mirror of
https://github.com/prowler-cloud/prowler.git
synced 2026-07-17 01:21:51 +00:00
10838de636
Co-authored-by: Chandrapal Badshah <12944530+Chan9390@users.noreply.github.com>
54 lines
2.7 KiB
Plaintext
54 lines
2.7 KiB
Plaintext
---
|
|
title: 'How It Works'
|
|
---
|
|
|
|
import { VersionBadge } from "/snippets/version-badge.mdx"
|
|
|
|
<VersionBadge version="5.8.0" />
|
|
|
|
Prowler Lighthouse AI integrates Large Language Models (LLMs) with Prowler security findings data.
|
|
|
|
Here's what's happening behind the scenes:
|
|
|
|
- The system uses a multi-agent architecture built with [LanggraphJS](https://github.com/langchain-ai/langgraphjs) for LLM logic and [Vercel AI SDK UI](https://sdk.vercel.ai/docs/ai-sdk-ui/overview) for frontend chatbot.
|
|
- It uses a ["supervisor" architecture](https://langchain-ai.lang.chat/langgraphjs/tutorials/multi_agent/agent_supervisor/) that interacts with different agents for specialized tasks. For example, `findings_agent` can analyze detected security findings, while `overview_agent` provides a summary of connected cloud accounts.
|
|
- The system connects to the configured LLM provider to understand user's query, fetches the right data, and responds to the query.
|
|
<Note>
|
|
Lighthouse AI supports multiple LLM providers including OpenAI, Amazon Bedrock, and OpenAI-compatible services. For configuration details, see [Using Multiple LLM Providers with Lighthouse](/user-guide/tutorials/prowler-app-lighthouse-multi-llm).
|
|
</Note>
|
|
- The supervisor agent is the main contact point. It is what users interact with directly from the chat interface. It coordinates with other agents to answer users' questions comprehensively.
|
|
|
|
<img src="/images/prowler-app/lighthouse-architecture.png" alt="Lighthouse AI Architecture" />
|
|
|
|
<Note>
|
|
All agents can only read relevant security data. They cannot modify your data or access sensitive information like configured secrets or tenant details.
|
|
|
|
</Note>
|
|
|
|
## Set up
|
|
|
|
Getting started with Prowler Lighthouse AI is easy:
|
|
|
|
1. Navigate to **Configuration** → **Lighthouse AI**
|
|
2. Click **Connect** under the desired provider (OpenAI, Amazon Bedrock, or OpenAI Compatible)
|
|
3. Enter the required credentials
|
|
4. Select a default model
|
|
5. Click **Connect** to save
|
|
|
|
<Note>
|
|
For detailed configuration instructions for each provider, see [Using Multiple LLM Providers with Lighthouse](/user-guide/tutorials/prowler-app-lighthouse-multi-llm).
|
|
</Note>
|
|
|
|
<img src="/images/prowler-app/lighthouse-configuration.png" alt="Lighthouse AI Configuration" />
|
|
|
|
### Adding Business Context
|
|
|
|
The optional business context field lets you provide additional information to help Lighthouse AI understand your environment and priorities, including:
|
|
|
|
- Your organization's cloud security goals
|
|
- Information about account owners or responsible teams
|
|
- Compliance requirements for your organization
|
|
- Current security initiatives or focus areas
|
|
|
|
Better context leads to more relevant responses and prioritization that aligns with your needs.
|