The Foundation of Every Ragfish Application

Build intelligent AI applications with a lightweight, modular framework designed for Retrieval-Augmented Generation (RAG), document processing, and enterprise knowledge systems.

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What is the Core Framework?

The Core Framework is the heart of the Ragfish ecosystem. Rather than combining AI models, vector databases, and data connectors into a single monolithic package, Ragfish focuses on the orchestration layer—the part responsible for managing the complete Retrieval-Augmented Generation (RAG) workflow.

This modular design allows developers to choose the AI providers, vector databases, and knowledge connectors that best fit their application while maintaining a consistent development experience.

Whether you're building a chatbot, document assistant, enterprise search platform, or intelligent business application, every Ragfish solution starts with the Core Framework.

Why a Core Framework?

Modern AI applications require multiple technologies working together.

AI models generate responses.

Connectors ingest business knowledge.

Applications manage users and workflows.

The Core Framework connects these technologies into a unified developer experience, allowing every component to work together seamlessly. Instead of writing custom integration code for every project, developers build on a stable foundation that is designed to grow with their applications.

Core Components

The Core Framework is built around five essential components.

Framework configuration

This modular design allows developers to choose the AI providers, vector databases, and knowledge connectors that best fit their application while maintaining a consistent development experience.

Connectors ingest business data.
Apps manage users and workflows.
Choose AI providers and vector DBs.

Document ingestion

Ragfish connects directly to your existing data sources - databases, file storage, CMS platforms, or APIs - and pulls content in without requiring manual uploads or format conversion.

Auto-syncs data from sources.
Supports multiple file formats.
Updates without manual re-import.

Content chunking

Once ingested, documents are broken into smaller, meaningful segments that preserve context. This lets the AI retrieve precise, relevant information instead of returning entire documents.

Splits content into coherent segments.
Preserves context across chunks.
Returns precise, relevant results.

Semantic retrieval

Instead of relying on exact keyword matches, Ragfish understands the meaning behind a query and retrieves the most relevant content — even when the wording differs from what's in the source data.

Matches queries by meaning, not keywords.
Ranks and surfaces relevant content.
Stays accurate across varied phrasing.

Chat orchestration

Ragfish manages the full conversation flow - tracking context across turns, routing queries to the right data sources, and assembling retrieved information into a clear, coherent response.

Maintains context across turns.
Auto-routes queries to connectors.
Combines multiple sources in responses

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How the Core Framework Works

Every user request follows a consistent execution flow.

User Question

Chat Engine

Retriever

Vector Store

Relevant Knowledge

AI Provider

AI Response

Knowledge Processing Pipeline

Before AI can answer questions, business knowledge must first be prepared.

Source Content

Connector

Ingestion

Chunking

Embedding Generation

Vector Store

Built for Extension

The Core Framework intentionally focuses only on orchestration. Additional functionality is delivered through official Ragfish packages.

Lightweight by Design

The Core Framework contains only the functionality required to orchestrate AI applications. This design keeps applications lightweight while giving developers complete flexibility to install only the packages they need.

Whether your project requires a single AI provider or a complex enterprise architecture, Ragfish scales with your requirements.

TypeScript First

Ragfish is built specifically for modern TypeScript development.

Strong type safety

IntelliSense support

Clean APIs

Modular package design

Excellent developer experience

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AI Providers are only one part of the Ragfish ecosystem.

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