curl-X POST 'https://pollo.ai/api/platform/v1/generation/pollo-ai/pollojourney-v7-image/image'\-H'Content-Type: application/json'\-H'x-api-key: YOUR_API_KEY'\-d'{ "input": { "prompt": "A cinematic shot of a golden retriever running through a field of sunflowers at sunset, warm rim light, shallow depth of field", "aspectRatio": "1:1" }}'
Opcjonalnie dołącz webhookUrl, aby otrzymać wywołanie zwrotne w przypadku powodzenia lub niepowodzenia zadania.
Opcjonalne pole żądania
{"input":{"prompt":"A cinematic shot of a golden retriever running through a field of sunflowers at sunset, warm rim light, shallow depth of field","aspectRatio":"1:1"},"webhookUrl":"https://example.com/webhooks/pollo"}
Schemat
Pola wejściowe dla wybranego punktu końcowego i trybu.
Pole
Typ
Wymagany
Opis
prompt
string
Tak
Text prompt describing the content to generate.
seed
integer
NIE
Random seed for reproducible generation.
aspectRatio
string
NIE
Output aspect ratio, as width:height (e.g. 16:9).
Błędy
Typowe publiczne kody odpowiedzi API.
400
Nieprawidłowe dane wejściowe lub ograniczenie modelu
Pollojourney V7 focuses on art-directed image generation, pairing photoreal detail with creative controls for outpainting, upscaling, and image-guided visual remixing.
With Pollojourney V7 on Pollo API, developers can add text-to-image and image-to-image generation to creative tools, ecommerce workflows, design platforms, and automated asset pipelines.
Key Features of Pollojourney V7 API
Art-Directed Photorealism
Pollojourney V7 produces realistic materials, lighting, and scene detail while still supporting expressive visual styles for concept art, branded assets, and editorial imagery.
Text and Image Guidance
Start from a written prompt, an existing image, or multiple reference images, giving builders flexible ways to support generation, remixing, and visual iteration.
Multi-Image Blending
The model can combine visual direction from several inputs, useful when users need to merge subjects, palettes, textures, or environments into one coherent image.
Outpainting for Expanded Frames
Pollojourney V7 supports extending an image beyond its original boundaries, helping teams adapt visuals for banners, thumbnails, covers, and wider creative formats.
Upscaling-Oriented Detail
Generated images can be refined for sharper delivery, making the model useful when a draft needs to become a cleaner visual asset for production.
Repeatable Creative Tests
Seed control helps teams reproduce useful generations, compare prompt changes, and build more predictable creative workflows around successful image directions.
Use Cases of Pollojourney V7 API
Creative App Image Generation: Let users create polished visuals from prompts, then refine them with reference images or expanded compositions.
Reference-Based Asset Remixing: Combine uploaded concepts, textures, or objects into new artwork without starting every visual from scratch.
Ecommerce Scene Creation: Place products into styled settings, blend brand references, and generate campaign-ready image variations.
Outpainting for Marketing Formats: Extend square or portrait visuals into banners, hero images, and social crops with better contextual continuity.
Concept Art Exploration: Generate environments, props, interiors, and mood frames from detailed creative briefs.
Brand Campaign Variants: Produce related image sets with consistent style direction while changing subjects, framing, or color mood.
Archive and Restoration Previews: Reimagine incomplete, cropped, or low-detail visual materials through expansion and upscaling workflows.
Developer Image Pipelines: Build repeatable generation systems with prompt, reference, aspect ratio, and seed controls.
How to Use Pollojourney V7 API
Get an API Key: Create a Pollo API account and generate your API key from the developer dashboard.
Choose the Model: Send requests to the Pollojourney V7 image model endpoint at /generation/pollojourney/pollojourney-v7-image/image, and use the current endpoint shown in Pollo API docs.
Add Your Inputs: Provide a prompt, imageUrl, then set useful options such as aspectRatio and seed.
Generate and Retrieve: Submit the task, poll the returned task status, and download the finished image after generation succeeds.
Prompting Best Practices for Pollojourney V7 API
Write prompts like an art direction note. Describe the subject, visual medium, reference relationship, composition, lighting, and what should expand or remain consistent.
A Simple Prompt Formula
Subject + reference role + composition + style or medium + lighting + expansion or detail goal
What You Should Notice
Name the Visual Priority: State whether realism, illustration, texture, lighting, or composition matters most.
Explain Reference Use: When using images, describe what to preserve, blend, restyle, or expand.
Frame the Output: Specify square, portrait, banner, or wide layout early so the composition fits the destination.
Guide Outpainting: Say what should appear beyond the original image edge, not just that the canvas should expand.
Use Seeds for Iteration: Keep a successful seed when testing small prompt changes across a visual direction.
Example Prompts
Museum Object Reconstruction
"Create a photoreal museum catalog image of a cracked porcelain ritual mask reconstructed from partial fragments, ivory glaze, faint blue hand-painted lines, black velvet background, soft conservation-lab lighting, expanded edges showing careful archival spacing."
Botanical Field Guide Plate
"Generate a detailed botanical illustration of three alpine flowers with translucent petals, exposed roots, seed pods, and handwritten-style spacing but no readable text, cream paper texture, balanced scientific plate composition, natural daylight."
Multi-Reference Fantasy Map Cover
"Blend the uploaded harbor map, brass compass, and storm-cloud reference into one antique fantasy atlas cover image, weathered paper, sea-green ink, dramatic but realistic metal detail, centered composition with expanded margins."
Interior Outpainting Concept
"Using the uploaded narrow apartment photo, extend the left side into a compact reading alcove with walnut shelves, warm wall lamp, linen chair, matching perspective, same evening light, realistic shadows, no people."
Pollojourney V7 vs GPT Image 2 vs Kling Image 3.0
Capability
Pollojourney V7
GPT Image 2
Kling Image 3.0
Core Focus
Artistic photoreal generation with outpainting, upscaling, and blending
Text rendering, instruction following, and production output
Story-driven images with character and style consistency
Text-to-Image
Supported
Supported
Supported
Image-to-Image
Supported
Supported
Supported
Multi-Image Workflows
Strong fit for visual blending and reference remixing
Strong fit for multi-subject composition
Strong fit for consistent characters and scenes
Best Creative Fit
Expanding, refining, and blending artistic visuals
Posters, packaging, diagrams, and text-heavy assets
Storyboards, character sheets, and narrative image sets
Recommended For
Creative apps needing photoreal art direction and canvas expansion
Apps needing readable text and precise visual instructions
Apps needing repeated characters or scene continuity
Why Choose Pollojourney V7 API?
Choose Pollojourney V7 when your product needs image generation that feels visually directed, not just prompt-responsive, with useful support for expansion, blending, and refinement.
Pollo API makes Pollojourney V7 easier to integrate alongside 300+ image and video models, with API keys, task status polling, webhooks, docs, and scalable generation workflows.
Start building with Pollojourney V7 API when your users need photoreal creative images they can remix, expand, and refine inside your own product.
Pollojourney V7 API FAQs
What is Pollojourney V7?
Pollojourney V7 is a Pollo AI image model for text-to-image and image-to-image generation, focused on artistic photorealism, outpainting, upscaling, and multi-image blending.
Does Pollojourney V7 API support image-to-image generation?
Yes. Developers can use image-guided workflows to restyle, remix, expand, or refine existing visuals while controlling the result with a written prompt.
Can Pollojourney V7 blend multiple images?
Yes. The documentation supports multiple image inputs, making it useful for combining references such as a subject, background, texture, or style guide.
Is Pollojourney V7 useful for outpainting?
Yes. Outpainting is one of its highlighted strengths, especially for adapting existing images into wider layouts, social formats, banners, and extended scenes.
Can I reproduce a previous Pollojourney V7 result?
Yes. Use seed control when you want repeatable tests, prompt comparisons, or a more predictable way to iterate from a generation you like.
Why run Pollojourney V7 through Pollo API?
Pollo API gives developers structured access to Pollojourney V7 with authentication, task submission, status checks, webhooks, and access to many other models through one platform.
