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cleanup routing example
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‎python-recipes/semantic-router/00_semantic_routing.ipynb‎

Lines changed: 51 additions & 78 deletions
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@@ -97,7 +97,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 17,
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"id": "aefda1d1",
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"metadata": {},
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"outputs": [],
@@ -132,7 +132,7 @@
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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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"execution_count": 18,
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"id": "c52d454a",
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"metadata": {},
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"outputs": [],
@@ -170,17 +170,17 @@
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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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"execution_count": 19,
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"id": "b986bf8d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"RouteMatch(name='block_list', distance=0.375403106213)"
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"RouteMatch(name='block_list', distance=0.375402927399)"
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]
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},
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"execution_count": 5,
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -219,12 +219,12 @@
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"\n",
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"Each route has a set of references that cover the \"semantic surface area\" of the\n",
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"route. The incoming query from a user needs to be semantically similar to one or\n",
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"more of the references in order to \"match\" on the route."
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"more of the references in order to \"match\" on the route. Note that each route can have it's own distinct `distance_threshold` that defines what is considered a match for the particular query. "
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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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"execution_count": 20,
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"id": "60ad280c",
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"metadata": {},
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"outputs": [],
@@ -239,7 +239,8 @@
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" \"tell me about the newest gadgets\",\n",
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" \"what's trending in tech?\"\n",
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" ],\n",
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" metadata={\"category\": \"tech\", \"priority\": 1}\n",
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" metadata={\"category\": \"tech\", \"priority\": 1},\n",
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" distance_threshold=0.5\n",
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")\n",
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"\n",
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"sports = Route(\n",
@@ -251,7 +252,8 @@
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" \"sports\",\n",
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" \"basketball and football\"\n",
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" ],\n",
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" metadata={\"category\": \"sports\", \"priority\": 2}\n",
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" metadata={\"category\": \"sports\", \"priority\": 2},\n",
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" distance_threshold=0.7\n",
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")\n",
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"\n",
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"entertainment = Route(\n",
@@ -261,7 +263,8 @@
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" \"who won the best actor award?\",\n",
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" \"what's new in the entertainment industry?\"\n",
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" ],\n",
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" metadata={\"category\": \"entertainment\", \"priority\": 3}\n",
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" metadata={\"category\": \"entertainment\", \"priority\": 3},\n",
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" distance_threshold=0.6\n",
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")"
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]
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},
@@ -277,7 +280,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 21,
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"id": "e80aaf84",
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"metadata": {},
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"outputs": [],
@@ -306,7 +309,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 22,
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"id": "3caedb77",
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"metadata": {},
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"outputs": [
@@ -348,17 +351,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 23,
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"id": "5b0e3208",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"RouteMatch(name='technology', distance=0.119614601135)"
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"RouteMatch(name='technology', distance=0.419145862261)"
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]
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},
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"execution_count": 9,
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"execution_count": 23,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -371,7 +374,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 24,
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"id": "ef90a1b8",
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"metadata": {},
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"outputs": [
@@ -381,7 +384,7 @@
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"RouteMatch(name=None, distance=None)"
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]
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},
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"execution_count": 10,
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -392,29 +395,6 @@
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"route_match"
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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": 11,
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"id": "a937b471",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"RouteMatch(name='sports', distance=0.554210424423)"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Toggle the runtime distance threshold\n",
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"route_match = multi_topic_router(\"Which basketball team will win the NBA finals?\", distance_threshold=0.7)\n",
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"route_match"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c3f8600a",
@@ -425,44 +405,42 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 34,
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"id": "70335f93",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[RouteMatch(name='sports', distance=0.758580780029),\n",
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" RouteMatch(name='entertainment', distance=0.812423845132),\n",
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" RouteMatch(name='technology', distance=0.884235262871)]"
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"[RouteMatch(name='sports', distance=0.274198234081),\n",
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" RouteMatch(name='entertainment', distance=0.521298646927)]"
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]
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},
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"execution_count": 12,
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"execution_count": 34,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Perform multi-class classification with route_many() -- toggle the max_k and the distance_threshold\n",
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"route_matches = multi_topic_router.route_many(\"Lebron James\", distance_threshold=1.0, max_k=3)\n",
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"route_matches = multi_topic_router.route_many(\"entertainment and sports\", max_k=3)\n",
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"route_matches"
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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": 14,
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"execution_count": 35,
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"id": "874b80fc",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[RouteMatch(name='sports', distance=0.663254141808),\n",
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" RouteMatch(name='entertainment', distance=0.712985336781),\n",
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" RouteMatch(name='technology', distance=0.832674443722)]"
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"[RouteMatch(name='sports', distance=0.263298630714),\n",
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" RouteMatch(name='entertainment', distance=0.512374281883)]"
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]
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},
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"execution_count": 14,
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"execution_count": 35,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -471,7 +449,7 @@
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"# Toggle the aggregation method -- note the different distances in the result\n",
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"from redisvl.extensions.router.schema import DistanceAggregationMethod\n",
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"\n",
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"route_matches = multi_topic_router.route_many(\"Lebron James\", aggregation_method=DistanceAggregationMethod.min, distance_threshold=1.0, max_k=3)\n",
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"route_matches = multi_topic_router.route_many(\"sports and entertainment\", aggregation_method=DistanceAggregationMethod.min, max_k=3)\n",
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"route_matches"
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]
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},
@@ -487,33 +465,31 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 36,
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"id": "86919de5",
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"metadata": {},
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"outputs": [],
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"source": [
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"from redisvl.extensions.router import RoutingConfig\n",
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"\n",
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"multi_topic_router.update_routing_config(\n",
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" RoutingConfig(distance_threshold=1.0, aggregation_method=DistanceAggregationMethod.min, max_k=3)\n",
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" RoutingConfig(aggregation_method=DistanceAggregationMethod.min, max_k=3)\n",
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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": 16,
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"execution_count": 37,
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"id": "cb883785",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[RouteMatch(name='sports', distance=0.663254141808),\n",
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" RouteMatch(name='entertainment', distance=0.712985336781),\n",
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" RouteMatch(name='technology', distance=0.832674443722)]"
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"[RouteMatch(name='sports', distance=0.663253903389)]"
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]
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},
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"execution_count": 16,
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"execution_count": 37,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -533,7 +509,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 38,
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"id": "f5ea2e61",
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"metadata": {},
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"outputs": [
@@ -545,27 +521,28 @@
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" 'references': ['what are the latest advancements in AI?',\n",
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" 'tell me about the newest gadgets',\n",
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" \"what's trending in tech?\"],\n",
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" 'metadata': {'category': 'tech', 'priority': '1'}},\n",
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" 'metadata': {'category': 'tech', 'priority': 1},\n",
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" 'distance_threshold': 0.5},\n",
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" {'name': 'sports',\n",
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" 'references': ['who won the game last night?',\n",
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" 'tell me about the upcoming sports events',\n",
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" \"what's the latest in the world of sports?\",\n",
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" 'sports',\n",
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" 'basketball and football'],\n",
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" 'metadata': {'category': 'sports', 'priority': '2'}},\n",
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" 'metadata': {'category': 'sports', 'priority': 2},\n",
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" 'distance_threshold': 0.7},\n",
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" {'name': 'entertainment',\n",
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" 'references': ['what are the top movies right now?',\n",
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" 'who won the best actor award?',\n",
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" \"what's new in the entertainment industry?\"],\n",
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" 'metadata': {'category': 'entertainment', 'priority': '3'}}],\n",
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" 'metadata': {'category': 'entertainment', 'priority': 3},\n",
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" 'distance_threshold': 0.6}],\n",
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" 'vectorizer': {'type': 'hf',\n",
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" 'model': 'sentence-transformers/all-mpnet-base-v2'},\n",
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" 'routing_config': {'distance_threshold': 1.0,\n",
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" 'max_k': 3,\n",
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" 'aggregation_method': 'min'}}"
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" 'routing_config': {'max_k': 3, 'aggregation_method': 'min'}}"
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]
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},
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"execution_count": 18,
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"execution_count": 38,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -576,27 +553,25 @@
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"id": "36ae6f50",
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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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"10:50:18 redisvl.index.index INFO Index already exists, not overwriting.\n"
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"11:18:33 redisvl.index.index INFO Index already exists, not overwriting.\n"
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]
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}
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],
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"source": [
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"router2 = SemanticRouter.from_dict(multi_topic_router.to_dict(), redis_url=\"redis://localhost:6379\")\n",
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"\n",
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"assert router2 == multi_topic_router"
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"router2 = SemanticRouter.from_dict(multi_topic_router.to_dict(), redis_url=\"redis://localhost:6379\")"
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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": 20,
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"execution_count": 43,
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"id": "f601b065",
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"metadata": {},
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"outputs": [],
@@ -606,22 +581,20 @@
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 44,
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"id": "63e4a847",
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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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"10:50:43 redisvl.index.index INFO Index already exists, not overwriting.\n"
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"11:18:53 redisvl.index.index INFO Index already exists, not overwriting.\n"
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]
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}
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],
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"source": [
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"router3 = SemanticRouter.from_yaml(\"router.yaml\", redis_url=\"redis://localhost:6379\")\n",
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"\n",
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"assert router3 == router2 == multi_topic_router"
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"router3 = SemanticRouter.from_yaml(\"router.yaml\", redis_url=\"redis://localhost:6379\")"
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]
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},
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{

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