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@databyjp
databyjp / mcp_generated_example.py
Created October 26, 2025 13:01
"""
End-to-End Weaviate Example: E-Commerce Product Collection
This script demonstrates:
1. Connecting to Weaviate Cloud
2. Creating a collection with RQ quantization and alias
3. Importing data with batching
4. Querying with the traditional Weaviate client
5. Querying with the Query Agent
"""
@databyjp
databyjp / Instruction.md
Created October 26, 2025 12:36

Option 1 - Add a .mcp.json file to your project root with this content:

Try the Weaviate Docs MCP like this:

{
  "mcpServers": {
    "weaviate-docs": {
      "type": "http",
 "url": "https://weaviate-docs-mcp-3hx7rjpxua-uc.a.run.app/mcp"
@databyjp
databyjp / export_weaviate_data.py
Last active March 14, 2024 16:49
Rough script to export data from Weaviate to a series of JSON files
import weaviate
from weaviate.collections import Collection
from weaviate.collections.classes.types import GeoCoordinate
from tqdm import tqdm
from typing import List
import os
import json
from datetime import date, datetime
client = weaviate.connect_to_wcs(
@databyjp
databyjp / link-checker.ipynb
Created March 14, 2023 09:01
@databyjp
databyjp / update_data.plist
Last active May 12, 2022 11:07
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>EnvironmentVariables</key>
<dict>
<key>PATH</key>
<string>/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/sbin</string>
</dict>
<key>ExitTimeOut</key>
@databyjp
databyjp / 20220511_test_sysargv.py
Created May 12, 2022 04:35
yr_ranges = None
if len(sys.argv) < 3:
logger.info(f'Season year arguments not provided')
else:
try:
if 2040 > int(sys.argv[1]) > 1980 and 2040 > int(sys.argv[2]) > 1980:
yr_ranges = [int(sys.argv[1]), int(sys.argv[2])]
else:
logger.error(f'The arguments should season years (e.g. 2021 2020) when data is available')
except:
@databyjp
databyjp / update_2021_data.plist
Last active May 12, 2022 01:50
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>EnvironmentVariables</key>
<dict>
<key>PATH</key>
<string>/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/sbin</string>
</dict>
<key>KeepAlive</key>
@databyjp
databyjp / example.plist
Last active May 12, 2022 01:50
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>EnvironmentVariables</key>
<dict>
<key>PATH</key>
<string>/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/sbin</string>
</dict>
<key>Label</key>
@databyjp
databyjp / generate csv 20220430_gameviz_generator.py
Created May 5, 2022 06:50
for gm_id in gm_ids:
shot_blot_dfs = list()
gm_df = playoffs_df[playoffs_df.GAME_ID == gm_id]
game_date = gm_df["realtime_dt"].min().date()
game_date_str = f"{game_date.day}_{game_date.strftime('%b')}_{game_date.strftime('%Y')}"
tm_ids = gm_df.teamId.unique()
tm_abvs = [teams.find_team_name_by_id(tm_id)['abbreviation'] for tm_id in tm_ids]
for tm_id in tm_ids:
tmp_dfs = list()
tm = teams.find_team_name_by_id(tm_id)
@databyjp
databyjp / 20220427_playoff_gameviz_refined_viz.py
Created April 28, 2022 14:22
fig = px.scatter(shot_blot_df,
title=f'{latest_day_str} - Playoff game shot profiles',
x="filt_avg", y="segment", size="pts_pct_x",
color="shot_ev", color_continuous_scale=px.colors.sequential.Blues,
facet_row="group", facet_col="shot_type",
template="plotly_white", width=1200, height=750,
range_color=[0.7, 1.7],
labels={'filt_avg': 'Distance from the rim', 'segment': 'Sample size',
'pts_pct_x': 'Proportion of points', 'shot_ev': 'Expected<BR>points<BR>per shot'}
)