curl --request GET \
--url 'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools' \
--header 'Authorization: Bearer <token>'
const response = await fetch(
'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools',
{
method: 'GET',
headers: {
'Authorization': 'Bearer <token>'
}
}
);
const data = await response.json();
import requests
url = "http://localhost:3000/api/v1/ollama/search"
headers = {"Authorization": "Bearer <token>"}
params = {
"query": "llama",
"order": "popular",
"categories": ["tools"]
}
response = requests.get(url, headers=headers, params=params)
data = response.json()
{
"success": true,
"models": [
{
"name": "llama2",
"description": "Meta's Llama 2 model for general chat and text generation",
"tags": ["chat", "7b", "13b", "70b"],
"downloads": 5420000,
"lastUpdated": "2024-01-10T15:30:00Z"
},
{
"name": "llama2-uncensored",
"description": "Uncensored version of Llama 2",
"tags": ["chat", "uncensored"],
"downloads": 890000,
"lastUpdated": "2024-01-08T10:00:00Z"
}
]
}
{
"success": false,
"error": "Unauthorized"
}
{
"success": false,
"error": "Search failed"
}
Ollama
Search Models
Search for available Ollama models with optional filtering and sorting
GET
/
api
/
v1
/
ollama
/
search
curl --request GET \
--url 'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools' \
--header 'Authorization: Bearer <token>'
const response = await fetch(
'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools',
{
method: 'GET',
headers: {
'Authorization': 'Bearer <token>'
}
}
);
const data = await response.json();
import requests
url = "http://localhost:3000/api/v1/ollama/search"
headers = {"Authorization": "Bearer <token>"}
params = {
"query": "llama",
"order": "popular",
"categories": ["tools"]
}
response = requests.get(url, headers=headers, params=params)
data = response.json()
{
"success": true,
"models": [
{
"name": "llama2",
"description": "Meta's Llama 2 model for general chat and text generation",
"tags": ["chat", "7b", "13b", "70b"],
"downloads": 5420000,
"lastUpdated": "2024-01-10T15:30:00Z"
},
{
"name": "llama2-uncensored",
"description": "Uncensored version of Llama 2",
"tags": ["chat", "uncensored"],
"downloads": 890000,
"lastUpdated": "2024-01-08T10:00:00Z"
}
]
}
{
"success": false,
"error": "Unauthorized"
}
{
"success": false,
"error": "Search failed"
}
Query Parameters
string
default:""
Search query string
array
Filter by model categories
Show Available categories
Show Available categories
embedding- Embedding modelscloud- Cloud-optimized modelsvision- Vision/multimodal modelstools- Tool-use modelsthinking- Reasoning models
string
default:"newest"
Sort order for results
newest- Sort by newest firstpopular- Sort by popularity (downloads)
Response
boolean
Indicates if the search was successful
array
curl --request GET \
--url 'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools' \
--header 'Authorization: Bearer <token>'
const response = await fetch(
'http://localhost:3000/api/v1/ollama/search?query=llama&order=popular&categories=tools',
{
method: 'GET',
headers: {
'Authorization': 'Bearer <token>'
}
}
);
const data = await response.json();
import requests
url = "http://localhost:3000/api/v1/ollama/search"
headers = {"Authorization": "Bearer <token>"}
params = {
"query": "llama",
"order": "popular",
"categories": ["tools"]
}
response = requests.get(url, headers=headers, params=params)
data = response.json()
{
"success": true,
"models": [
{
"name": "llama2",
"description": "Meta's Llama 2 model for general chat and text generation",
"tags": ["chat", "7b", "13b", "70b"],
"downloads": 5420000,
"lastUpdated": "2024-01-10T15:30:00Z"
},
{
"name": "llama2-uncensored",
"description": "Uncensored version of Llama 2",
"tags": ["chat", "uncensored"],
"downloads": 890000,
"lastUpdated": "2024-01-08T10:00:00Z"
}
]
}
{
"success": false,
"error": "Unauthorized"
}
{
"success": false,
"error": "Search failed"
}
Notes
- Leave
queryempty to browse all models - Multiple categories can be specified to filter results
- Results are paginated automatically by the Ollama registry
⌘I

