Spaces:
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commression functions for activity log
Browse files- app.py +3 -1
- library.ipynb +15 -2
app.py
CHANGED
@@ -5,7 +5,7 @@ import anvil.server
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import pathlib
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import textwrap
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import import_ipynb
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from library import call_gpt, call_gemini
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from background_service import BackgroundTaskService
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import numpy as np
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@@ -33,6 +33,8 @@ encoder = AutoModel.from_pretrained('allenai/specter')
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anvil.server.callable(call_gpt)
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anvil.server.callable(call_gemini)
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service=BackgroundTaskService(max_tasks=10)
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service.register(call_gpt)
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import pathlib
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import textwrap
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import import_ipynb
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from library import call_gpt, call_gemini, compress_bool_list, uncompress_bool_list
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from background_service import BackgroundTaskService
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import numpy as np
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anvil.server.callable(call_gpt)
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anvil.server.callable(call_gemini)
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anvil.server.callable(compress_bool_list)
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anvil.server.callable(uncompress_bool_list)
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service=BackgroundTaskService(max_tasks=10)
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service.register(call_gpt)
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library.ipynb
CHANGED
@@ -11,8 +11,21 @@
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"import pathlib\n",
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"import textwrap\n",
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"import google.generativeai as genai #comment this for local deployment and uncomment dummy def below\n",
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"
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]
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},
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{
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"import pathlib\n",
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"import textwrap\n",
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"import google.generativeai as genai #comment this for local deployment and uncomment dummy def below\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def compress_bool_list(bools):\n",
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" compressed_bits = np.packbits(bools,bitorder='big')\n",
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" return [compressed_bits,len(bools)]\n",
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"\n",
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"def uncompress_bool_list(log):\n",
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" return [bool(b) for b in np.unpackbits(log[0],bitorder='big')[:log[1]]]"
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]
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},
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{
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