Spaces:
Running
Running
feat: Implement a Qdrant vector store using GTE-small embeddings. Initialized it with golf shot data collected over time.
Browse files- .gitignore +5 -2
- data/processed/.gitkeep +0 -0
- data/raw/.gitkeep +0 -0
- notebooks/01_Embed_and_Store_Shots_GTE_with_Qdrant.ipynb +345 -0
- notebooks/02_Retrieve_and_Test_Recommendations_GTE_with_Qdrant.ipynb +138 -0
- pyproject.toml +6 -2
- uv.lock +0 -0
.gitignore
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# Data files
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data/raw/*
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data/processed/*
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notebooks/01_Embed_and_Store_Shots_GTE_with_Qdrant.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "e20d8915",
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"metadata": {},
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"source": [
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"# 📌 Notebook 1: Embed and Store Shot Data in Qdrant\n",
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"\n",
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"This notebook loads your cleaned shot data, embeds it using `bge-small-en-v1.5`, and stores the embeddings in Qdrant for use in retrieval and recommendation."
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]
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},
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{
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"cell_type": "markdown",
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"id": "b11634a3",
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"metadata": {},
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"source": [
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"# Initial Setup"
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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": "edc009c4",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Step 1: Initial Setup:\n",
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"\n",
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"# Load sentence-transformers and GTE-small model\n",
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"from sentence_transformers import SentenceTransformer\n",
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"model = SentenceTransformer('thenlper/gte-small')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8d5248e0",
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"metadata": {},
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"source": [
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"## Load Shot Data From .csv"
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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": "dce5090d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Date</th>\n",
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" <th>Club Type</th>\n",
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" <th>Club Description</th>\n",
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" <th>Carry Distance</th>\n",
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" <th>Total Distance</th>\n",
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" <th>Ball Speed</th>\n",
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" <th>Club Speed</th>\n",
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" <th>Spin Rate</th>\n",
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" <th>Attack Angle</th>\n",
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" <th>Descent Angle</th>\n",
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" <th>Shot Classification</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>2025-02-04 12:41:00</td>\n",
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" <td>Driver</td>\n",
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" <td>TopGolf - Driver (+1; N; 2.75T)</td>\n",
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" <td>124.33</td>\n",
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" <td>171.19</td>\n",
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" <td>122.16</td>\n",
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" <td>85.92</td>\n",
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" <td>1154</td>\n",
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" <td>2.95</td>\n",
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" <td>11.33</td>\n",
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" <td>Hook</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>2025-02-04 12:41:42</td>\n",
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" <td>Driver</td>\n",
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" <td>TopGolf - Driver (+1; N; 2.75T)</td>\n",
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" <td>104.75</td>\n",
|
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" <td>150.95</td>\n",
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" <td>120.35</td>\n",
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" <td>84.20</td>\n",
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" <td>1666</td>\n",
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" <td>2.45</td>\n",
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" <td>8.19</td>\n",
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" <td>Push Hook</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>2025-02-04 12:42:17</td>\n",
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" <td>Driver</td>\n",
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" <td>TopGolf - Driver (+1; N; 2.75T)</td>\n",
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" <td>163.45</td>\n",
|
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" <td>195.51</td>\n",
|
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" <td>115.05</td>\n",
|
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" <td>86.28</td>\n",
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" <td>1227</td>\n",
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" <td>4.30</td>\n",
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" <td>23.02</td>\n",
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" <td>Push</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>2025-02-04 12:43:05</td>\n",
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129 |
+
" <td>Driver</td>\n",
|
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+
" <td>TopGolf - Driver (+1; N; 2.75T)</td>\n",
|
131 |
+
" <td>162.57</td>\n",
|
132 |
+
" <td>192.56</td>\n",
|
133 |
+
" <td>110.91</td>\n",
|
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+
" <td>81.96</td>\n",
|
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+
" <td>1783</td>\n",
|
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+
" <td>1.74</td>\n",
|
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" <td>24.87</td>\n",
|
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" <td>Push</td>\n",
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" </tr>\n",
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" <tr>\n",
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+
" <th>4</th>\n",
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" <td>2025-02-04 12:44:18</td>\n",
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+
" <td>Driver</td>\n",
|
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+
" <td>TopGolf - Driver (+1; N; 2.75T)</td>\n",
|
145 |
+
" <td>105.30</td>\n",
|
146 |
+
" <td>152.00</td>\n",
|
147 |
+
" <td>118.83</td>\n",
|
148 |
+
" <td>80.78</td>\n",
|
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+
" <td>1478</td>\n",
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+
" <td>1.29</td>\n",
|
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+
" <td>8.67</td>\n",
|
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+
" <td>Push Draw</td>\n",
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+
" </tr>\n",
|
154 |
+
" </tbody>\n",
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+
"</table>\n",
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+
"</div>"
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],
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"text/plain": [
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+
" Date Club Type Club Description \\\n",
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"0 2025-02-04 12:41:00 Driver TopGolf - Driver (+1; N; 2.75T) \n",
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+
"1 2025-02-04 12:41:42 Driver TopGolf - Driver (+1; N; 2.75T) \n",
|
162 |
+
"2 2025-02-04 12:42:17 Driver TopGolf - Driver (+1; N; 2.75T) \n",
|
163 |
+
"3 2025-02-04 12:43:05 Driver TopGolf - Driver (+1; N; 2.75T) \n",
|
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+
"4 2025-02-04 12:44:18 Driver TopGolf - Driver (+1; N; 2.75T) \n",
|
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+
"\n",
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" Carry Distance Total Distance Ball Speed Club Speed Spin Rate \\\n",
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+
"0 124.33 171.19 122.16 85.92 1154 \n",
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"1 104.75 150.95 120.35 84.20 1666 \n",
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"2 163.45 195.51 115.05 86.28 1227 \n",
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"3 162.57 192.56 110.91 81.96 1783 \n",
|
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"4 105.30 152.00 118.83 80.78 1478 \n",
|
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+
"\n",
|
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+
" Attack Angle Descent Angle Shot Classification \n",
|
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+
"0 2.95 11.33 Hook \n",
|
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+
"1 2.45 8.19 Push Hook \n",
|
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+
"2 4.30 23.02 Push \n",
|
177 |
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"3 1.74 24.87 Push \n",
|
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+
"4 1.29 8.67 Push Draw "
|
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+
]
|
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+
},
|
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+
"execution_count": 5,
|
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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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+
"# Step 2: Load cleaned shot data\n",
|
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+
"import pandas as pd\n",
|
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+
"shot_data = pd.read_csv('../data/raw/cleaned_shot_data.csv')\n",
|
190 |
+
"shot_data.head()"
|
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+
]
|
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+
},
|
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{
|
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+
"cell_type": "markdown",
|
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"id": "56e952f9",
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"metadata": {},
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"source": [
|
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"## Embed Shot Data"
|
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+
]
|
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},
|
201 |
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{
|
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"cell_type": "code",
|
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"execution_count": 6,
|
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"id": "a5052716",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Step 3: Format shot data into text chunks for embedding\n",
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"def create_embedding_text(row):\n",
|
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" return f\"{row['Club Type']} | Carry: {row['Carry Distance']} yds | Ball Speed: {row['Ball Speed']} mph | Classification: {row['Shot Classification']}\"\n",
|
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"\n",
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"texts = shot_data.apply(create_embedding_text, axis=1).tolist()"
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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": 7,
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"id": "fbd10b62",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Batches: 100%|██████████| 16/16 [00:17<00:00, 1.10s/it]\n"
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]
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}
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],
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"source": [
|
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"# Generate embeddings for shot text\n",
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"embeddings = model.encode(texts, show_progress_bar=True)"
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]
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},
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{
|
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"cell_type": "markdown",
|
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"id": "b5744da3",
|
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"metadata": {},
|
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"source": [
|
239 |
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"## Upload Embedded Shot Data to Qdrant"
|
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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": 8,
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"id": "d95b07f7",
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"metadata": {},
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"outputs": [],
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"source": [
|
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"# Collect the Qdrant API key\n",
|
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"from getpass import getpass\n",
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"\n",
|
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"qdrant_api_key = getpass('🔑 Enter your Qdrant API Key: ')\n"
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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": "c4a90e06",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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+
"/var/folders/5p/gq47dsys3k5663k1r5z8s3c40000gn/T/ipykernel_54911/3543225837.py:11: DeprecationWarning: `recreate_collection` method is deprecated and will be removed in the future. Use `collection_exists` to check collection existence and `create_collection` instead.\n",
|
266 |
+
" client.recreate_collection(\n"
|
267 |
+
]
|
268 |
+
},
|
269 |
+
{
|
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+
"data": {
|
271 |
+
"text/plain": [
|
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+
"True"
|
273 |
+
]
|
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+
},
|
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+
"execution_count": 11,
|
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+
"metadata": {},
|
277 |
+
"output_type": "execute_result"
|
278 |
+
}
|
279 |
+
],
|
280 |
+
"source": [
|
281 |
+
"# Qdrant setup\n",
|
282 |
+
"from qdrant_client import QdrantClient\n",
|
283 |
+
"from qdrant_client.models import VectorParams, PointStruct, Distance\n",
|
284 |
+
"\n",
|
285 |
+
"client = QdrantClient(\n",
|
286 |
+
" url='https://6f592f43-f667-4234-ad3a-4f15ed5882ef.us-west-2-0.aws.cloud.qdrant.io:6333',\n",
|
287 |
+
" api_key=qdrant_api_key\n",
|
288 |
+
")\n",
|
289 |
+
"\n",
|
290 |
+
"# Recreate the collection to flush old data\n",
|
291 |
+
"client.recreate_collection(\n",
|
292 |
+
" collection_name='golf_shot_vectors',\n",
|
293 |
+
" vectors_config=VectorParams(size=384, distance=Distance.COSINE)\n",
|
294 |
+
")"
|
295 |
+
]
|
296 |
+
},
|
297 |
+
{
|
298 |
+
"cell_type": "code",
|
299 |
+
"execution_count": 12,
|
300 |
+
"id": "f5c0f891",
|
301 |
+
"metadata": {},
|
302 |
+
"outputs": [
|
303 |
+
{
|
304 |
+
"data": {
|
305 |
+
"text/plain": [
|
306 |
+
"UpdateResult(operation_id=0, status=<UpdateStatus.COMPLETED: 'completed'>)"
|
307 |
+
]
|
308 |
+
},
|
309 |
+
"execution_count": 12,
|
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+
"metadata": {},
|
311 |
+
"output_type": "execute_result"
|
312 |
+
}
|
313 |
+
],
|
314 |
+
"source": [
|
315 |
+
"# Upload embedded vectors to Qdrant\n",
|
316 |
+
"points = [\n",
|
317 |
+
" PointStruct(id=i, vector=embeddings[i], payload={'text': texts[i]})\n",
|
318 |
+
" for i in range(len(embeddings))\n",
|
319 |
+
"]\n",
|
320 |
+
"client.upsert(collection_name='golf_shot_vectors', points=points)"
|
321 |
+
]
|
322 |
+
}
|
323 |
+
],
|
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+
"metadata": {
|
325 |
+
"kernelspec": {
|
326 |
+
"display_name": ".venv",
|
327 |
+
"language": "python",
|
328 |
+
"name": "python3"
|
329 |
+
},
|
330 |
+
"language_info": {
|
331 |
+
"codemirror_mode": {
|
332 |
+
"name": "ipython",
|
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+
"version": 3
|
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+
},
|
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+
"file_extension": ".py",
|
336 |
+
"mimetype": "text/x-python",
|
337 |
+
"name": "python",
|
338 |
+
"nbconvert_exporter": "python",
|
339 |
+
"pygments_lexer": "ipython3",
|
340 |
+
"version": "3.12.9"
|
341 |
+
}
|
342 |
+
},
|
343 |
+
"nbformat": 4,
|
344 |
+
"nbformat_minor": 5
|
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+
}
|
notebooks/02_Retrieve_and_Test_Recommendations_GTE_with_Qdrant.ipynb
ADDED
@@ -0,0 +1,138 @@
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|
1 |
+
{
|
2 |
+
"cells": [
|
3 |
+
{
|
4 |
+
"cell_type": "markdown",
|
5 |
+
"id": "f36ee4e7",
|
6 |
+
"metadata": {},
|
7 |
+
"source": [
|
8 |
+
" # 📌 Notebook 2: Retrieve and Test Recommendations (GTE-small)\n",
|
9 |
+
"This notebook allows you to enter a shot scenario and retrieve semantically similar historical shots using Qdrant with GTE-small embeddings.\n",
|
10 |
+
" "
|
11 |
+
]
|
12 |
+
},
|
13 |
+
{
|
14 |
+
"cell_type": "markdown",
|
15 |
+
"id": "aabcef6d",
|
16 |
+
"metadata": {},
|
17 |
+
"source": [
|
18 |
+
"## Initial Setup"
|
19 |
+
]
|
20 |
+
},
|
21 |
+
{
|
22 |
+
"cell_type": "code",
|
23 |
+
"execution_count": 1,
|
24 |
+
"id": "b3a051bc",
|
25 |
+
"metadata": {},
|
26 |
+
"outputs": [
|
27 |
+
{
|
28 |
+
"name": "stderr",
|
29 |
+
"output_type": "stream",
|
30 |
+
"text": [
|
31 |
+
"/Users/mwalker/development/TAMARKDesigns/AI-Maker-Space/cohort-6/projects/session-05/AIE6-Golf-Agent/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
|
32 |
+
" from .autonotebook import tqdm as notebook_tqdm\n"
|
33 |
+
]
|
34 |
+
}
|
35 |
+
],
|
36 |
+
"source": [
|
37 |
+
"# Step 1: Initial Setup:\n",
|
38 |
+
"\n",
|
39 |
+
"# Load sentence-transformers and GTE-small model\n",
|
40 |
+
"from sentence_transformers import SentenceTransformer\n",
|
41 |
+
"model = SentenceTransformer('thenlper/gte-small')"
|
42 |
+
]
|
43 |
+
},
|
44 |
+
{
|
45 |
+
"cell_type": "code",
|
46 |
+
"execution_count": 2,
|
47 |
+
"id": "83fa3f1d",
|
48 |
+
"metadata": {},
|
49 |
+
"outputs": [],
|
50 |
+
"source": [
|
51 |
+
"# Embed the query using GTE-small\n",
|
52 |
+
"\n",
|
53 |
+
"def get_embedding(text):\n",
|
54 |
+
" return model.encode(text)\n",
|
55 |
+
"\n",
|
56 |
+
"# Define a test query\n",
|
57 |
+
"query = \"What club should I use from 145 yards if I want to avoid a slice?\"\n",
|
58 |
+
"\n",
|
59 |
+
"query_vector = get_embedding(query)"
|
60 |
+
]
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"cell_type": "code",
|
64 |
+
"execution_count": 3,
|
65 |
+
"id": "bfa9fd99",
|
66 |
+
"metadata": {},
|
67 |
+
"outputs": [],
|
68 |
+
"source": [
|
69 |
+
"# Collect the Qdrant API key\n",
|
70 |
+
"from getpass import getpass\n",
|
71 |
+
"\n",
|
72 |
+
"qdrant_api_key = getpass('🔑 Enter your Qdrant API Key: ')"
|
73 |
+
]
|
74 |
+
},
|
75 |
+
{
|
76 |
+
"cell_type": "code",
|
77 |
+
"execution_count": 14,
|
78 |
+
"id": "42a05a2e",
|
79 |
+
"metadata": {},
|
80 |
+
"outputs": [
|
81 |
+
{
|
82 |
+
"name": "stdout",
|
83 |
+
"output_type": "stream",
|
84 |
+
"text": [
|
85 |
+
"Score: 0.8943 | Text: Approach Wedge | Carry: 99.81 yds | Ball Speed: 74.13 mph | Classification: Slice\n",
|
86 |
+
"Score: 0.8941 | Text: Approach Wedge | Carry: 99.57 yds | Ball Speed: 74.27 mph | Classification: Slice\n",
|
87 |
+
"Score: 0.8869 | Text: Approach Wedge | Carry: 52.12 yds | Ball Speed: 52.12 mph | Classification: Push Slice\n",
|
88 |
+
"Score: 0.8868 | Text: Lob Wedge | Carry: 67.72 yds | Ball Speed: 59.75 mph | Classification: Slice\n",
|
89 |
+
"Score: 0.8867 | Text: Lob Wedge | Carry: 41.49 yds | Ball Speed: 45.45 mph | Classification: Slice\n"
|
90 |
+
]
|
91 |
+
}
|
92 |
+
],
|
93 |
+
"source": [
|
94 |
+
"# Retrieve top 5 most similar entries\n",
|
95 |
+
"from qdrant_client import QdrantClient\n",
|
96 |
+
"\n",
|
97 |
+
"client = QdrantClient(\n",
|
98 |
+
" url=\"https://6f592f43-f667-4234-ad3a-4f15ed5882ef.us-west-2-0.aws.cloud.qdrant.io:6333\",\n",
|
99 |
+
" api_key=qdrant_api_key\n",
|
100 |
+
")\n",
|
101 |
+
"\n",
|
102 |
+
"collection_name = \"golf_shot_vectors\"\n",
|
103 |
+
"\n",
|
104 |
+
"search_result = client.query_points(\n",
|
105 |
+
" collection_name=collection_name,\n",
|
106 |
+
" query=query_vector, # Pass the vector directly\n",
|
107 |
+
" limit=5,\n",
|
108 |
+
" with_payload=True\n",
|
109 |
+
" )\n",
|
110 |
+
" \n",
|
111 |
+
"# Access the points from the QueryResponse\n",
|
112 |
+
"for point in search_result.points:\n",
|
113 |
+
" print(f\"Score: {point.score:.4f} | Text: {point.payload['text']}\")"
|
114 |
+
]
|
115 |
+
}
|
116 |
+
],
|
117 |
+
"metadata": {
|
118 |
+
"kernelspec": {
|
119 |
+
"display_name": ".venv",
|
120 |
+
"language": "python",
|
121 |
+
"name": "python3"
|
122 |
+
},
|
123 |
+
"language_info": {
|
124 |
+
"codemirror_mode": {
|
125 |
+
"name": "ipython",
|
126 |
+
"version": 3
|
127 |
+
},
|
128 |
+
"file_extension": ".py",
|
129 |
+
"mimetype": "text/x-python",
|
130 |
+
"name": "python",
|
131 |
+
"nbconvert_exporter": "python",
|
132 |
+
"pygments_lexer": "ipython3",
|
133 |
+
"version": "3.12.9"
|
134 |
+
}
|
135 |
+
},
|
136 |
+
"nbformat": 4,
|
137 |
+
"nbformat_minor": 5
|
138 |
+
}
|
pyproject.toml
CHANGED
@@ -12,13 +12,17 @@ dependencies = [
|
|
12 |
"pypdf", # for PDF processing
|
13 |
"PyPDF2>=3.0.0",
|
14 |
"numpy>=1.24.0",
|
|
|
15 |
"langchain>=0.1.0",
|
16 |
"langchain-community>=0.0.22",
|
17 |
-
"langchain-openai>=0.0.8",
|
|
|
18 |
"pytest>=7.0.0", # Added pytest dependency
|
19 |
-
"pytest-asyncio>=0.23.0", # Added pytest-asyncio dependency
|
|
|
20 |
"tavily-python>=0.3.0", # Added tavily dependency
|
21 |
"langgraph>=0.0.15", # Added langgraph dependency
|
|
|
22 |
]
|
23 |
|
24 |
[build-system]
|
|
|
12 |
"pypdf", # for PDF processing
|
13 |
"PyPDF2>=3.0.0",
|
14 |
"numpy>=1.24.0",
|
15 |
+
"pandas>=2.0.0", # for data analysis
|
16 |
"langchain>=0.1.0",
|
17 |
"langchain-community>=0.0.22",
|
18 |
+
"langchain-openai>=0.0.8",
|
19 |
+
"qdrant-client>=1.14.2", # Vector storage
|
20 |
"pytest>=7.0.0", # Added pytest dependency
|
21 |
+
"pytest-asyncio>=0.23.0", # Added pytest-asyncio dependency
|
22 |
+
"pytest-cov>=4.1.0", # Coverage reporting
|
23 |
"tavily-python>=0.3.0", # Added tavily dependency
|
24 |
"langgraph>=0.0.15", # Added langgraph dependency
|
25 |
+
"sentence-transformers", #used for embeddings
|
26 |
]
|
27 |
|
28 |
[build-system]
|
uv.lock
CHANGED
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|
|