
Nano Banana Text-to-Image API by Google
Google's state-of-the-art image generation and editing model.
INPUT
OUTPUT
IdleYour request will cost $0.038 per run. For $10 you can run this model approximately 263 times.
Here's what you can do next:
Esempio di codice
import requests
import time
# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "google/nano-banana/text-to-image",
"prompt": "A beautiful landscape with mountains and lake",
"width": 512,
"height": 512,
"steps": 20,
"guidance_scale": 7.5,
}
generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]
# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
def check_status():
while True:
response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
result = response.json()
if result["data"]["status"] == "completed":
print("Generated image:", result["data"]["outputs"][0])
return result["data"]["outputs"][0]
elif result["data"]["status"] == "failed":
raise Exception(result["data"]["error"] or "Generation failed")
else:
# Still processing, wait 2 seconds
time.sleep(2)
image_url = check_status()Installa
Installa il pacchetto richiesto per il tuo linguaggio.
pip install requestsAutenticazione
Tutte le richieste API richiedono l'autenticazione tramite una chiave API. Puoi ottenere la tua chiave API dalla dashboard di Atlas Cloud.
export ATLASCLOUD_API_KEY="your-api-key-here"Header HTTP
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Non esporre mai la tua chiave API nel codice lato client o nei repository pubblici. Utilizza invece variabili d'ambiente o un proxy backend.
Invia una richiesta
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "your-model",
"prompt": "A beautiful landscape"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())Invia una richiesta
Invia una richiesta di generazione asincrona. L'API restituisce un ID di previsione che puoi usare per controllare lo stato e recuperare il risultato.
/api/v1/model/generateImageCorpo della richiesta
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "google/nano-banana/text-to-image",
"input": {
"prompt": "A beautiful landscape with mountains and lake"
}
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")Risposta
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Controlla lo stato
Interroga l'endpoint di previsione per verificare lo stato attuale della tua richiesta.
/api/v1/model/prediction/{prediction_id}Esempio di polling
import requests
import time
prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
while True:
response = requests.get(url, headers=headers)
result = response.json()
status = result["data"]["status"]
print(f"Status: {status}")
if status in ["completed", "succeeded"]:
output_url = result["data"]["outputs"][0]
print(f"Output URL: {output_url}")
break
elif status == "failed":
print(f"Error: {result['data'].get('error', 'Unknown')}")
break
time.sleep(3)Valori di stato
processingLa richiesta Γ¨ ancora in fase di elaborazione.completedLa generazione Γ¨ completata. I risultati sono disponibili.succeededLa generazione Γ¨ riuscita. I risultati sono disponibili.failedLa generazione Γ¨ fallita. Controlla il campo errore.Risposta completata
{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}Carica file
Carica file nello storage Atlas Cloud e ottieni un URL utilizzabile nelle tue richieste API. Usa multipart/form-data per il caricamento.
/api/v1/model/uploadMediaEsempio di caricamento
import requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")Risposta
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Schema di input
I seguenti parametri sono accettati nel corpo della richiesta.
Nessun parametro disponibile.
Esempio di corpo della richiesta
{
"model": "google/nano-banana/text-to-image"
}Schema di output
L'API restituisce una risposta di previsione con gli URL degli output generati.
Esempio di risposta
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills
Atlas Cloud Skills integra oltre 300 modelli di IA direttamente nel tuo assistente di codifica IA. Un comando per installare, poi usa il linguaggio naturale per generare immagini, video e chattare con LLM.
Client supportati
Installa
npx skills add AtlasCloudAI/atlas-cloud-skillsConfigura chiave API
Ottieni la tua chiave API dalla dashboard di Atlas Cloud e impostala come variabile d'ambiente.
export ATLASCLOUD_API_KEY="your-api-key-here"FunzionalitΓ
Una volta installato, puoi usare il linguaggio naturale nel tuo assistente IA per accedere a tutti i modelli Atlas Cloud.
Server MCP
Il server MCP di Atlas Cloud collega il tuo IDE con oltre 300 modelli di IA tramite il Model Context Protocol. Funziona con qualsiasi client compatibile MCP.
Client supportati
Installa
npx -y atlascloud-mcpConfigurazione
Aggiungi la seguente configurazione al file delle impostazioni MCP del tuo IDE.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Strumenti disponibili
API Schema
Schema not availablePlease log in to view request history
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Log InSeedance 1.5 Pro
GENERAZIONE AUDIO-VISIVA NATIVASuono e Visione, Tutto in Una Sola Ripresa
Il rivoluzionario modello di IA di ByteDance che genera audio e video perfettamente sincronizzati simultaneamente da un unico processo unificato. Sperimenta la vera generazione audio-visiva nativa con sincronizzazione labiale di precisione millimetrica in oltre 8 lingue.
- Multi-image fusion technology
- Character consistency across generations
- Style-preserving transformations
- High-resolution output up to 4K
- Text-based intelligent editing
- Object addition and removal
- Background replacement
- Style transfer and artistic effects
Prompt Examples & Templates
Explore curated prompt templates to unlock the full potential of Nano Banana AI. Click to copy any prompt and start creating immediately.

Photo to Character Figure
Transform any photo into a realistic character figure with packaging and displayturn this photo into a character figure. Behind it, place a box with the character's image printed on it, and a computer showing the Blender modeling process on its screen. In front of the box, add a round plastic base with the character figure standing on it. set the scene indoors if possible

Anime to Cosplay
Transform anime illustrations into realistic cosplay photographyGenerate a highly detailed photo of a girl cosplaying this illustration, at Comiket. Exactly replicate the same pose, body posture, hand gestures, facial expression, and camera framing as in the original illustration. Keep the same angle, perspective, and composition, without any deviation

Person to Action Figure
Transform people from photos into collectible action figures with custom packagingTransform the the person in the photo into an action figure, styled after [CHARACTER_NAME] from [SOURCE / CONTEXT]. Next to the figure, display the accessories including [ITEM_1], [ITEM_2], and [ITEM_3]. On the top of the toy box, write "[BOX_LABEL_TOP]", and underneath it, "[BOX_LABEL_BOTTOM]". Place the box in a [BACKGROUND_SETTING] environment. Visualize this in a highly realistic way with attention to fine details.

Person to Funko Pop Figure
Transform photos into Funko Pop style collectible figures with custom packagingTransform the person in the photo into the style of a Funko Pop figure packaging box, presented in an isometric perspective. Label the packaging with the title 'ZHOGUE'. Inside the box, showcase the figure based on the person in the photo, accompanied by their essential items (such as cosmetics, bags, or others). Next to the box, also display the actual figure itself outside of the packaging, rendered in a realistic and lifelike style.

Product Design to Photorealistic Render
Transform product design sketches into photorealistic rendersturn this illustration of a perfume into a realistic version, Frosted glass bottle with a marble cap

Transform to Q-Version Character
Create cartoon characters with face shape reference controlTransform the person from image 1 into a Q-version character design based on the face shape from image 2

Building to 3D Architecture Model
Convert architectural photos into detailed physical modelsconvert this photo into a architecture model. Behind the model, there should be a cardboard box with an image of the architecture from the photo on it. There should also be a computer, with the content on the computer screen showing the Blender modeling process of the figurine. In front of the cardboard box, place a cardstock and put the architecture model from the photo I provided on it. I hope the PVC material can be clearly presented. It would be even better if the background is indoors.
Technical Highlights
Optimized for speed with generation times under 2 seconds for most tasks, making it perfect for real-time applications and rapid prototyping workflows.
Leveraging Google's advanced AI architecture to produce highly detailed, photorealistic images with accurate lighting, textures, and compositions.
Revolutionary 2D-to-3D conversion capabilities enabling creation of multiple viewpoints from a single image, opening new possibilities for content creation.
Perfetto Per
Why Choose Nano Banana?
No Setup Required
Start creating immediately without complex configurations or installationsPrecision Control
Fine-tune every aspect of your creation with intuitive text commandsConsistent Results
Maintain character and style consistency across multiple generationsSpecifiche Tecniche
Sperimenta la Generazione Audio-Visiva Nativa
Unisciti a cineasti, inserzionisti e creatori di tutto il mondo che stanno rivoluzionando la creazione di contenuti video con la tecnologia rivoluzionaria di Seedance 1.5 Pro.
Google Nano Banana Text-to-Image
Nano Banana Text-to-Image is Googleβs lightweight yet powerful AI image generation model, built for creators who need fast, high-quality visuals from simple text prompts. It transforms words into expressive, realistic images with remarkable clarity, composition, and style diversity β all within seconds.
Try the New Version of Nano Banana!
- Nano Banana Pro
- Nano Banana Pro edit
- Nano Banana Pro Ultra
- Nano Banana Pro Edit Ultra
- Nano Banana Pro Multi
π Why it stands out
-
Instant Image Creation Generate beautiful, coherent visuals from just a short text prompt β no design skills required.
-
Versatile Visual Styles Supports realistic, illustrative, anime, and painterly outputs, adapting naturally to your creative intent.
-
Accurate Text-to-Scene Understanding Accurately interprets subjects, backgrounds, and object relationships to create contextually correct compositions.
-
Fast & Efficient Optimized for quick turnaround and minimal compute cost, perfect for rapid prototyping and social content.
-
Clean, Balanced Lighting Produces visually appealing results without overexposure or unnatural shadows β ideal for portraits, landscapes, and product imagery.
βοΈ Capabilities
-
Input: text prompt
-
Output: high-quality image (JPEG/PNG/WEBP)
-
Supports multiple aspect ratios and output format
-
Compatible with descriptive prompts such as:
- βA golden retriever playing in a field of sunflowers at sunset.β
- βA futuristic city skyline with neon reflections on wet streets.β
- βAn elegant still-life photo of coffee and croissants by a window.β
π° Pricing
- $0.0304 per image
- Commercial use allowed
π‘ Best Use Cases
- Social Media & Marketing β Create on-brand visuals instantly.
- Concept Art & Storyboarding β Generate design ideas and moodboards effortlessly.
- E-commerce & Advertising β Produce high-quality product images without photography.
- Education & Presentation β Visualize complex ideas or creative concepts easily.
π Notes
Please ensure your prompts comply with Googleβs Safety Guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.






