From c3a0117c6f2ebf40c9cac0d13c5eba1f4e2bac96 Mon Sep 17 00:00:00 2001 From: cmuhao Date: Tue, 16 Apr 2024 22:22:59 -0700 Subject: [PATCH] add notebook Signed-off-by: cmuhao --- .gitignore | 3 +- module_4_rag/.gitignore | 1 + module_4_rag/.python-version | 1 + module_4_rag/batch_score_documents.py | 8 +- module_4_rag/feature_repo/entities.py | 3 + module_4_rag/feature_repo/feature_store.yaml | 20 + module_4_rag/feature_repo/features.py | 28 + module_4_rag/feature_repo/module_1.ipynb | 354 ++ module_4_rag/poetry.lock | 3370 ++++++++++++++++++ module_4_rag/pyproject.toml | 2 +- 10 files changed, 3785 insertions(+), 5 deletions(-) create mode 100644 module_4_rag/.gitignore create mode 100644 module_4_rag/.python-version create mode 100644 module_4_rag/feature_repo/entities.py create mode 100644 module_4_rag/feature_repo/feature_store.yaml create mode 100644 module_4_rag/feature_repo/features.py create mode 100644 module_4_rag/feature_repo/module_1.ipynb create mode 100644 module_4_rag/poetry.lock diff --git a/.gitignore b/.gitignore index 2853b55..ad641bf 100644 --- a/.gitignore +++ b/.gitignore @@ -11,4 +11,5 @@ terraform.tfstate.backup .vscode/* **/derby.log **/metastore_db/* -.env \ No newline at end of file +.env +.idea \ No newline at end of file diff --git a/module_4_rag/.gitignore b/module_4_rag/.gitignore new file mode 100644 index 0000000..07f43b8 --- /dev/null +++ b/module_4_rag/.gitignore @@ -0,0 +1 @@ +data/* \ No newline at end of file diff --git a/module_4_rag/.python-version b/module_4_rag/.python-version new file mode 100644 index 0000000..bd28b9c --- /dev/null +++ b/module_4_rag/.python-version @@ -0,0 +1 @@ +3.9 diff --git a/module_4_rag/batch_score_documents.py b/module_4_rag/batch_score_documents.py index 53a45c4..996d933 100644 --- a/module_4_rag/batch_score_documents.py +++ b/module_4_rag/batch_score_documents.py @@ -4,8 +4,8 @@ import torch import torch.nn.functional as F -INPUT_FILENAME = "city_wikipedia_summaries.csv" -EXPORT_FILENAME = "city_wikipedia_summaries_with_embeddings.csv" +INPUT_FILENAME = "./data/city_wikipedia_summaries.csv" +EXPORT_FILENAME = "./data/city_wikipedia_summaries_with_embeddings.parquet" TOKENIZER = 'sentence-transformers/all-MiniLM-L6-v2' MODEL = 'sentence-transformers/all-MiniLM-L6-v2' @@ -35,8 +35,10 @@ def score_data() -> None: print('shape = ', df.shape) df['Embeddings'] = list(embeddings.detach().cpu().numpy()) print("embeddings generated...") + df['event_timestamp'] = pd.to_datetime('today') + df["item_id"] = df.index print(df.head()) - df.to_csv(EXPORT_FILENAME, index=False) + df.to_parquet(EXPORT_FILENAME, index=False) print("...data exported. job complete") else: print("scored data found...skipping generating embeddings.") diff --git a/module_4_rag/feature_repo/entities.py b/module_4_rag/feature_repo/entities.py new file mode 100644 index 0000000..7d2797e --- /dev/null +++ b/module_4_rag/feature_repo/entities.py @@ -0,0 +1,3 @@ +from feast import Entity + +item = Entity(name="item_id") diff --git a/module_4_rag/feature_repo/feature_store.yaml b/module_4_rag/feature_repo/feature_store.yaml new file mode 100644 index 0000000..709f901 --- /dev/null +++ b/module_4_rag/feature_repo/feature_store.yaml @@ -0,0 +1,20 @@ +project: feast_demo_local +provider: local +registry: + registry_type: sql + path: postgresql://@localhost:5432/feast +online_store: + type: postgres + pgvector_enabled: true + vector_len: 384 + host: 127.0.0.1 + port: 5432 + database: feast + user: "" + password: "" + + +offline_store: + type: file +entity_key_serialization_version: 2 + diff --git a/module_4_rag/feature_repo/features.py b/module_4_rag/feature_repo/features.py new file mode 100644 index 0000000..37ff6ff --- /dev/null +++ b/module_4_rag/feature_repo/features.py @@ -0,0 +1,28 @@ +from datetime import timedelta + +from feast import ( + FeatureView, + Field, FileSource, +) +from feast.data_format import ParquetFormat +from feast.types import Float32, Array +from entities import item + + +parquet_file_path = "../data/city_wikipedia_summaries_with_embeddings.parquet" + +source = FileSource( + file_format=ParquetFormat(), + path=parquet_file_path, + timestamp_field="event_timestamp", +) + +city_embeddings_feature_view = FeatureView( + name="city_embeddings", + entities=[item], + schema=[ + Field(name="Embeddings", dtype=Array(Float32)), + ], + source=source, + ttl=timedelta(hours=2), +) diff --git a/module_4_rag/feature_repo/module_1.ipynb b/module_4_rag/feature_repo/module_1.ipynb new file mode 100644 index 0000000..a2c12f2 --- /dev/null +++ b/module_4_rag/feature_repo/module_1.ipynb @@ -0,0 +1,354 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Module 1: Use Postgres (Pgvector) vector database as an online store for retrieving documents" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Overview\n", + "In this notebook, we explore how to use Feast to retrieve documents from a Postgres (Pgvector) vector database. We will use the `city_embeddings` feature table that we created in the previous notebook. We will use the `retrieve_online_documents` method to retrieve the top-k documents that are closest to the query vector.\n", + "\n", + "If you haven't already, look at the [README](../README.md) for setup instructions prior to starting this notebook." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1. Setup the feature store" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Apply feature repository\n", + "We first run `feast apply` to register the data sources + features and setup Redis." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n", + "To disable this warning, you can either:\n", + "\t- Avoid using `tokenizers` before the fork if possible\n", + "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\r\n", + " warnings.warn(\r\n", + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/feast/infra/offline_stores/file.py:8: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \r\n", + "In a future release, Dask DataFrame will use a new implementation that\r\n", + "contains several improvements including a logical query planning.\r\n", + "The user-facing DataFrame API will remain unchanged.\r\n", + "\r\n", + "The new implementation is already available and can be enabled by\r\n", + "installing the dask-expr library:\r\n", + "\r\n", + " $ pip install dask-expr\r\n", + "\r\n", + "and turning the query planning option on:\r\n", + "\r\n", + " >>> import dask\r\n", + " >>> dask.config.set({'dataframe.query-planning': True})\r\n", + " >>> import dask.dataframe as dd\r\n", + "\r\n", + "API documentation for the new implementation is available at\r\n", + "https://docs.dask.org/en/stable/dask-expr-api.html\r\n", + "\r\n", + "Any feedback can be reported on the Dask issue tracker\r\n", + "https://github.com/dask/dask/issues \r\n", + "\r\n", + "To disable this warning in the future, set dask config:\r\n", + "\r\n", + " # via Python\r\n", + " >>> dask.config.set({'dataframe.query-planning-warning': False})\r\n", + "\r\n", + " # via CLI\r\n", + " dask config set dataframe.query-planning-warning False\r\n", + "\r\n", + "\r\n", + " import dask.dataframe as dd\r\n", + "Deploying infrastructure for \u001B[1m\u001B[32mcity_embeddings\u001B[0m\r\n" + ] + } + ], + "source": [ + "!feast apply" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# 2. Materialize training data\n", + "The datasets are prepared in the data directory. You can get them locally by running the commands in README.md. We will materialize the training data into the online store." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 6, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\r\n", + " warnings.warn(\r\n", + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/feast/infra/offline_stores/file.py:8: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \r\n", + "In a future release, Dask DataFrame will use a new implementation that\r\n", + "contains several improvements including a logical query planning.\r\n", + "The user-facing DataFrame API will remain unchanged.\r\n", + "\r\n", + "The new implementation is already available and can be enabled by\r\n", + "installing the dask-expr library:\r\n", + "\r\n", + " $ pip install dask-expr\r\n", + "\r\n", + "and turning the query planning option on:\r\n", + "\r\n", + " >>> import dask\r\n", + " >>> dask.config.set({'dataframe.query-planning': True})\r\n", + " >>> import dask.dataframe as dd\r\n", + "\r\n", + "API documentation for the new implementation is available at\r\n", + "https://docs.dask.org/en/stable/dask-expr-api.html\r\n", + "\r\n", + "Any feedback can be reported on the Dask issue tracker\r\n", + "https://github.com/dask/dask/issues \r\n", + "\r\n", + "To disable this warning in the future, set dask config:\r\n", + "\r\n", + " # via Python\r\n", + " >>> dask.config.set({'dataframe.query-planning-warning': False})\r\n", + "\r\n", + " # via CLI\r\n", + " dask config set dataframe.query-planning-warning False\r\n", + "\r\n", + "\r\n", + " import dask.dataframe as dd\r\n", + "Materializing \u001B[1m\u001B[32m1\u001B[0m feature views from \u001B[1m\u001B[32m2024-03-31 17:00:00-07:00\u001B[0m to \u001B[1m\u001B[32m2024-04-16 17:00:00-07:00\u001B[0m into the \u001B[1m\u001B[32mpostgres\u001B[0m online store.\r\n", + "\r\n", + "\u001B[1m\u001B[32mcity_embeddings\u001B[0m:\r\n", + "100%|██████████████████████████████████████████████████████████████| 49/49 [00:00<00:00, 956.19it/s]\r\n" + ] + } + ], + "source": [ + "!feast materialize 2024-04-01T00:00:00 2024-04-17T00:00:00" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we instantiate a Feast `FeatureStore` object to push data to" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n", + " warnings.warn(\n", + "/Users/haoxu/dev/feast-workshop/.virtualenv/lib/python3.9/site-packages/feast/infra/offline_stores/file.py:8: DeprecationWarning: The current Dask DataFrame implementation is deprecated. \n", + "In a future release, Dask DataFrame will use a new implementation that\n", + "contains several improvements including a logical query planning.\n", + "The user-facing DataFrame API will remain unchanged.\n", + "\n", + "The new implementation is already available and can be enabled by\n", + "installing the dask-expr library:\n", + "\n", + " $ pip install dask-expr\n", + "\n", + "and turning the query planning option on:\n", + "\n", + " >>> import dask\n", + " >>> dask.config.set({'dataframe.query-planning': True})\n", + " >>> import dask.dataframe as dd\n", + "\n", + "API documentation for the new implementation is available at\n", + "https://docs.dask.org/en/stable/dask-expr-api.html\n", + "\n", + "Any feedback can be reported on the Dask issue tracker\n", + "https://github.com/dask/dask/issues \n", + "\n", + "To disable this warning in the future, set dask config:\n", + "\n", + " # via Python\n", + " >>> dask.config.set({'dataframe.query-planning-warning': False})\n", + "\n", + " # via CLI\n", + " dask config set dataframe.query-planning-warning False\n", + "\n", + "\n", + " import dask.dataframe as dd\n" + ] + } + ], + "source": [ + "from feast import FeatureStore\n", + "store = FeatureStore(repo_path=\".\")" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Prepare a query vector" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [], + "source": [ + "from batch_score_documents import run_model, TOKENIZER, MODEL\n", + "from transformers import AutoTokenizer, AutoModel" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [ + { + "name": "stdout", + 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"cell_type": "markdown", + "source": [ + "# Retrieve the top-k documents" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Embeddings : [[0.11749927699565887, -0.04684491828083992, 0.074561707675457, 0.10036394000053406, -0.02789139188826084, 0.004901227541267872, -0.025490708649158478, -0.014385512098670006, -0.03353535756468773, -0.03694501891732216, 0.019829893484711647, -0.08767078071832657, 0.15164919197559357, -0.05422529578208923, 0.04684631526470184, -0.016555113717913628, 0.06950949877500534, 0.012052210047841072, 0.024535944685339928, -0.0060577718541026115, 0.06979842483997345, 0.026241665706038475, -0.06335429847240448, 0.03742428496479988, -0.006074287462979555, 0.12012293934822083, 0.012978488579392433, 0.019200358539819717, -0.09065929055213928, -0.010197900235652924, 0.046665437519550323, 0.07225364446640015, 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