able to reuse this secret in all of your notebooks.\n","Please note that authentication is recommended but still optional to access public models or datasets.\n","  warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["config.json: 0.00B [00:00, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"189d524fb2094108bbd6de7f3c1852e6"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["pytorch_model.bin:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a2e7a0f8cbbf41ceadec1a584069ac8d"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"5bd5f4edb473477fb589ea1817c78cac"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, 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AI systems achieve this by analyzing vast amounts of data to identify patterns, understand language, and recognize objects . Key applications of AI include natural language processing, computer vision and autonomous systems .\n","\n","===== Extractive Summary =====\n","AI systems achieve this by analyzing vast amounts of data to identify patterns, understand language, and recognize objects, similar to how humans think and behave. Key applications of AI include natural language processing, computer vision, and autonomous systems, impacting various industries by automating tasks and improving decision-making. The four common types of Artificial Intelligence (AI), based on their functionality, are: Reactive Machines, Limited Memory, Theory of Mind, and Self-aware AI.\n"]}]}]}