Create Research Task

Python SDK

from tavily import TavilyClient

tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")
response = tavily_client.research("What are the latest developments in AI?")

print(response)

const { tavily } = require("@tavily/core");

const tvly = tavily({ apiKey: "tvly-YOUR_API_KEY" });
const response = await tvly.research("What are the latest developments in AI?");

console.log(response);

curl --request POST \
  --url https://api.tavily.com/research \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "What are the latest developments in AI?",
  "model": "auto",
  "stream": false,
  "output_schema": {
    "properties": {
      "company": {
        "type": "string",
        "description": "The name of the company"
      },
      "key_metrics": {
        "type": "array",
        "description": "List of key performance metrics",
        "items": {
          "type": "string"
        }
      },
      "financial_details": {
        "type": "object",
        "description": "Detailed financial breakdown",
        "properties": {
          "operating_income": {
            "type": "number",
            "description": "Operating income for the period"
          }
        }
      }
    },
    "required": [
      "company"
    ]
  },
  "citation_format": "numbered",
  "include_domains": [
    "sec.gov",
    "ec.europa.eu"
  ],
  "exclude_domains": [
    "reddit.com",
    "quora.com"
  ],
  "output_length": "standard",
  "files": [
    {
      "name": "q1-report.md",
      "data": "<base64-encoded file contents>",
      "type": "base64"
    }
  ]
}
'

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.tavily.com/research",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'input' => 'What are the latest developments in AI?',
    'model' => 'auto',
    'stream' => false,
    'output_schema' => [
        'properties' => [
                'company' => [
                                'type' => 'string',
                                'description' => 'The name of the company'
                ],
                'key_metrics' => [
                                'type' => 'array',
                                'description' => 'List of key performance metrics',
                                'items' => [
                                                                'type' => 'string'
                                ]
                ],
                'financial_details' => [
                                'type' => 'object',
                                'description' => 'Detailed financial breakdown',
                                'properties' => [
                                                                'operating_income' => [
                                                                                                                                'type' => 'number',
                                                                                                                                'description' => 'Operating income for the period'
                                                                ]
                                ]
                ]
        ],
        'required' => [
                'company'
        ]
    ],
    'citation_format' => 'numbered',
    'include_domains' => [
        'sec.gov',
        'ec.europa.eu'
    ],
    'exclude_domains' => [
        'reddit.com',
        'quora.com'
    ],
    'output_length' => 'standard',
    'files' => [
        [
                'name' => 'q1-report.md',
                'data' => '<base64-encoded file contents>',
                'type' => 'base64'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.tavily.com/research"

	payload := strings.NewReader("{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.tavily.com/research")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.tavily.com/research")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

{
  "request_id": "123e4567-e89b-12d3-a456-426614174111",
  "created_at": "2025-01-15T10:30:00Z",
  "status": "pending",
  "input": "What are the latest developments in AI?",
  "model": "mini",
  "response_time": 1.23
}

{
  "detail": {
    "error": "Invalid model. Must be one of: mini, pro, auto"
  }
}

{
  "detail": {
    "error": "Unauthorized: missing or invalid API key."
  }
}

{
  "detail": {
    "error": "Your request has been blocked due to excessive requests. Please reduce the rate of requests."
  }
}

{
  "detail": {
    "error": "This request exceeds your plan's set usage limit. Please upgrade your plan or contact support@tavily.com"
  }
}

{
  "detail": {
    "error": "This request exceeds the pay-as-you-go limit. You can increase your limit on the Tavily dashboard."
  }
}

{
  "detail": {
    "error": "Error when executing research task"
  }
}

POST

research

Python SDK

from tavily import TavilyClient

tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")
response = tavily_client.research("What are the latest developments in AI?")

print(response)

const { tavily } = require("@tavily/core");

const tvly = tavily({ apiKey: "tvly-YOUR_API_KEY" });
const response = await tvly.research("What are the latest developments in AI?");

console.log(response);

curl --request POST \
  --url https://api.tavily.com/research \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "What are the latest developments in AI?",
  "model": "auto",
  "stream": false,
  "output_schema": {
    "properties": {
      "company": {
        "type": "string",
        "description": "The name of the company"
      },
      "key_metrics": {
        "type": "array",
        "description": "List of key performance metrics",
        "items": {
          "type": "string"
        }
      },
      "financial_details": {
        "type": "object",
        "description": "Detailed financial breakdown",
        "properties": {
          "operating_income": {
            "type": "number",
            "description": "Operating income for the period"
          }
        }
      }
    },
    "required": [
      "company"
    ]
  },
  "citation_format": "numbered",
  "include_domains": [
    "sec.gov",
    "ec.europa.eu"
  ],
  "exclude_domains": [
    "reddit.com",
    "quora.com"
  ],
  "output_length": "standard",
  "files": [
    {
      "name": "q1-report.md",
      "data": "<base64-encoded file contents>",
      "type": "base64"
    }
  ]
}
'

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.tavily.com/research",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'input' => 'What are the latest developments in AI?',
    'model' => 'auto',
    'stream' => false,
    'output_schema' => [
        'properties' => [
                'company' => [
                                'type' => 'string',
                                'description' => 'The name of the company'
                ],
                'key_metrics' => [
                                'type' => 'array',
                                'description' => 'List of key performance metrics',
                                'items' => [
                                                                'type' => 'string'
                                ]
                ],
                'financial_details' => [
                                'type' => 'object',
                                'description' => 'Detailed financial breakdown',
                                'properties' => [
                                                                'operating_income' => [
                                                                                                                                'type' => 'number',
                                                                                                                                'description' => 'Operating income for the period'
                                                                ]
                                ]
                ]
        ],
        'required' => [
                'company'
        ]
    ],
    'citation_format' => 'numbered',
    'include_domains' => [
        'sec.gov',
        'ec.europa.eu'
    ],
    'exclude_domains' => [
        'reddit.com',
        'quora.com'
    ],
    'output_length' => 'standard',
    'files' => [
        [
                'name' => 'q1-report.md',
                'data' => '<base64-encoded file contents>',
                'type' => 'base64'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.tavily.com/research"

	payload := strings.NewReader("{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.tavily.com/research")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.tavily.com/research")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\",\n  \"include_domains\": [\n    \"sec.gov\",\n    \"ec.europa.eu\"\n  ],\n  \"exclude_domains\": [\n    \"reddit.com\",\n    \"quora.com\"\n  ],\n  \"output_length\": \"standard\",\n  \"files\": [\n    {\n      \"name\": \"q1-report.md\",\n      \"data\": \"<base64-encoded file contents>\",\n      \"type\": \"base64\"\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

{
  "request_id": "123e4567-e89b-12d3-a456-426614174111",
  "created_at": "2025-01-15T10:30:00Z",
  "status": "pending",
  "input": "What are the latest developments in AI?",
  "model": "mini",
  "response_time": 1.23
}

{
  "detail": {
    "error": "Invalid model. Must be one of: mini, pro, auto"
  }
}

{
  "detail": {
    "error": "Unauthorized: missing or invalid API key."
  }
}

{
  "detail": {
    "error": "Your request has been blocked due to excessive requests. Please reduce the rate of requests."
  }
}

{
  "detail": {
    "error": "This request exceeds your plan's set usage limit. Please upgrade your plan or contact support@tavily.com"
  }
}

{
  "detail": {
    "error": "This request exceeds the pay-as-you-go limit. You can increase your limit on the Tavily dashboard."
  }
}

{
  "detail": {
    "error": "Error when executing research task"
  }
}

Authorizations

Authorization

string

header

required

Bearer authentication header in the form Bearer , where is your Tavily API key (e.g., Bearer tvly-YOUR_API_KEY).

Body

application/json

Parameters for the Tavily Research request.

input

string

required

The research task or question to investigate.

Example:

"What are the latest developments in AI?"

model

enum<string>

default:auto

The model used by the research agent. "mini" is optimized for targeted, efficient research and works best for narrow or well-scoped questions. "pro" provides comprehensive, multi-angle research and is suited for complex topics that span multiple subtopics or domains

Available options:

mini,

pro,

auto

stream

boolean

default:false

Whether to stream the research results as they are generated. When 'true', returns a Server-Sent Events (SSE) stream. See Streaming documentation for details.

output_schema

object

A JSON Schema object that defines the structure of the research output. When provided, the research response will be structured to match this schema, ensuring a predictable and validated output shape. Must include a 'properties' field, and may optionally include 'required' field.

Show child attributes

Example:

{
  "properties": {
    "company": {
      "type": "string",
      "description": "The name of the company"
    },
    "key_metrics": {
      "type": "array",
      "description": "List of key performance metrics",
      "items": { "type": "string" }
    },
    "financial_details": {
      "type": "object",
      "description": "Detailed financial breakdown",
      "properties": {
        "operating_income": {
          "type": "number",
          "description": "Operating income for the period"
        }
      }
    }
  },
  "required": ["company"]
}

citation_format

enum<string>

default:numbered

The format for citations in the research report.

Available options:

numbered,

mla,

apa,

chicago

include_domains

string[]

Soft preference for sources. The research agent prioritizes these domains, but URLs from other domains can still appear in the final report. Matching is host-based and includes subdomains (e.g., sec.gov matches sec.gov and data.sec.gov). Maximum 20 entries.

Maximum array length: 20

Example:

["sec.gov", "ec.europa.eu"]

exclude_domains

string[]

Hard blocklist. No URL from a listed domain or any of its subdomains appears in the response. Subdomain matching is downward only — blocking medium.com also blocks blog.medium.com, but blocking blog.medium.com leaves medium.com itself allowed. Maximum 20 entries.

Maximum array length: 20

Example:

["reddit.com", "quora.com"]

output_length

enum<string>

default:standard

Typed control over response size. Ranges are targets, not hard caps — individual responses can fall outside when the question requires it.

Available options:

short,

standard,

long

files

object[]

Attach files to the research request and the agent uses their contents as a source alongside the web. Each entry carries a filename and its base64-encoded contents. The agent reads the relevant parts of each file, grounds its answer in them, and cites any file it draws from.

Supported file types: .txt, .md, .json.

Limits: up to 5 files per request; max 80,000 words per text file; max 80,000 words combined across all files.

Maximum array length: 5

Show child attributes

Example:

[
  {
    "name": "q1-report.md",
    "data": "<base64-encoded file contents>",
    "type": "base64"
  }
]

Response

Research task queued successfully (when not streaming)

request_id

string

required

A unique identifier for the research task.

Example:

"123e4567-e89b-12d3-a456-426614174111"

created_at

string

required

Timestamp when the research task was created.

Example:

"2025-01-15T10:30:00Z"

status

string

required

The current status of the research task.

Example:

"pending"

input

string

required

The research task or question investigated.

Example:

"What are the latest developments in AI?"

model

string

required

The model used by the research agent.

Example:

"mini"

response_time

integer

required

Time in seconds it took to complete the request.

Example:

1.23

Core Endpoints

Research Agent

Feedback

Account

Enterprise Endpoints

Python SDK

JavaScript SDK

Authorizations

Body

Response