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<li class="md-nav__item">
|
||||
<a href="/how-to-guides/configure-service/" class="md-nav__link">
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How to configure GreatAI
|
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</a>
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</li>
|
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|
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|
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|
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|
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<li class="md-nav__item">
|
||||
<a href="/how-to-guides/use-service/" class="md-nav__link">
|
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How to use a GreatAI service
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<li class="md-nav__item">
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<a href="/how-to-guides/handle-training-data/" class="md-nav__link">
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How to handle training data
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<li class="md-nav__item">
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<a href="/how-to-guides/large_file/" class="md-nav__link">
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How to use LargeFile
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</a>
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</li>
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<a href="/how-to-guides/call_remote.md" class="md-nav__link">
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None
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</a>
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<li class="md-nav__item">
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<a href="/how-to-guides/scraping/" class="md-nav__link">
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Scraping
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<li class="md-nav__item">
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<a href="/reference/" class="md-nav__link">
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Reference
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GreatAI reference
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@ -458,6 +542,115 @@
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<li class="md-nav__item md-nav__item--nested">
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<label class="md-nav__link" for="__nav_5">
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Examples
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Examples
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
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<label class="md-nav__link" for="__nav_5_1">
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Explainable Naive Bayes
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<span class="md-nav__icon md-icon"></span>
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</label>
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<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
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<label class="md-nav__title" for="__nav_5_1">
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<span class="md-nav__icon md-icon"></span>
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Explainable Naive Bayes
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="/examples/simple/data/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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<li class="md-nav__item">
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<a href="/examples/simple/train/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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<li class="md-nav__item">
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<a href="/examples/simple/deploy/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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||||
</li>
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||||
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||||
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</ul>
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</nav>
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<a href="/explanation/" class="md-nav__link">
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Explanation
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@ -360,6 +360,90 @@
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<li class="md-nav__item">
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<a href="../../../how-to-guides/configure-service/" class="md-nav__link">
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How to configure GreatAI
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</a>
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</li>
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|
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|
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<li class="md-nav__item">
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<a href="../../../how-to-guides/use-service/" class="md-nav__link">
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How to use a GreatAI service
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../../how-to-guides/handle-training-data/" class="md-nav__link">
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How to handle training data
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../../how-to-guides/large_file/" class="md-nav__link">
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How to use LargeFile
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</a>
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</li>
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||||
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<li class="md-nav__item">
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<a href="../../../how-to-guides/call_remote.md" class="md-nav__link">
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None
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../../how-to-guides/scraping/" class="md-nav__link">
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Scraping
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</a>
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</li>
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</ul>
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</nav>
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</li>
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@ -401,7 +485,7 @@
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<li class="md-nav__item">
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<a href="../../../reference/" class="md-nav__link">
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Reference
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GreatAI reference
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</a>
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||||
</li>
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||||
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@ -463,6 +547,115 @@
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
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<label class="md-nav__link" for="__nav_5">
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Examples
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<span class="md-nav__icon md-icon"></span>
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</label>
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<nav class="md-nav" aria-label="Examples" data-md-level="1">
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<label class="md-nav__title" for="__nav_5">
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<span class="md-nav__icon md-icon"></span>
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||||
Examples
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
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<label class="md-nav__link" for="__nav_5_1">
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||||
Explainable Naive Bayes
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<span class="md-nav__icon md-icon"></span>
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</label>
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<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
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<label class="md-nav__title" for="__nav_5_1">
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<span class="md-nav__icon md-icon"></span>
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Explainable Naive Bayes
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../simple/data/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../simple/train/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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<a href="../../simple/deploy/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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</ul>
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</nav>
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Explanation
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226m2022-06-25 14:25:24,989 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,990 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,990 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,991 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,992 | INFO | Settings: configured ✅\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,993 | INFO | 🔩 tracing_database: MongodbDriver\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,993 | INFO | 🔩 tracing_database: MongoDbDriver\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,994 | INFO | 🔩 large_file_implementation: LargeFileMongo\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,994 | INFO | 🔩 is_production: False\u001b[0m\n",
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"\u001b[38;5;39m2022-06-25 14:25:24,995 | INFO | 🔩 should_log_exception_stack: True\u001b[0m\n",
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<li class="md-nav__item">
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<a href="../../../how-to-guides/configure-service/" class="md-nav__link">
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How to configure GreatAI
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</a>
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</li>
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||||
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||||
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<li class="md-nav__item">
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<a href="../../../how-to-guides/use-service/" class="md-nav__link">
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||||
How to use a GreatAI service
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</a>
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||||
</li>
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||||
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||||
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||||
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||||
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||||
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<li class="md-nav__item">
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<a href="../../../how-to-guides/handle-training-data/" class="md-nav__link">
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How to handle training data
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</a>
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||||
</li>
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||||
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||||
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<li class="md-nav__item">
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||||
<a href="../../../how-to-guides/large_file/" class="md-nav__link">
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How to use LargeFile
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</a>
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||||
</li>
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||||
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||||
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||||
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||||
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||||
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<li class="md-nav__item">
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<a href="../../../how-to-guides/call_remote.md" class="md-nav__link">
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None
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</a>
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||||
</li>
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<li class="md-nav__item">
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||||
<a href="../../../how-to-guides/scraping/" class="md-nav__link">
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Scraping
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</a>
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||||
</li>
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||||
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||||
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</ul>
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</nav>
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</li>
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<li class="md-nav__item">
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<a href="../../../reference/" class="md-nav__link">
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Reference
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GreatAI reference
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</a>
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||||
</li>
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||||
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||||
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@ -463,6 +547,194 @@
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||||
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" checked>
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||||
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||||
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||||
<label class="md-nav__link" for="__nav_5">
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Examples
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<span class="md-nav__icon md-icon"></span>
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</label>
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||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
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<label class="md-nav__title" for="__nav_5">
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<span class="md-nav__icon md-icon"></span>
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||||
Examples
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||||
</label>
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||||
<ul class="md-nav__list" data-md-scrollfix>
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||||
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||||
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||||
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||||
<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" checked>
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||||
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||||
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||||
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||||
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||||
<label class="md-nav__link" for="__nav_5_1">
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||||
Explainable Naive Bayes
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||||
<span class="md-nav__icon md-icon"></span>
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||||
</label>
|
||||
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||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
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||||
<span class="md-nav__icon md-icon"></span>
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||||
Explainable Naive Bayes
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||||
</label>
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||||
<ul class="md-nav__list" data-md-scrollfix>
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
<li class="md-nav__item md-nav__item--active">
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||||
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||||
<input class="md-nav__toggle md-toggle" data-md-toggle="toc" type="checkbox" id="__toc">
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||||
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||||
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||||
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||||
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||||
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||||
<label class="md-nav__link md-nav__link--active" for="__toc">
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||||
Train a domain classifier on the semantic scholar dataset
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||||
<span class="md-nav__icon md-icon"></span>
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||||
</label>
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||||
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||||
<a href="./" class="md-nav__link md-nav__link--active">
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||||
Train a domain classifier on the semantic scholar dataset
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||||
</a>
|
||||
|
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|
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|
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|
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Extract
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|
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|
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|
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<a href="#transform" class="md-nav__link">
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Transform
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|
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|
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|
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<li class="md-nav__item">
|
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<a href="../train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
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|
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|
||||
|
||||
|
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|
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|
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|
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|
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|
||||
|
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|
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<a href="../deploy/" class="md-nav__link">
|
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Train a domain classifier on the semantic scholar dataset
|
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Explanation
|
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|
|
@ -2020,10 +2292,10 @@ add_ground_truth(X, y, train_split_ratio=0.8, test_split_ratio=0.2)</div>
|
|||
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
|
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<pre><span style="color: rgb(255,255,0)">2022-06-25 14:25:24,989 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,990 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,990 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,991 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,992 | INFO | Settings: configured ✅</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,993 | INFO | 🔩 tracing_database: MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,993 | INFO | 🔩 tracing_database: MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,994 | INFO | 🔩 large_file_implementation: LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,994 | INFO | 🔩 is_production: False</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:25:24,995 | INFO | 🔩 should_log_exception_stack: True</span>
|
||||
|
|
@ -2078,6 +2350,42 @@ add_ground_truth(X, y, train_split_ratio=0.8, test_split_ratio=0.2)</div>
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<a href="../train/" class="md-footer__link md-footer__link--next" aria-label="Next: Train a domain classifier on the semantic scholar dataset" rel="next">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M4 11v2h12l-5.5 5.5 1.42 1.42L19.84 12l-7.92-7.92L10.5 5.5 16 11H4Z"/></svg>
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|
@ -24,10 +24,10 @@
|
|||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[38;5;226m2022-06-25 14:57:20,629 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,629 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,629 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,630 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,631 | INFO | Settings: configured ✅\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,631 | INFO | 🔩 tracing_database: MongodbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,631 | INFO | 🔩 tracing_database: MongoDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,631 | INFO | 🔩 large_file_implementation: LargeFileMongo\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,632 | INFO | 🔩 is_production: False\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:57:20,633 | INFO | 🔩 should_log_exception_stack: True\u001b[0m\n",
|
||||
|
|
|
|||
|
|
@ -360,6 +360,90 @@
|
|||
|
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|
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|
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|
||||
|
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|
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|
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<li class="md-nav__item">
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<a href="../../../how-to-guides/configure-service/" class="md-nav__link">
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How to configure GreatAI
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<a href="../../../how-to-guides/use-service/" class="md-nav__link">
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How to use a GreatAI service
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</li>
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<li class="md-nav__item">
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<a href="../../../how-to-guides/handle-training-data/" class="md-nav__link">
|
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How to handle training data
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|
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</li>
|
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|
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|
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|
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|
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<li class="md-nav__item">
|
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<a href="../../../how-to-guides/large_file/" class="md-nav__link">
|
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How to use LargeFile
|
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</a>
|
||||
</li>
|
||||
|
||||
|
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|
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|
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<li class="md-nav__item">
|
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<a href="../../../how-to-guides/call_remote.md" class="md-nav__link">
|
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None
|
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</a>
|
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</li>
|
||||
|
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|
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<li class="md-nav__item">
|
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<a href="../../../how-to-guides/scraping/" class="md-nav__link">
|
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Scraping
|
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|
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</ul>
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@ -401,7 +485,7 @@
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<li class="md-nav__item">
|
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<a href="../../../reference/" class="md-nav__link">
|
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Reference
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|
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|
|
@ -463,6 +547,160 @@
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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<ul class="md-nav__list" data-md-scrollfix>
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<a href="../data/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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|
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|
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|
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<li class="md-nav__item">
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<a href="../train/" class="md-nav__link">
|
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Train a domain classifier on the semantic scholar dataset
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</a>
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</li>
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|
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|
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<label class="md-nav__link md-nav__link--active" for="__toc">
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Train a domain classifier on the semantic scholar dataset
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<span class="md-nav__icon md-icon"></span>
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<a href="./" class="md-nav__link md-nav__link--active">
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<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
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Check accuracy on the test split
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<li class="md-nav__item">
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<a href="../../../explanation/" class="md-nav__link">
|
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Explanation
|
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|
|
@ -1757,10 +1995,10 @@ def get_label(
|
|||
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
|
||||
<pre><span style="color: rgb(255,255,0)">2022-06-25 14:57:20,629 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,629 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,629 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,630 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,631 | INFO | Settings: configured ✅</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,631 | INFO | 🔩 tracing_database: MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,631 | INFO | 🔩 tracing_database: MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,631 | INFO | 🔩 large_file_implementation: LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,632 | INFO | 🔩 is_production: False</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:57:20,633 | INFO | 🔩 should_log_exception_stack: True</span>
|
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|
|
@ -1991,6 +2229,42 @@ class="
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<footer class="md-footer">
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<nav class="md-footer__inner md-grid" aria-label="Footer" >
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<a href="../train/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Train a domain classifier on the semantic scholar dataset" rel="prev">
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<div class="md-footer-meta__inner md-grid">
|
||||
<div class="md-copyright">
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||||
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|||
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@ -360,6 +360,90 @@
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|||
|
||||
|
||||
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|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
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|
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|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
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<a href="../../../how-to-guides/use-service/" class="md-nav__link">
|
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How to use a GreatAI service
|
||||
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|
||||
</li>
|
||||
|
||||
|
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|
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|
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|
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|
||||
|
||||
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|
||||
<li class="md-nav__item">
|
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|
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How to handle training data
|
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|
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|
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|
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|
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|
||||
<li class="md-nav__item">
|
||||
<a href="../../../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
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|
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||||
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||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
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|
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|
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|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
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|
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|
|
@ -401,7 +485,7 @@
|
|||
|
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<li class="md-nav__item">
|
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<a href="../../../reference/" class="md-nav__link">
|
||||
Reference
|
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|
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|
||||
</li>
|
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|
||||
|
|
@ -463,6 +547,187 @@
|
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|
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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<label class="md-nav__link" for="__nav_5_1">
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|
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|
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Train a domain classifier on the semantic scholar dataset
|
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|
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|
||||
|
||||
|
||||
|
||||
|
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Train a domain classifier on the semantic scholar dataset
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|
||||
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|
||||
|
||||
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Train a domain classifier on the semantic scholar dataset
|
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|
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<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
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<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
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|
||||
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|
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<a href="#load-data-that-has-been-extracted-in-part-1" class="md-nav__link">
|
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Load data that has been extracted in part 1
|
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|
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|
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|
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|
||||
<li class="md-nav__item">
|
||||
<a href="#optimise-and-train-multinomial-naive-bayes-classifier" class="md-nav__link">
|
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Optimise and train Multinomial Naive Bayes classifier
|
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</a>
|
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|
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|
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|
||||
<li class="md-nav__item">
|
||||
<a href="#export-the-model-using-greatai" class="md-nav__link">
|
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Export the model using GreatAI
|
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</a>
|
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|
||||
<nav class="md-nav" aria-label="Export the model using GreatAI">
|
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<ul class="md-nav__list">
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|
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|
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Next: Part 3
|
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|
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|
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</li>
|
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|
||||
</ul>
|
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</nav>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
|
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|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
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</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
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||||
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||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
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|
||||
|
||||
|
||||
|
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|
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|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -1668,10 +1933,10 @@ y = [domain for d in data for domain in d.feedback]</div>
|
|||
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
|
||||
<pre><span style="color: rgb(255,255,0)">2022-06-25 14:50:29,879 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,880 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,880 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,881 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,881 | INFO | Settings: configured ✅</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,882 | INFO | 🔩 tracing_database: MongodbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,882 | INFO | 🔩 tracing_database: MongoDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,883 | INFO | 🔩 large_file_implementation: LargeFileMongo</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,883 | INFO | 🔩 is_production: False</span>
|
||||
<span style="color: rgb(0,175,255)">2022-06-25 14:50:29,884 | INFO | 🔩 should_log_exception_stack: True</span>
|
||||
|
|
@ -2598,6 +2863,42 @@ save_model(classifier, key="small-domain-prediction", keep_last_n=5)</div>
|
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|
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<footer class="md-footer">
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<a href="../data/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Train a domain classifier on the semantic scholar dataset" rel="prev">
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|
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Previous
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Train a domain classifier on the semantic scholar dataset
|
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</a>
|
||||
|
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|
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|
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<a href="../deploy/" class="md-footer__link md-footer__link--next" aria-label="Next: Train a domain classifier on the semantic scholar dataset" rel="next">
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Next
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Train a domain classifier on the semantic scholar dataset
|
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|
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|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M4 11v2h12l-5.5 5.5 1.42 1.42L19.84 12l-7.92-7.92L10.5 5.5 16 11H4Z"/></svg>
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</nav>
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<div class="md-footer-meta md-typeset">
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|
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<div class="md-copyright">
|
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|
|
|
|||
|
|
@ -33,10 +33,10 @@
|
|||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[38;5;226m2022-06-25 14:50:29,879 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,880 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongodbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,880 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising MongoDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,881 | INFO | Found credentials file (/data/projects/great_ai_example/mongo.ini), initialising LargeFileMongo\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,881 | INFO | Settings: configured ✅\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,882 | INFO | 🔩 tracing_database: MongodbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,882 | INFO | 🔩 tracing_database: MongoDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,883 | INFO | 🔩 large_file_implementation: LargeFileMongo\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,883 | INFO | 🔩 is_production: False\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-06-25 14:50:29,884 | INFO | 🔩 should_log_exception_stack: True\u001b[0m\n",
|
||||
|
|
|
|||
|
|
@ -3,5 +3,5 @@
|
|||
A lot more details and discussion about the problem context and approaches of GreatAI can be found in my thesis.
|
||||
|
||||
<div style="display: flex; justify-content: space-evenly;" markdown>
|
||||
[::fontawesome-solid-graduation-cap: Download](thesis/main.py){ .md-button .md-button--primary }
|
||||
[::fontawesome-solid-graduation-cap: Download](thesis/main.pdf){ .md-button .md-button--primary }
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -360,6 +360,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
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|
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|
||||
|
||||
|
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|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
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</li>
|
||||
|
|
@ -401,7 +485,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/" class="md-nav__link">
|
||||
Reference
|
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GreatAI reference
|
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</a>
|
||||
</li>
|
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|
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@ -464,6 +548,115 @@
|
|||
|
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|
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|
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<li class="md-nav__item md-nav__item--nested">
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|
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<label class="md-nav__link" for="__nav_5_1">
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Explainable Naive Bayes
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<span class="md-nav__icon md-icon"></span>
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<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
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Explainable Naive Bayes
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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|
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|
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|
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<li class="md-nav__item">
|
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<a href="../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
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|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--active">
|
||||
|
||||
|
|
@ -523,7 +716,7 @@
|
|||
<h1 id="explanation">Explanation<a class="headerlink" href="#explanation" title="Permanent link">#</a></h1>
|
||||
<p>A lot more details and discussion about the problem context and approaches of GreatAI can be found in my thesis.</p>
|
||||
<div style="display: flex; justify-content: space-evenly;">
|
||||
<p><a class="md-button md-button--primary" href="thesis/main.py">:<span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 640 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M623.1 136.9 340.4 35.7a62.951 62.951 0 0 0-42.43 0L16.05 136.9C6.438 140.4 0 149.6 0 160s6.438 19.65 16.05 23.09l60.02 21.51c-11.89 15.8-20.26 34.16-24.55 53.95C40.05 263.4 32 274.8 32 288c0 9.953 4.814 18.49 11.94 24.36l-24.83 149C17.48 471.1 25 480 34.89 480h58.22c9.887 0 17.41-8.879 15.78-18.63l-24.83-149C91.19 306.5 96 297.1 96 288c0-10.29-5.174-19.03-12.72-24.89a106.301 106.301 0 0 1 24.94-47.03l190.6 68.23a62.951 62.951 0 0 0 42.43 0l282.7-101.2C633.6 179.6 640 170.4 640 160s-6.4-19.6-16.9-23.1zm-272 177.5c-9.4 3.7-20.2 5.6-31.1 5.6a94.767 94.767 0 0 1-32-5.555L142.8 262.5 128 405.3c0 41.3 85.1 74.7 192 74.7 105.1 0 192-33.4 192-74.67l-14.78-142.9L351.1 314.4z"/></svg></span> Download</a></p>
|
||||
<p><a class="md-button md-button--primary" href="thesis/main.pdf">:<span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 640 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M623.1 136.9 340.4 35.7a62.951 62.951 0 0 0-42.43 0L16.05 136.9C6.438 140.4 0 149.6 0 160s6.438 19.65 16.05 23.09l60.02 21.51c-11.89 15.8-20.26 34.16-24.55 53.95C40.05 263.4 32 274.8 32 288c0 9.953 4.814 18.49 11.94 24.36l-24.83 149C17.48 471.1 25 480 34.89 480h58.22c9.887 0 17.41-8.879 15.78-18.63l-24.83-149C91.19 306.5 96 297.1 96 288c0-10.29-5.174-19.03-12.72-24.89a106.301 106.301 0 0 1 24.94-47.03l190.6 68.23a62.951 62.951 0 0 0 42.43 0l282.7-101.2C633.6 179.6 640 170.4 640 160s-6.4-19.6-16.9-23.1zm-272 177.5c-9.4 3.7-20.2 5.6-31.1 5.6a94.767 94.767 0 0 1-32-5.555L142.8 262.5 128 405.3c0 41.3 85.1 74.7 192 74.7 105.1 0 192-33.4 192-74.67l-14.78-142.9L351.1 314.4z"/></svg></span> Download</a></p>
|
||||
</div>
|
||||
|
||||
<hr>
|
||||
|
|
@ -531,7 +724,7 @@
|
|||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 9, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
@ -552,7 +745,7 @@
|
|||
<nav class="md-footer__inner md-grid" aria-label="Footer" >
|
||||
|
||||
|
||||
<a href="../reference/views/" class="md-footer__link md-footer__link--prev" aria-label="Previous: View models" rel="prev">
|
||||
<a href="../examples/simple/deploy/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Train a domain classifier on the semantic scholar dataset" rel="prev">
|
||||
<div class="md-footer__button md-icon">
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>
|
||||
</div>
|
||||
|
|
@ -561,7 +754,7 @@
|
|||
<span class="md-footer__direction">
|
||||
Previous
|
||||
</span>
|
||||
View models
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</div>
|
||||
</div>
|
||||
</a>
|
||||
|
|
|
|||
|
|
@ -0,0 +1,2 @@
|
|||
# Call remote GreatAI instances
|
||||
|
||||
|
|
@ -17,7 +17,7 @@
|
|||
|
||||
|
||||
|
||||
<title>Call remote - GreatAI documentation</title>
|
||||
<title>Call remote GreatAI instances - GreatAI documentation</title>
|
||||
|
||||
|
||||
|
||||
|
|
@ -69,6 +69,11 @@
|
|||
<label class="md-overlay" for="__drawer"></label>
|
||||
<div data-md-component="skip">
|
||||
|
||||
|
||||
<a href="#call-remote-greatai-instances" class="md-skip">
|
||||
Skip to content
|
||||
</a>
|
||||
|
||||
</div>
|
||||
<div data-md-component="announce">
|
||||
|
||||
|
|
@ -98,7 +103,7 @@
|
|||
<div class="md-header__topic" data-md-component="header-topic">
|
||||
<span class="md-ellipsis">
|
||||
|
||||
Call remote
|
||||
Call remote GreatAI instances
|
||||
|
||||
</span>
|
||||
</div>
|
||||
|
|
@ -355,6 +360,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -396,7 +485,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -458,6 +547,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -484,6 +682,8 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
</nav>
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -503,16 +703,14 @@
|
|||
|
||||
|
||||
|
||||
<h1>Call remote</h1>
|
||||
|
||||
|
||||
<h1 id="call-remote-greatai-instances">Call remote GreatAI instances<a class="headerlink" href="#call-remote-greatai-instances" title="Permanent link">#</a></h1>
|
||||
|
||||
<hr>
|
||||
<div class="md-source-file">
|
||||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 10, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
|
|||
101
how-to-guides/configure-service/configure-service.md
Normal file
101
how-to-guides/configure-service/configure-service.md
Normal file
|
|
@ -0,0 +1,101 @@
|
|||
# How to configure GreatAI
|
||||
|
||||
GreatAI aims to provide reasonable defaults wherever possible. The current configuration is always prominently displayed (and updated) on the dashboard and in the command-line startup banner.
|
||||
|
||||
## Using [great_ai.configure][]
|
||||
|
||||
You can override any of the default settings by calling [great_ai.configure][]. If you don't call `configure`, the default settings are applied on the first call to most `great-ai` functions.
|
||||
|
||||
!!! warning
|
||||
You must call [great_ai.configure][] before calling (or decorating with) any other `great-ai` function. However, importing other functions before calling [great_ai.configure][] is permitted.
|
||||
|
||||
```python title="configure-demo.py"
|
||||
from great_ai import configure, RouteConfig
|
||||
import logging
|
||||
|
||||
configure(
|
||||
version='1.0.0',
|
||||
log_level=logging.INFO,
|
||||
seed=2,
|
||||
should_log_exception_stack=False,
|
||||
prediction_cache_size=0, #(1)
|
||||
disable_se4ml_banner=True,
|
||||
dashboard_table_size=200,
|
||||
route_config=RouteConfig( #(2)
|
||||
feedback_endpoints_enabled=False,
|
||||
dashboard_enabled=False
|
||||
)
|
||||
)
|
||||
```
|
||||
|
||||
1. Completely disable caching.
|
||||
2. The unspecified routes are enabled by default.
|
||||
|
||||
## Using remote storage
|
||||
|
||||
The only aspect that cannot be automated is choosing the backing storage for the database and file storage.
|
||||
|
||||
Right now, you have 3 options for storing the models and large datasets: [great_ai.large_file.LargeFileLocal][], [great_ai.large_file.LargeFileMongo][], and [great_ai.large_file.LargeFileS3][].
|
||||
|
||||
Without explicit configuration, [great_ai.large_file.LargeFileLocal][] is selected by default. This one still version-controls your files but it only stores them in a local path.
|
||||
|
||||
!!! important
|
||||
If your working directory contains a `mongo.ini` or `s3.ini` file, an attempt is made to auto-configure [LargeFileMongo][great_ai.large_file.LargeFileMongo] or [LargeFileS3][great_ai.large_file.LargeFileS3] respectively.
|
||||
|
||||
To use [LargeFileMongo][great_ai.large_file.LargeFileMongo] or [LargeFileS3][great_ai.large_file.LargeFileS3] explicitly, configure them before calling any other `great-ai` function.
|
||||
|
||||
### S3-compatible
|
||||
|
||||
```toml title="s3.ini"
|
||||
aws_region_name = eu-west-2
|
||||
aws_access_key_id = MY_AWS_ACCESS_KEY # ENV:MY_AWS_ACCESS_KEY would also work
|
||||
aws_secret_access_key = MY_AWS_SECRET_KEY
|
||||
large_files_bucket_name = bucket-for-models
|
||||
```
|
||||
|
||||
```python title="use-s3.py"
|
||||
from great_ai.large_file import LargeFileS3
|
||||
from great_ai import save_model
|
||||
|
||||
LargeFileS3.configure_credentials_from_file('s3.ini') #(1)
|
||||
|
||||
model = [4, 3]
|
||||
save_model(model, 'my-model')
|
||||
```
|
||||
|
||||
1. This line isn't strictly necceseary because if `s3.ini` (or `mongo.ini`) is available in the current working directory, they are automatically used to configure their respective LargeFile implementations/databases.
|
||||
|
||||
??? note "Departing from AWS"
|
||||
With the `aws_endpoint_url` argument, it is possible to use any other S3-compatible service such as [Backblaze](https://www.backblaze.com/){ target=_blank }. In that case, it would be `aws_endpoint_url=https://s3.us-west-002.backblazeb2.com`.
|
||||
|
||||
### GridFS
|
||||
|
||||
[GridFS](https://www.mongodb.com/docs/manual/core/gridfs/#:~:text=GridFS%20is%20a%20specification%20for,chunk%20as%20a%20separate%20document.){ target=_blank } specifies how to store files in MongoDB. The official MongoDB server and many compatible implementations support it.
|
||||
|
||||
```toml title="mongo.ini"
|
||||
MONGO_CONNECTION_STRING=mongodb://localhost:27017 # this is the default value
|
||||
# if `MONGO_CONNECTION_STRING` is specified, this default is overridden
|
||||
MONGO_CONNECTION_STRING=ENV:MONGO_CONNECTION_STRING
|
||||
MONGO_DATABASE=my-database # it is automatically created if doesn't exist
|
||||
```
|
||||
|
||||
```python title="use-mongo.py"
|
||||
from great_ai.large_file import LargeFileMongo
|
||||
from great_ai import save_model
|
||||
|
||||
LargeFileMongo.configure_credentials_from_file('mongo.ini')
|
||||
|
||||
model = [4, 3]
|
||||
save_model(model, 'my-model')
|
||||
```
|
||||
|
||||
!!! note "Simplifying config files"
|
||||
You can combine `mongo.ini` or `s3.ini` with your application's config file because the unneeded keys are ignored by the `configure_credentials_from_file` method.
|
||||
|
||||
## Using a database
|
||||
|
||||
By default, a thread-safe version of [TinyDB](https://tinydb.readthedocs.io/en/latest/){ target=_blank } is utilised for saving the prediction traces into a local file. Unfortunately, for most production needs, this method is not suitable.
|
||||
|
||||
### MongoDB
|
||||
|
||||
At the moment, only MongoDB is supported as a production-ready `TracingDatabase`. In order to use it, you have to either place a file named `mongo.ini` in your working directory, or explicitly call [MongoDbDriver.configure_credentials_from_file][great_ai.MongoDbDriver.configure_credentials_from_file] or [MongoDbDriver.configure_credentials][great_ai.MongoDbDriver.configure_credentials].
|
||||
1053
how-to-guides/configure-service/index.html
Normal file
1053
how-to-guides/configure-service/index.html
Normal file
File diff suppressed because it is too large
Load diff
|
|
@ -1,6 +1,6 @@
|
|||
# How to create a GreatAI service
|
||||
|
||||
The core value of `great-ai` lies in its [GreatAI][great_ai.deploy.GreatAI] class. In order to take advantage of it, you need to create an instance wrapping your code.
|
||||
The core value of `great-ai` lies in its [GreatAI][great_ai.GreatAI] class. In order to take advantage of it, you need to create an instance wrapping your code.
|
||||
|
||||
Let's say that you have the following greeter function:
|
||||
|
||||
|
|
@ -9,7 +9,7 @@ def my_greeter_function(your_name):
|
|||
return f'Hi {your_name}!'
|
||||
```
|
||||
|
||||
You can simply decorate (wrap) this function using the [@GreatAI.create][great_ai.deploy.GreatAI.create] factory.
|
||||
You can simply decorate (wrap) this function using the [@GreatAI.create][great_ai.GreatAI.create] factory.
|
||||
|
||||
```python title="greeter.py"
|
||||
from great_ai import GreatAI
|
||||
|
|
@ -20,7 +20,7 @@ def greeter(your_name):
|
|||
```
|
||||
|
||||
??? info "Why not simply use `@GreatAI?`"
|
||||
The purpose of the [@GreatAI.create][great_ai.deploy.GreatAI.create] is simply to provide you with type-checking through MyPy, Pylance, and similar libraries. However, the overloading support for `__new__` is lacking in MyPy, thus, a static factory method is used instead.
|
||||
The purpose of the [@GreatAI.create][great_ai.GreatAI.create] is simply to provide you with type-checking through MyPy, Pylance, and similar libraries. However, the overloading support for `__new__` is lacking in MyPy, thus, a static factory method is used instead.
|
||||
|
||||
## With types
|
||||
|
||||
|
|
@ -52,9 +52,9 @@ async def async_greeter(your_name: str) -> str:
|
|||
|
||||
## With decorators
|
||||
|
||||
GreatAI can decorate already decorated functions. The only restriction is that [@GreatAI.create][great_ai.deploy.GreatAI.create] always has to come last. There are two built-in decorators that you can use to customise your function but you can you use any third-party decorator as well.
|
||||
GreatAI can decorate already decorated functions. The only restriction is that [@GreatAI.create][great_ai.GreatAI.create] always has to come last. There are two built-in decorators that you can use to customise your function but you can you use any third-party decorator as well.
|
||||
|
||||
### Using `use_model`
|
||||
### Using `@use_model`
|
||||
|
||||
If you have previously saved a model with [save_model][great_ai.save_model], you can inject it into your function by calling [@use_model][great_ai.use_model].
|
||||
|
||||
|
|
@ -72,14 +72,14 @@ assert type_safe_greeter('Andras').output == 'Hi Andras'
|
|||
1. By default, the parameter named `model` will be replaced by the loaded model. This behaviour can be customised by setting the `model_kwarg_name`. This way, even multiple models can be injected into a single function.
|
||||
|
||||
!!! important
|
||||
You must call [@use_model][great_ai.use_model] before [@GreatAI.create][great_ai.deploy.GreatAI.create]. Feel free to use [@use_model][great_ai.use_model] in other places of the codebase, it works equally well outside of GreatAI services.
|
||||
You must call [@use_model][great_ai.use_model] before [@GreatAI.create][great_ai.GreatAI.create]. Feel free to use [@use_model][great_ai.use_model] in other places of the codebase, it works equally well outside of GreatAI services.
|
||||
|
||||
### Using `parameter`
|
||||
### Using `@parameter`
|
||||
|
||||
If you wish to turn of logging or specify custom validation for your parameters, you can use the [@parameter][great_ai.parameter] decorator.
|
||||
|
||||
!!! note
|
||||
By default, all parameters that are not affected by an explicit [@parameter][great_ai.parameter] or [@use_model][great_ai.use_model] are automatically decorated with [@parameter][great_ai.parameter] when [@GreatAI.create][great_ai.deploy.GreatAI.create] is called.
|
||||
By default, all parameters that are not affected by an explicit [@parameter][great_ai.parameter] or [@use_model][great_ai.use_model] are automatically decorated with [@parameter][great_ai.parameter] when [@GreatAI.create][great_ai.GreatAI.create] is called.
|
||||
|
||||
```python title="greeter_with_validation.py"
|
||||
from great_ai import GreatAI, use_model
|
||||
|
|
@ -93,7 +93,7 @@ assert type_safe_greeter('Andras').output == 'Hi Andras'
|
|||
```
|
||||
|
||||
!!! important
|
||||
You must call [@parameter][great_ai.parameter] before [@GreatAI.create][great_ai.deploy.GreatAI.create]. Feel free to use [@parameter][great_ai.parameter] in other places of the codebase, it works equally well outside of GreatAI services.
|
||||
You must call [@parameter][great_ai.parameter] before [@GreatAI.create][great_ai.GreatAI.create]. Feel free to use [@parameter][great_ai.parameter] in other places of the codebase, it works equally well outside of GreatAI services.
|
||||
|
||||
## Complex example
|
||||
|
||||
|
|
|
|||
|
|
@ -411,14 +411,14 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="#using-use_model" class="md-nav__link">
|
||||
Using use_model
|
||||
Using @use_model
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#using-parameter" class="md-nav__link">
|
||||
Using parameter
|
||||
Using @parameter
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
|
@ -444,6 +444,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -485,7 +569,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -547,6 +631,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -605,14 +798,14 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="#using-use_model" class="md-nav__link">
|
||||
Using use_model
|
||||
Using @use_model
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#using-parameter" class="md-nav__link">
|
||||
Using parameter
|
||||
Using @parameter
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
|
@ -688,7 +881,7 @@
|
|||
</code></pre></div>
|
||||
<h2 id="with-decorators">With decorators<a class="headerlink" href="#with-decorators" title="Permanent link">#</a></h2>
|
||||
<p>GreatAI can decorate already decorated functions. The only restriction is that <a class="autorefs autorefs-internal" href="../../reference/#great_ai.deploy.great_ai.GreatAI.create">@GreatAI.create</a> always has to come last. There are two built-in decorators that you can use to customise your function but you can you use any third-party decorator as well.</p>
|
||||
<h3 id="using-use_model">Using <code>use_model</code><a class="headerlink" href="#using-use_model" title="Permanent link">#</a></h3>
|
||||
<h3 id="using-use_model">Using <code>@use_model</code><a class="headerlink" href="#using-use_model" title="Permanent link">#</a></h3>
|
||||
<p>If you have previously saved a model with <a class="autorefs autorefs-internal" href="../../reference/#great_ai.save_model">save_model</a>, you can inject it into your function by calling <a class="autorefs autorefs-internal" href="../../reference/#great_ai.use_model">@use_model</a>.</p>
|
||||
<div class="highlight"><span class="filename">greeter_with_model.py</span><pre><span></span><code><a id="__codelineno-4-1" name="__codelineno-4-1" href="#__codelineno-4-1"></a><span class="kn">from</span> <span class="nn">great_ai</span> <span class="kn">import</span> <span class="n">GreatAI</span><span class="p">,</span> <span class="n">use_model</span>
|
||||
<a id="__codelineno-4-2" name="__codelineno-4-2" href="#__codelineno-4-2"></a>
|
||||
|
|
@ -706,7 +899,7 @@
|
|||
<p class="admonition-title">Important</p>
|
||||
<p>You must call <a class="autorefs autorefs-internal" href="../../reference/#great_ai.use_model">@use_model</a> before <a class="autorefs autorefs-internal" href="../../reference/#great_ai.deploy.great_ai.GreatAI.create">@GreatAI.create</a>. Feel free to use <a class="autorefs autorefs-internal" href="../../reference/#great_ai.use_model">@use_model</a> in other places of the codebase, it works equally well outside of GreatAI services. </p>
|
||||
</div>
|
||||
<h3 id="using-parameter">Using <code>parameter</code><a class="headerlink" href="#using-parameter" title="Permanent link">#</a></h3>
|
||||
<h3 id="using-parameter">Using <code>@parameter</code><a class="headerlink" href="#using-parameter" title="Permanent link">#</a></h3>
|
||||
<p>If you wish to turn of logging or specify custom validation for your parameters, you can use the <a class="autorefs autorefs-internal" href="../../reference/#great_ai.parameter">@parameter</a> decorator.</p>
|
||||
<div class="admonition note">
|
||||
<p class="admonition-title">Note</p>
|
||||
|
|
@ -785,13 +978,13 @@
|
|||
|
||||
|
||||
|
||||
<a href="../../reference/" class="md-footer__link md-footer__link--next" aria-label="Next: Reference" rel="next">
|
||||
<a href="../configure-service/" class="md-footer__link md-footer__link--next" aria-label="Next: How to configure GreatAI" rel="next">
|
||||
<div class="md-footer__title">
|
||||
<div class="md-ellipsis">
|
||||
<span class="md-footer__direction">
|
||||
Next
|
||||
</span>
|
||||
Reference
|
||||
How to configure GreatAI
|
||||
</div>
|
||||
</div>
|
||||
<div class="md-footer__button md-icon">
|
||||
|
|
|
|||
|
|
@ -0,0 +1,6 @@
|
|||
# How to handle training data
|
||||
|
||||
## Upload data
|
||||
|
||||
## Use feedback
|
||||
|
||||
|
|
@ -17,7 +17,7 @@
|
|||
|
||||
|
||||
|
||||
<title>How to use a GreatAI service - GreatAI documentation</title>
|
||||
<title>How to handle training data - GreatAI documentation</title>
|
||||
|
||||
|
||||
|
||||
|
|
@ -70,7 +70,7 @@
|
|||
<div data-md-component="skip">
|
||||
|
||||
|
||||
<a href="#how-to-use-a-greatai-service" class="md-skip">
|
||||
<a href="#how-to-handle-training-data" class="md-skip">
|
||||
Skip to content
|
||||
</a>
|
||||
|
||||
|
|
@ -103,7 +103,7 @@
|
|||
<div class="md-header__topic" data-md-component="header-topic">
|
||||
<span class="md-ellipsis">
|
||||
|
||||
How to use a GreatAI service
|
||||
How to handle training data
|
||||
|
||||
</span>
|
||||
</div>
|
||||
|
|
@ -326,10 +326,12 @@
|
|||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" >
|
||||
<li class="md-nav__item md-nav__item--active md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" checked>
|
||||
|
||||
|
||||
|
||||
|
|
@ -360,6 +362,138 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--active">
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="toc" type="checkbox" id="__toc">
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link md-nav__link--active" for="__toc">
|
||||
How to handle training data
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<a href="./" class="md-nav__link md-nav__link--active">
|
||||
How to handle training data
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__title" for="__toc">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Table of contents
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#upload-data" class="md-nav__link">
|
||||
Upload data
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#use-feedback" class="md-nav__link">
|
||||
Use feedback
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -401,7 +535,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -463,6 +597,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
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|
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||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
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|
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<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
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<label class="md-nav__title" for="__nav_5">
|
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<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
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<ul class="md-nav__list" data-md-scrollfix>
|
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<li class="md-nav__item md-nav__item--nested">
|
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|
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
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||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
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<label class="md-nav__title" for="__nav_5_1">
|
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<span class="md-nav__icon md-icon"></span>
|
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Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
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|
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|
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|
||||
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||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
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|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -491,6 +734,28 @@
|
|||
|
||||
|
||||
|
||||
<label class="md-nav__title" for="__toc">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Table of contents
|
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</label>
|
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<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#upload-data" class="md-nav__link">
|
||||
Upload data
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#use-feedback" class="md-nav__link">
|
||||
Use feedback
|
||||
</a>
|
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|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -504,28 +769,22 @@
|
|||
|
||||
|
||||
|
||||
<a href="https://github.com/schmelczer/great-ai/edit/main/docs/how-to-guides/using-service.md" title="Edit this page" class="md-content__button md-icon">
|
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<a href="https://github.com/schmelczer/great-ai/edit/main/docs/how-to-guides/handle-training-data.md" title="Edit this page" class="md-content__button md-icon">
|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<h1 id="how-to-use-a-greatai-service">How to use a GreatAI service<a class="headerlink" href="#how-to-use-a-greatai-service" title="Permanent link">#</a></h1>
|
||||
<p>After <a href="/how-to-guides/cerate-service">creating a GreatAI service</a> by wrapping your prediction function, it's time to do some prediction.</p>
|
||||
<p>Let's use the following example:</p>
|
||||
<p>```python "type_safe_greeter.py"
|
||||
from great_ai import GreatAI</p>
|
||||
<p>@GreatAI.create
|
||||
def type_safe_greeter(your_name: str) -> str:
|
||||
return f'Hi {your_name}'
|
||||
```</p>
|
||||
<h1 id="how-to-handle-training-data">How to handle training data<a class="headerlink" href="#how-to-handle-training-data" title="Permanent link">#</a></h1>
|
||||
<h2 id="upload-data">Upload data<a class="headerlink" href="#upload-data" title="Permanent link">#</a></h2>
|
||||
<h2 id="use-feedback">Use feedback<a class="headerlink" href="#use-feedback" title="Permanent link">#</a></h2>
|
||||
|
||||
<hr>
|
||||
<div class="md-source-file">
|
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<small>
|
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|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 10, 2022</span>
|
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<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
@ -542,6 +801,42 @@ def type_safe_greeter(your_name: str) -> str:
|
|||
|
||||
<footer class="md-footer">
|
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|
||||
|
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<nav class="md-footer__inner md-grid" aria-label="Footer" >
|
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|
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|
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<a href="../use-service/" class="md-footer__link md-footer__link--prev" aria-label="Previous: How to use a GreatAI service" rel="prev">
|
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<div class="md-footer__button md-icon">
|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>
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</div>
|
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<div class="md-footer__title">
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<div class="md-ellipsis">
|
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<span class="md-footer__direction">
|
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Previous
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How to use a GreatAI service
|
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</div>
|
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</div>
|
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</a>
|
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|
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|
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|
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<a href="../large_file/" class="md-footer__link md-footer__link--next" aria-label="Next: How to use LargeFile" rel="next">
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<div class="md-footer__title">
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<div class="md-ellipsis">
|
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<span class="md-footer__direction">
|
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Next
|
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</span>
|
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How to use LargeFile
|
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</div>
|
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</div>
|
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<div class="md-footer__button md-icon">
|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M4 11v2h12l-5.5 5.5 1.42 1.42L19.84 12l-7.92-7.92L10.5 5.5 16 11H4Z"/></svg>
|
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</div>
|
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</a>
|
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|
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</nav>
|
||||
|
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<div class="md-footer-meta md-typeset">
|
||||
<div class="md-footer-meta__inner md-grid">
|
||||
<div class="md-copyright">
|
||||
|
|
@ -12,19 +12,19 @@
|
|||
<meta name="author" content="András Schmelczer">
|
||||
|
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|
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<link rel="icon" href="../media/favicon.ico">
|
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<link rel="icon" href="../../media/favicon.ico">
|
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<meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.3.9">
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|
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<title>[open(S3)](https://pypi.org/project/open-large/) - GreatAI documentation</title>
|
||||
<title>How to use LargeFile - GreatAI documentation</title>
|
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|
||||
|
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|
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<link rel="stylesheet" href="../assets/stylesheets/main.1d29e8d0.min.css">
|
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<link rel="stylesheet" href="../../assets/stylesheets/main.1d29e8d0.min.css">
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<link rel="stylesheet" href="../../assets/stylesheets/palette.cbb835fc.min.css">
|
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|
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|
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|
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|
|
@ -40,9 +40,9 @@
|
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|
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|
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|
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<link rel="stylesheet" href="../assets/_mkdocstrings.css">
|
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<link rel="stylesheet" href="../../assets/_mkdocstrings.css">
|
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|
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<script>__md_scope=new URL("..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
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<script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
|
||||
|
||||
|
||||
|
||||
|
|
@ -70,7 +70,7 @@
|
|||
<div data-md-component="skip">
|
||||
|
||||
|
||||
<a href="#opens3" class="md-skip">
|
||||
<a href="#how-to-use-largefile" class="md-skip">
|
||||
Skip to content
|
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</a>
|
||||
|
||||
|
|
@ -84,7 +84,7 @@
|
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|
||||
<header class="md-header" data-md-component="header">
|
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<nav class="md-header__inner md-grid" aria-label="Header">
|
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<a href=".." title="GreatAI documentation" class="md-header__button md-logo" aria-label="GreatAI documentation" data-md-component="logo">
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<a href="../.." title="GreatAI documentation" class="md-header__button md-logo" aria-label="GreatAI documentation" data-md-component="logo">
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|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 8a3 3 0 0 0 3-3 3 3 0 0 0-3-3 3 3 0 0 0-3 3 3 3 0 0 0 3 3m0 3.54C9.64 9.35 6.5 8 3 8v11c3.5 0 6.64 1.35 9 3.54 2.36-2.19 5.5-3.54 9-3.54V8c-3.5 0-6.64 1.35-9 3.54Z"/></svg>
|
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|
|
@ -103,7 +103,7 @@
|
|||
<div class="md-header__topic" data-md-component="header-topic">
|
||||
<span class="md-ellipsis">
|
||||
|
||||
[open(S3)](https://pypi.org/project/open-large/)
|
||||
How to use LargeFile
|
||||
|
||||
</span>
|
||||
</div>
|
||||
|
|
@ -204,7 +204,7 @@
|
|||
|
||||
<nav class="md-nav md-nav--primary" aria-label="Navigation" data-md-level="0">
|
||||
<label class="md-nav__title" for="__drawer">
|
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<a href=".." title="GreatAI documentation" class="md-nav__button md-logo" aria-label="GreatAI documentation" data-md-component="logo">
|
||||
<a href="../.." title="GreatAI documentation" class="md-nav__button md-logo" aria-label="GreatAI documentation" data-md-component="logo">
|
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|
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|
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 8a3 3 0 0 0 3-3 3 3 0 0 0-3-3 3 3 0 0 0-3 3 3 3 0 0 0 3 3m0 3.54C9.64 9.35 6.5 8 3 8v11c3.5 0 6.64 1.35 9 3.54 2.36-2.19 5.5-3.54 9-3.54V8c-3.5 0-6.64 1.35-9 3.54Z"/></svg>
|
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|
|
@ -235,7 +235,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href=".." class="md-nav__link">
|
||||
<a href="../.." class="md-nav__link">
|
||||
Overview
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -276,7 +276,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../tutorial/" class="md-nav__link">
|
||||
<a href="../../tutorial/" class="md-nav__link">
|
||||
Tutorial overview
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -290,7 +290,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../tutorial/train/" class="md-nav__link">
|
||||
<a href="../../tutorial/train/" class="md-nav__link">
|
||||
Train your model
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -304,7 +304,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../tutorial/deploy/" class="md-nav__link">
|
||||
<a href="../../tutorial/deploy/" class="md-nav__link">
|
||||
Harden and deploy your app
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -326,10 +326,12 @@
|
|||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
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<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" >
|
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
|
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|
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|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" checked>
|
||||
|
||||
|
||||
|
||||
|
|
@ -352,7 +354,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/create-service/" class="md-nav__link">
|
||||
<a href="../create-service/" class="md-nav__link">
|
||||
How to create a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -360,6 +362,219 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--active">
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="toc" type="checkbox" id="__toc">
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link md-nav__link--active" for="__toc">
|
||||
How to use LargeFile
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<a href="./" class="md-nav__link md-nav__link--active">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
|
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|
||||
|
||||
|
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|
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|
||||
|
||||
<label class="md-nav__title" for="__toc">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Table of contents
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#motivation" class="md-nav__link">
|
||||
Motivation
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#solution" class="md-nav__link">
|
||||
Solution
|
||||
</a>
|
||||
|
||||
<nav class="md-nav" aria-label="Solution">
|
||||
<ul class="md-nav__list">
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#simple-example" class="md-nav__link">
|
||||
Simple example
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#more-details" class="md-nav__link">
|
||||
More details
|
||||
</a>
|
||||
|
||||
<nav class="md-nav" aria-label="More details">
|
||||
<ul class="md-nav__list">
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#i-only-need-a-path" class="md-nav__link">
|
||||
I only need a path
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#command-line-example" class="md-nav__link">
|
||||
Command-line example
|
||||
</a>
|
||||
|
||||
<nav class="md-nav" aria-label="Command-line example">
|
||||
<ul class="md-nav__list">
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#setup" class="md-nav__link">
|
||||
Setup
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#print-the-expected-options" class="md-nav__link">
|
||||
Print the expected options
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#upload-some-files" class="md-nav__link">
|
||||
Upload some files
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#download-some-files-to-the-local-cache" class="md-nav__link">
|
||||
Download some files to the local cache
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#delete-remote-files" class="md-nav__link">
|
||||
Delete remote files
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -400,8 +615,8 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/" class="md-nav__link">
|
||||
Reference
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -414,7 +629,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/utilities/" class="md-nav__link">
|
||||
<a href="../../reference/utilities/" class="md-nav__link">
|
||||
Utilities
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -428,7 +643,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/large-file/" class="md-nav__link">
|
||||
<a href="../../reference/large-file/" class="md-nav__link">
|
||||
LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -442,7 +657,7 @@
|
|||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/views/" class="md-nav__link">
|
||||
<a href="../../reference/views/" class="md-nav__link">
|
||||
View models
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -463,8 +678,117 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../explanation/" class="md-nav__link">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
</a>
|
||||
</li>
|
||||
|
|
@ -607,13 +931,13 @@
|
|||
|
||||
|
||||
|
||||
<a href="https://github.com/schmelczer/great-ai/edit/main/docs/open_s3.md" title="Edit this page" class="md-content__button md-icon">
|
||||
<a href="https://github.com/schmelczer/great-ai/edit/main/docs/how-to-guides/large_file.md" title="Edit this page" class="md-content__button md-icon">
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<h1 id="opens3"><a href="https://pypi.org/project/open-large/">open(S3)</a><a class="headerlink" href="#opens3" title="Permanent link">#</a></h1>
|
||||
<h1 id="how-to-use-largefile">How to use LargeFile<a class="headerlink" href="#how-to-use-largefile" title="Permanent link">#</a></h1>
|
||||
<p>Storing, versioning, and downloading files from S3 made as easy as using <code>open()</code> in Python. Caching included.</p>
|
||||
<h2 id="motivation">Motivation<a class="headerlink" href="#motivation" title="Permanent link">#</a></h2>
|
||||
<p>Oftentimes, especially when working with data-heavy applications, large files can proliferate in a repository. Version controlling them is an obvious next step, however, GitHub's git LFS implementation <a href="https://docs.github.com/en/repositories/working-with-files/managing-large-files/removing-files-from-git-large-file-storage#git-lfs-objects-in-your-repository">doesn't support the deletion</a> of large files, making it easy for them to eat-up the LFS quota and explode the size of your repos.</p>
|
||||
|
|
@ -702,7 +1026,7 @@ In this case, the latest version is already in the local cache, no download is r
|
|||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 8, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
@ -719,6 +1043,42 @@ In this case, the latest version is already in the local cache, no download is r
|
|||
|
||||
<footer class="md-footer">
|
||||
|
||||
|
||||
<nav class="md-footer__inner md-grid" aria-label="Footer" >
|
||||
|
||||
|
||||
<a href="../handle-training-data/" class="md-footer__link md-footer__link--prev" aria-label="Previous: How to handle training data" rel="prev">
|
||||
<div class="md-footer__button md-icon">
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>
|
||||
</div>
|
||||
<div class="md-footer__title">
|
||||
<div class="md-ellipsis">
|
||||
<span class="md-footer__direction">
|
||||
Previous
|
||||
</span>
|
||||
How to handle training data
|
||||
</div>
|
||||
</div>
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<a href="../scraping/" class="md-footer__link md-footer__link--next" aria-label="Next: Scraping" rel="next">
|
||||
<div class="md-footer__title">
|
||||
<div class="md-ellipsis">
|
||||
<span class="md-footer__direction">
|
||||
Next
|
||||
</span>
|
||||
Scraping
|
||||
</div>
|
||||
</div>
|
||||
<div class="md-footer__button md-icon">
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M4 11v2h12l-5.5 5.5 1.42 1.42L19.84 12l-7.92-7.92L10.5 5.5 16 11H4Z"/></svg>
|
||||
</div>
|
||||
</a>
|
||||
|
||||
</nav>
|
||||
|
||||
<div class="md-footer-meta md-typeset">
|
||||
<div class="md-footer-meta__inner md-grid">
|
||||
<div class="md-copyright">
|
||||
|
|
@ -766,10 +1126,10 @@ In this case, the latest version is already in the local cache, no download is r
|
|||
<div class="md-dialog" data-md-component="dialog">
|
||||
<div class="md-dialog__inner md-typeset"></div>
|
||||
</div>
|
||||
<script id="__config" type="application/json">{"base": "..", "features": ["content.code.annotate", "content.tooltips"], "search": "../assets/javascripts/workers/search.b97dbffb.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}}</script>
|
||||
<script id="__config" type="application/json">{"base": "../..", "features": ["content.code.annotate", "content.tooltips"], "search": "../../assets/javascripts/workers/search.b97dbffb.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}}</script>
|
||||
|
||||
|
||||
<script src="../assets/javascripts/bundle.6c7ad80a.min.js"></script>
|
||||
<script src="../../assets/javascripts/bundle.6c7ad80a.min.js"></script>
|
||||
|
||||
|
||||
</body>
|
||||
|
|
@ -1,4 +1,4 @@
|
|||
# [open(S3)](https://pypi.org/project/open-large/)
|
||||
# How to use LargeFile
|
||||
|
||||
Storing, versioning, and downloading files from S3 made as easy as using `open()` in Python. Caching included.
|
||||
|
||||
|
|
@ -321,10 +321,12 @@
|
|||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" >
|
||||
<li class="md-nav__item md-nav__item--active md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_3" type="checkbox" id="__nav_3" checked>
|
||||
|
||||
|
||||
|
||||
|
|
@ -355,6 +357,98 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--active">
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="toc" type="checkbox" id="__toc">
|
||||
|
||||
|
||||
|
||||
<a href="./" class="md-nav__link md-nav__link--active">
|
||||
Scraping
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -396,7 +490,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -458,6 +552,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
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|
||||
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|
||||
|
||||
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|
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Train a domain classifier on the semantic scholar dataset
|
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||||
|
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|
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<li class="md-nav__item">
|
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|
||||
Explanation
|
||||
|
|
@ -1585,6 +1788,113 @@ async with httpx.AsyncClient(
|
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</div>
|
||||
</div>
|
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</div>
|
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</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell ">
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<div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">great_ai</span> <span class="kn">import</span> <span class="n">configure</span><span class="p">,</span> <span class="n">RouteConfig</span>
|
||||
<span class="kn">from</span> <span class="nn">great_ai</span> <span class="kn">import</span> <span class="n">GreatAI</span>
|
||||
|
||||
|
||||
<span class="nd">@GreatAI</span><span class="o">.</span><span class="n">create</span>
|
||||
<span class="k">def</span> <span class="nf">greeter</span><span class="p">(</span><span class="n">your_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="sa">f</span><span class="s2">"Hi </span><span class="si">{</span><span class="n">your_name</span><span class="si">}</span><span class="s2">"</span>
|
||||
|
||||
|
||||
<span class="n">greeter</span><span class="p">(</span><span class="s2">"Bob"</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
<div id="cell-2" class="clipboard-copy-txt">from great_ai import configure, RouteConfig
|
||||
from great_ai import GreatAI
|
||||
|
||||
|
||||
@GreatAI.create
|
||||
def greeter(your_name: str) -> str:
|
||||
return f"Hi {your_name}"
|
||||
|
||||
|
||||
greeter("Bob")</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
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|
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|
||||
|
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|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
|
||||
<pre><span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span>
|
||||
<span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | Cannot find credentials files, defaulting to using ParallelTinyDbDriver</span>
|
||||
<span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | The selected tracing database (ParallelTinyDbDriver) is not recommended for production</span>
|
||||
<span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | Cannot find credentials files, defaulting to using LargeFileLocal</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | GreatAI (v0.1.3): configured ✅</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 tracing_database: ParallelTinyDbDriver</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 large_file_implementation: LargeFileLocal</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 is_production: False</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 should_log_exception_stack: True</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 prediction_cache_size: 512</span>
|
||||
<span style="color: rgb(0,175,255)">2022-07-11 19:00:27 | INFO | 🔩 dashboard_table_size: 50</span>
|
||||
<span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | You still need to check whether you follow all best practices before trusting your deployment.</span>
|
||||
<span style="color: rgb(255,255,0)">2022-07-11 19:00:27 | WARNING | > Find out more at https://se-ml.github.io/practices</span>
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="jp-OutputArea-child">
|
||||
|
||||
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[1]:</div>
|
||||
|
||||
|
||||
|
||||
|
||||
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
|
||||
<pre>Trace[str]({'created': '2022-07-11T17:00:27.064568',
|
||||
'exception': None,
|
||||
'feedback': None,
|
||||
'logged_values': {'arg:your_name:length': 3, 'arg:your_name:value': 'Bob'},
|
||||
'models': [],
|
||||
'original_execution_time_ms': 0.0896,
|
||||
'output': 'Hi Bob',
|
||||
'tags': ['greeter', 'online', 'development'],
|
||||
'trace_id': '8ff5b268-2613-4e85-96ae-f248666a051f'})</pre>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -1596,7 +1906,7 @@ async with httpx.AsyncClient(
|
|||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 9, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
@ -1613,6 +1923,42 @@ async with httpx.AsyncClient(
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|||
|
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<footer class="md-footer">
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|
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|
|
@ -16,13 +16,88 @@
|
|||
") as client:\n",
|
||||
" pass"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | Cannot find credentials files, defaulting to using ParallelTinyDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | The selected tracing database (ParallelTinyDbDriver) is not recommended for production\u001b[0m\n",
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | Cannot find credentials files, defaulting to using LargeFileLocal\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | GreatAI (v0.1.3): configured ✅\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 tracing_database: ParallelTinyDbDriver\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 large_file_implementation: LargeFileLocal\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 is_production: False\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 should_log_exception_stack: True\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 prediction_cache_size: 512\u001b[0m\n",
|
||||
"\u001b[38;5;39m2022-07-11 19:00:27 | INFO | 🔩 dashboard_table_size: 50\u001b[0m\n",
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | You still need to check whether you follow all best practices before trusting your deployment.\u001b[0m\n",
|
||||
"\u001b[38;5;226m2022-07-11 19:00:27 | WARNING | > Find out more at https://se-ml.github.io/practices\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Trace[str]({'created': '2022-07-11T17:00:27.064568',\n",
|
||||
" 'exception': None,\n",
|
||||
" 'feedback': None,\n",
|
||||
" 'logged_values': {'arg:your_name:length': 3, 'arg:your_name:value': 'Bob'},\n",
|
||||
" 'models': [],\n",
|
||||
" 'original_execution_time_ms': 0.0896,\n",
|
||||
" 'output': 'Hi Bob',\n",
|
||||
" 'tags': ['greeter', 'online', 'development'],\n",
|
||||
" 'trace_id': '8ff5b268-2613-4e85-96ae-f248666a051f'})"
|
||||
]
|
||||
},
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from great_ai import configure, RouteConfig\n",
|
||||
"from great_ai import GreatAI\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"@GreatAI.create\n",
|
||||
"def greeter(your_name: str) -> str:\n",
|
||||
" return f\"Hi {your_name}\"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"greeter(\"Bob\")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.10.4 ('.env': venv)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"orig_nbformat": 4
|
||||
"language_info": {
|
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"codemirror_mode": {
|
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"name": "ipython",
|
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"version": 3
|
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},
|
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"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.4"
|
||||
},
|
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"orig_nbformat": 4,
|
||||
"vscode": {
|
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"interpreter": {
|
||||
"hash": "02dd6d3afbfa9fbbe1037d64ad9014965528a1ccad21929d6e72f466389a68ad"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
|
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|
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|
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@ -1,586 +0,0 @@
|
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|
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1098
how-to-guides/use-service/index.html
Normal file
1098
how-to-guides/use-service/index.html
Normal file
File diff suppressed because it is too large
Load diff
131
how-to-guides/use-service/use-service.md
Normal file
131
how-to-guides/use-service/use-service.md
Normal file
|
|
@ -0,0 +1,131 @@
|
|||
# How to use a GreatAI service
|
||||
|
||||
After [creating a GreatAI service](/how-to-guides/create-service) by wrapping your prediction function, and optionally [configuring it](/how-to-guides/configure-service), it's time to do some prediction.
|
||||
|
||||
Let's take the following example:
|
||||
|
||||
```python title="greeter.py"
|
||||
from great_ai import GreatAI
|
||||
|
||||
@GreatAI.create
|
||||
def greeter(your_name: str) -> str:
|
||||
return f'Hi {your_name}'
|
||||
```
|
||||
|
||||
## One-off prediction
|
||||
|
||||
Even though `greeter` is now an instance of [GreatAI][great_ai.GreatAI], you can continue using it as a regular function.
|
||||
|
||||
```python
|
||||
>>> greeter('Bob')
|
||||
Trace[str]({'created': '2022-07-11T14:31:46.183764',
|
||||
'exception': None,
|
||||
'feedback': None,
|
||||
'logged_values': {'arg:your_name:length': 3, 'arg:your_name:value': 'Bob'},
|
||||
'models': [],
|
||||
'original_execution_time_ms': 0.0381,
|
||||
'output': 'Hi Bob',
|
||||
'tags': ['greeter', 'online', 'development'],
|
||||
'trace_id': '7c284fd7-7f0d-4464-b5f8-3ef126df34af'})
|
||||
```
|
||||
|
||||
As you can see, the original return value is wrapped in a [Trace][great_ai.Trace] object (which is also persisted in your database of choice). You can access the original value under the `output` property.
|
||||
|
||||
## Online prediction
|
||||
|
||||
Likely, the main way you would like to expose your model is through an HTTP API. [@GreatAI.create][great_ai.GreatAI.create] scaffolds many REST API endpoints for your model and creates a [FastAPI](https://fastapi.tiangolo.com/){ target=_blank } app available under [GreatAI.app][great_ai.GreatAI]. This can be served using [uvicorn](https://www.uvicorn.org/){ target=_blank } or any other [ASGI server](https://asgi.readthedocs.io/en/latest/){ target=_blank }.
|
||||
|
||||
Since most ML code lives in [Jupyter](https://jupyter.org/){ target=_blank } notebooks, therefore, deploying a notebook containing the inference function is supported. To this end, `uvicorn` is wrapped by the `great-ai` command-line utility which, among others, takes care of feeding a notebook into `uvicorn`. It also supports auto-reloading.
|
||||
|
||||
### In development
|
||||
|
||||
```sh
|
||||
great-ai greeter.py
|
||||
```
|
||||
|
||||
!!! success
|
||||
Your model is accessible at [localhost:6060](http:/127.0.0.1:6060){ target=_blank }.
|
||||
|
||||
Some configuration options are also supported.
|
||||
|
||||
```sh
|
||||
great-ai greeter.py --port 8000 --host 127.0.0.1 --timeout_keep_alive 10
|
||||
```
|
||||
> For more options (but no Notebook support, use [uvicorn](https://www.uvicorn.org/){ target=_blank })
|
||||
|
||||
### In production
|
||||
|
||||
There are three main approaches for deploying a GreatAI service.
|
||||
|
||||
#### Manual deployment
|
||||
|
||||
The app is run in *production-mode* if the value of the `ENVIRONMENT` environment variable is set to `production`.
|
||||
|
||||
```sh
|
||||
ENVIRONMENT=production great-ai greeter.py
|
||||
```
|
||||
|
||||
Simply run `ENVIRONMENT=production great-ai deploy.ipynb` in the command-line of a production machine.
|
||||
> This is the crudest approach, however, it might be fitting for some contexts.
|
||||
|
||||
#### Containerised deployment
|
||||
|
||||
Run the notebook directly in a container or create a service for it using your favourite container orchestrator.
|
||||
|
||||
```sh
|
||||
docker run -p 6060:6060 --volume `pwd`:/app --rm \
|
||||
schmelczera/great-ai deploy.ipynb
|
||||
```
|
||||
> You can replace ``pwd`` with the path to your code's folder.
|
||||
|
||||
#### Use a Platform-as-a-Service
|
||||
|
||||
Similarly to the previous approach, your code will run in a container. However, instead of manually managing it, you can just choose from a plethora of PaaS providers (such as [DO App platform](https://www.digitalocean.com/products/app-platform){ target=_blank } or [MLEM](https://mlem.ai/){ target=_blank }) that take a Docker image as a source and handle the rest of the deployment.
|
||||
|
||||
To this end, you can also create a custom Docker image. It is especially useful if you have third-party dependencies, such as [PyTorch](https://pytorch.org/){ target=_blank } or [TensorFlow](https://www.tensorflow.org/){ target=_blank }.
|
||||
|
||||
```Dockerfile
|
||||
FROM schmelczera/great-ai:latest
|
||||
|
||||
# Remove this block if you don't have a requirements.txt
|
||||
COPY requirements.txt ./
|
||||
RUN pip install --no-cache-dir --requirement requirements.txt
|
||||
|
||||
# If you store your models in S3 or GridFS, it may be a
|
||||
# good idea to cache them in the image so that you don't
|
||||
# have to download it each time a container starts
|
||||
RUN large-file --backend s3 --secrets s3.ini --cache my-domain-predictor
|
||||
|
||||
# Add you application code to the image
|
||||
COPY . .
|
||||
|
||||
# The default ENTRYPOINT is great-ai, specify it's argument using CMD
|
||||
CMD ["deploy.ipynb"]
|
||||
|
||||
```
|
||||
|
||||
## Batch prediction
|
||||
|
||||
Processing larger amounts of data on a single machine is made easy by the [GreatAI][great_ai.GreatAI]'s [process_batch][great_ai.GreatAI.process_batch] method. This relies on multiprocessing ([parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map]) to take full advantage of all available CPU-cores.
|
||||
|
||||
```python
|
||||
>>> greeter.process_batch(['Alice', 'Bob'])
|
||||
[Trace[str]({'created': '2022-07-11T14:36:37.119183',
|
||||
'exception': None,
|
||||
'feedback': None,
|
||||
'logged_values': {'arg:your_name:length': 5, 'arg:your_name:value': 'Alice'},
|
||||
'models': [],
|
||||
'original_execution_time_ms': 0.1251,
|
||||
'output': 'Hi Alice',
|
||||
'tags': ['greeter', 'online', 'development'],
|
||||
'trace_id': '90ffa15f-e839-41c4-8e7a-3211168bc138'}),
|
||||
Trace[str]({'created': '2022-07-11T14:36:37.166659',
|
||||
'exception': None,
|
||||
'feedback': None,
|
||||
'logged_values': {'arg:your_name:length': 3, 'arg:your_name:value': 'Bob'},
|
||||
'models': [],
|
||||
'original_execution_time_ms': 0.0571,
|
||||
'output': 'Hi Bob',
|
||||
'tags': ['greeter', 'online', 'development'],
|
||||
'trace_id': 'f48e94c7-0815-48b3-a864-41349d3dae84'})]
|
||||
```
|
||||
|
|
@ -1,14 +0,0 @@
|
|||
# How to use a GreatAI service
|
||||
|
||||
After [creating a GreatAI service](/how-to-guides/cerate-service) by wrapping your prediction function, it's time to do some prediction.
|
||||
|
||||
Let's use the following example:
|
||||
|
||||
```python "type_safe_greeter.py"
|
||||
from great_ai import GreatAI
|
||||
|
||||
@GreatAI.create
|
||||
def type_safe_greeter(your_name: str) -> str:
|
||||
return f'Hi {your_name}'
|
||||
```
|
||||
|
||||
211
index.html
211
index.html
|
|
@ -425,6 +425,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -466,7 +550,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -528,6 +612,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
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|
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|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
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|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
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Examples
|
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<span class="md-nav__icon md-icon"></span>
|
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</label>
|
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|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
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|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -622,12 +815,11 @@
|
|||
</div>
|
||||
|
||||
<p><a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar line coverage" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=coverage" /></a>
|
||||
<a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar technical debt" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=sqale_index" /></a>
|
||||
<a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar LoC" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=ncloc" /></a>
|
||||
<a href="https://github.com/schmelczer/great-ai/actions/workflows/test.yml"><img alt="Test" src="https://github.com/schmelczer/great-ai/actions/workflows/test.yml/badge.svg" /></a>
|
||||
<a href="https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml"><img alt="Publish on PyPI" src="https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml/badge.svg" /></a>
|
||||
<a href="https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml"><img alt="Publish on DockerHub" src="https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml/badge.svg" /></a>
|
||||
<a href="https://pepy.tech/project/great-ai"><img alt="Downloads" src="https://pepy.tech/badge/great-ai/month" /></a></p>
|
||||
<a href="https://badge.fury.io/py/great-ai"><img alt="PyPI version" src="https://badge.fury.io/py/great-ai.svg" /></a>
|
||||
<a href="https://pepy.tech/project/great-ai"><img alt="Downloads" src="https://pepy.tech/badge/great-ai/month" /></a>
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/schmelczera/great-ai" /></p>
|
||||
<p>Applying AI is becoming increasingly easier but many case studies have shown that these applications are often deployed poorly. This may lead to suboptimal performance and to introducing <a href="https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction" target="_blank">unintended biases</a>. GreatAI helps fixing this by allowing you to <mark>easily transform your prototype AI code into production-ready software</mark>.</p>
|
||||
<details class="quote">
|
||||
<summary>Case studies</summary>
|
||||
|
|
@ -656,6 +848,7 @@
|
|||
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Deployable Jupyter Notebooks</li>
|
||||
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Dashboard for high-level overview and analysing traces</li>
|
||||
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Support for direct file input</li>
|
||||
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Support for PostgreSQL</li>
|
||||
</ul>
|
||||
<h2 id="hello-world">Hello world<a class="headerlink" href="#hello-world" title="Permanent link">#</a></h2>
|
||||
<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a>pip install great-ai
|
||||
|
|
@ -698,7 +891,7 @@
|
|||
</div>
|
||||
<h2 id="why-is-this-great">Why is this GREAT?<a class="headerlink" href="#why-is-this-great" title="Permanent link">#</a></h2>
|
||||
<p><img alt="scope of GreatAI" src="media/scope-simple.drawio.svg" /></p>
|
||||
<p>GreatAI fits between the prototype and deployment phase of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:</p>
|
||||
<p>GreatAI fits between the prototype and deployment phases of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:</p>
|
||||
<ul>
|
||||
<li><strong>G</strong>eneral: use any Python library without restriction</li>
|
||||
<li><strong>R</strong>obust: have error-handling and well-tested utilities out-of-the-box </li>
|
||||
|
|
@ -715,15 +908,15 @@
|
|||
</div>
|
||||
<h2 id="production-use">Production use<a class="headerlink" href="#production-use" title="Permanent link">#</a></h2>
|
||||
<p>GreatAI has been battle-tested on the core platform services of <a href="https://www.scoutinscience.com/" target="_blank">ScoutinScience</a>.</p>
|
||||
<p><img alt="ScoutinScience logo" src="media/scoutinscience.svg#only-light" />
|
||||
<img alt="ScoutinScience logo" src="media/scoutinscience-white.svg#only-dark" /></p>
|
||||
<p><img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience.svg#only-light" />
|
||||
<img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience-white.svg#only-dark" /></p>
|
||||
|
||||
<hr>
|
||||
<div class="md-source-file">
|
||||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 10, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
|
|||
13
index.md
13
index.md
|
|
@ -4,12 +4,12 @@
|
|||
</div>
|
||||
|
||||
[](https://sonar.scoutinscience.com/dashboard?id=great-ai)
|
||||
[](https://sonar.scoutinscience.com/dashboard?id=great-ai)
|
||||
[](https://sonar.scoutinscience.com/dashboard?id=great-ai)
|
||||
[](https://github.com/schmelczer/great-ai/actions/workflows/test.yml)
|
||||
[](https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml)
|
||||
[](https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml)
|
||||
[](https://badge.fury.io/py/great-ai)
|
||||
[](https://pepy.tech/project/great-ai)
|
||||
|
||||
|
||||
|
||||
Applying AI is becoming increasingly easier but many case studies have shown that these applications are often deployed poorly. This may lead to suboptimal performance and to introducing [unintended biases](https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction){ target=_blank }. GreatAI helps fixing this by allowing you to ==easily transform your prototype AI code into production-ready software==.
|
||||
|
||||
|
|
@ -42,6 +42,7 @@ Applying AI is becoming increasingly easier but many case studies have shown tha
|
|||
- [x] Deployable Jupyter Notebooks
|
||||
- [x] Dashboard for high-level overview and analysing traces
|
||||
- [ ] Support for direct file input
|
||||
- [ ] Support for PostgreSQL
|
||||
|
||||
## Hello world
|
||||
|
||||
|
|
@ -85,7 +86,7 @@ great-ai hello-world.py
|
|||
|
||||
|
||||
|
||||
GreatAI fits between the prototype and deployment phase of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:
|
||||
GreatAI fits between the prototype and deployment phases of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:
|
||||
|
||||
- **G**eneral: use any Python library without restriction
|
||||
- **R**obust: have error-handling and well-tested utilities out-of-the-box
|
||||
|
|
@ -110,5 +111,5 @@ However, research indicates that professionals rarely use them. This may be due
|
|||
|
||||
GreatAI has been battle-tested on the core platform services of [ScoutinScience](https://www.scoutinscience.com/){ target=_blank }.
|
||||
|
||||
|
||||
|
||||
{ loading=lazy }
|
||||
{ loading=lazy }
|
||||
|
|
|
|||
BIN
objects.inv
BIN
objects.inv
Binary file not shown.
2791
reference/index.html
2791
reference/index.html
File diff suppressed because it is too large
Load diff
|
|
@ -1,4 +1,4 @@
|
|||
# Reference
|
||||
# GreatAI reference
|
||||
|
||||
```python
|
||||
from great_ai import *
|
||||
|
|
@ -54,3 +54,17 @@ from great_ai import *
|
|||
::: great_ai.delete_ground_truth
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
## Tracing databases
|
||||
|
||||
::: great_ai.TracingDatabaseDriver
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.MongoDbDriver
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.ParallelTinyDbDriver
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load diff
|
|
@ -3,3 +3,19 @@
|
|||
```python
|
||||
from great_ai.large_file import *
|
||||
```
|
||||
|
||||
::: great_ai.large_file.LargeFileLocal
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.large_file.LargeFileS3
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.large_file.LargeFileMongo
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.large_file.LargeFileBase
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load diff
|
|
@ -10,22 +10,26 @@ Well-tested tools that can be used in production with confidence. The toolbox of
|
|||
|
||||
::: great_ai.utilities.clean
|
||||
::: great_ai.utilities.get_sentences
|
||||
::: great_ai.utilities.language.predict_language
|
||||
::: great_ai.utilities.language.is_english
|
||||
::: great_ai.utilities.language.english_name_of_language
|
||||
::: great_ai.utilities.evaluate_ranking.evaluate_ranking
|
||||
::: great_ai.utilities.predict_language
|
||||
::: great_ai.utilities.is_english
|
||||
::: great_ai.utilities.english_name_of_language
|
||||
::: great_ai.utilities.evaluate_ranking
|
||||
|
||||
## Parallel processing
|
||||
|
||||
Multiprocessing and multithreading-based parallelism with support for `async` functions. Its main purpose is to implement [great_ai.GreatAI.process_batch][], however, the parallel processing functions are also convenient for covering other types of mapping needs with a friendlier API than [joblib](https://joblib.readthedocs.io/en/latest/parallel.html){ target=_blank } or [multiprocess](https://pypi.org/project/multiprocess/){ target=_blank }.
|
||||
|
||||
::: great_ai.utilities.parallel_map.simple_parallel_map
|
||||
::: great_ai.utilities.simple_parallel_map
|
||||
options:
|
||||
show_root_heading: true
|
||||
::: great_ai.utilities.parallel_map.parallel_map
|
||||
::: great_ai.utilities.parallel_map.threaded_parallel_map
|
||||
::: great_ai.utilities.threaded_parallel_map
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
## Composable parallel processing
|
||||
|
||||
Because both [threaded_parallel_map][great_ai.utilities.parallel_map.threaded_parallel_map.threaded_parallel_map] and [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map] have a streaming interface, it is easy to compose them and end up with, for example, a process for each CPU core with its own thread-pool or event-loop. Longer pipelines are also easy to imagine. The chunking methods help in these compositions.
|
||||
Because both [threaded_parallel_map][great_ai.utilities.parallel_map.threaded_parallel_map.threaded_parallel_map] and [parallel_map][great_ai.utilities.parallel_map.parallel_map] have a streaming interface, it is easy to compose them and end up with, for example, a process for each CPU core with its own thread-pool or event-loop. Longer pipelines are also easy to imagine. The chunking methods help in these compositions.
|
||||
|
||||
For more info, check-out [the scraping guide](/how-to-guides/scraping).
|
||||
|
||||
|
|
@ -34,5 +38,10 @@ For more info, check-out [the scraping guide](/how-to-guides/scraping).
|
|||
|
||||
## Operations
|
||||
|
||||
::: great_ai.utilities.config_file.config_file
|
||||
::: great_ai.utilities.logger.get_logger
|
||||
::: great_ai.utilities.ConfigFile
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
||||
::: great_ai.utilities.get_logger
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
|
|
|||
|
|
@ -360,6 +360,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -403,7 +487,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -453,10 +537,150 @@
|
|||
|
||||
|
||||
|
||||
<label class="md-nav__link md-nav__link--active" for="__toc">
|
||||
View models
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<a href="./" class="md-nav__link md-nav__link--active">
|
||||
View models
|
||||
</a>
|
||||
|
||||
|
||||
|
||||
<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__title" for="__toc">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Table of contents
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#great_ai.Trace" class="md-nav__link">
|
||||
Trace
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
|
@ -503,6 +727,21 @@
|
|||
|
||||
|
||||
|
||||
<label class="md-nav__title" for="__toc">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Table of contents
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#great_ai.Trace" class="md-nav__link">
|
||||
Trace
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
||||
</nav>
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -529,6 +768,13 @@
|
|||
|
||||
|
||||
|
||||
<h3 id="great_ai.Trace" class="doc doc-heading">
|
||||
<code>Trace</code>
|
||||
|
||||
|
||||
<a href="#great_ai.Trace" class="headerlink" title="Permanent link">#</a></h3>
|
||||
|
||||
|
||||
<div class="doc doc-contents first">
|
||||
<p class="doc doc-class-bases">
|
||||
Bases: <code><span title="typing.Generic">Generic</span>[<span title="great_ai.views.trace.T">T</span>]</code>, <code><span title="great_ai.views.hashable_base_model.HashableBaseModel">HashableBaseModel</span></code></p>
|
||||
|
|
@ -610,7 +856,9 @@
|
|||
<span class="normal"><a href="#__codelineno-0-82">82</a></span>
|
||||
<span class="normal"><a href="#__codelineno-0-83">83</a></span>
|
||||
<span class="normal"><a href="#__codelineno-0-84">84</a></span>
|
||||
<span class="normal"><a href="#__codelineno-0-85">85</a></span></pre></div></td><td class="code"><div><pre><span></span><code><a id="__codelineno-0-12" name="__codelineno-0-12"></a><span class="k">class</span> <span class="nc">Trace</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">T</span><span class="p">],</span> <span class="n">HashableBaseModel</span><span class="p">):</span>
|
||||
<span class="normal"><a href="#__codelineno-0-85">85</a></span>
|
||||
<span class="normal"><a href="#__codelineno-0-86">86</a></span>
|
||||
<span class="normal"><a href="#__codelineno-0-87">87</a></span></pre></div></td><td class="code"><div><pre><span></span><code><a id="__codelineno-0-12" name="__codelineno-0-12"></a><span class="k">class</span> <span class="nc">Trace</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">T</span><span class="p">],</span> <span class="n">HashableBaseModel</span><span class="p">):</span>
|
||||
<a id="__codelineno-0-13" name="__codelineno-0-13"></a> <span class="n">trace_id</span><span class="p">:</span> <span class="nb">str</span>
|
||||
<a id="__codelineno-0-14" name="__codelineno-0-14"></a> <span class="n">created</span><span class="p">:</span> <span class="nb">str</span>
|
||||
<a id="__codelineno-0-15" name="__codelineno-0-15"></a> <span class="n">original_execution_time_ms</span><span class="p">:</span> <span class="nb">float</span>
|
||||
|
|
@ -683,7 +931,9 @@
|
|||
<a id="__codelineno-0-82" name="__codelineno-0-82"></a> <span class="p">}</span>
|
||||
<a id="__codelineno-0-83" name="__codelineno-0-83"></a>
|
||||
<a id="__codelineno-0-84" name="__codelineno-0-84"></a> <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
|
||||
<a id="__codelineno-0-85" name="__codelineno-0-85"></a> <span class="k">return</span> <span class="sa">f</span><span class="s2">"Trace[</span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">output</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2">](</span><span class="si">{</span><span class="n">pformat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dict</span><span class="p">(),</span> <span class="n">indent</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">compact</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span>
|
||||
<a id="__codelineno-0-85" name="__codelineno-0-85"></a> <span class="k">return</span> <span class="sa">f</span><span class="s2">"""Trace[</span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">output</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2">](</span><span class="si">{</span>
|
||||
<a id="__codelineno-0-86" name="__codelineno-0-86"></a> <span class="n">pformat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dict</span><span class="p">(),</span> <span class="n">indent</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">compact</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">'{ '</span><span class="p">,</span> <span class="s1">'{'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<a id="__codelineno-0-87" name="__codelineno-0-87"></a> <span class="si">}</span><span class="s2">)"""</span>
|
||||
</code></pre></div></td></tr></table></div>
|
||||
</details>
|
||||
|
||||
|
|
@ -712,7 +962,7 @@
|
|||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 10, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
@ -749,13 +999,13 @@
|
|||
|
||||
|
||||
|
||||
<a href="../../explanation/" class="md-footer__link md-footer__link--next" aria-label="Next: Explanation" rel="next">
|
||||
<a href="../../examples/simple/data/" class="md-footer__link md-footer__link--next" aria-label="Next: Train a domain classifier on the semantic scholar dataset" rel="next">
|
||||
<div class="md-footer__title">
|
||||
<div class="md-ellipsis">
|
||||
<span class="md-footer__direction">
|
||||
Next
|
||||
</span>
|
||||
Explanation
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</div>
|
||||
</div>
|
||||
<div class="md-footer__button md-icon">
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
# View models
|
||||
|
||||
::: great_ai.views.trace.Trace
|
||||
::: great_ai.Trace
|
||||
options:
|
||||
show_root_heading: true
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -95,4 +95,9 @@
|
|||
<lastmod>2022-07-11</lastmod>
|
||||
<changefreq>daily</changefreq>
|
||||
</url>
|
||||
<url>
|
||||
<loc>None</loc>
|
||||
<lastmod>2022-07-11</lastmod>
|
||||
<changefreq>daily</changefreq>
|
||||
</url>
|
||||
</urlset>
|
||||
BIN
sitemap.xml.gz
BIN
sitemap.xml.gz
Binary file not shown.
|
|
@ -131,49 +131,7 @@
|
|||
"source": [
|
||||
"Now that you've made sure your application is hardened enough for the intended use case, it is time to deploy it. The responsibilities of GreatAI end when it wraps your inference function and model into a production-ready service. You're given the freedom and responsibility to deploy this service. Fortunately, you (or your organisation) probably already has an established routine for deploying services.\n",
|
||||
"\n",
|
||||
"There are three main approaches to deploy a GreatAI service.\n",
|
||||
"\n",
|
||||
"### Manual deployment\n",
|
||||
"\n",
|
||||
"Simply run `ENVIRONMENT=production great-ai deploy.ipynb` in the command-line of a production machine.\n",
|
||||
"> This is the crudest approach, however, it might be fitting for some contexts.\n",
|
||||
"\n",
|
||||
"### Containerised deployment\n",
|
||||
"\n",
|
||||
"Run the notebook directly in a container or create a service for it using your favourite orchestrator.\n",
|
||||
"\n",
|
||||
"```sh\n",
|
||||
"docker run \\\n",
|
||||
" -p 6060:6060 \\\n",
|
||||
" --volume `pwd`:/app \\\n",
|
||||
" --rm \\\n",
|
||||
" schmelczera/great-ai deploy.ipynb\n",
|
||||
"```\n",
|
||||
"> You can replace ``pwd`` with the path to your code's folder.\n",
|
||||
"\n",
|
||||
"#### Use a Platform-as-a-Service\n",
|
||||
"\n",
|
||||
"Similarly to the previous approach, your code will run in a container. However, instead of manually managing it, you can just choose from a plethora of PaaS providers that take a Docker image as a source and handle the rest of the deployment.\n",
|
||||
"\n",
|
||||
"To this end, you can also create a custom Docker image. It is especially useful if you have third-party dependencies, such as pytorch or tensorflow.\n",
|
||||
"\n",
|
||||
"```Dockerfile\n",
|
||||
"FROM schmelczera/great-ai:latest\n",
|
||||
"\n",
|
||||
"# Remove this block if you don't have a requirements.txt\n",
|
||||
"COPY requirements.txt ./ \n",
|
||||
"RUN pip install --no-cache-dir --requirement requirements.txt\n",
|
||||
"\n",
|
||||
"# If you store your models in S3 or GridFS, it may be a \n",
|
||||
"# good idea to # cache them in the image so that you don't\n",
|
||||
"# have to download it each time a container starts\n",
|
||||
"# RUN large-file --backend s3 --secrets s3.ini --cache my-domain-predictor\n",
|
||||
"\n",
|
||||
"COPY . .\n",
|
||||
"\n",
|
||||
"CMD [\"deploy.ipynb\"]\n",
|
||||
"\n",
|
||||
"```"
|
||||
"There are three main approaches to deploy a GreatAI service: For more info about them, check out [the deployment how-to](/how-to-guides/use-service)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
|
|||
|
|
@ -340,30 +340,10 @@
|
|||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#manual-deployment" class="md-nav__link">
|
||||
Manual deployment
|
||||
<a href="#go-back-to-the-summary" class="md-nav__link">
|
||||
Go back to the summary
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#containerised-deployment" class="md-nav__link">
|
||||
Containerised deployment
|
||||
</a>
|
||||
|
||||
<nav class="md-nav" aria-label="Containerised deployment">
|
||||
<ul class="md-nav__list">
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#use-a-platform-as-a-service" class="md-nav__link">
|
||||
Use a Platform-as-a-Service
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
|
@ -423,6 +403,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -464,7 +528,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -526,6 +590,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -561,30 +734,10 @@
|
|||
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#manual-deployment" class="md-nav__link">
|
||||
Manual deployment
|
||||
<a href="#go-back-to-the-summary" class="md-nav__link">
|
||||
Go back to the summary
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#containerised-deployment" class="md-nav__link">
|
||||
Containerised deployment
|
||||
</a>
|
||||
|
||||
<nav class="md-nav" aria-label="Containerised deployment">
|
||||
<ul class="md-nav__list">
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="#use-a-platform-as-a-service" class="md-nav__link">
|
||||
Use a Platform-as-a-Service
|
||||
</a>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
|
||||
</li>
|
||||
|
||||
</ul>
|
||||
|
|
@ -1899,36 +2052,7 @@ def predict_domain(sentence, model):
|
|||
<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
|
||||
</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown">
|
||||
<p>Now that you've made sure your application is hardened enough for the intended use case, it is time to deploy it. The responsibilities of GreatAI end when it wraps your inference function and model into a production-ready service. You're given the freedom and responsibility to deploy this service. Fortunately, you (or your organisation) probably already has an established routine for deploying services.</p>
|
||||
<p>There are three main approaches to deploy a GreatAI service.</p>
|
||||
<h3 id="manual-deployment">Manual deployment<a class="anchor-link" href="#manual-deployment">¶</a></h3><p>Simply run <code>ENVIRONMENT=production great-ai deploy.ipynb</code> in the command-line of a production machine.</p>
|
||||
<blockquote><p>This is the crudest approach, however, it might be fitting for some contexts.</p>
|
||||
</blockquote>
|
||||
<h3 id="containerised-deployment">Containerised deployment<a class="anchor-link" href="#containerised-deployment">¶</a></h3><p>Run the notebook directly in a container or create a service for it using your favourite orchestrator.</p>
|
||||
<div class="highlight"><pre><span></span>docker run <span class="se">\</span>
|
||||
-p <span class="m">6060</span>:6060 <span class="se">\</span>
|
||||
--volume <span class="sb">`</span><span class="nb">pwd</span><span class="sb">`</span>:/app <span class="se">\</span>
|
||||
--rm <span class="se">\</span>
|
||||
schmelczera/great-ai deploy.ipynb
|
||||
</pre></div>
|
||||
<blockquote><p>You can replace <code>pwd</code> with the path to your code's folder.</p>
|
||||
</blockquote>
|
||||
<h4 id="use-a-platform-as-a-service">Use a Platform-as-a-Service<a class="anchor-link" href="#use-a-platform-as-a-service">¶</a></h4><p>Similarly to the previous approach, your code will run in a container. However, instead of manually managing it, you can just choose from a plethora of PaaS providers that take a Docker image as a source and handle the rest of the deployment.</p>
|
||||
<p>To this end, you can also create a custom Docker image. It is especially useful if you have third-party dependencies, such as pytorch or tensorflow.</p>
|
||||
<div class="highlight"><pre><span></span><span class="k">FROM</span><span class="w"> </span><span class="s">schmelczera/great-ai:latest</span>
|
||||
|
||||
<span class="c"># Remove this block if you don't have a requirements.txt</span>
|
||||
<span class="k">COPY</span><span class="w"> </span>requirements.txt ./
|
||||
<span class="k">RUN</span><span class="w"> </span>pip install --no-cache-dir --requirement requirements.txt
|
||||
|
||||
<span class="c"># If you store your models in S3 or GridFS, it may be a </span>
|
||||
<span class="c"># good idea to # cache them in the image so that you don't</span>
|
||||
<span class="c"># have to download it each time a container starts</span>
|
||||
<span class="c"># RUN large-file --backend s3 --secrets s3.ini --cache my-domain-predictor</span>
|
||||
|
||||
<span class="k">COPY</span><span class="w"> </span>. .
|
||||
|
||||
<span class="k">CMD</span><span class="w"> </span><span class="p">[</span><span class="s2">"deploy.ipynb"</span><span class="p">]</span>
|
||||
</pre></div>
|
||||
<p>There are three main approaches to deploy a GreatAI service: For more info about them, check out <a href="/how-to-guides/use-service">the deployment how-to</a>.</p>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -1954,7 +2078,7 @@ def predict_domain(sentence, model):
|
|||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 9, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
|
|||
|
|
@ -437,6 +437,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -478,7 +562,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -540,6 +624,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
@ -657,7 +850,7 @@
|
|||
</div>
|
||||
<h2 id="summary">Summary<a class="headerlink" href="#summary" title="Permanent link">#</a></h2>
|
||||
<h3 id="the-training-notebook">The <a href="train/">training notebook</a><a class="headerlink" href="#the-training-notebook" title="Permanent link">#</a></h3>
|
||||
<p>We load and preprocess the dataset while relying on [great_ai.utilities.clean][] for the heavy-lifting. Additionally, the preprocessing is parallelised using <a class="autorefs autorefs-internal" href="../reference/utilities/#great_ai.utilities.parallel_map.simple_parallel_map.simple_parallel_map">great_ai.utilities.simple_parallel_map</a></p>
|
||||
<p>We load and preprocess the dataset while relying on [great_ai.utilities.clean][] for the heavy-lifting. Additionally, the preprocessing is parallelised using <a class="autorefs autorefs-internal" href="../reference/utilities/#great_ai.utilities.simple_parallel_map">great_ai.utilities.simple_parallel_map</a></p>
|
||||
<p>After training and evaluating a model, it is exported using <a class="autorefs autorefs-internal" href="../reference/#great_ai.save_model">great_ai.save_model</a>.</p>
|
||||
<details class="tip">
|
||||
<summary>Remote storage</summary>
|
||||
|
|
@ -692,14 +885,14 @@
|
|||
<li><a class="autorefs autorefs-internal" href="../reference/#great_ai.use_model">@use_model</a> loads and injects your model into the <code>predict_domain</code> function's <code>model</code> argument.
|
||||
You can freely reference it knowing that it is always given to the function.</li>
|
||||
</ol>
|
||||
<p>Finally, we deploy the model, inference function, and the GreatAI wrapping all of these. For that we either use: <code>great-ai deploy.ipynb</code> or build a Docker image.</p>
|
||||
<p>Finally, we test the model's inference function through the GreatAI dashboard. <a href="/how-to-guides/use-service">The only thing left is to deploy the hardened-service.</a></p>
|
||||
|
||||
<hr>
|
||||
<div class="md-source-file">
|
||||
<small>
|
||||
|
||||
Last update:
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 10, 2022</span>
|
||||
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
|
||||
|
||||
|
||||
</small>
|
||||
|
|
|
|||
|
|
@ -70,4 +70,4 @@ def predict_domain(sentence, model):
|
|||
1. [@use_model][great_ai.use_model] loads and injects your model into the `predict_domain` function's `model` argument.
|
||||
You can freely reference it knowing that it is always given to the function.
|
||||
|
||||
Finally, we deploy the model, inference function, and the GreatAI wrapping all of these. For that we either use: `great-ai deploy.ipynb` or build a Docker image.
|
||||
Finally, we test the model's inference function through the GreatAI dashboard. [The only thing left is to deploy the hardened-service.](/how-to-guides/use-service)
|
||||
|
|
@ -403,6 +403,90 @@
|
|||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/configure-service/" class="md-nav__link">
|
||||
How to configure GreatAI
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/use-service/" class="md-nav__link">
|
||||
How to use a GreatAI service
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/handle-training-data/" class="md-nav__link">
|
||||
How to handle training data
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/large_file/" class="md-nav__link">
|
||||
How to use LargeFile
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/call_remote.md" class="md-nav__link">
|
||||
None
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../how-to-guides/scraping/" class="md-nav__link">
|
||||
Scraping
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
|
@ -444,7 +528,7 @@
|
|||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../reference/" class="md-nav__link">
|
||||
Reference
|
||||
GreatAI reference
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
|
@ -506,6 +590,115 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5" type="checkbox" id="__nav_5" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5">
|
||||
Examples
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Examples" data-md-level="1">
|
||||
<label class="md-nav__title" for="__nav_5">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Examples
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item md-nav__item--nested">
|
||||
|
||||
|
||||
<input class="md-nav__toggle md-toggle" data-md-toggle="__nav_5_1" type="checkbox" id="__nav_5_1" >
|
||||
|
||||
|
||||
|
||||
|
||||
<label class="md-nav__link" for="__nav_5_1">
|
||||
Explainable Naive Bayes
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
</label>
|
||||
|
||||
<nav class="md-nav" aria-label="Explainable Naive Bayes" data-md-level="2">
|
||||
<label class="md-nav__title" for="__nav_5_1">
|
||||
<span class="md-nav__icon md-icon"></span>
|
||||
Explainable Naive Bayes
|
||||
</label>
|
||||
<ul class="md-nav__list" data-md-scrollfix>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/data/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/train/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../examples/simple/deploy/" class="md-nav__link">
|
||||
Train a domain classifier on the semantic scholar dataset
|
||||
</a>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
</ul>
|
||||
</nav>
|
||||
</li>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<li class="md-nav__item">
|
||||
<a href="../../explanation/" class="md-nav__link">
|
||||
Explanation
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue