Dimensions

curl --request POST \
  --url https://api.upriver.ai/v1/audience_dimensions \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "brand_url": "<string>",
  "response_config": {
    "include_rollup": false,
    "verbosity": "standard",
    "metadata_mode": "basic",
    "max_results": 5,
    "min_confidence": 0.55,
    "max_facts": 25,
    "min_fact_confidence": 0.3,
    "include_evidence_snippets": true,
    "max_snippets_per_fact": 3
  }
}
'

import requests

url = "https://api.upriver.ai/v1/audience_dimensions"

payload = {
    "brand_url": "<string>",
    "response_config": {
        "include_rollup": False,
        "verbosity": "standard",
        "metadata_mode": "basic",
        "max_results": 5,
        "min_confidence": 0.55,
        "max_facts": 25,
        "min_fact_confidence": 0.3,
        "include_evidence_snippets": True,
        "max_snippets_per_fact": 3
    }
}
headers = {
    "X-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    brand_url: '<string>',
    response_config: {
      include_rollup: false,
      verbosity: 'standard',
      metadata_mode: 'basic',
      max_results: 5,
      min_confidence: 0.55,
      max_facts: 25,
      min_fact_confidence: 0.3,
      include_evidence_snippets: true,
      max_snippets_per_fact: 3
    }
  })
};

fetch('https://api.upriver.ai/v1/audience_dimensions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.upriver.ai/v1/audience_dimensions",
  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([
    'brand_url' => '<string>',
    'response_config' => [
        'include_rollup' => false,
        'verbosity' => 'standard',
        'metadata_mode' => 'basic',
        'max_results' => 5,
        'min_confidence' => 0.55,
        'max_facts' => 25,
        'min_fact_confidence' => 0.3,
        'include_evidence_snippets' => true,
        'max_snippets_per_fact' => 3
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($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.upriver.ai/v1/audience_dimensions"

	payload := strings.NewReader("{\n  \"brand_url\": \"<string>\",\n  \"response_config\": {\n    \"include_rollup\": false,\n    \"verbosity\": \"standard\",\n    \"metadata_mode\": \"basic\",\n    \"max_results\": 5,\n    \"min_confidence\": 0.55,\n    \"max_facts\": 25,\n    \"min_fact_confidence\": 0.3,\n    \"include_evidence_snippets\": true,\n    \"max_snippets_per_fact\": 3\n  }\n}")

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

	req.Header.Add("X-API-Key", "<api-key>")
	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.upriver.ai/v1/audience_dimensions")
  .header("X-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"brand_url\": \"<string>\",\n  \"response_config\": {\n    \"include_rollup\": false,\n    \"verbosity\": \"standard\",\n    \"metadata_mode\": \"basic\",\n    \"max_results\": 5,\n    \"min_confidence\": 0.55,\n    \"max_facts\": 25,\n    \"min_fact_confidence\": 0.3,\n    \"include_evidence_snippets\": true,\n    \"max_snippets_per_fact\": 3\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.upriver.ai/v1/audience_dimensions")

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

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"brand_url\": \"<string>\",\n  \"response_config\": {\n    \"include_rollup\": false,\n    \"verbosity\": \"standard\",\n    \"metadata_mode\": \"basic\",\n    \"max_results\": 5,\n    \"min_confidence\": 0.55,\n    \"max_facts\": 25,\n    \"min_fact_confidence\": 0.3,\n    \"include_evidence_snippets\": true,\n    \"max_snippets_per_fact\": 3\n  }\n}"

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

{
  "meta": {
    "generated_at": "2023-11-07T05:31:56Z",
    "industries": [
      "<string>"
    ],
    "continuation_token": "<string>",
    "counts": {
      "total": 123,
      "by_scope": {
        "general": 0,
        "multi_platform": 0,
        "platform_specific": 0
      }
    },
    "source_filters": {
      "platforms": [
        "<string>"
      ],
      "source_names": [
        "<string>"
      ],
      "source_urls": [
        "<string>"
      ],
      "restriction": "none"
    },
    "debug_info": {
      "duration_ms": 123,
      "candidates_before_filter": 123,
      "applied_filters": [
        {
          "name": "<string>",
          "value": "<unknown>",
          "reason": "<string>"
        }
      ]
    },
    "sources_analyzed": [
      "<string>"
    ],
    "content_analyzed_count": 0,
    "pipeline_version": "<string>"
  },
  "brand_name": "<string>",
  "facts": [
    {
      "fact": "<string>",
      "confidence": 0.5,
      "source_count": 2,
      "example_sources": [
        "<string>"
      ],
      "tier": "long_tail",
      "evidence_snippets": [
        {
          "source_id": "<string>",
          "source": "<string>",
          "title": "<string>",
          "text_snippet": "<string>",
          "url": "<string>"
        }
      ]
    }
  ],
  "brand_url": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}