Gemini Embedding 001 Serverless API

MTEB #1 text embeddings for RAG, search, and clustering.

 1import requests
 2import json
 3
 4url = "https://api.segmind.com/v1/gemini-embedding-001"
 5headers = {
 6    "x-api-key": "YOUR_API_KEY",
 7    "Content-Type": "application/json"
 8}
 9
10data = {
11    "input": "Segmind provides fast and affordable AI model inference APIs for image, video, audio, and text generation.",
12    "task_type": "RETRIEVAL_DOCUMENT"
13}
14
15response = requests.post(url, headers=headers, json=data)
16
17if response.status_code == 200:
18    result = response.json()
19    print(json.dumps(result, indent=2))
20else:
21    print(f"Error: {response.status_code}")
22    print(response.text)

API Endpoint

POSThttps://api.segmind.com/v1/gemini-embedding-001

Parameters

promptrequired
string

Text prompt describing the image you want to generate

widthoptional
integer

Width of the generated image in pixels

Default: 512Range: 256 - 1024
heightoptional
integer

Height of the generated image in pixels

Default: 512Range: 256 - 1024
stepsoptional
integer

Number of denoising steps. Higher values generally produce higher quality images

Default: 25Range: 1 - 100
guidance_scaleoptional
number

Controls how closely the model follows the prompt. Higher values = more faithful to prompt

Default: 7.5Range: 1 - 20
negative_promptoptional
string

Negative prompt to specify what you do not want in the image

scheduleroptional
string

Sampling scheduler to use for generation

Default: "DDIM"
Allowed values :
"DDIM""PNDM""LMSDiscrete""DPMSolverMultistep""EulerAncestralDiscrete"
seedoptional
integer

Random seed for reproducible results. Use -1 for random seed

Default: -1Range: -1 - 2147483647

Response Type

Returns: Text/JSON

Common Error Codes

The API returns standard HTTP status codes. Detailed error messages are provided in the response body.

400

Bad Request

Invalid parameters or request format

401

Unauthorized

Missing or invalid API key

403

Forbidden

Insufficient permissions

404

Not Found

Model or endpoint not found

406

Insufficient Credits

Not enough credits to process request

429

Rate Limited

Too many requests

500

Server Error

Internal server error

502

Bad Gateway

Service temporarily unavailable

504

Timeout

Request timed out