AI Real State Agent

# configurations
.idea
.vscode

# crawlee and apify storage folders
apify_storage
crawlee_storage
storage

# installed files
node_modules

# git folder
.git

# dist folder
dist

root = true

[*]
indent_style = space
indent_size = 2
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
end_of_line = lf

APIFY_TOKEN="apify_api_1234"
ACTOR_TEST_PAY_PER_EVENT=true
LANGSMITH_TRACING=false
LANGSMITH_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
.vscode
storage
apify_storage
crawlee_storage
node_modules
dist
tsconfig.tsbuildinfo
.env

# Added by Apify CLI
.venv

image: gitpod/workspace-base:latest
tasks:
  - 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." && exit

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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 packages
RUN 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 image
FROM apify/actor-node:22

# Check preinstalled packages
RUN 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 debugging
RUN 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 image
COPY --from=builder /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 loaded
9dotenv.config();
10
11/**
12 * Actor input schema
13 */
14type Input = {
15  instructions: string;
16  modelName?: string;
17  openaiApiKey?: string;
18  debug?: boolean;
19}
20
21/**
22 * Actor initialization code
23*/
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 input
33const {
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 datasets
56const apifyClient = new ApifyClient({
57  token: userToken,
58});
59
60/**
61 * LangGraph StateGraph schema
62 */
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 initialized
91  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 🤖 : ${response.output}`);
100  await costHandler.logOrChargeForTokens(modelName, tokenCostActive);
101  return { bestLocations: response.output };
102}
103
104async function researcher(state: StateSchema) {
105  // The researcher agent gets initialized
106  const researcherAgent = new ResearcherAgent({
107    apifyClient,
108    modelName,
109    openaiApiKey: openaiApiKey ?? process.env.OPENAI_API_KEY,
110    log,
111  });
112  const { agentExecutor, costHandler } = researcherAgent;
113  const input = 'The user asked sent this exact query:\n\n'
114    + `'${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-aware
135);
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 | Console
59  ): StructuredToolInterface[] {
60    // Tools are initialized to be passed to the agent
61    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 DuckDuckGo
83        + '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 | Console
57  ): StructuredToolInterface[] {
58    // Tools are initialized to be passed to the agent
59    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 function
16 */
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: 30
56    };
57    this.log.debug(
58      `Calling DuckDuckGo with input: ${JSON.stringify(actorInput)}`
59    );
60    const actorRun = await this.apifyClient
61      .actor('canadesk/duckduckgo-serp-api')
62      .call(actorInput);
63    const dataset = await this.apifyClient
64      .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 default
16 */
17const sampleInput = {
18  method: 'getAllItems',
19  output: '{"results":[""]}',
20};
21
22/**
23 * Tool that uses the WebsiteScraper function
24 */
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.apifyClient
58      .actor('zeeb0t/web-scraping-api---scrape-any-website')
59      .call(actorInput, callOptions);
60    const dataset = await this.apifyClient
61      .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 function
16 */
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.apifyClient
52      .actor('maxcopell/zillow-zip-search')
53      .call(actorInput);
54    const dataset = await this.apifyClient
55      .dataset(actorRun.defaultDatasetId)
56      .listItems();
57    await chargeForToolUsage(this.name, dataset.total);
58    // returns only the top 10 properties to avoid sending too much data
59    // NOTE: this tool could return the dataset-id and use another tool to read it
60    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 function
16 */
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;