weisisheng

// Types for the result object with discriminated union
type Success<T> = {
  data: T;
  error: null;
};

type Failure<E> = {
  data: null;
  error: E;
};

weisisheng

-- Query the API directly and flatten the nested JSON structure
WITH raw_data AS (
  SELECT * FROM read_json_auto('https://public.api.bsky.app/xrpc/app.bsky.feed.getAuthorFeed?actor=did:plc:edglm4muiyzty2snc55ysuqx&limit=10')
),
unnested_feed AS (
  SELECT unnest(feed) as post_data FROM raw_data
)
SELECT 
  -- Post basics
  post_data.post.uri as post_uri,

weisisheng

import json
import os
import duckdb
import boto3
import datetime
from typing import Any, Dict


def construct_prepared_sql_and_params(sql_template, bind_params):
    single_value_params = {k: v for k, v in bind_params.items() if not isinstance(v, list)}

weisisheng

const AWS = require("aws-sdk");
const csv = require("csv-parser");
const { Readable } = require("stream");
const simpleParser = require("mailparser").simpleParser;

const s3 = new AWS.S3();
const documentClient = new AWS.DynamoDB.DocumentClient();

const TableName = process.env.TABLE;

weisisheng

1. Install (TinyMCE 5.x)

npm install --save tinymce @tinymce/tinymce-react copy-webpack-plugin

2. Copy static files(tinymce skins) to public folder. Edit file next.config.js

const path = require('path');
const webpack = require('webpack');
const CopyPlugin = require('copy-webpack-plugin');

weisisheng

//! How to get all records from a Dynamo DB Table and store as regular JSON

// 1. Run the following command in the terminal
// * Note that the output will be in Dynamo JSON format
// aws dynamodb scan --region REGION --profile PROFILE_NAME --table-name TABLE_NAME > exports.json

// 2. Convert from Dynamo JSON to regular JSON.
const AWS = require('aws-sdk')
const fs = require('fs')

weisisheng

# Near Simplest Language model API, with room to expand!
# runs GPT-J-6B on 3090 and TITAN and servers it using FastAPI
# change "seq" (which is the context size) to adjust footprint
#
# seq   vram usage
# 512   14.7G
# 900   15.3G

# uses FastAPI, so install that
# https://fastapi.tiangolo.com/tutorial/

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{
  "basics": {
    "name": "Your first and last name",
    "label": "",
    "picture": "",
    "email": "Your email address",
    "phone": "A phone number, with any formatting you like. E.g. (555) 555-5555.",
    "degree": "",
    "website": "Your website URL",
    "summary": "A one-sentence to one-paragraph overview text. Do not include any line-breaks.",

weisisheng

Set up a cross-account IAM role in the destination account

• Add a new IAM role
• For type of trusted entity select "another AWS account"
• Specify the accountId of the account that will be using the resource in the destination account. You can find your AWS Account ID, which is available on the support homepage when you are logged in.
• Create a policy that allows lambda:InvokeFunction for your function and attach it to this new role.

Create a lambda in the calling account.

• Set up a role for your lambda that is allowed to assumeRole
• Use the AWS SDK to assume the new role in the destination account.
• Pass the credentials to the lambda object when you create it

weisisheng

import uvicorn
from fastapi import FastAPI
from model import SentimentModel, SentimentQueryModel

app = FastAPI()
model = SentimentModel()

@app.post('/predict')
def predict(data: SentimentQueryModel):
    data = data.dict()