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chore(notebooks): update all notebooks to use Jedis 6.2.0
Updated from 5.2.0 to match actual project dependency. - 01_getting_started.ipynb - 02_hybrid_queries.ipynb - 03_llmcache.ipynb - 04_vectorizers.ipynb - 05_hash_vs_json.ipynb - 08_semantic_router.ipynb - 10_embeddings_cache.ipynb
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7 files changed

+148
-357
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+148
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‎notebooks/01_getting_started.ipynb‎

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"outputs": [],
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"source": [
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"// Load Maven dependencies\n",
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"%maven redis.clients:jedis:5.2.0\n",
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"%maven redis.clients:jedis:6.2.0\n",
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"%maven org.slf4j:slf4j-nop:2.0.16\n",
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"%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n",
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"%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n",
@@ -388,7 +388,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[user_simple_docs:01K4NAFK4KJTBH75N50BG54D5N, user_simple_docs:01K4NAFK4KEMAQBPPYN199YZ8F, user_simple_docs:01K4NAFK4MBTQRZ20ZB89NCHNE]\n"
391+
"[user_simple_docs:01K70ZR1PYMQFQ737CTSDCMAP5, user_simple_docs:01K70ZR1PY414PXY73W2AEANE7, user_simple_docs:01K70ZR1PYZZTV2QSHM4DJYB89]\n"
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]
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}
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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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"[user_simple_docs:01K4NAFK9ZXN8T7PGYYSRVX246]\n"
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"[user_simple_docs:01K70ZR1WATEXBRXMSNFVP4GCH]\n"
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]
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}
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],
@@ -553,9 +553,9 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{credit_score=high, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK4KJTBH75N50BG54D5N, job=engineer, user=john, age=1}\n",
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"{credit_score=low, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK4KEMAQBPPYN199YZ8F, job=doctor, user=mary, age=2}\n",
558-
"{credit_score=high, score=1.0, vector_distance=0.0566298961639, user_embedding=���=���>\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK9ZXN8T7PGYYSRVX246, job=engineer, user=tyler, age=9}\n"
556+
"{credit_score=high, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1PYMQFQ737CTSDCMAP5, job=engineer, user=john, age=1}\n",
557+
"{credit_score=low, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1PY414PXY73W2AEANE7, job=doctor, user=mary, age=2}\n",
558+
"{credit_score=high, score=1.0, vector_distance=0.0566298961639, user_embedding=���=���>\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1WATEXBRXMSNFVP4GCH, job=engineer, user=tyler, age=9}\n"
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]
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}
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],
@@ -636,9 +636,9 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{credit_score=high, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK4KJTBH75N50BG54D5N, job=engineer, user=john, age=1}\n",
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"{credit_score=low, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK4KEMAQBPPYN199YZ8F, job=doctor, user=mary, age=2}\n",
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"{credit_score=high, score=1.0, vector_distance=0.0566298961639, user_embedding=���=���>\u0000\u0000\u0000?, id=user_simple_docs:01K4NAFK9ZXN8T7PGYYSRVX246, job=engineer, user=tyler, age=9}\n"
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"{credit_score=low, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1PY414PXY73W2AEANE7, job=doctor, user=mary, age=2}\n",
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"{credit_score=high, score=1.0, vector_distance=0, user_embedding=���=���=\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1PYMQFQ737CTSDCMAP5, job=engineer, user=john, age=1}\n",
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"{credit_score=high, score=1.0, vector_distance=0.0566298961639, user_embedding=���=���>\u0000\u0000\u0000?, id=user_simple_docs:01K70ZR1WATEXBRXMSNFVP4GCH, job=engineer, user=tyler, age=9}\n"
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]
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}
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],

‎notebooks/02_hybrid_queries.ipynb‎

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],
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"source": [
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"// Load Maven dependencies\n",
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"%maven redis.clients:jedis:5.2.0\n",
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"%maven redis.clients:jedis:6.2.0\n",
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"%maven org.slf4j:slf4j-nop:2.0.16\n",
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"%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n",
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"%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n",

‎notebooks/03_llmcache.ipynb‎

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"outputs": [],
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"source": [
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"// Load Maven dependencies\n",
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"%maven redis.clients:jedis:5.2.0\n",
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"%maven redis.clients:jedis:6.2.0\n",
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"%maven org.slf4j:slf4j-nop:2.0.16\n",
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"%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n",
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"%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n",
@@ -267,7 +267,7 @@
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" Prompt: What is the capital of France?\n",
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" Response: Paris\n",
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" Distance: 0.0\n",
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" Metadata: {country=france, vector_distance=0, updated_at=1758775412, city=Paris, id=2fecdce0-a4f7-4349-b61f-7b4b5ec8d6c2, inserted_at=1758775412}\n"
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" Metadata: {country=france, vector_distance=0, id=7dc948dd-e705-4828-a62e-c68535374afe, updated_at=1759896302, city=Paris, inserted_at=1759896302}\n"
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]
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}
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],
@@ -513,7 +513,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Without caching, a call to OpenAI to answer this simple question took 0.684 seconds.\n",
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"Without caching, a call to OpenAI to answer this simple question took 1.859 seconds.\n",
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"Added to cache\n"
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]
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}
@@ -542,8 +542,8 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Avg time taken with LLM cache enabled: 0.0241\n",
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"Percentage of time saved: 96.48%\n"
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"Avg time taken with LLM cache enabled: 0.0315\n",
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"Percentage of time saved: 98.31%\n"
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]
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}
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],

‎notebooks/04_vectorizers.ipynb‎

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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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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": "// Load Maven dependencies\n%maven redis.clients:jedis:6.2.0\n%maven org.slf4j:slf4j-nop:2.0.16\n%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n%maven com.github.f4b6a3:ulid-creator:5.2.3\n%maven dev.langchain4j:langchain4j:0.36.2\n%maven dev.langchain4j:langchain4j-open-ai:0.36.2\n%maven dev.langchain4j:langchain4j-cohere:0.36.2\n%maven dev.langchain4j:langchain4j-voyage-ai:0.36.2\n%maven com.microsoft.onnxruntime:onnxruntime:1.16.3\n%maven com.squareup.okhttp3:okhttp:4.12.0\n%maven com.google.code.gson:gson:2.10.1\n%maven ai.djl.huggingface:tokenizers:0.30.0\n\n// Note: RedisVL JAR is in classpath (loaded automatically by Docker container)\n\n// Import RedisVL classes\nimport com.redis.vl.utils.vectorize.*;\nimport com.redis.vl.index.SearchIndex;\nimport com.redis.vl.schema.IndexSchema;\nimport com.redis.vl.schema.VectorField;\nimport com.redis.vl.query.VectorQuery;\n\n// Import Redis client\nimport redis.clients.jedis.UnifiedJedis;\nimport redis.clients.jedis.HostAndPort;\n\n// Import LangChain4J\nimport dev.langchain4j.model.openai.OpenAiEmbeddingModel;\nimport dev.langchain4j.model.cohere.CohereEmbeddingModel;\nimport dev.langchain4j.model.voyageai.VoyageAiEmbeddingModel;\n\n// Import Java standard libraries\nimport java.util.*;"
28+
"source": [
29+
"// Load Maven dependencies\n",
30+
"%maven redis.clients:jedis:6.2.0\n",
31+
"%maven org.slf4j:slf4j-nop:2.0.16\n",
32+
"%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n",
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"%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n",
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"%maven com.github.f4b6a3:ulid-creator:5.2.3\n",
35+
"%maven dev.langchain4j:langchain4j:0.36.2\n",
36+
"%maven dev.langchain4j:langchain4j-open-ai:0.36.2\n",
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"%maven dev.langchain4j:langchain4j-cohere:0.36.2\n",
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"%maven dev.langchain4j:langchain4j-voyage-ai:0.36.2\n",
39+
"%maven com.microsoft.onnxruntime:onnxruntime:1.16.3\n",
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"%maven com.squareup.okhttp3:okhttp:4.12.0\n",
41+
"%maven com.google.code.gson:gson:2.10.1\n",
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"%maven ai.djl.huggingface:tokenizers:0.30.0\n",
43+
"\n",
44+
"// Note: RedisVL JAR is in classpath (loaded automatically by Docker container)\n",
45+
"\n",
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"// Import RedisVL classes\n",
47+
"import com.redis.vl.utils.vectorize.*;\n",
48+
"import com.redis.vl.index.SearchIndex;\n",
49+
"import com.redis.vl.schema.IndexSchema;\n",
50+
"import com.redis.vl.schema.VectorField;\n",
51+
"import com.redis.vl.query.VectorQuery;\n",
52+
"\n",
53+
"// Import Redis client\n",
54+
"import redis.clients.jedis.UnifiedJedis;\n",
55+
"import redis.clients.jedis.HostAndPort;\n",
56+
"\n",
57+
"// Import LangChain4J\n",
58+
"import dev.langchain4j.model.openai.OpenAiEmbeddingModel;\n",
59+
"import dev.langchain4j.model.cohere.CohereEmbeddingModel;\n",
60+
"import dev.langchain4j.model.voyageai.VoyageAiEmbeddingModel;\n",
61+
"\n",
62+
"// Import Java standard libraries\n",
63+
"import java.util.*;"
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]
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},
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{
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"cell_type": "markdown",
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"output_type": "stream",
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"text": [
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"OpenAI Vector dimensions: 1536\n",
144-
"First 10 dimensions: [-0.0011391325, -0.0032063872, 0.0023801322, -0.004501554, -0.010328997, 0.012922565, -0.00549112, -0.0029864837, -0.0073279613, -0.033658173]\n",
180+
"First 10 dimensions: [-0.0010550643, -0.003138513, 0.0023639908, -0.0045145433, -0.01032912, 0.012896847, -0.005494419, -0.002988136, -0.0072633694, -0.03365857]\n",
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"Created 3 embeddings\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": 6,
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"metadata": {},
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"source": "String cohereApiKey = System.getenv(\"COHERE_API_KEY\");\nif (cohereApiKey == null || cohereApiKey.isEmpty()) {\n System.out.println(\"Skipping Cohere example - COHERE_API_KEY not set\");\n} else {\n // Note: Cohere v3 models require inputType to be specified\n var cohereModel = CohereEmbeddingModel.builder()\n .apiKey(cohereApiKey)\n .modelName(\"embed-english-v3.0\")\n .inputType(\"search_query\")\n .build();\n \n BaseVectorizer co = new LangChain4JVectorizer(\"embed-english-v3.0\", cohereModel);\n \n float[] cohereTest = co.embed(\"This is a test sentence.\");\n System.out.println(\"Cohere Vector dimensions: \" + cohereTest.length);\n System.out.println(\"First 10 dimensions: \" + Arrays.toString(Arrays.copyOfRange(cohereTest, 0, 10)));\n}"
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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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"Cohere Vector dimensions: 1024\n",
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"First 10 dimensions: [-0.010856628, -0.019683838, -0.0062179565, 0.003545761, -0.047943115, 9.365082E-4, -0.005924225, 0.016174316, -0.03289795, 0.049194336]\n"
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]
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}
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],
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"source": [
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"String cohereApiKey = System.getenv(\"COHERE_API_KEY\");\n",
238+
"if (cohereApiKey == null || cohereApiKey.isEmpty()) {\n",
239+
" System.out.println(\"Skipping Cohere example - COHERE_API_KEY not set\");\n",
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"} else {\n",
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" // Note: Cohere v3 models require inputType to be specified\n",
242+
" var cohereModel = CohereEmbeddingModel.builder()\n",
243+
" .apiKey(cohereApiKey)\n",
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" .modelName(\"embed-english-v3.0\")\n",
245+
" .inputType(\"search_query\")\n",
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" .build();\n",
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" \n",
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" BaseVectorizer co = new LangChain4JVectorizer(\"embed-english-v3.0\", cohereModel);\n",
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" \n",
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" float[] cohereTest = co.embed(\"This is a test sentence.\");\n",
251+
" System.out.println(\"Cohere Vector dimensions: \" + cohereTest.length);\n",
252+
" System.out.println(\"First 10 dimensions: \" + Arrays.toString(Arrays.copyOfRange(cohereTest, 0, 10)));\n",
253+
"}"
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]
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},
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{
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"cell_type": "markdown",
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"output_type": "stream",
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"text": [
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"Loaded 3 documents\n",
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"Keys: [doc:01K70W4SXV6219Z5SD4RJW986B, doc:01K70W4SXV6X0MWYDKENSG41JB, doc:01K70W4SXV35AGKEG2MK8CZRPZ]\n"
419+
"Keys: [doc:01K70ZPYFTE128NAKYDDT6SNSR, doc:01K70ZPYFVNBZK8JVHJ3D8J6N6, doc:01K70ZPYFVRQQANM5GKTHESABV]\n"
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]
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}
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],
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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}

‎notebooks/05_hash_vs_json.ipynb‎

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@@ -41,7 +41,7 @@
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],
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"source": [
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"// Load Maven dependencies\n",
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"%maven redis.clients:jedis:5.2.0\n",
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"%maven redis.clients:jedis:6.2.0\n",
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"%maven org.slf4j:slf4j-nop:2.0.16\n",
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"%maven com.fasterxml.jackson.core:jackson-databind:2.18.0\n",
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"%maven com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.18.0\n",
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"output_type": "stream",
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"text": [
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"Loaded 2 bikes\n",
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" bike-json:01K4NAK1FBNB4D84M190Y8KGAY\n",
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" bike-json:01K4NAK1FC923PB0N6MXTVWW7F\n"
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" bike-json:01K70ZYCD71HJGX2QSKSK98MC8\n",
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" bike-json:01K70ZYCD7XXPNHHSM7TXJ7Y74\n"
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]
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}
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],
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"name": "stdout",
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"text": [
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"ID: bike-json:01K4NAK1FBNB4D84M190Y8KGAY\n",
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"ID: bike-json:01K70ZYCD71HJGX2QSKSK98MC8\n",
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" Brand: Specialized\n",
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" Name: Specialized Stumpjumper\n",
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" Type: Enduro bikes\n",
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" Cosine Distance: 0.623969972134\n",
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" Similarity Score: 0.3760\n",
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"\n",
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"ID: bike-json:01K4NAK1FC923PB0N6MXTVWW7F\n",
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"ID: bike-json:01K70ZYCD7XXPNHHSM7TXJ7Y74\n",
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" Brand: Trek\n",
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" Name: bike_2\n",
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" Type: Enduro bikes\n",

‎notebooks/08_semantic_router.ipynb‎

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@@ -29,7 +29,7 @@
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],
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"source": [
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"// Load Maven dependencies\n",
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"%maven redis.clients:jedis:5.2.0\n",
32+
"%maven redis.clients:jedis:6.2.0\n",
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"%maven org.slf4j:slf4j-nop:2.0.16\n",
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"%maven com.microsoft.onnxruntime:onnxruntime:1.16.3\n",
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"%maven com.squareup.okhttp3:okhttp:4.12.0\n",
@@ -400,15 +400,15 @@
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"Route details:\n",
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" Route: technology\n",
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" Distance threshold: 0.71\n",
403-
" Metadata: {category=tech, priority=1}\n",
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" Metadata: {priority=1, category=tech}\n",
404404
" References: 3\n",
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" Route: sports\n",
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" Distance threshold: 0.72\n",
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" Metadata: {category=sports, priority=2}\n",
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" Metadata: {priority=2, category=sports}\n",
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" References: 5\n",
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" Route: entertainment\n",
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" Distance threshold: 0.7\n",
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" Metadata: {category=entertainment, priority=3}\n",
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" Metadata: {priority=3, category=entertainment}\n",
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" References: 3\n"
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]
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}
@@ -549,24 +549,24 @@
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"output_type": "stream",
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"text": [
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"Found 5 references for technology route:\n",
552-
" Reference: what's trending in tech?\n",
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" Reference ID: 149a9c9919c58534\n",
552+
" Reference: new tech gadgets\n",
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" Reference ID: 7e4bca5853c1c329\n",
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" Route: technology\n",
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"\n",
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" Reference: latest AI trends\n",
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" Reference ID: f243fb2d073774e8\n",
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" Route: technology\n",
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"\n",
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" Reference: tell me about the newest gadgets\n",
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" Reference ID: 85cc73a1437df27c\n",
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" Reference: what's trending in tech?\n",
561+
" Reference ID: 149a9c9919c58534\n",
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" Route: technology\n",
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"\n",
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" Reference: what are the latest advancements in AI?\n",
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" Reference ID: 851f51cce5a9ccfb\n",
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" Route: technology\n",
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"\n",
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" Reference: new tech gadgets\n",
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" Reference ID: 7e4bca5853c1c329\n",
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" Reference: tell me about the newest gadgets\n",
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" Reference ID: 85cc73a1437df27c\n",
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" Route: technology\n",
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"\n"
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]
@@ -595,8 +595,8 @@
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"output_type": "stream",
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"text": [
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"Retrieved reference by ID:\n",
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" Reference: what's trending in tech?\n",
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" Reference ID: 149a9c9919c58534\n"
598+
" Reference: new tech gadgets\n",
599+
" Reference ID: 7e4bca5853c1c329\n"
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]
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}
602602
],

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