Inference Logoinference.sh
apps/you/search

search

web search api — ground your apps in reliable, web-scale knowledge with contextual snippets

run with your agent
# install belt
$curl -fsSL https://cli.inference.sh | sh
# view schema & details
$belt app get you/search
# run
$belt app run you/search

api reference

about

web search api — ground your apps in reliable, web-scale knowledge with contextual snippets

1. calling the api

install the client

the client provides a convenient way to interact with the api.

bash
1pip install inferencesh

setup your api key

set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.

bash
1export INFERENCE_API_KEY="inf_your_key"

run and get result

submit a request and wait for the final result. best for batch processing or when you don't need progress updates.

python
1from inferencesh import inference23client = inference()456result = client.run({7        "app": "you/search",8        "input": {}9    })1011print(result["output"])

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks.

python
1from inferencesh import inference23client = inference()456# stream=True yields updates as they arrive7for update in client.run({8        "app": "you/search",9        "input": {}10    }, stream=True):11    if update.get("progress"):12        print(f"progress: {update['progress']}%")13    if update.get("output"):14        print(f"output: {update['output']}")

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

the python sdk automatically detects local file paths and uploads them. urls are passed through as-is.

python
1# local file paths are automatically uploaded2result = client.run({3    "app": "you/search",4    "input": {5        "image": "/path/to/local/image.png",  # detected & uploaded6        "audio": "https://example.com/audio.mp3",  # url passed through7    }8})

manual upload

you can also upload files manually and use the returned url.

python
1# upload and get a hosted URL2file = client.files.upload("/path/to/file.png")3print(file.uri)  # https://cloud.inference.sh/...

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

python
1result = client.run({2    "app": "you/search",3    "input": {},4    "webhook": "https://your-server.com/webhook"5}, wait=False)

webhook payload

your endpoint receives a JSON POST with the task result:

json
1{2  "id": "task_abc123",3  "status": 9,4  "output": { ... },5  "error": "",6  "session_id": null,7  "created_at": "2024-01-15T10:30:00Z",8  "updated_at": "2024-01-15T10:30:05Z"9}
idstringtask id
statusnumberterminal status (9=completed, 10=failed, 11=cancelled)
outputobjecttask output (when completed)
errorstringerror message (when failed)
session_idstringsession id (if using sessions)
created_atstringiso timestamp
updated_atstringiso timestamp

5. schema

input

querystring*

search query

countinteger

number of results (1-20)

default: 10min:1max:20
countrystring

iso 3166-1 alpha-2 country code for location targeting

search_langstring

bcp 47 language code to filter results

livecrawlboolean

enable live crawling for full page content (adds latency, billed separately)

default: false
include_domainsarray

only return results from these domains

exclude_domainsarray

exclude results from these domains

boost_domainsarray

boost results from these domains

recent_past_dayboolean

only results from the past day

default: false
recent_past_weekboolean

only results from the past week

default: false
recent_past_monthboolean

only results from the past month

default: false

output

rawobject*

full api response

resultsarray*

search results

ready to run search?

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