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build-paths-beginner

Scaffold a RAG chatbot with OracleVS embeddings and a Grok-4 chat UI.

4.3k|807|Updated Jan 16, 2024
Search Tags:#embeddings#rag#open webui#oracle 26ai free#grok 4#fastapi adapter#langchain-oracledb
One-click install
npx skills add https://github.com/oracle-devrel/oracle-ai-developer-hub --skill build-paths-beginner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: build-paths-beginner
Source: https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/build-paths/beginner
Command: npx skills add https://github.com/oracle-devrel/oracle-ai-developer-hub --skill build-paths-beginner

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps new AI developers scaffold a production-shaped Retrieval-Augmented Generation (RAG) chatbot that works end-to-end, from Oracle 26ai Free in Docker to a Grok 4 chat UI.

Core Features & Use Cases

  • Scaffolds an end-to-end mini-product: Oracle 26ai Free + vector store + chat history + FastAPI adapter + Open WebUI.
  • Supports three starter corpora: PDFs, Markdown notes, or Web pages—sharing the same chat skeleton.
  • Enables grounded answers with citations: the chain retrieves relevant chunks and returns cited responses in the chat UI.
  • Embeddings and chat are wired correctly for Oracle: uses sentence-transformers/all-MiniLM-L6-v2 (384 dims) and LangChain OracleDB store/history helpers.

Quick Start

Invite the Skill to scaffold the beginner path, confirm the OCI GenAI requirements during the interview, then run verify and boot Open WebUI.

Frequently Asked Questions about build-paths-beginner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a RAG chatbot with Grok 4 and Oracle 26ai Free?▼

Yes, Open WebUI connects to your RAG chatbot through an OpenAI-compatible FastAPI adapter. The adapter serves the Grok-4-powered chat interface, allowing Open WebUI to render grounded answers with citations directly from your stored corpus.

Do I need Docker to run Oracle 26ai Free for a retrieval-augmented generation pipeline?▼

The RAG pipeline uses the sentence-transformers/all-MiniLM-L6-v2 model to generate 384-dimensional embeddings. These embeddings are stored in OracleVS to retrieve relevant chunks and provide cited responses in the chat UI.

What's the best way to configure OCI GenAI Grok 4 bearer tokens for a LangChain RAG application?▼

The RAG chatbot supports ingesting PDFs, Markdown notes, and Web pages as starter corpora. It shares the same chat skeleton across all three formats, allowing you to test grounded answers with citations from different document types.

Can I use Open WebUI with an Oracle-backed vector store for chat history?▼

Yes, Open WebUI connects to your Oracle-backed vector store via an OpenAI-compatible FastAPI adapter. The Skill uses LangChain OracleDB store and history helpers to maintain persistent chat history and serve cited responses in the UI.

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