ai_provider_quant_cloud
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Quant Cloud AI Provider
Code is currently in GitHub, but will be synced to drupal.org soon.
This module provides a Quant Cloud provider for the AI module. It connects your Drupal site to Quant Cloud, a managed AI platform with access to foundation models from Anthropic (Claude), Amazon, and Cohere.
Quant Cloud handles the infrastructure, streaming, and scaling. No direct cloud provider credentials or AI infrastructure management required.
Integrated AI and Vector Database
Quant Cloud provides both LLM access and a managed vector database through a single API. This means:
- One provider for chat, embeddings, image generation, and vector storage
- No separate database infrastructure to provision or maintain
- Index content directly - send text, get searchable vectors
- Single API key for all operations
This simplifies RAG (retrieval-augmented generation) and semantic search implementations by removing the need to coordinate multiple services.
What does it do?
This module provides the following AI module operation types:
- Chat - Conversational AI with message history, streaming responses, and tool calling
- Embeddings - Generate vector embeddings for text using Titan or Cohere models
- Text-to-Image - Generate images from text prompts using Nova Canvas
- Image-to-Image - Transform images with variations, inpainting, outpainting, and background removal
- Vector Database - Store and search embeddings with semantic similarity
Available Models
Chat / Text Generation
- Claude model family (Opus 4.5, Sonnet 4.5, Haiku 4.5, and earlier versions)
- Nova Pro, Nova Lite, Nova Micro
Embeddings
- Titan Embed Text v1 and v2
- Cohere Embed English/Multilingual v3
Image Generation
- Nova Canvas (text-to-image, inpainting, outpainting, background removal)
Features
Chat
- Multi-turn conversations with message history
- Real-time streaming via Server-Sent Events
- Tool/function calling
- Structured JSON output with schema validation
- Multimodal input (images, documents)
Image Generation
- Text-to-image generation
- Image variations from reference images
- Inpainting and outpainting
- Background removal
- Multiple style presets
- Resolutions up to 2048x2048
Vector Database
- Managed vector storage (no external database required)
- Automatic embedding generation from text
- Semantic similarity search
- Integration with Search API via AI Search module
Requirements
For vector database features:
- Search API module
- AI Search module
Configuration
- Install and enable the module and its dependencies
- Navigate to Administration > Configuration > AI > Quant Cloud
- Click "Connect to Quant Cloud" to authenticate via OAuth
- Select your default models for each operation type
Related Modules
- AI - Required base module that provides the provider plugin system
- AI Search - Integrates AI embeddings with Search API
- Key - Secure storage for API credentials