Projects

Overview: Kling Video O1 API is an OpenAI-compatible endpoint providing high-quality video generation through advanced reasoning capabilities. It offers a base URL and a single key for all API calls, eliminating the need for separate billing and subscription models. Key features: - Supports text-to-video and image-to-video generation - Pricing is per generated second, with a default resolution of 720P - Billing is based on actual usage, with a minimum cost of $1 per task - Returns the exact amount in the response for each completed task - Tasks are processed asynchronously, with task IDs for monitoring Tech stack: Python Why it matters: This API is crucial for developers looking to integrate AI-driven video generation into their projects without the complexity of managing multiple models and billing systems. It simplifies the process of creating high-quality videos by leveraging advanced reasoning capabilities, ensuring unmatched visual fidelity. GitHub stars: 12 Repository: jawdibps44n/kling-o1-api-ru

### Overview: Seedream 5.0 Pro Prompts: 8 Tested Recipes With Outputs ### Key Features: - **Model ID:** `seedream-5-0-pro` - **Price:** $0.0146 per image - **Aspect Ratios:** 1:1, 1:2, 1:3, 1:4, 1:5, 1:6, 1:7, 1:8 - **Cost Per Image:** $0.014625 per image (1K-layer $0.014625 · 1K $0.02925 · 2K-layer $0.02925) ### Tech Stack: Python ### Why It Matters: Seedream 5.0 Pro Prompts provides tested image prompt recipes, aspect ratios, and the model ID, along with example renders, aspect ratios, and the cost per image. This resource is useful for developers looking to optimize their image generation workflows and ensure consistent and high-quality output.

Overview: This project provides tested image prompt recipes for the Wan 2.7 Image Pro model, including examples, aspect ratios, and the associated call costs. Key features: - 8 tested recipes with example renders, aspect ratios, and the model ID (`wan2.7-image-pro`). - The recipes are structured to help developers create effective and efficient prompts. Tech stack: Python Why it matters: This resource is useful for developers looking to optimize their image prompts for the Wan 2.7 Image Pro model, ensuring they get the best possible results without unnecessary costs.

Overview: This repository contains tested image prompt recipes for the MiniMax H3 model, including 8 recipes with example renders, aspect ratios, and the model ID (`MiniMax-H3-Regeneration`). The cost per image is provided, along with a billing model and pricing details. Key features: - 8 tested image prompt recipes - Example renders, aspect ratios, and model ID - Model: `MiniMax-H3-Regeneration` - Effective price: $0.0343 per second Tech stack: Python Why it matters: This repository offers a practical guide for developers looking to integrate the MiniMax H3 model into their projects, providing clear instructions and cost information for each recipe. Repository: ji7eb5cmdte2/minimax-h3-regeneration-prompts-ru GitHub stars: 12

### Overview: Nano Banana 2 Prompts offers tested image prompt recipes with example renders, aspect ratios, and the model ID (`gemini-3.1-flash-image-preview`). It provides cost per image and includes a model page for further details. ### Key Features: - **8 Recipes**: Eight tested image prompt recipes with example renders, aspect ratios, and the model ID. - **Effective Price**: $0.015 per image, with an estimated cost of $0.12 for the entire set. - **Model ID**: `gemini-3.1-flash-image-preview` - **API Key**: Available for free, no subscription required. ### Tech Stack: Python ### Why It Matters: Nano Banana 2 Prompts provides a straightforward way to access Nano Banana 2 (`gemini-3.1-flash-image-preview`) via an OpenAI-compatible endpoint, allowing teams to catalog their images without the need for a subscription or scaling plans. The API is flexible, with a single `model` field to configure, making it easy to use. The pricing is transparent, with all costs reflected in the response, and the system handles failed tasks gracefully. The prompt structure is detailed, ensuring that materials, lighting, framing, and settings are correctly specified for optimal results.

Overview: Wan 2.7 API (`wan2.7`) is a state-of-the-art image-to-video model that offers high-quality visuals, motion coherence, and professional-grade performance. It supports a wide range of resolutions and is compatible with OpenAI-compatible endpoints, providing a cost-effective and flexible solution for video generation. Key features: - Supports Wan 2.7 (`wan2.7`) and 300+ other image, video, and language models through a single base URL and `Authorization` header. - Charges per generated second, with a minimum of $1 and no monthly plan required. - Reports the exact amount billed in the response, making budgeting straightforward. - Batches and retries are handled by a queue, ensuring reliable processing without bespoke integration. - Supports first frame, last frame, and style references for Wan I2V (image-to-video) functionality. Tech stack: Python Why it matters: Wan 2.7 API on APIMart provides a powerful tool for video generation, offering superior quality and flexibility without the need for a subscription or monthly plan. Its compatibility with OpenAI endpoints makes it ideal for AI-driven content creation and video production workflows. Repository: jlx8f1v/wan-2-7-api-gateway GitHub stars: 12 GitHub description: Wan 2.7 API (`wan2.7`): model id, pricing, parameters, and copy-paste examples for the OpenAI-compatible APIMart endpoint.

### Overview: Nano Banana 2 Prompts: A Comprehensive Guide to Image Prompt Recipes ### Key features: - **Model ID:** `gemini-3.1-flash-image-preview` - **Aspect Ratios:** 1:1, 1:2, 2:3, 3:4, 4:5, 5:7, 7:10, 10:13, 13:20 - **Cost per Image:** $0.015 ### Tech stack: Python ### Why it matters: Nano Banana 2 Prompts offers a straightforward and effective way to generate high-quality image prompts, ensuring that your designs are both visually appealing and cost-efficient. By following the provided recipes, you can achieve professional results without the need for complex setup or expensive subscriptions.

Overview: Cecil is a persistent memory and identity protocol designed for AI systems, providing evidence-aware recall and inspectable memory. Key features: - Persistent memory storage - Identity tracking - Evidence-aware recall - Structured world model - Reflective capabilities Tech stack: TypeScript Why it matters: Cecil enhances AI systems by remembering conversations, commitments, and beliefs, ensuring better and more accurate responses and insights. Repository: johnkf5-ops/cecil-protocol GitHub stars: 12 GitHub description: Persistent memory and identity protocol for AI systems with evidence-aware recall and inspectable memory.

### Overview: GPT Image 2.5 Sunburst prompts: tested image prompt recipes with example renders, aspect ratios, the model id (`gpt-image-2.5-ext`), and the cost per image. This repository provides a catalog of 8 tested recipes, each accompanied by an example render, the ratio, and the call cost on the APIMart route. ### Key Features: - **8 Recipes**: Eight distinct image prompt recipes with detailed examples, ratios, and costs. - **Model ID**: `gpt-image-2.5-ext` - **Aspect Ratios**: 1:1, 4:3, 8:5, etc. - **Cost**: $0.0106 per image on the APIMart route, estimated cost of the whole set: $0.085 ### Tech Stack: - Python ### Why It Matters: - **Easy Access**: The same base URL and authorization token provide access to GPT Image 2.5 Sunburst (`gpt-image-2.5-ext`) and over 300 other image, video, and language models. - **Cost Efficiency**: No subscription or prepaid plans required; charges are applied per call. - **Transparent Pricing**: The total cost is reflected in the response, and tasks marked as failed are refunded. - **Asynchronous Processing**: Tasks are submitted, retrieved, and processed through a queue, ensuring efficient handling of requests without custom integrations. ### What Separates a Usable Recipe from a Wasted Call: - **Subject**: The

Overview: Wan 2.7 API (`wan2.7`) provides access to a high-performance AI model that can generate videos, images, and text-based content. It offers a cost-effective solution for developers looking to integrate AI into their applications without the need for a subscription. Key features: - **Model ID and Pricing**: The API uses a single base URL and a common authorization header to access Wan 2.7 (`wan2.7`) and over 300 other models. - **Pricing Model**: The pricing is based on the generated cost per second, with a minimum charge of $1 per call. - **Billing Model**: The API charges for each task completed, and any failed tasks are refunded. - **Asynchronous Processing**: Tasks are processed in the background, and the results are available through the `GET /v1/tasks/{task_id}` endpoint. Tech stack: Python Why it matters: Wan 2.7 API (`wan2.7`) is designed for developers who want to integrate AI into their applications efficiently without the need for a monthly subscription. It offers a cost-effective solution with a simple API endpoint and flexible pricing options, making it ideal for various use cases. Repository: jqcwg/wan-2-7-api-es Primary language: Python GitHub stars: 12 GitHub description: Wan 2.7 API (`wan2.7`): model id, pricing, parameters and copy-paste examples for the OpenAI-compatible APIMart endpoint.

Overview: This project provides a Gemini Nano Banana 2.1 API endpoint for OpenAI-compatible models, offering a cost-effective solution for image generation and editing. Key features: - One API key for multiple models and resolutions - Billing based on per-image cost - Supports text-to-image and reference-image editing - Minimal cost with no upfront subscription - Summaries returned in the response Tech stack: Python Why it matters: This API simplifies accessing Google's image model on APIMart, making it easier and more cost-effective for developers to integrate image generation and editing functionalities into their projects. Repository: jqhc31it1vme/nano-banana-2-1-api-ru Primary language: Python GitHub stars: 12 GitHub description: Gemini Nano Banana 2.1 API (`gemini-nano-banana-2.1`): model id, pricing, parameters and copy-paste examples for the OpenAI-compatible APIMart endpoint. README excerpt: # Gemini Nano Banana 2.1 API (`gemini-nano-banana-2.1`) <!-- conv-kit:v1 --> <p align="center"> <img src="assets/badges/price.svg" alt="observed unit price"> <img src="assets/badges/billing.svg" alt="billing model"> <img src="assets/badges/compat.svg" alt="OpenAI-compatible endpoint"> </p> <p align="center"> <img src="assets/01-product-hero-perfume.jpg

### Overview: This repository contains MAI-Image-2.6 prompts, a collection of 8 tested recipes with example renders, aspect ratios, the model ID (`mai-image-2.6`), and the cost per image on the APIMart route. The price is $0.0311 per image, and the total estimated cost for the set is $0.2488. ### Key Features: - **Model ID:** `mai-image-2.6` - **Recipes:** 8 (machine-readable in `data/prompts.json`, table in `PROMPTS.md`) - **Effective Price:** $0.0311 per image - **Cost on APIMart Route:** $0.0311 per image - **Prompt Structure:** A cheat-sheet for structuring prompts - **Framing Rules:** Ensure the subject is named, the light is set explicitly, and the framing is clear ### Tech Stack: Python ### Why It Matters: The repository provides a practical guide for developers looking to use MAI-Image-2.6 to generate high-quality image prompts efficiently. It offers a cost-effective solution for those seeking to integrate image generation into their projects without the need for a subscription or upfront payment. The structured prompts and clear framing rules help ensure that each call results in a well-rendered image, making it easier to achieve the desired aesthetic and functionality.

### Overview: SkyReels V4 Fast Prompts: A Comprehensive Guide to Image Prompt Recipes This repository provides a collection of 8 tested recipes for the SkyReels V4 Fast model, including example renders, duration, and the cost per image on the APIMart route. The model is compatible with OpenAI and offers a cost-effective API key for $0.064 per second, making it ideal for developers and creatives looking to enhance their projects. ### Key Features: - **Model ID:** `skyreels-v4-fast` - **Effective Price:** $0.064 per second - **Duration:** 5 seconds - **Cost:** $0.064 ### Tech Stack: - Python ### Why It Matters: - **One-Stop Shop:** Access to SkyReels V4 Fast and over 300 other image, video, and language models using the same base URL and authorization headers. - **Cost Efficiency:** Pay-as-you-go pricing, no upfront subscription or monthly fees. - **Immediate Feedback:** The cost is reflected in the response, and failed tasks are reimbursable. - **Asynchronous Processing:** Tasks can be submitted, retrieved, and monitored via the `GET /v1/tasks/{id}` endpoint, with processing handled through a standard queue system. ### Recipes: - **Model:** `skyreels-v4-fast` - **Recipes:** 4 (available in `data/prompts.json` and `PROMPTS.md`) - **Effective Price:** $0.064

Overview: Wan 2.5 是阿里巴巴的高质量视频生成模型，支持文本到视频和图像到视频的转换。 Key features: - 文本到视频和图像到视频的高质量转换 - 一个 API key 可以访问 Wan 2.5（`wan-2.5`）及其 300 多个模型 - 按秒计费，无需包月套餐 - 实时价格，每个任务报告实际费用 - 原生异步设计，无需定制集成 - 通义万相的中文环境 Tech stack: Python Why it matters: Wan 2.5 是阿里巴巴推出的高质量视频生成模型，支持文本到视频和图像到视频的转换。它提供了一个 API key 可以访问 Wan 2.5（`wan-2.5`）及其 300 多个模型的途径，按秒计费，无需包月套餐，实时价格，每个任务报告实际费用，原生异步设计，无需定制集成，非常适合需要高质量视频生成的场景。 Repository: k1zfb6fitl-5/wan-2-5-api-cn Primary language: Python GitHub stars: 12 GitHub description: 通义万相 — Wan 2.5 API (`wan-2.5`): model id, pricing, parameters and copy-paste examples for the OpenAI-compatible APIMart endpoint.

### Overview: HappyHorse 1.0 Prompts: 8 Tested Recipes With Outputs <!-- conv-kit:v1 --> <p align="center"> <img src="assets/badges/price.svg" alt="observed unit price"> <img src="assets/badges/billing.svg" alt="billing model"> <img src="assets/badges/compat.svg" alt="OpenAI-compatible endpoint"> </p> <p align="center"> <img src="assets/01-product-ad-ceramic-mug-thumb.jpg" width="820" alt="Sample video frame generated through APIMart"> </p> > **from $0.13 per second** on the APIMart route — ein einziger OpenAI-kompatibler Endpoint unter `https://api.apimart.ai/v1`, kein Monatsabo nötig. *(erfasst am 2026-10-12)* **[Get an API key](https://go.apimart.ai/k-ed35ed)** · **[Live pricing](https://go.apimart.ai/k-438edd)** · **[Model page](https://go.apimart.ai/k-f8793f)** · [⚡ 60-second quickstart](#quickstart) **Warum Teams HappyHorse 1.0 (`happyhorse-1.0`) über APIMart nutzen** - **Ein Key, der gesamte Katalog.** Dieselbe Base-URL `

Overview: HappyHorse 1.1 API is a single endpoint for accessing the OpenAI-compatible APIMart, providing model id, pricing, and parameters for 300+ models, including images, videos, and language models. Key features: - Single API key for catalog access - Per-image pricing, no monthly subscription required - Supports 300+ models including images, videos, and language models - Supports both synchronous and asynchronous design - Reports exact cost for completed tasks and refunds failed ones Tech stack: Python Why it matters: Simplifies access to multiple models and pricing, making it ideal for developers looking to integrate OpenAI-compatible APIs without the complexity of multiple endpoints or subscriptions. Repository: k8vhk457a/happyhorse-1-1-api-ja Primary language: Python GitHub stars: 12 GitHub description: HappyHorse 1.1 API (`happyhorse-1.1`): model id, pricing, parameters and copy-paste examples for the OpenAI-compatible APIMart endpoint.

### Overview: Wan 2.6 I2V API (`wan2.6-i2v`) is a cutting-edge AI video model offering superior visual quality, high motion coherence, and professional-grade performance. This API is compatible with OpenAI and provides a single key for all catalog items, making it easy to integrate with various applications. ### Key Features: - **Single Image to Video**: Generate videos from single images using the Wan 2.6 I2V model. - **One API Key**: Use a single key to access all Wan 2.6 I2V models and 300+ additional models. - **Pricing**: Per generated second, with a base price of $0.0664 per second. - **Asynchronous**: Tasks are processed asynchronously, with `task_id` returned for monitoring progress. - **Billing**: Cost is reported in the response, and tasks that fail are refunded. ### Tech Stack: - Python ### Why It Matters: - **Single Key for All Models**: A single key allows access to all Wan 2.6 I2V models and 300+ additional models, simplifying integration. - **Dynamic Pricing**: Prices are per generated second, making it easy to manage costs based on usage. - **Asynchronous Processing**: Tasks are processed asynchronously, ensuring minimal downtime. - **Refundable Cost**: Any failed tasks are refunded, providing a transparent and reliable cost model. ### Repository: Repository: k9vlr7/wan-2-6-i2v-api-id GitHub Stars

Overview: Grok Imagine Video 1.5 API is an OpenAI-compatible endpoint that allows developers to generate high-quality videos from text or images, with pricing based on the number of seconds generated. Key features: - Supports text-to-video and image-to-video conversions - Pricing model: $0.064 per second on the APIMart route, no monthly plan required - Model id and routes: `grok-imagine-video-1.5` with tiered pricing - Pricing details: List price 0.08, effective price 0.064 - Request parameters: `model`, `prompt`, `duration`, `resolution`, `size`, `image_urls`, `seed` Tech stack: Python Why it matters: Grok Imagine Video 1.5 API simplifies the process of generating videos from text or images, providing a scalable and cost-effective solution for developers looking to integrate advanced AI capabilities into their projects without the complexities of managing a subscription-based service.

### Overview: AstraPix is an AI-powered image generation platform that uses advanced Replicate models for text-to-image and image editing. It offers both text-to-image and image-to-image generation, supports manual authentication via GitHub OAuth, and integrates a token-based payment system via Razorpay for premium features. The platform is designed to be modern and intuitive, with a sleek UI and a user-friendly experience. ### Key Features: - **AI-Powered Image Generation**: Generate high-quality images using advanced deep learning models. - **Text-to-Image (txt2img)**: Convert text prompts into visually stunning images. - **Image-to-Image (img2img)**: Modify or enhance existing images using AI. - **Fine-Tuned Replicate Models**: Optimized models for generating highly realistic and artistic images. - **User Authentication**: Secure login/signup with manual credentials and OAuth via GitHub. - **Token-Based Payment System**: Purchase credits via Razorpay for image generation. - **Free vs Premium Access**: Free users can generate limited images during specified hours, while premium users get unrestricted access. - **API Access for Developers**: AstraPix provides API endpoints for developers to integrate AI-powered image generation into their applications. - **Modern & Intuitive UI**: Designed with a futuristic yet minimalist interface for a smooth user experience. ### Tech Stack: - **Frontend:** - React.js - TailwindCSS for a sleek and responsive design - Axios for API requests - **Backend:** - Node.js with Express.js - MongoDB with Mongoose for user and

Overview: Veo 3.1 API (`veo3.1-fast-ext`) is an OpenAI-compatible endpoint that provides access to Veo 3 models, including the latest generation, offering enhanced audiovisual quality and advanced cinematic controls for professional video creation. Key features: - Model access to both `veo3.1-fast` and `veo3.1-quality` models - Pricing based on the number of generated seconds, with a minimum charge of $1 - The cost is reported in the response, and tasks can be retried in case of failure - The API is asynchroneous, allowing for batch processing and retries through a queue Tech stack: Python Why it matters: Veo 3.1 API simplifies the process of integrating Veo 3 models into projects, providing a single endpoint that is compatible with OpenAI, making it easier for developers to leverage the latest advancements in video creation technology. GitHub stars: 12