TypeScript SDK Specification

Getting started

Installing the exa-js SDK

npm
pnpm


npm install exa-js

and then instantiate an Exa client

TypeScript

import Exa from 'exa-js';

const exa = new Exa(process.env.EXA_API_KEY);

Get API Key

Follow this link to get your API key

`search` Method

Perform an Exa search given an input query and retrieve a list of relevant results as links.

Input Example

const result = await exa.search(
  "hottest AI startups",
  {
    numResults: 2
  }
);

Input Parameters

Parameter	Type	Description	Default
query	string	The input query string.	Required
numResults	number	Number of search results to return. Limits vary by search type: with “keyword”: max 10, with “neural”: max 100. If you want to increase the num results, contact sales ([email protected])	10
includeDomains	string[]	List of domains to include in the search.	undefined
excludeDomains	string[]	List of domains to exclude in the search.	undefined
startCrawlDate	string	Results will only include links crawled after this date.	undefined
endCrawlDate	string	Results will only include links crawled before this date.	undefined
startPublishedDate	string	Results will only include links with a published date after this date.	undefined
endPublishedDate	string	Results will only include links with a published date before this date.	undefined
type	string	The type of search, “keyword” or “neural”.	“auto”
category	string	data category to focus on when searching, with higher comprehensivity and data cleanliness. Available categories: “company”, “research paper”, “news”, “linkedin profile”, “github”, “tweet”, “movie”, “song”, “personal site”, “pdf”, “financial report”.	undefined
includeText	string[]	List of strings that must be present in webpage text of results. Currently, only 1 string is supported, of up to 5 words.	undefined
excludeText	string[]	List of strings that must not be present in webpage text of results. Currently, only 1 string is supported, of up to 5 words. Checks from the first 1000 words of the webpage text.	undefined

Returns Example

{
  "autopromptString": "Here is a link to one of the hottest AI startups:",
  "results": [
    {

      "title": "Adept: Useful General Intelligence",
      "id": "https://www.adept.ai/",
      "url": "https://www.adept.ai/",
      "publishedDate": "2000-01-01",
      "author": null
    },
    {

      "title": "Home | Tenyx, Inc.",
      "id": "https://www.tenyx.com/",
      "url": "https://www.tenyx.com/",
      "publishedDate": "2019-09-10",
      "author": null
    }
  ]
}

Return Parameters

`SearchResponse`

Field	Type	Description
results	Result[]	List of Result objects

`Result` Object

Field	Type	Description
url	string	URL of the search result
id	string	Temporary ID for the document
title	string \| null	Title of the search result

`searchAndContents` Method

Perform an Exa search given an input query and retrieve a list of relevant results as links, optionally including the full text and/or highlights of the content.

Input Example

TypeScript

// Search with full text content
const resultWithText = await exa.searchAndContents(
  "AI in healthcare",
  {
    text: true,
    numResults: 2
  }
);

// Search with highlights
const resultWithHighlights = await exa.searchAndContents(
  "AI in healthcare",
  {
    highlights: true,
    numResults: 2
  }
);

// Search with both text and highlights
const resultWithTextAndHighlights = await exa.searchAndContents(
  "AI in healthcare",
  {
    text: true,
    highlights: true,
    numResults: 2
  }
);

// Search with context string for RAG
const resultWithContext = await exa.searchAndContents(
  "AI in healthcare",
  {
    context: true,
    numResults: 5
  }
);

// Search with context string and character limit
const resultWithLimitedContext = await exa.searchAndContents(
  "AI in healthcare",
  {
    context: { maxCharacters: 10000 },
    numResults: 5
  }
);

// Search with structured summary schema
const companySchema = {
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Company Information",
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "The name of the company"
    },
    "industry": {
      "type": "string",
      "description": "The industry the company operates in"
    },
    "foundedYear": {
      "type": "number",
      "description": "The year the company was founded"
    },
    "keyProducts": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "List of key products or services offered by the company"
    },
    "competitors": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "List of main competitors"
    }
  },
  "required": ["name", "industry"]
};

const resultWithStructuredSummary = await exa.searchAndContents(
  "OpenAI company information",
  {
    summary: {
      schema: companySchema
    },
    category: "company",
    numResults: 3
  }
);

// Parse the structured summary (returned as a JSON string)
const firstResult = resultWithStructuredSummary.results[0];
if (firstResult.summary) {
  const structuredData = JSON.parse(firstResult.summary);
  console.log(structuredData.name);        // e.g. "OpenAI"
  console.log(structuredData.industry);    // e.g. "Artificial Intelligence"
  console.log(structuredData.keyProducts); // e.g. ["GPT-4", "DALL-E", "ChatGPT"]
}

Input Parameters

Parameter	Type	Description	Default
query	string	The input query string.	Required
text	boolean \| { maxCharacters?: number, includeHtmlTags?: boolean }	If provided, includes the full text of the content in the results.	undefined
highlights	boolean \| { query?: string, numSentences?: number, highlightsPerUrl?: number }	If provided, includes highlights of the content in the results.	undefined
context	boolean \| { maxCharacters?: number }	Return page contents as a context string for LLM RAG. When true, combines all result contents into one string. We recommend 10000+ characters for best results. Context strings often perform better than highlights for RAG applications.	undefined
numResults	number	Number of search results to return. Limits vary by search type: with “keyword”: max 10, with “neural”: max 100. If you want to increase the num results, contact sales ([email protected])	10
includeDomains	string[]	List of domains to include in the search.	undefined
excludeDomains	string[]	List of domains to exclude in the search.	undefined
startCrawlDate	string	Results will only include links crawled after this date.	undefined
endCrawlDate	string	Results will only include links crawled before this date.	undefined
startPublishedDate	string	Results will only include links with a published date after this date.	undefined
endPublishedDate	string	Results will only include links with a published date before this date.	undefined
type	string	The type of search, “keyword” or “neural”.	“auto”
category	string	A data category to focus on when searching, with higher comprehensivity and data cleanliness. Available categories: “company”, “research paper”, “news”, “linkedin profile”, “github”, “tweet”, “movie”, “song”, “personal site”, “pdf” and “financial report”.	undefined
includeText	string[]	List of strings that must be present in webpage text of results. Currently, only 1 string is supported, of up to 5 words.	undefined
excludeText	string[]	List of strings that must not be present in webpage text of results. Currently, only 1 string is supported, of up to 5 words. Checks from the first 1000 words of the webpage text.	undefined

Returns Example

JSON

{
  "results": [
    {

      "title": "2023 AI Trends in Health Care",
      "id": "https://aibusiness.com/verticals/2023-ai-trends-in-health-care-",
      "url": "https://aibusiness.com/verticals/2023-ai-trends-in-health-care-",
      "publishedDate": "2022-12-29",
      "author": "Wylie Wong",
      "text": "While the health care industry was initially slow to [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "But to do so, many health care institutions would like to share data, so they can build a more comprehensive dataset to use to train an AI model. Traditionally, they would have to move the data to one central repository. However, with federated or swarm learning, the data does not have to move. Instead, the AI model goes to each individual health care facility and trains on the data, he said. This way, health care providers can maintain security and governance over their data."
      ],
      "highlightScores": [
        0.5566554069519043
      ]
    },
    {

      "title": "AI in healthcare: Innovative use cases and applications",
      "id": "https://www.leewayhertz.com/ai-use-cases-in-healthcare",
      "url": "https://www.leewayhertz.com/ai-use-cases-in-healthcare",
      "publishedDate": "2023-02-13",
      "author": "Akash Takyar",
      "text": "The integration of AI in healthcare is not [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "The ability of AI to analyze large amounts of medical data and identify patterns has led to more accurate and timely diagnoses. This has been especially helpful in identifying complex medical conditions, which may be difficult to detect using traditional methods. Here are some examples of successful implementation of AI in healthcare. IBM Watson Health: IBM Watson Health is an AI-powered system used in healthcare to improve patient care and outcomes. The system uses natural language processing and machine learning to analyze large amounts of data and provide personalized treatment plans for patients."
      ],
      "highlightScores": [
        0.6563674807548523
      ]
    }
  ]
}

Return Parameters

`SearchResponse`

Field	Type	Description
results	SearchResult<T>[]	List of SearchResult objects

`SearchResult`

Extends the Result object from the search method with additional fields based on T:

Field	Type	Description
text?	string	Text of the search result page (if requested)
highlights?	string[]	Highlights of the search result (if requested)
highlightScores?	number[]	Scores of the highlights (if requested)

Note: The actual fields present in the SearchResult<T> object depend on the options provided in the searchAndContents call.

`findSimilar` Method

Find a list of similar results based on a webpage’s URL.

Input Example

const similarResults = await exa.findSimilar(
  "https://www.example.com",
  {
    numResults: 2,
    excludeSourceDomain: true
  }
);

Input Parameters

Parameter	Type	Description	Default
url	string	The URL of the webpage to find similar results for.	Required
numResults	number	Number of similar results to return.	undefined
includeDomains	string[]	List of domains to include in the search.	undefined
excludeDomains	string[]	List of domains to exclude from the search.	undefined
startCrawlDate	string	Results will only include links crawled after this date.	undefined
endCrawlDate	string	Results will only include links crawled before this date.	undefined
startPublishedDate	string	Results will only include links with a published date after this date.	undefined
endPublishedDate	string	Results will only include links with a published date before this date.	undefined
excludeSourceDomain	boolean	If true, excludes results from the same domain as the input URL.	undefined
category	string	A data category to focus on when searching, with higher comprehensivity and data cleanliness.	undefined

Returns Example

JSON

{
  "results": [
    {

      "title": "Play New Free Online Games Every Day",
      "id": "https://www.minigames.com/new-games",
      "url": "https://www.minigames.com/new-games",
      "publishedDate": "2000-01-01",
      "author": null
    },
    {

      "title": "Play The best Online Games",
      "id": "https://www.minigames.com/",
      "url": "https://www.minigames.com/",
      "publishedDate": "2000-01-01",
      "author": null
    }
  ]
}

Return Parameters

`SearchResponse`

Field	Type	Description
results	Result[]	List of Result objects

`Result` Object

Field	Type	Description
url	string	URL of the search result
id	string	Temporary ID for the document
title	string \| null	Title of the search result

`findSimilarAndContents` Method

Find a list of similar results based on a webpage’s URL, optionally including the text content or highlights of each result.

Input Example

TypeScript

// Find similar with full text content
const similarWithText = await exa.findSimilarAndContents(
  "https://www.example.com/article",
  {
    text: true,
    numResults: 2
  }
);

// Find similar with highlights
const similarWithHighlights = await exa.findSimilarAndContents(
  "https://www.example.com/article",
  {
    highlights: true,
    numResults: 2
  }
);

// Find similar with both text and highlights
const similarWithTextAndHighlights = await exa.findSimilarAndContents(
  "https://www.example.com/article",
  {
    text: true,
    highlights: true,
    numResults: 2,
    excludeSourceDomain: true
  }
);

Input Parameters

Parameter	Type	Description	Default
url	string	The URL of the webpage to find similar results for.	Required
text	boolean \| { maxCharacters?: number, includeHtmlTags?: boolean }	If provided, includes the full text of the content in the results.	undefined
highlights	boolean \| { query?: string, numSentences?: number, highlightsPerUrl?: number }	If provided, includes highlights of the content in the results.	undefined
numResults	number	Number of similar results to return.	undefined
includeDomains	string[]	List of domains to include in the search.	undefined
excludeDomains	string[]	List of domains to exclude from the search.	undefined
startCrawlDate	string	Results will only include links crawled after this date.	undefined
endCrawlDate	string	Results will only include links crawled before this date.	undefined
startPublishedDate	string	Results will only include links with a published date after this date.	undefined
endPublishedDate	string	Results will only include links with a published date before this date.	undefined
excludeSourceDomain	boolean	If true, excludes results from the same domain as the input URL.	undefined
category	string	A data category to focus on when searching, with higher comprehensivity and data cleanliness.	undefined

Returns Example

JSON

{
  "results": [
    {

      "title": "Similar Article: AI and Machine Learning",
      "id": "https://www.similarsite.com/ai-ml-article",
      "url": "https://www.similarsite.com/ai-ml-article",
      "publishedDate": "2023-05-15",
      "author": "Jane Doe",
      "text": "Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various industries. [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "AI and ML are transforming how businesses operate, enabling more efficient processes and data-driven decision making.",
        "The future of AI looks promising, with potential applications in healthcare, finance, and autonomous vehicles."
      ],
      "highlightScores": [
        0.95,
        0.89
      ]
    },
    {

      "title": "The Impact of AI on Modern Technology",
      "id": "https://www.techblog.com/ai-impact",
      "url": "https://www.techblog.com/ai-impact",
      "publishedDate": "2023-06-01",
      "author": "John Smith",
      "text": "In recent years, artificial intelligence has made significant strides in various technological domains. [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "AI is not just a buzzword; it's a transformative technology that's reshaping industries and creating new opportunities.",
        "As AI continues to evolve, ethical considerations and responsible development become increasingly important."
      ],
      "highlightScores": [
        0.92,
        0.88
      ]
    }
  ]
}

Return Parameters

`SearchResponse`

Field	Type	Description
results	SearchResult<T>[]	List of SearchResult objects

SearchResult

Extends the Result object with additional fields based on the requested content:

Field	Type	Description
url	string	URL of the search result
id	string	Temporary ID for the document
title	`string	null`	Title of the search result

`getContents` Method

Retrieves contents of documents based on a list of document IDs.

Input Example

TypeScript

// Get contents for a single ID
const singleContent = await exa.getContents("https://www.example.com/article");

// Get contents for multiple IDs
const multipleContents = await exa.getContents([
  "https://www.example.com/article1",
  "https://www.example.com/article2"
]);

// Get contents with specific options
const contentsWithOptions = await exa.getContents(
  ["https://www.example.com/article1", "https://www.example.com/article2"],
  {
    text: { maxCharacters: 1000 },
    highlights: { query: "AI", numSentences: 2 }
  }
);

Input Parameters

Parameter	Type	Description	Default
ids	string \| string[] \| SearchResult[]`	A single ID, an array of IDs, or an array of SearchResults.	Required
text	boolean \| { maxCharacters?: number, includeHtmlTags?: boolean }	If provided, includes the full text of the content in the results.	undefined
highlights	boolean \| { query?: string, numSentences?: number, highlightsPerUrl?: number }	If provided, includes highlights of the content in the results.	undefined

Returns Example

JSON

{
  "results": [
    {
      "id": "https://www.example.com/article1",
      "url": "https://www.example.com/article1",
      "title": "The Future of Artificial Intelligence",
      "publishedDate": "2023-06-15",
      "author": "Jane Doe",
      "text": "Artificial Intelligence (AI) has made significant strides in recent years. [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "AI is revolutionizing industries from healthcare to finance, enabling more efficient processes and data-driven decision making.",
        "As AI continues to evolve, ethical considerations and responsible development become increasingly important."
      ],
      "highlightScores": [
        0.95,
        0.92
      ]
    },
    {
      "id": "https://www.example.com/article2",
      "url": "https://www.example.com/article2",
      "title": "Machine Learning Applications in Business",
      "publishedDate": "2023-06-20",
      "author": "John Smith",
      "text": "Machine Learning (ML) is transforming how businesses operate and make decisions. [... TRUNCATED FOR BREVITY ...]",
      "highlights": [
        "Machine Learning algorithms can analyze vast amounts of data to identify patterns and make predictions.",
        "Businesses are leveraging ML for customer segmentation, demand forecasting, and fraud detection."
      ],
      "highlightScores": [
        0.93,
        0.90
      ]
    }
  ]
}

Return Parameters

`SearchResponse`

Field	Type	Description
results	SearchResult<T>[]	List of SearchResult objects

`SearchResult`

The fields in the SearchResult<T> object depend on the options provided in the getContents call:

Field	Type	Description
id	string	Temporary ID for the document
url	string	URL of the search result
title	`string	null`	Title of the search result
publishedDate?	string	Estimated creation date
author?	string	Author of the content, if available
text?	string	Text of the search result page (if requested)
highlights?	string[]	Highlights of the search result (if requested)
highlightScores?	number[]	Scores of the highlights (if requested)

Note: The actual fields present in the SearchResult<T> object depend on the options provided in the getContents call. If neither text nor highlights is specified, the method defaults to including the full text content.

`answer` Method

Generate an answer to a query using Exa’s search and LLM capabilities. This returns an AnswerResponse object with the answer text and citations used. You may optionally retrieve the full text of each source by setting text: true.

Input Example

TypeScript

// Basic usage
const answerResponse = await exa.answer("What is the capital of France?");
console.log(answerResponse);

// If you want the full text of each citation in the result
const answerWithText = await exa.answer("What is the capital of France?", { text: true });
console.log(answerWithText);

Input Parameters

Parameter	Type	Description	Default
query	string	The question or query to answer.	Required
options	{text?: boolean}	If text is true, each source in the result includes its full text.

Returns Example

JSON

{
  "answer": "The capital of France is Paris.",
  "citations": [
    {
      "id": "https://www.example.com/france",
      "url": "https://www.example.com/france",
      "title": "France - Wikipedia",
      "publishedDate": "2023-01-01",
      "author": null,
      "text": "France, officially the French Republic, is a country in... [truncated for brevity]"
    }
  ],
  "requestId": "abc123"
}

Return Parameters

`AnswerResponse`

TypeScript

interface AnswerResponse {
  answer: string;
  citations: SearchResult<{}>[];
  requestId?: string;
}

Field	Type	Description
answer	string	The generated answer text
citations	SearchResult<{ }>[]	The citations used to generate the answer
requestId?	string	Optional request ID for reference

Each citation is a SearchResult<{}> — a basic result object that can include text if options.text was set to true.

`streamAnswer` Method

Generate a streaming answer to a query with Exa’s LLM capabilities. This returns an async generator yielding chunks of text and/or citations as they become available.

Input Example

TypeScript

for await (const chunk of exa.streamAnswer("Explain quantum entanglement in simple terms.", { text: true })) {
  if (chunk.content) {
    process.stdout.write(chunk.content); // partial text
  }
  if (chunk.citations) {
    console.log("\nCitations:");
    console.log(chunk.citations);
  }
}

Input Parameters

Parameter	Type	Description	Default
query	string	The question to answer.	Required
options	{ text?: boolean }	If text is true, each citation chunk includes its full text.

Return Type

An async generator of objects with the type:

TypeScript

interface AnswerStreamChunk {
  content?: string;
  citations?: Array<{
    id: string;
    url: string;
    title?: string;
    publishedDate?: string;
    author?: string;
    text?: string;
  }>;
}

content is the partial text content of the answer so far (streamed in chunks).
citations is an array of citation objects that appear at this chunk in the response.

You can end iteration by using a break or by letting the loop finish naturally.

`research.create` Method

Create an asynchronous research task that performs multi-step web research and returns structured JSON results with citations.

Input Example

TypeScript

import Exa, { ResearchModel } from "exa-js";

const exa = new Exa(process.env.EXA_API_KEY);

// Simple research task
const instructions = "What is the latest valuation of SpaceX?";
const schema = {
  type: "object",
  properties: {
    valuation: { type: "string" },
    date: { type: "string" },
    source: { type: "string" }
  }
};

const task = await exa.research.create({
  instructions: instructions,
  outputSchema: schema
});

// Or even simpler - let the model infer the schema
const simpleTask = await exa.research.create({
  instructions: "What are the main benefits of meditation?",
  outputSchema: undefined // Schema will be inferred
});

console.log(`Task created with ID: ${task.researchId}`);

Input Parameters

Parameter	Type	Description	Default
instructions	string	Natural language instructions describing what the research task should accomplish.	Required
model	ResearchModel	The research model to use. Options: ResearchModel.exa_research, ResearchModel.exa_research_pro	exa_research
outputSchema	object	Optional JSON schema for structured output. If not provided, schema will be inferred.	undefined

Returns Example

JSON

{
  "researchId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}

Return Type

TypeScript

interface CreateTaskResponse {
  researchId: string;
}

Field	Type	Description
researchId	string	The unique identifier for the task

`research.get` Method

Get the current status and results of a research task by its ID.

Input Example

TypeScript

// Get a research task by ID
const researchId = "your-research-id-here";
const task = await exa.research.get(researchId);

console.log(`Task status: ${task.status}`);
if (task.status === "completed") {
  console.log(`Results: ${JSON.stringify(task.data)}`);
  console.log(`Citations: ${JSON.stringify(task.citations)}`);
}

Input Parameters

Parameter	Type	Description	Default
researchId	string	The unique identifier of the task	Required

Returns Example

JSON

{
  "researchId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "status": "completed",
  "instructions": "What is the latest valuation of SpaceX?",
  "schema": {
    "type": "object",
    "properties": {
      "valuation": {"type": "string"},
      "date": {"type": "string"},
      "source": {"type": "string"}
    }
  },
  "data": {
    "valuation": "$350 billion",
    "date": "December 2024",
    "source": "Financial Times"
  },
  "citations": {
    "valuation": [
      {
        "id": "https://www.ft.com/content/...",
        "url": "https://www.ft.com/content/...",
        "title": "SpaceX valued at $350bn in employee share sale",
        "snippet": "SpaceX has been valued at $350bn..."
      }
    ]
  }
}

Return Type

TypeScript

interface ResearchTask {
  researchId: string;
  status: "running" | "completed" | "failed";
  instructions: string;
  schema?: object;
  data?: object;
  citations?: Record<string, Citation[]>;
}

interface Citation {
  id: string;
  url: string;
  title?: string;
  snippet: string;
}

Field	Type	Description
researchId	string	The unique identifier for the task
status	string	Task status: “running”, “completed”, or “failed”
instructions	string	The original instructions provided
schema	object (optional)	The JSON schema specification used
data	object (optional)	The research results (when completed)
citations	Record<string, Citation[]> (optional)	Citations grouped by root field (when completed)

`research.pollUntilFinished` Method

Poll a research task until it completes or fails, returning the final result.

Input Example

TypeScript

// Create and poll a task until completion
const task = await exa.research.create({
  instructions: "Get information about Paris, France",
  outputSchema: {
    type: "object",
    properties: {
      name: { type: "string" },
      population: { type: "string" },
      founded_date: { type: "string" }
    }
  }
});

// Poll until completion
const result = await exa.research.pollUntilFinished(task.researchId);
console.log(`Research complete: ${JSON.stringify(result.data)}`);

Input Parameters

Parameter	Type	Description	Default
researchId	string	The unique identifier of the task	Required

Note: The pollUntilFinished method automatically polls every 1 second with a timeout of 10 minutes.

Returns

Returns a ResearchTask object with the completed task data (same structure as getTask).

`research.list` Method

List all research tasks with optional pagination.

Input Example

TypeScript

// List all research tasks
const response = await exa.research.list();
console.log(`Found ${response.data.length} tasks`);

// List with pagination
const paginatedResponse = await exa.research.list({ limit: 10 });
if (paginatedResponse.hasMore) {
  const nextPage = await exa.research.list({
    cursor: paginatedResponse.nextCursor
  });
}

Input Parameters

Parameter	Type	Description	Default
cursor	string	Pagination cursor from previous request	undefined
limit	number	Number of results to return (1-200)	25

Returns Example

JSON

{
  "data": [
    {
      "id": "task-1",
      "status": "completed",
      "instructions": "Research SpaceX valuation",
      ...
    },
    {
      "id": "task-2",
      "status": "running",
      "instructions": "Compare GPU specifications",
      ...
    }
  ],
  "hasMore": true,
  "nextCursor": "eyJjcmVhdGVkQXQiOiIyMDI0LTAxLTE1VDE4OjMwOjAwWiIsImlkIjoidGFzay0yIn0="
}

Return Type

TypeScript

interface ListTasksResponse {
  data: ResearchTask[];
  hasMore: boolean;
  nextCursor?: string;
}

Field	Type	Description
data	ResearchTask[]	List of research task objects
hasMore	boolean	Whether there are more results to paginate
nextCursor	string (optional)	Cursor for the next page (if hasMore is true)

SDKs

​Getting started

Get API Key

​search Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​SearchResponse

​Result Object

​searchAndContents Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​SearchResponse

​SearchResult

​findSimilar Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​SearchResponse

​Result Object

​findSimilarAndContents Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​SearchResponse

​SearchResult

​getContents Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​SearchResponse

​SearchResult

​answer Method

​Input Example

​Input Parameters

​Returns Example

​Return Parameters

​AnswerResponse

​streamAnswer Method

​Input Example

​Input Parameters

​Return Type

​research.create Method

​Input Example

​Input Parameters

​Returns Example

​Return Type

​research.get Method

​Input Example

​Input Parameters

​Returns Example

​Return Type

​research.pollUntilFinished Method

​Input Example

​Input Parameters

​Returns

​research.list Method

​Input Example

​Input Parameters

​Returns Example

​Return Type

Getting started

`search` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`SearchResponse`

`Result` Object

`searchAndContents` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`SearchResponse`

`SearchResult`

`findSimilar` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`SearchResponse`

`Result` Object

`findSimilarAndContents` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`SearchResponse`

SearchResult

`getContents` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`SearchResponse`

`SearchResult`

`answer` Method

Input Example

Input Parameters

Returns Example

Return Parameters

`AnswerResponse`

`streamAnswer` Method

Input Example

Input Parameters

Return Type

`research.create` Method

Input Example

Input Parameters

Returns Example

Return Type

`research.get` Method

Input Example

Input Parameters

Returns Example

Return Type

`research.pollUntilFinished` Method

Input Example

Input Parameters

Returns

`research.list` Method

Input Example

Input Parameters

Returns Example

Return Type