Moondream
Integra
moondream/batched
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/moondream/batched?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/moondream/batched?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/moondream/batched", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/it/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "moondream/batched",
"input": {
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}
}
Chiama il modello Moondream (moondream/batched) tramite Doitong API. Documentazione per gli agenti: https://doitong.com/it/developers/models/moondream/batched.md
POST https://api.doitong.com/v1/run/moondream/batched?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}
Se lo stato della risposta è "queued" o "running", interroga GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 finché non diventa "succeeded"; i file si trovano in outputs[].url. POST https://api.doitong.com/v1/quote/moondream/batched con lo stesso body restituisce il prezzo esatto prima dell'esecuzione.
Questa richiesta: ≈0,004 $ 4 crediti API Esegui in questa pagina
La tua nuova chiave API. Viene mostrata solo ora ed è già presente nel codice e nel campo della chiave API qui sotto. Mantienila segreta: non inserirla mai nel codice eseguito in un browser.
Il tuo primo risultato apparirà qui
Crea una richiesta qui sotto ed eseguila con la tua chiave API. Gli output vengono copiati nella nostra archiviazione, conservati per sempre oppure 7 giorni gratuitamente.
Crea una richiesta
I controlli vengono generati dallo schema del modello. Il codice e il prezzo si aggiornano mentre li modifichi.
/run/moondream/batched?wait=20
preventivo → 0,004 $
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/moondream/batched?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/moondream/batched?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/moondream/batched", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "moondream/batched",
"input": {
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
},
"wait_seconds": 20
}
}
}
Esegui questa richiesta
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Informazioni su Moondream
Una versione batch del modello vision-language Moondream. Passa un elenco di oggetti in `inputs`, ciascuno contenente un prompt e un URL di immagine, e ricevi un elenco di output generati insieme ai nomi dei file elaborati e ai tempi. La generazione è regolata con `max_tokens` (da 32 a 1024, predefinito 64), `temperature` (da 0 a 1), `top_p` e `repetition_penalty` (da 1 a 2). La risposta include anche un flag che indica se il risultato è parziale.
Parametri
inputsobbligatorio
inputs[].image_urlobbligatorio
inputs[].promptfacoltativo
max_tokensfacoltativo
temperaturefacoltativo
top_pfacoltativo
repetition_penaltyfacoltativo
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "moondream/batched",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 4,
"usd": "0.004",
"charged": 4,
"refunded": 0
},
"input": {
"inputs": [
{
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
]
},
"output": {
"outputs": [
"string"
],
"partial": false,
"timings": {},
"filenames": [
"string"
]
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Campi dell'output
- outputs
- array of stringElenco contenente i risultati generati.
- partial
- booleanIndica se l'output è incompleto.
- timings
- objectMisurazioni dei tempi per le singole fasi di elaborazione.
- filenames
- array of string | nullNomi dei file immagine elaborati.
Altri modelli: Visione
Per gli agenti AI: questa pagina in Markdown è disponibile all'indirizzo https://doitong.com/it/developers/models/moondream/batched.md. Tutti i modelli e le guide: https://doitong.com/developers/llms.txt