Deprecated
Pricing
Pay per event
Deprecated
This AI agent helps users discover their ideal home effortlessly. Simply input preferences like budget, number of bedrooms, bathrooms, pet-friendliness, and the AI does the rest. It analyzes listings, filters properties based on your criteria and delivers tailored recommendations.
0.0 (0)
Pricing
Pay per event
0
Total users
2
Monthly users
2
Runs succeeded
>99%
Last modified
a month ago
# configurations.idea.vscode
# crawlee and apify storage foldersapify_storagecrawlee_storagestorage
# installed filesnode_modules
# git folder.git
# dist folderdistroot = true
[*]indent_style = spaceindent_size = 2charset = utf-8trim_trailing_whitespace = trueinsert_final_newline = trueend_of_line = lfAPIFY_TOKEN="apify_api_1234"ACTOR_TEST_PAY_PER_EVENT=trueLANGSMITH_TRACING=falseLANGSMITH_ENDPOINT="https://api.smith.langchain.com"LANGSMITH_API_KEY="lsv2_pt_1234"LANGSMITH_PROJECT="langsmith-cool-project-name"OPENAI_API_KEY="sk-proj-1234"{ "root": false, "env": { "browser": true, "es2020": true, "node": true }, "extends": [ "@apify/eslint-config-ts" ], "parserOptions": { "project": "./tsconfig.json", "ecmaVersion": 2020 }, "ignorePatterns": [ "node_modules", "dist", "**/*.d.ts" ], "rules": { "indent": ["error", 2], "comma-dangle": ["off", 0], "prefer-rest-params": ["off", 0], "max-len": ["error", { "ignoreComments": true, "ignoreStrings": true, "ignoreUrls": true, "ignoreTemplateLiterals": true }] }}# This file tells Git which files shouldn't be added to source control
.idea.vscodestorageapify_storagecrawlee_storagenode_modulesdisttsconfig.tsbuildinfo.env
# Added by Apify CLI.venvimage: gitpod/workspace-base:latesttasks: - name: main init: > nvm use lts/jod && npm install -g npm@11 && npm install -g eslint@^8.50.0 && npm install -g apify-cli command: echo "Login to apify to get an API Key, export your APIFY_TOKEN, create an INPUT.json file and run npm start!" - name: config before: > (([[ ! -z $GITCONFIG ]] && echo $GITCONFIG | base64 -d > ~/.gitconfig && chmod 644 ~/.gitconfig) || unset GITCONFIG) && (([[ ! -z $GNUPG_1 ]] && rm -rf ~/.gnupg && cd / && echo $GNUPG_1$GNUPG_2 | base64 -d | tar --no-same-owner -xzf -) || unset GNUPG_1) command: echo "Ready! Start a new terminal session in order to use GPG." && exitApache License Version 2.0, January 2004 http://www.apache.org/licenses/
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.1declare global {2 namespace NodeJS {3 interface ProcessEnv {4 APIFY_TOKEN: string;5 LANGSMITH_TRACING: string;6 LANGSMITH_ENDPOINT: string;7 LANGSMITH_API_KEY: string;8 LANGSMITH_PROJECT: string;9 OPENAI_API_KEY: string;10 ZIP_API_KEY: string;11 NODE_ENV: 'development' | 'production';12 }13 }14}15
16// If this file has no import/export statements (i.e. is a script)17// convert it into a module by adding an empty export statement.18export {}{ "name": "ai-real-state-agent", "version": "0.0.1", "type": "module", "description": "This is an example of a Crawlee project.", "engines": { "node": ">=22.0.0" }, "dependencies": { "@langchain/core": "^0.3.42", "@langchain/langgraph": "^0.2.54", "@langchain/openai": "^0.4.4", "apify": "^3.3.2", "dotenv": "^16.4.7", "langchain": "^0.3.19", "zod": "^3.24.2" }, "devDependencies": { "@apify/eslint-config-ts": "^0.3.0", "@apify/tsconfig": "^0.1.0", "@eslint/js": "^9.21.0", "@types/node": "^22.0.0", "@typescript-eslint/eslint-plugin": "^7.18.0", "@typescript-eslint/parser": "^7.18.0", "eslint": "^8.57.1", "globals": "^16.0.0", "tsx": "^4.4.0", "typescript": "~5.5.0", "typescript-eslint": "^8.26.0" }, "scripts": { "start": "npm run start:dev", "start:prod": "node dist/main.js", "start:dev": "tsx src/main.ts", "build": "tsc", "lint": "eslint src", "test": "echo \"Error: oops, the actor has no tests yet, sad!\" && exit 1" }, "author": "It's not you it's me", "license": "ISC"}{ "extends": "@apify/tsconfig", "compilerOptions": { "module": "NodeNext", "moduleResolution": "NodeNext", "target": "ES2022", "outDir": "dist", "noUnusedLocals": false, "skipLibCheck": true, "lib": ["DOM"], }, "include": [ "./*.d.ts", "./src/**/*", ]}# Specify the base Docker image. You can read more about# the available images at https://docs.apify.com/sdk/js/docs/guides/docker-images# You can also use any other image from Docker Hub.FROM apify/actor-node:22 AS builder
# Check preinstalled packagesRUN npm ls crawlee apify puppeteer playwright
# Copy just package.json and package-lock.json# to speed up the build using Docker layer cache.COPY package*.json ./
# Install all dependencies. Don't audit to speed up the installation.RUN npm install --include=dev --audit=false
# Next, copy the source files using the user set# in the base image.COPY . ./
# Install all dependencies and build the project.# Don't audit to speed up the installation.RUN npm run build
# Create final imageFROM apify/actor-node:22
# Check preinstalled packagesRUN npm ls crawlee apify puppeteer playwright
# Copy just package.json and package-lock.json# to speed up the build using Docker layer cache.COPY package*.json ./
# Install NPM packages, skip optional and development dependencies to# keep the image small. Avoid logging too much and print the dependency# tree for debuggingRUN npm --quiet set progress=false \ && npm install --omit=dev --omit=optional \ && echo "Installed NPM packages:" \ && (npm list --omit=dev --all || true) \ && echo "Node.js version:" \ && node --version \ && echo "NPM version:" \ && npm --version \ && rm -r ~/.npm
# Copy built JS files from builder imageCOPY /usr/src/app/dist ./dist
# Next, copy the remaining files and directories with the source code.# Since we do this after NPM install, quick build will be really fast# for most source file changes.COPY . ./
# Create and run as a non-root user.RUN adduser -h /home/apify -D apify && \ chown -R apify:apify ./USER apify
# Run the image.CMD npm run start:prod --silent{ "actorSpecification": 1, "name": "ai-real-state-agent", "version": "0.1", "buildTag": "latest", "title": "AI Real State Agent", "description": "AI agent that uses a multi-agent approach to find you the best home recommendations using a natural language prompt.", "meta": { "templateId": "ts-empty" }, "environmentVariables": { "OPENAI_API_KEY": "@defaultOpenaiApiKey", "APIFY_TOKEN": "@defaultApifyToken" }, "dockerfile": "./Dockerfile", "input": "./input_schema.json", "storages": { "dataset": "./dataset_schema.json" }}{ "actorSpecification": 1, "views": { "overview": { "title": "Overview", "transformation": { "fields": ["actorName", "response"] }, "display": { "component": "table", "properties": { "actorName": { "label": "Actor name", "format": "text" }, "response": { "label": "Actor evaluation", "format": "text" } } } } }}{ "title": "Web Automation Agent", "type": "object", "schemaVersion": 1, "properties": { "instructions": { "title": "Instructions for the AI Real State Agent", "type": "string", "description": "Ask the agent for help to find the perfect home.", "editor": "textarea", "prefill": "I want to buy a house with a pool in Miami for less than 1 million dollars. Can you help me?" }, "openaiApiKey": { "title": "OpenAI API key", "type": "string", "description": "The API key for accessing OpenAI. You can get it from <a href='https://platform.openai.com/account/api-keys' target='_blank' rel='noopener'>OpenAI platform</a>.", "editor": "textfield", "isSecret": true }, "model": { "title": "GPT model", "type": "string", "description": "Select a GPT model. See <a href='https://platform.openai.com/docs/models/overview' target='_blank' rel='noopener'>models overview</a>. Keep in mind that each model has different pricing and features.", "editor": "select", "default": "gpt-4o-mini", "prefill": "gpt-4o-mini", "enum": ["gpt-4o", "gpt-4o-mini", "gpt-3.5-turbo", "o3-mini", "o1-mini"] } }, "required": ["instructions", "model"]}{ "actor-start-gb": { "eventTitle": "Actor start per 1 GB", "eventDescription": "Flat fee for starting an Actor run for each 1 GB of memory.", "eventPriceUsd": 0.01 }, "openai-1000-tokens-gpt-4o": { "eventTitle": "Price per 1000 OpenAI tokens for gpt-4o", "eventDescription": "Flat fee for every 1000 tokens (input/output) used with gpt-4o.", "eventPriceUsd": 0.01 }, "openai-1000-tokens-gpt-4o-mini": { "eventTitle": "Price per 1000 OpenAI tokens for gpt-4o-mini", "eventDescription": "Flat fee for every 1000 tokens (input/output) used with gpt-4o-mini.", "eventPriceUsd": 0.0006 }, "openai-1000-tokens-gpt-3.5-turbo": { "eventTitle": "Price per 1000 OpenAI tokens for gpt-3.5-turbo", "eventDescription": "Flat fee for every 1000 tokens (input/output) used with gpt-3.5-turbo.", "eventPriceUsd": 0.0015 }, "openai-1000-tokens-gpt-o3-mini": { "eventTitle": "Price per 1000 OpenAI tokens for gpt-o3-mini", "eventDescription": "Flat fee for every 1000 tokens (input/output) used with gpt-o3-mini.", "eventPriceUsd": 0.0044 }, "openai-1000-tokens-gpt-o1-mini": { "eventTitle": "Price per 1000 OpenAI tokens for gpt-o1-mini", "eventDescription": "Flat fee for every 1000 tokens (input/output) used with gpt-o1-mini.", "eventPriceUsd": 0.0044 }, "duck-duck-go": { "eventTitle": "Price per Duck Duck Go search", "eventDescription": "Flat fee for every Duck Duck Go search.", "eventPriceUsd": 0.01 }, "website-scraper':": { "eventTitle": "Price per web page scraped", "eventDescription": "Flat fee for every web page scraped.", "eventPriceUsd": 0.01 }, "zillow-search':": { "eventTitle": "Price per Zillow search result", "eventDescription": "Flat fee for every result when searching Zillow.", "eventPriceUsd": 0.002 }, "zip-code-search": { "eventTitle": "Price per Zip Code search", "eventDescription": "Flat fee for every Zip Code search.", "eventPriceUsd": 0.01 }}1import dotenv from 'dotenv';2import { Actor, ApifyClient, log } from 'apify';3import { StateGraph, StateGraphArgs, START, END } from '@langchain/langgraph';4import LocationExpertAgent from './agents/location_expert.js';5import ResearcherAgent from './agents/researcher.js';6import { chargeForActorStart } from './utils/ppe_handler.js';7
8// if available, .env variables are loaded9dotenv.config();10
11/**12 * Actor input schema13 */14type Input = {15 instructions: string;16 modelName?: string;17 openaiApiKey?: string;18 debug?: boolean;19}20
21/**22 * Actor initialization code23*/24await Actor.init();25await chargeForActorStart();26
27const userToken = Actor.getEnv().token;28if (!userToken) {29 throw new Error('User token is required. Use `apify login` and export your secret as APIFY_TOKEN.');30}31
32// Handle and validate input33const {34 instructions,35 modelName = 'gpt-4o-mini',36 openaiApiKey,37 debug,38} = await Actor.getInput() as Input;39if (debug) {40 log.setLevel(log.LEVELS.DEBUG);41} else {42 log.setLevel(log.LEVELS.INFO);43}44// if available, the Actor uses the user's openaiApiKey. Otherwise it charges for use.45const tokenCostActive = (openaiApiKey ?? '').length === 0;46if (tokenCostActive) {47 log.info("No openaiApiKey was detected. You'll be charged for token usage.");48} else {49 log.info("Env openaiApiKey detected. You won't be charged for token usage.");50}51if (!instructions) {52 throw new Error('Instructions are required. Create an INPUT.json file in the `storage/key_value_stores/default` folder and add the respective keys.');53}54
55// Apify is used to call tools and manage datasets56const apifyClient = new ApifyClient({57 token: userToken,58});59
60/**61 * LangGraph StateGraph schema62 */63type StateSchema = {64 instructions: string;65 bestLocations: string;66 recommendations: string[];67 output: string;68}69
70const graphState: StateGraphArgs<StateSchema>['channels'] = {71 instructions: {72 value: (x?: string, y?: string) => y ?? x ?? '',73 default: () => instructions,74 },75 bestLocations: {76 value: (x?: string, y?: string) => y ?? x ?? '',77 default: () => '',78 },79 recommendations: {80 value: (x?: string[], y?: string[]) => y ?? x ?? [],81 default: () => [],82 },83 output: {84 value: (x?: string, y?: string) => y ?? x ?? '',85 default: () => '',86 },87};88
89async function locationExpert(state: StateSchema) {90 // The researcher agent gets initialized91 const locationExpertAgent = new LocationExpertAgent({92 apifyClient,93 modelName,94 openaiApiKey: openaiApiKey ?? process.env.OPENAI_API_KEY,95 log,96 });97 const { agentExecutor, costHandler } = locationExpertAgent;98 const response = await agentExecutor.invoke({ input: state.instructions });99 log.debug(`locationExpert 🤖 : ${response.output}`);100 await costHandler.logOrChargeForTokens(modelName, tokenCostActive);101 return { bestLocations: response.output };102}103
104async function researcher(state: StateSchema) {105 // The researcher agent gets initialized106 const researcherAgent = new ResearcherAgent({107 apifyClient,108 modelName,109 openaiApiKey: openaiApiKey ?? process.env.OPENAI_API_KEY,110 log,111 });112 const { agentExecutor, costHandler } = researcherAgent;113 const input = 'The user asked sent this exact query:\n\n'114 + `'${state.instructions}'\n\n`115 + 'You asked someone for help to get the best locations in that city and state. '116 + 'The answer you received was this:\n\n'117 + `'${state.bestLocations}'\n\n`118 + 'Please answer the user accordingly.';119 const response = await agentExecutor.invoke({ input });120 await costHandler.logOrChargeForTokens(modelName, tokenCostActive);121 return { output: response.output };122}123
124const graph = new StateGraph({ channels: graphState })125 .addNode('location_expert', locationExpert)126 .addNode('researcher', researcher)127 .addEdge(START, 'location_expert')128 .addEdge('location_expert', 'researcher')129 .addEdge('researcher', END);130
131const runnable = graph.compile();132const response = await runnable.invoke(133 { input: instructions },134 { configurable: { thread_id: 42 } }, // this line shows that the agent can be thread-aware135);136
137log.debug(`Agent 🤖 : ${response.output}`);138
139await Actor.pushData({140 actorName: 'AI Real State Agent',141 response: response.output,142});143
144await Actor.exit();1import { Log, ApifyClient } from 'apify';2import { ChatPromptTemplate } from '@langchain/core/prompts';3import { createToolCallingAgent, AgentExecutor } from 'langchain/agents';4import { ChatOpenAI } from '@langchain/openai';5import { StructuredToolInterface } from '@langchain/core/tools';6import DuckDuckGo from '../tools/duck_duck_go.js';7import WebsiteScraper from '../tools/website_scraper.js';8// import ZipCodeSearch from '../tools/zip_code_search.js';9import { CostHandler } from '../utils/cost_handler.js';10
11/**12 * Interface for parameters required by LocationExpertAgent class.13 */14export interface LocationExpertAgentParams {15 apifyClient: ApifyClient,16 modelName: string,17 openaiApiKey: string,18 log: Log | Console;19}20
21/**22 * Tool that uses the MagicTool function. This is an example function to use as template.23 */24export class LocationExpertAgent {25 protected log: Log | Console;26 protected apifyClient: ApifyClient;27 public agentExecutor: AgentExecutor;28 public costHandler: CostHandler;29
30 constructor(fields?: LocationExpertAgentParams) {31 this.log = fields?.log ?? console;32 this.apifyClient = fields?.apifyClient ?? new ApifyClient();33 this.costHandler = new CostHandler(fields?.modelName ?? 'gpt-4o-mini', this.log);34 const llm = new ChatOpenAI({35 model: fields?.modelName,36 apiKey: fields?.openaiApiKey,37 temperature: 0,38 callbacks: [39 this.costHandler,40 ],41 });42 const tools = this.buildTools(this.apifyClient, this.log);43 const prompt = this.buildPrompt();44 const agent = createToolCallingAgent({45 llm,46 tools,47 prompt,48 });49 this.agentExecutor = new AgentExecutor({50 agent,51 tools,52 verbose: false,53 maxIterations: 5,54 });55 }56
57 protected buildTools(58 apifyClient: ApifyClient, log: Log | Console59 ): StructuredToolInterface[] {60 // Tools are initialized to be passed to the agent61 const duckDuckGo = new DuckDuckGo({ apifyClient, log });62 const websiteScraper = new WebsiteScraper({ apifyClient, log });63 // const zipCodeSearch = new ZipCodeSearch({ log });64 return [65 duckDuckGo,66 websiteScraper,67 // zipCodeSearch,68 ];69 }70
71 protected buildPrompt(): ChatPromptTemplate {72 return ChatPromptTemplate.fromMessages([73 ['system',74 'You are a experienced real state agent that wants to help the user to find the perfect home. '75 + "You will stick to the following steps, but notify the user if you get stuck or can't continue. "76 + 'Step 1. The user will ask you for advice regarding a specific city in the US. '77 + 'If the user does not provide a state (like CA or NY), try to guess to which state a city belongs to. '78 + 'If the user does not provide a state, try to guess to which state a city belongs to. '79 + 'If from the input you cannot get a city and a state or you think that the city is not in US territory, '80 + 'end the conversation and help the user with the input. '81 + "Make sure to convert the state to a two-letter ISO standard. For example, if the user says 'New York', store it as 'NY' before using it. \n"82 // 2. Fetch best Zip Codes to live using DuckDuckGo83 + 'Step 2. With the city and state in hand, use DuckDuckGo replacing the following query: '84 + "'best places to live near [city], [state] by zip code site:niche.com'. "85 + 'If there the results, use a website scraper on the URLs you think will show you this information. '86 + 'Iterate until you find the best 3 Zip Codes near the selected city. '87 + "For best performance when using the website scraper, you can use method='getBestZipCodesToLive' and output=null'. "88 + 'Instead of answering the original question, just return the top 3 Zip Codes and explain to the user why you selected those Zip Codes. \n'89 ],90 ['placeholder', '{chat_history}'],91 ['human', '{input}'],92 ['placeholder', '{agent_scratchpad}'],93 ]);94 }95}96
97export default LocationExpertAgent;1import { Log, ApifyClient } from 'apify';2import { ChatPromptTemplate } from '@langchain/core/prompts';3import { createToolCallingAgent, AgentExecutor } from 'langchain/agents';4import { ChatOpenAI } from '@langchain/openai';5import { StructuredToolInterface } from '@langchain/core/tools';6import ZillowSearch from '../tools/zillow_search.js';7import { CostHandler } from '../utils/cost_handler.js';8
9/**10 * Interface for parameters required by ResearcherAgent class.11 */12export interface ResearcherAgentParams {13 apifyClient: ApifyClient,14 modelName: string,15 openaiApiKey: string,16 log: Log | Console;17}18
19/**20 * Tool that uses the MagicTool function. This is an example function to use as template.21 */22export class ResearcherAgent {23 protected log: Log | Console;24 protected apifyClient: ApifyClient;25 public agentExecutor: AgentExecutor;26 public costHandler: CostHandler;27
28 constructor(fields?: ResearcherAgentParams) {29 this.log = fields?.log ?? console;30 this.apifyClient = fields?.apifyClient ?? new ApifyClient();31 this.costHandler = new CostHandler(fields?.modelName ?? 'gpt-4o-mini', this.log);32 const llm = new ChatOpenAI({33 model: fields?.modelName,34 apiKey: fields?.openaiApiKey,35 temperature: 0,36 callbacks: [37 this.costHandler,38 ],39 });40 const tools = this.buildTools(this.apifyClient, this.log);41 const prompt = this.buildPrompt();42 const agent = createToolCallingAgent({43 llm,44 tools,45 prompt,46 });47 this.agentExecutor = new AgentExecutor({48 agent,49 tools,50 verbose: false,51 maxIterations: 5,52 });53 }54
55 protected buildTools(56 apifyClient: ApifyClient, log: Log | Console57 ): StructuredToolInterface[] {58 // Tools are initialized to be passed to the agent59 const zillowSearch = new ZillowSearch({ apifyClient, log });60 return [61 zillowSearch,62 ];63 }64
65 protected buildPrompt(): ChatPromptTemplate {66 return ChatPromptTemplate.fromMessages([67 ['system',68 'You are a experienced real state agent that wants to help the user to find the perfect home. '69 + "You will stick to the following steps, but notify the user if you get stuck or can't continue. "70 + 'Step 1. Using the selected Zip Codes, search on Zillow for properties that match the user requirements. '71 // + "Remember: Don't perform a Zillow Search until you find a good ranking (every search costs money and you want to save). "72 + 'The user must specify if he or she is looking to rent or buy a property (default to rent if the information is not given). '73 + 'The user can specify if the ideal property has a minimum value (default to 1 if the information is not given). '74 + 'The user can specify if the ideal property has a maximum value (default to 1000 if the information is not given). '75 + 'Inform the user of the assumptions you make before delivering any results. \n'76 + 'Step 2. Based on the results, use your expertise to recommend the best 5 properties that you found. '77 + 'The user may have specified other requests like pets, pool, beds, baths, sqft, gym, etc. '78 + 'Filter the results based on this information or notify the user if you are unable to do so. '79 + 'Make sure that you show the address, price and a link to view more information about the chosen properties. '80 + 'At the end, please explain why you chose those properties. '81 ],82 ['placeholder', '{chat_history}'],83 ['human', '{input}'],84 ['placeholder', '{agent_scratchpad}'],85 ]);86 }87}88
89export default ResearcherAgent;1import { Log, ApifyClient } from 'apify';2import { StructuredTool } from '@langchain/core/tools';3import { z } from 'zod';4import { chargeForToolUsage } from '../utils/ppe_handler.js';5
6/**7 * Interface for parameters required by DuckDuckGo class.8 */9export interface DuckDuckGoParams {10 apifyClient: ApifyClient;11 log: Log | Console;12}13
14/**15 * Tool that uses the DuckDuckGo function16 */17export class DuckDuckGo extends StructuredTool {18 protected log: Log | Console;19 protected apifyClient: ApifyClient;20
21 name = 'duck_duck_go';22
23 description = 'Performs a search on the search engine DuckDuckGo and returns a stringified JSON with the results.';24
25 schema = z.object({26 keywords: z.string(),27 locale: z.enum(['us-en', 'uk-en', 'cz-cs', 'cl-es']) || undefined,28 maximum: z.number() || undefined,29 });30
31 constructor(fields?: DuckDuckGoParams) {32 super(...arguments);33 this.log = fields?.log ?? console;34 this.apifyClient = fields?.apifyClient ?? new ApifyClient();35 }36
37 override async _call(arg: z.output<typeof this.schema>) {38 const actorInput = {39 keywords: arg.keywords,40 proxy: {41 useApifyProxy: true,42 apifyProxyGroups: [43 'RESIDENTIAL'44 ],45 apifyProxyCountry: 'US'46 },47 locale: arg.locale ?? 'us-en',48 operation: 'st',49 safe: 'Partial',50 daterange: 'all',51 img_type: 'all',52 img_size: 'all',53 vid_duration: 'all',54 maximum: arg.maximum ?? 5,55 timeout: 3056 };57 this.log.debug(58 `Calling DuckDuckGo with input: ${JSON.stringify(actorInput)}`59 );60 const actorRun = await this.apifyClient61 .actor('canadesk/duckduckgo-serp-api')62 .call(actorInput);63 const dataset = await this.apifyClient64 .dataset(actorRun.defaultDatasetId)65 .listItems();66 const { items } = dataset;67 this.log.debug(`DuckDuckGo response: ${JSON.stringify(items)}`);68 await chargeForToolUsage(this.name, 1);69 return JSON.stringify(items);70 }71}72
73export default DuckDuckGo;1import { Log } from 'apify';2import { Tool } from '@langchain/core/tools';3
4/**5 * Interface for parameters required by MagicTool class.6 */7export interface MagicToolParams {8 apiKey?: string;9 log: Log | Console;10}11
12/**13 * Tool that uses the MagicTool function. This is an example function to use as template.14 */15export class MagicTool extends Tool {16 static override lc_name() {17 return 'MagicTool';18 }19
20 protected log: Log | Console;21 protected apiKey: string;22
23 name = 'magic_function';24
25 description = 'Applies a magic function to an input.';26
27 constructor(fields?: MagicToolParams) {28 super(...arguments);29 this.log = fields?.log ?? console;30 const apiKey = fields?.apiKey ?? process.env.SECRET_API_KEY ?? '';31 if (apiKey === undefined) {32 this.log.debug(33 "Secret API key not set. You can set it as 'SECRET_API_KEY' in your environment variables."34 );35 }36 this.apiKey = apiKey;37 }38
39 async _call(rawInput: string) {40 this.log.debug(`rawInput: ${rawInput}`);41 const number = parseInt(rawInput, 10);42 return `${number + 2}`;43 }44}45
46export default MagicTool;1import { Log, ApifyClient } from 'apify';2import { StructuredTool } from '@langchain/core/tools';3import { z } from 'zod';4import { chargeForToolUsage } from '../utils/ppe_handler.js';5
6/**7 * Interface for parameters required by WebsiteScraper class.8 */9export interface WebsiteScraperParams {10 apifyClient: ApifyClient;11 log: Log | Console;12}13
14/**15 * An example input that serves as a good default16 */17const sampleInput = {18 method: 'getAllItems',19 output: '{"results":[""]}',20};21
22/**23 * Tool that uses the WebsiteScraper function24 */25export class WebsiteScraper extends StructuredTool {26 protected log: Log | Console;27 protected apifyClient: ApifyClient;28
29 name = 'website_scraper';30
31 description = 'Scrapes a URL aiming the search based on a method (for example: getAllItems) and returns a stringified JSON with the results using the specified output format (for example: {"results":[""]}).';32
33 schema = z.object({34 url: z.string(),35 method: z.string() || undefined,36 // output: z.string() || undefined || null,37 });38
39 constructor(fields?: WebsiteScraperParams) {40 super(...arguments);41 this.log = fields?.log ?? console;42 this.apifyClient = fields?.apifyClient ?? new ApifyClient();43 }44
45 override async _call(arg: z.output<typeof this.schema>) {46 const actorInput = {47 url: arg.url,48 method: arg.method ?? sampleInput.method,49 output: sampleInput.output,50 };51 const callOptions = {52 timeout: 60,53 };54 this.log.debug(55 `Calling WebsiteScraper with input: ${JSON.stringify(actorInput)}`56 );57 const actorRun = await this.apifyClient58 .actor('zeeb0t/web-scraping-api---scrape-any-website')59 .call(actorInput, callOptions);60 const dataset = await this.apifyClient61 .dataset(actorRun.defaultDatasetId)62 .listItems();63 const { items } = dataset;64 this.log.debug(`WebsiteScraper response: ${JSON.stringify(items)}`);65 await chargeForToolUsage(this.name, 1);66 return JSON.stringify(items);67 }68}69
70export default WebsiteScraper;1import { Log, ApifyClient } from 'apify';2import { StructuredTool } from '@langchain/core/tools';3import { z } from 'zod';4import { chargeForToolUsage } from '../utils/ppe_handler.js';5
6/**7 * Interface for parameters required by ZillowSearch class.8 */9export interface ZillowSearchParams {10 apifyClient: ApifyClient;11 log: Log | Console;12}13
14/**15 * Tool that uses the ZillowSearch function16 */17export class ZillowSearch extends StructuredTool {18 protected log: Log | Console;19 protected apifyClient: ApifyClient;20
21 name = 'zillow_search';22
23 description = 'Searches for properties on Zillow based on a list of Zip Codes (at least one) and returns a stringified JSON with the results.';24
25 schema = z.object({26 zipCodes: z.string().array(),27 minimumPrice: z.number(),28 maximumPrice: z.number(),29 forRent: z.boolean(),30 });31
32 constructor(fields?: ZillowSearchParams) {33 super(...arguments);34 this.log = fields?.log ?? console;35 this.apifyClient = fields?.apifyClient ?? new ApifyClient();36 }37
38 override async _call(arg: z.output<typeof this.schema>) {39 const actorInput = {40 forRent: arg.forRent,41 forSaleByAgent: true,42 forSaleByOwner: true,43 priceMax: arg.maximumPrice,44 priceMin: arg.minimumPrice,45 sold: false,46 zipCodes: arg.zipCodes,47 };48 this.log.debug(49 `Calling ZillowSearch with input: ${JSON.stringify(actorInput)}`50 );51 const actorRun = await this.apifyClient52 .actor('maxcopell/zillow-zip-search')53 .call(actorInput);54 const dataset = await this.apifyClient55 .dataset(actorRun.defaultDatasetId)56 .listItems();57 await chargeForToolUsage(this.name, dataset.total);58 // returns only the top 10 properties to avoid sending too much data59 // NOTE: this tool could return the dataset-id and use another tool to read it60 const cappedItems = dataset.items.slice(0, 10);61 this.log.debug(`ZillowSearch response: ${JSON.stringify(cappedItems)}`);62 return JSON.stringify(cappedItems);63 }64}65
66export default ZillowSearch;1import { Log } from 'apify';2import { StructuredTool } from '@langchain/core/tools';3import { z } from 'zod';4import { chargeForToolUsage } from '../utils/ppe_handler.js';5
6/**7 * Interface for parameters required by ZipCodeSearch class.8 */9export interface ZipCodeSearchParams {10 apiKey?: string;11 log: Log | Console;12}13
14/**15 * Tool that uses the ZipCodeSearch function16 */17export class ZipCodeSearch extends StructuredTool {18 protected log: Log | Console;19 protected apiKey: string;20
21 name = 'zip_code_search';22
23 description = 'Returns a list of Zip Codes for a city and the state it belongs to.';24
25 schema = z.object({26 city: z.string(),27 state: z.string(),28 });29
30 constructor(fields?: ZipCodeSearchParams) {31 super(...arguments);32 this.log = fields?.log ?? console;33 const apiKey = fields?.apiKey ?? process.env.ZIP_API_KEY ?? '';34 if (apiKey === undefined) {35 this.log.debug(36 "Secret API key not set. You can set it as 'ZIP_API_KEY' in your environment variables."37 );38 }39 this.apiKey = apiKey;40 }41
42 protected buildUrl = (city: string, state: string): string => {43 const baseUrl = `https://www.zipcodeapi.com/rest/${this.apiKey}/city-zips.json`;44 return `${baseUrl}/${city}/${state}`;45 };46
47 override async _call(arg: z.output<typeof this.schema>) {48 const serviceUrl = this.buildUrl(arg.city, arg.state);49 this.log.debug(50 `Calling ZipCodeSearch with city='${arg.city}' and state='${arg.state}'`51 );52 const resp = await fetch(serviceUrl);53 const json = await resp.json();54 this.log.debug(`ZipCodeSearch response: ${JSON.stringify(json)}`);55 await chargeForToolUsage(this.name, 1);56 const zipCodes = (json.zip_codes || []).join(', ');57 return zipCodes;58 }59}60
61export default ZipCodeSearch;1import { Log } from 'apify';2import { BaseTracer } from 'langchain/callbacks';3import { Run } from '@langchain/core/tracers/tracer_langchain';4import { GPT_MODEL_LIST, OpenaiAPICost } from './openai_models.js';5import { chargeForModelTokens } from './ppe_handler.js';6
7interface TotalCost {8 usd: number;9 inputTokens: number;10 outputTokens: number;11 totalModelCalls: number;12}13
14export class CostHandler extends BaseTracer {15 protected log: Log | Console;16 name: string;17 modelName: string;18 modelCost: OpenaiAPICost;19 totalCost: TotalCost;20
21 constructor(modelName: string, log?: Log | Console) {22 super();23 this.log = log ?? console;24 this.name = 'cost_handler';25 this.modelName = modelName;26 this.modelCost = GPT_MODEL_LIST[this.modelName].cost;27 this.totalCost = {28 usd: 0,29 inputTokens: 0,30 outputTokens: 0,31 totalModelCalls: 0,32 };33 }34
35 // NOTE: We do not need to persist runs in this handler.36 // eslint-disable-next-line @typescript-eslint/no-unused-vars37 persistRun(_run: Run) {38 return Promise.resolve();39 }40
41 /**42 * Logs tokens usage in $.43 * @returns void44 */45 override onLLMEnd(run: Run) {46 const tokenUsage = run?.outputs?.llmOutput?.tokenUsage;47 if (tokenUsage) {48 const inputCostsUSD = this.modelCost.input49 * (tokenUsage.promptTokens / 1000);50 const outputCostsUSD = this.modelCost.output51 * (tokenUsage.completionTokens / 1000);52 const callCostUSD = inputCostsUSD + outputCostsUSD;53 this.totalCost.usd += inputCostsUSD + outputCostsUSD;54 this.totalCost.inputTokens += tokenUsage.promptTokens;55 this.totalCost.outputTokens += tokenUsage.completionTokens;56 this.totalCost.totalModelCalls++;57 const durationSecs = run.end_time && run.start_time58 && (run.end_time - run.start_time) / 1000;59 this.log.debug(`LLM model call processed`,60 {61 durationSecs,62 callCostUSD,63 totalCostUSD: this.totalCost.usd,64 inputTokens: this.totalCost.inputTokens,65 outputTokens: this.totalCost.outputTokens,66 }67 );68 }69 }70
71 override onLLMStart(run: Run) {72 this.log.debug(`Calling LLM model`, run);73 }74
75 getTotalCost() {76 return this.totalCost;77 }78
79 async logOrChargeForTokens(modelName: string, tokenCostActive: boolean) {80 const costs = this.totalCost;81 if (tokenCostActive) {82 const tokens = costs.inputTokens + costs.outputTokens;83 const tokensCost = this.modelCost.output * (tokens / 1000);84 this.log.info(`Total tokens processed: ${tokens}. Usage cost: ${tokensCost}`);85 await chargeForModelTokens(modelName, tokens);86 } else {87 this.log.info(`Estimated OpenAI cost: $${costs.usd} USD`);88 }89 }90}1export interface OpenaiAPICost {2 input: number; // USD cost per 1000 tokens3 output: number; // USD cost per 1000 tokens4}5
6export interface GPTModelConfig {7 model: string;8 maxTokens: number;9 maxOutputTokens?: number;10 interface: 'text' | 'chat';11 cost: OpenaiAPICost; // USD cost per 1000 tokens12}13
14/**15* List of GPT models that can be used.16* Should be in sync with https://platform.openai.com/docs/models/17* Last updated on 2025-03-0918*/19export const GPT_MODEL_LIST: {[key: string]: GPTModelConfig} = {20 'gpt-4o': {21 model: 'gpt-4o',22 maxTokens: 16384,23 interface: 'chat',24 cost: {25 input: 0.0025,26 output: 0.01,27 },28 },29 'gpt-4o-mini': {30 model: 'gpt-4o-mini',31 maxTokens: 16384,32 interface: 'chat',33 cost: {34 input: 0.00015,35 output: 0.0006,36 },37 },38 'gpt-3.5-turbo': {39 model: 'gpt-3.5-turbo',40 maxTokens: 8192,41 interface: 'chat',42 cost: {43 input: 0.0005,44 output: 0.0015,45 },46 },47 'o3-mini': {48 model: 'o3-mini',49 maxTokens: 4096,50 interface: 'chat',51 cost: {52 input: 0.0011,53 output: 0.0044,54 },55 },56 'o1-mini': {57 model: 'o1-mini',58 maxTokens: 2048,59 interface: 'chat',60 cost: {61 input: 0.0011,62 output: 0.0044,63 },64 },65};1export const PPE_EVENT = {2 ACTOR_START_GB: 'actor-start-gb',3 GPT_4O: 'openai-1000-tokens-gpt-4o',4 GPT_4O_MINI: 'openai-1000-tokens-gpt-4o-mini',5 GPT_3_5_TURBO: 'openai-1000-tokens-gpt-3.5-turbo',6 GPT_O3_MINI: 'openai-1000-tokens-gpt-o3-mini',7 GPT_O1_MINI: 'openai-1000-tokens-gpt-o1-mini',8 DUCK_DUCK_GO: 'duck-duck-go-search',9 WEBSITE_SCRAPER: 'site-scraped',10 ZILLOW_SEARCH: 'zillow-results',11 ZIP_CODE_SEARCH: 'zip-code-search',12} as const;1import { Actor, log } from 'apify';2import { PPE_EVENT } from './ppe_events.js';3
4/**5 * Charges for the tokens used by a specific model.6 *7 * @param modelName - The name of the model.8 * @param tokens - The number of tokens to charge for.9 * @throws Will throw an error if the model name is unknown.10 */11export async function chargeForModelTokens(modelName: string, tokens: number) {12 const tokensK = Math.ceil(tokens / 1000);13 log.debug(`Charging for ${tokens} tokens (${tokensK}k) for model ${modelName}`);14 let eventName: string = PPE_EVENT.GPT_4O;15 switch (modelName) {16 case 'gpt-4o-mini':17 eventName = PPE_EVENT.GPT_4O_MINI;18 break;19 case 'gpt-3.5-turbo':20 eventName = PPE_EVENT.GPT_3_5_TURBO;21 break;22 case 'gpt-o3-mini':23 eventName = PPE_EVENT.GPT_O3_MINI;24 break;25 case 'gpt-o1-mini':26 eventName = PPE_EVENT.GPT_O1_MINI;27 break;28 default:29 eventName = PPE_EVENT.GPT_4O;30 break;31 }32 await Actor.charge(33 { eventName, count: tokensK }34 );35}36
37export async function chargeForActorStart() {38 if (39 Actor.getChargingManager()40 .getChargedEventCount(PPE_EVENT.ACTOR_START_GB) === 041 ) {42 const count = Math.ceil((Actor.getEnv().memoryMbytes || 1024) / 1024);43 await Actor.charge({ eventName: PPE_EVENT.ACTOR_START_GB, count });44 }45}46
47export async function chargeForToolUsage(toolName: string, count: number) {48 log.debug(`Charging #${count} times for tool ${toolName}`);49 let eventName: string = '';50 switch (toolName) {51 case 'duck_duck_go':52 eventName = PPE_EVENT.DUCK_DUCK_GO;53 break;54 case 'website_scraper':55 eventName = PPE_EVENT.WEBSITE_SCRAPER;56 break;57 case 'zillow_search':58 eventName = PPE_EVENT.ZILLOW_SEARCH;59 break;60 case 'zip_code_search':61 eventName = PPE_EVENT.ZIP_CODE_SEARCH;62 break;63 default:64 eventName = '';65 break;66 }67 await Actor.charge({ eventName, count });68}