LLM-Ready Components

Multi-provider image generation supporting OpenAI DALL-E, Stability AI, and Replicate. Handles prompt-based generation, size options, and base64/URL output formats.

Vector embedding storage and semantic search. Supports Pinecone, Qdrant, and pgvector. Index documents with embeddings and query by semantic similarity for RAG pipelines, recommendation engines, and duplicate detection.

Structured LLM tool use (function calling) for OpenAI and Anthropic. Define typed tools, run agentic loops, and receive validated structured results. Handles multi-turn tool execution automatically.

Force LLM responses to match a JSON schema. Wraps OpenAI and Anthropic with schema-validated generation, automatic retry on parse failure, and TypeScript type inference from the schema.

Extract text and structured data from PDFs, images, and scanned documents. Supports Tesseract (local), Google Vision, and Azure Document Intelligence. Handles multi-page PDFs, tables, and form fields.

Audio transcription using OpenAI Whisper or Deepgram APIs. Supports file upload, language detection, timestamps, and multiple output formats.

Text-to-speech synthesis using OpenAI TTS or ElevenLabs. Produces audio from text with configurable voice, speed, and output format.

End-to-end Retrieval-Augmented Generation pipeline. Ingests documents, chunks and embeds them into an in-memory vector index, then answers queries by retrieving relevant context and calling an LLM completion endpoint.

Classify text into categories using LLM-powered classification or rule-based approaches. Supports single and batch classification, custom category definitions with descriptions, and a trainable keyword-based fallback for offline use.

Route prompts to different AI models or agents based on intent classification. Supports static rule-based routing, LLM-powered intent detection, and fallback chains for reliable multi-agent orchestration.

Validate LLM inputs and outputs against configurable safety rules including PII detection, content filtering, prompt injection detection, and length limits. Provides a rule engine for building custom validation pipelines.

Manage and render prompt templates with variable interpolation, conditional sections, and few-shot example injection. Supports template registration, validation, and composable prompt construction for LLM workflows.