From c1bd61f944d46e3539b4a136e4273df79b1b7eed Mon Sep 17 00:00:00 2001 From: James Briggs <35938317+jamescalam@users.noreply.github.com> Date: Tue, 6 Feb 2024 15:31:49 +0000 Subject: [PATCH] updated semantic search notebook (#1033) --- .../pinecone/Semantic_Search.ipynb | 5903 ++++++----------- 1 file changed, 1923 insertions(+), 3980 deletions(-) diff --git a/examples/vector_databases/pinecone/Semantic_Search.ipynb b/examples/vector_databases/pinecone/Semantic_Search.ipynb index 33fa4b95..eafdf597 100644 --- a/examples/vector_databases/pinecone/Semantic_Search.ipynb +++ b/examples/vector_databases/pinecone/Semantic_Search.ipynb @@ -1,7 +1,6 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "metadata": { "id": "izNeUi--hSSA" @@ -58,100 +57,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "SGQoz_JmtRNh", - "outputId": "389c79fc-2ee9-452b-fc58-9598899090c2" + "outputId": "83bc678c-1b3b-4331-8685-f022bc1e29d7" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - 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This behaviour is the source of the following dependency conflicts.\n", + "llmx 0.0.15a0 requires cohere, which is not installed.\n", + "llmx 0.0.15a0 requires tiktoken, which is not installed.\n", + "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.9.0 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0m" ] } ], "source": [ - "!pip install -qU pinecone-client openai datasets" + "!pip install -qU \\\n", + " pinecone-client==3.0.2 \\\n", + " openai==1.10.0 \\\n", + " datasets==2.16.1" ] }, { @@ -162,458 +102,22 @@ "source": [ "### Creating Embeddings\n", "\n", - "Then we initialize our connection to OpenAI Embeddings *and* Pinecone vector DB. Sign up for an API key over at [OpenAI](https://beta.openai.com/signup) and [Pinecone](https://app.pinecone.io)." + "Then we initialize our connection to OpenAI Embeddings *and* Pinecone vector DB. Sign up for an API key over at [OpenAI](https://platform.openai.com) and [Pinecone](https://app.pinecone.io)." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "yo5uw4sPtRNn", - "outputId": "92914528-696d-4598-dbb3-04457a0eba86" + "id": "yo5uw4sPtRNn" }, - "outputs": [ - { - "data": { - "text/plain": [ - " JSON: {\n", - " \"data\": [\n", - " {\n", - " \"created\": null,\n", - " \"id\": \"babbage\",\n", - " \"object\": \"engine\",\n", - " \"owner\": \"openai\",\n", - " \"permissions\": null,\n", - " \"ready\": true\n", - " },\n", - " {\n", - " \"created\": null,\n", - " \"id\": \"ada\",\n", - " \"object\": \"engine\",\n", - " \"owner\": \"openai\",\n", - " \"permissions\": null,\n", - " \"ready\": true\n", - " },\n", - " {\n", - " \"created\": null,\n", - " \"id\": \"davinci\",\n", - " \"object\": \"engine\",\n", - " \"owner\": \"openai\",\n", - " \"permissions\": null,\n", - " 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get API key from platform.openai.com" ] }, { @@ -627,3112 +131,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Hg0yIGu3tRNo", - "outputId": "58fb10c1-53f0-4dd1-b0fd-14491d4decf3" + "outputId": "94de178a-f29b-43f1-bf8b-3126b61059be" }, "outputs": [ { "data": { "text/plain": [ - " JSON: {\n", - " \"data\": [\n", - " {\n", - " \"embedding\": [\n", - " -0.003040769835934043,\n", - " 0.011684642173349857,\n", - " -0.005026957020163536,\n", - " -0.027237210422754288,\n", - " -0.016361193731427193,\n", - " 0.03234503045678139,\n", - " -0.016159038990736008,\n", - " -0.001036894042044878,\n", - " -0.025822116062045097,\n", - " -0.00666779326274991,\n", - " 0.02014825865626335,\n", - " 0.016657691448926926,\n", - " -0.009164425544440746,\n", - " 0.023423193022608757,\n", - " -0.0101212989538908,\n", - " 0.01344340294599533,\n", - " 0.02522912435233593,\n", - " -0.016873324289917946,\n", - 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0.01578393019735813, -0.0029870744328945875, -0.014528216794133186, -0.0011786577524617314, 0.011187260039150715, 0.026529787108302116, -0.009436871856451035, 0.0011272876290604472, 0.01639275997877121, -0.007614186033606529, -0.00643457705155015, -0.02566220425069332, 0.012298375368118286, 0.017123356461524963, 0.01261801179498434, -0.001627670251764357, -0.003949787467718124, -0.00968040432780981, -0.03981751203536987, 0.020197950303554535, -0.01837145909667015, -0.0007795884157530963, 0.014581489376723766, 0.04188753664493561, 0.006232901941984892, -0.017001591622829437, 0.019178159534931183, -0.006887394469231367], index=1, object='embedding')], model='text-embedding-3-small', object='list', usage=Usage(prompt_tokens=13, total_tokens=13))" ] }, "execution_count": 4, @@ -3743,24 +154,24 @@ "source": [ "MODEL = \"text-embedding-3-small\"\n", "\n", - "res = openai.Embedding.create(\n", + "res = client.embeddings.create(\n", " input=[\n", " \"Sample document text goes here\",\n", " \"there will be several phrases in each batch\"\n", - " ], engine=MODEL\n", + " ], model=MODEL\n", ")\n", "res" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-Egz35DjtRNo", - "outputId": "78c4c022-d3a8-4fa7-8fa8-59c45eca1298" + "outputId": "50896ded-4ddc-47af-e7b6-fcbc57478528" }, "outputs": [ { @@ -3773,18 +184,18 @@ } ], "source": [ - "print(f\"vector 0: {len(res['data'][0]['embedding'])}\\nvector 1: {len(res['data'][1]['embedding'])}\")" + "print(f\"vector 0: {len(res.data[0].embedding)}\\nvector 1: {len(res.data[1].embedding)}\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ZguN6obBtRNp", - "outputId": "bd20d4be-0772-4383-9d1e-9960d8b5f183" + "outputId": "4c102c7c-b20a-47a4-c821-fe7df8f397c1" }, "outputs": [ { @@ -3800,7 +211,7 @@ ], "source": [ "# we can extract embeddings to a list\n", - "embeds = [record['embedding'] for record in res['data']]\n", + "embeds = [record.embedding for record in res.data]\n", "len(embeds)" ] }, @@ -3815,13 +226,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "OnyoBu-BRNOs", - "outputId": "4d40b553-4ff2-4336-baab-24ff6424fead" + "outputId": "b067e43e-163e-4916-bd9d-78d00be24ed9" }, "outputs": [ { @@ -3830,7 +241,7 @@ "1536" ] }, - "execution_count": 13, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -3840,27 +251,85 @@ ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": { - "id": "I2KLRbN-tRNq" + "id": "Q2ln8mWLBNvo" + }, + "source": [ + "Initialize connection to Pinecone, you can get a free API key in the [Pinecone dashboard](https://app.pinecone.io)." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "mhnW1ntWBOlw" }, "outputs": [], "source": [ - "import pinecone\n", + "from pinecone import Pinecone\n", + "\n", + "pc = Pinecone(api_key=\"...\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "og94xxfGBOSD" + }, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "I2KLRbN-tRNq", + "outputId": "2afa97da-c59e-4026-d494-a4238a42df32" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'dimension': 1536,\n", + " 'index_fullness': 0.0,\n", + " 'namespaces': {},\n", + " 'total_vector_count': 0}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import time\n", + "from pinecone import ServerlessSpec\n", + "\n", + "spec = ServerlessSpec(cloud=\"aws\", region=\"us-west-2\")\n", "\n", "index_name = 'semantic-search-openai'\n", "\n", - "# initialize connection to pinecone (get API key at app.pinecone.io)\n", - "pinecone.init(\n", - " api_key=\"PINECONE_API_KEY\",\n", - " environment=\"PINECONE_ENVIRONMENT\" # find next to api key in console\n", - ")\n", - "# check if 'openai' index already exists (only create index if not)\n", - "if index_name not in pinecone.list_indexes():\n", - " pinecone.create_index(index_name, dimension=len(embeds[0]))\n", + "# check if index already exists (if shouldn't if this is your first run)\n", + "if index_name not in pc.list_indexes().names():\n", + " # if does not exist, create index\n", + " pc.create_index(\n", + " index_name,\n", + " dimension=len(embeds[0]), # dimensionality of text-embed-3-small\n", + " metric='dotproduct',\n", + " spec=spec\n", + " )\n", + " # wait for index to be initialized\n", + " while not pc.describe_index(index_name).status['ready']:\n", + " time.sleep(1)\n", + "\n", "# connect to index\n", - "index = pinecone.Index(index_name)" + "index = pc.Index(index_name)\n", + "time.sleep(1)\n", + "# view index stats\n", + "index.describe_index_stats()" ] }, { @@ -3876,22 +345,130 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "colab": { - "base_uri": "https://localhost:8080/" + "base_uri": "https://localhost:8080/", + "height": 339, + "referenced_widgets": [ + "a72d7574882944b5aee45661ec7560d3", + "1848c2abc72943588250eb975234d8fe", + "d004ed64975847c29675fd1d27416397", + "96ca3534ca6d4ad782062807f5f7c57d", + "18c01f6cf74746f8ac9541846b2b4373", + "4ac1bc327ff74c3e9812c8ccb48ef75c", + "f53e5d3ae3144161a6961d5fccb85ecd", + "2fb24c44bf8a4af8b380b12057f4ce37", + "42a0c8aaa7fb4578ab4afa99ddb8cb10", + "c89461d9ca604c4891cb5eb99764d193", + "e131678ea1e1432dbe4cdac45fc55266", + "0255c5e58be446f898b56205e71cbc45", + "8f770df4943f4011976095e98338f21d", + "e7a5320949c44503a1cd6eee10ccfca0", + "1c6d6a1749db4bfcb8e3dd7694e27bf6", + "fb369dfba44b4adeb38c6344298935d7", + "f78d9bff756e4da496003037aa37a813", + "c0ba78e9e0fa405ca7475057e341a07b", + "44ff66c97b504fe5854e2118ae74b426", + "574e4c76ef4244c99e4883e2ec67bbdf", + "6a7c54c44b3a4d148eec4fed35e582cd", + "ff1b1595754040afb02ce19b4f58aee6", + "da5c46d1754f48c9a0469a6d75a4a043", + "9445c0fdb2fd460481bf68f2f3d280d3", + "4ae59298208e4b2dbf8d325a1ad9bc7f", + "bc1b503eb4df4cccb6c50085db322bb6", + "cf91de4f72054fdca0a67cca5f6fccc9", + "f920a4e70f6a431bb64079c0b5976a87", + "2ebb92f4ac824a2baf47bbe7fe46bba3", + "304927a6b49c44e29884d27fa40b23e0", + "319ca2893a0b47caa26118db664cbf67", + "94ff31fc610245d28028d56e933ce7d1", + "b07ea4767b5240cbb14240eb2106395f", + "8ec02f0a33a74a87aa7e61356010d25d", + "674acd6867fb4d0dae97856bd0a155c4", + "753a274f377a4be1b9cfb71776847604", + "9a588ef0a0d44db0a5238bcc0f796b0c", + "d2f4288e373f4907a4e45f93892e511a", + "f85259c6bc904c3999eaf04109db524d", + "5c37fd39dec04e469da17b8115f1b28c", + "0af09cc751dc4bf18c6373be2b6beff0", + "d762997c6bc24e55b17e4ff388501163", + "2f2f8e8f53c14003b044948ead62388b", + "86e9eb6ecf9e4284abd3102226b9956f" + ] }, "id": "JiSfCTK-lhXx", - "outputId": "bcb82771-a0d5-4c63-d2ad-69a963f93620" + "outputId": "e16d023a-de25-4706-86d1-1a56ab39d30f" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:datasets.builder:Found cached dataset trec (/root/.cache/huggingface/datasets/trec/default/2.0.0/f2469cab1b5fceec7249fda55360dfdbd92a7a5b545e91ea0f78ad108ffac1c2)\n" + "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", + "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", + "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" ] }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a72d7574882944b5aee45661ec7560d3", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading data: 0%| | 0.00/213k [00:00