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pavlos-ppavlos-p
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added code to convert model to base64, fixed URL hooks
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-78
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+171
-78
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‎projects/aries-fl/notebooks/hospital/Hospital.ipynb

Lines changed: 31 additions & 39 deletions
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@@ -3,7 +3,7 @@
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "incredible-yemen",
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"id": "voluntary-psychiatry",
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"metadata": {},
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"outputs": [
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{
@@ -12,17 +12,6 @@
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"text": [
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"IPython autoawait is `on`, and set to use `asyncio`\n"
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]
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},
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'aries_basic_controller'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-1-cf8eac349ea5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0masyncio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0maries_basic_controller\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maries_controller\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mAriesAgentController\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mWEBHOOK_HOST\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"0.0.0.0\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'aries_basic_controller'"
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]
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}
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],
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"source": [
@@ -34,16 +23,17 @@
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"WEBHOOK_HOST = \"0.0.0.0\"\n",
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"WEBHOOK_PORT = 8052\n",
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"WEBHOOK_BASE = \"\"\n",
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"ADMIN_URL = \"http://hospital1-agent:8051\"\n",
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"# ADMIN_URL = \"http://hospital1-agent:8051\"\n",
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"ADMIN_URL = \"http://0.0.0.0:8051\"\n",
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"\n",
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"agent_controller = AriesAgentController(webhook_host=WEBHOOK_HOST, webhook_port=WEBHOOK_PORT,\n",
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" webhook_base=WEBHOOK_BASE, admin_url=ADMIN_URL)"
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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": 4,
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"id": "adaptive-monte",
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"execution_count": 2,
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"id": "hairy-richardson",
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"metadata": {},
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"outputs": [],
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"source": [
@@ -77,42 +67,34 @@
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},
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{
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"cell_type": "markdown",
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"id": "quick-shanghai",
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"id": "potential-satellite",
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"metadata": {},
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"source": [
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"## Copy Invite from Researcher"
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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": 5,
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"id": "rubber-thirty",
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"execution_count": 3,
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"id": "charming-newton",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Paste in invitation from researcher agent\n",
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"invitation = {'@type': 'did:sov:BzCbsNYhMrjHiqZDTUASHg;spec/connections/1.0/invitation', '@id': '31d22c96-b531-467a-8637-867f0e9199ac', 'label': 'Health Researcher', 'serviceEndpoint': 'http://172.17.0.1:8040', 'recipientKeys': ['Hu8va1kwBxycxKa731q6FeenAmhk5s3x2X3MXXR7CckE']}"
84+
"invitation = {'@type': 'did:sov:BzCbsNYhMrjHiqZDTUASHg;spec/connections/1.0/invitation', '@id': '0ffe0480-5b18-432e-869d-a8d0b44e1095', 'serviceEndpoint': 'http://192.168.65.3:8040', 'recipientKeys': ['9unc3yUPfSsTxM9FsrDmVwFWe3icW3qokVFwiNzNKbhs'], 'label': 'Health Researcher'}"
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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": 6,
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"id": "micro-attraction",
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"execution_count": 4,
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"id": "religious-xerox",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State invitation\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State request\n",
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"Connection {'invitation_key': 'Hu8va1kwBxycxKa731q6FeenAmhk5s3x2X3MXXR7CckE', 'state': 'request', 'connection_id': 'ec35bfc5-68ef-45c4-87c6-5d9f63819c77', 'routing_state': 'none', 'updated_at': '2021-01-23 14:22:15.871577Z', 'initiator': 'external', 'invitation_mode': 'once', 'created_at': '2021-01-23 14:22:15.851490Z', 'accept': 'manual', 'their_label': 'Health Researcher', 'my_did': 'ALrPXCqEuqa5wYFUDDkfeo', 'request_id': 'b9560178-dc00-4496-9a8c-2da146166b4d'}\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State response\n",
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"Connection Handler Called\n",
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"Connection ec35bfc5-68ef-45c4-87c6-5d9f63819c77 in State active\n"
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"Connection {'routing_state': 'none', 'request_id': '4daeee1e-55f7-4595-abf3-9d3415c87062', 'their_label': 'Health Researcher', 'invitation_key': '9unc3yUPfSsTxM9FsrDmVwFWe3icW3qokVFwiNzNKbhs', 'accept': 'manual', 'initiator': 'external', 'invitation_mode': 'once', 'created_at': '2021-01-25 11:03:59.525988Z', 'connection_id': 'c10446d0-7783-4db2-8817-02162115162c', 'my_did': '7vWuaxg22g8mo7WBS1e8vn', 'state': 'request', 'updated_at': '2021-01-25 11:03:59.560705Z'}\n"
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]
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}
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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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"id": "civilian-exhibit",
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"execution_count": 5,
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"id": "boxed-scott",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Alice AGENT CONNECTION\n",
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"{'routing_state': 'none', 'request_id': '4daeee1e-55f7-4595-abf3-9d3415c87062', 'their_label': 'Health Researcher', 'invitation_key': '9unc3yUPfSsTxM9FsrDmVwFWe3icW3qokVFwiNzNKbhs', 'accept': 'manual', 'initiator': 'external', 'invitation_mode': 'once', 'created_at': '2021-01-25 11:03:59.525988Z', 'connection_id': 'c10446d0-7783-4db2-8817-02162115162c', 'my_did': '7vWuaxg22g8mo7WBS1e8vn', 'state': 'request', 'updated_at': '2021-01-25 11:03:59.560705Z'}\n",
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"State: request\n"
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]
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}
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],
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"source": [
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"# Print connection list\n",
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"connection = await agent_controller.connections.get_connection(alice_id)\n",
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "external-compact",
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"id": "considerable-consequence",
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "markdown",
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"id": "numerous-fruit",
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"id": "peaceful-thousand",
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"metadata": {},
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"source": [
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"# For the Training follow the Number's Sequence"
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]
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},
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{
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"cell_type": "markdown",
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"id": "instructional-feelings",
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"id": "copyrighted-charger",
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"metadata": {},
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"source": [
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"## 2. The Hospital receives the model from the Researcher, Trains it using its own dataset, and saves it as \"/../trained_model.pt\""
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "black-boards",
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"id": "binary-indonesian",
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"metadata": {
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"scrolled": true
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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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"id": "dependent-increase",
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"id": "familiar-conspiracy",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "nearby-advocate",
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"id": "medical-philosophy",
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"metadata": {},
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"outputs": [],
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"source": [

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