shibanovp

Task 1

From our clients we receive two files and imported the to a database:

1. vehicles.csv → a list of trucks
2. Trackings.csv → vehicle data with timestamp ("time") and position ("lat", "lng") • Consider and treat these files as if they were tables • Both tables can be matched via the vehicle_id. Please answer the following questions via a SQL script:
3. Which vehicles are active/inactive (in the sense of having tracking data at all)? Result table with two columns: vehicle_id, active_Boolean

SELECT v.vehicle_id,

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{
  "name": "setup-chat",
  "description": "the gist to setup Build your own AI-Powered chat app with Next.js and LangChain from blog.experienced.dev",
  "version": "0.3.0",
  "engines": {
    "node": ">=18"
  },
  "bin": "./setup.js"
}

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npx create-next-app@latest --ts --tailwind --experimental-app chat

cd chat

# https://github.com/debug-js/debug/issues/912
npm install -S langchain debug supports-color@^8.1.1

# Don't forget to set your API_KEY!
# .env  https://gist.github.com/shibanovp/2178a3e80d92d0ff2a9ce983b3c512ee

shibanovp

import { ChatOpenAI } from "langchain/chat_models/openai";
import { CallbackManager } from "langchain/callbacks";
import {
  ChatPromptTemplate,
  HumanMessagePromptTemplate,
  SystemMessagePromptTemplate,
  MessagesPlaceholder,
} from "langchain/prompts";

import { ConversationChain } from "langchain/chains";

shibanovp

import Chat from "./components/Chat";

export const metadata = {
  title: "Chat with short-term memory",
};

export default function Home() {
  return (
    <main>
      <Chat />