Search Elixpo

OreoLook

A curious, open-source AI search scout with real-time web research, RAG, and an OpenAI-compatible API.

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[](https://github.com/pollinations/lixSearch/stargazers) [](https://github.com/pollinations/lixSearch/network) [](https://github.com/pollinations/lixSearch/issues) [](https://github.com/pollinations/lixSearch/commits/main)

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✨ What Makes OreoLook Different?

• Don't wait for search results. OreoLook remembers what you've already asked about and serves up answers instantly from its memory. Same question, instant answer.

• Unlike regular search engines, OreoLook understands what you're really asking for. It searches the web, watches YouTube videos, analyzes images, and pieces everything together into a coherent answer.

• Every answer comes with sources. Read the original articles, watch the videos, see exactly where the information came from. No fluff, no guessing.

• Ask a follow-up question and OreoLook remembers what you were just talking about. It's like chatting with someone who actually paid attention to the conversation.

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🚩 Released Packages

| Package | Registry | Install / Pull | Description | |---------|----------|---------------|-------------| | lix-open-cache | PyPI | pip install lix-open-cache | Standalone 3-layer Redis caching + Huffman disk archival for conversational AI | | LixSearch | Docker Hub / GHCR | docker pull elixpo/lixsearch OR docker pull ghcr.io/circuit-overtime/lixsearch | Full self-hostable search engine (API + Redis + ChromaDB + Playwright) both on Docker Hub and GitHub Container Registry |

• lix-open-cache — standalone caching library, works independently with just Redis. No server needed. Only depends on redis, numpy, loguru.
• LixSearch Docker — the full search engine. Run docker compose --env-file .env.local up and get a working API.

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⚙️ How It Works

When you ask OreoLook a question, here's what happens behind the scenes:

1. You Ask - Type your question naturally, like you're talking to a friend
2. We Understand - OreoLook breaks down your question into its key parts
3. We Search - Multiple search agents fan out across the web, YouTube, and images simultaneously
4. We Read - Automatically extract the important information from articles and videos
5. We Synthesize - An AI reads through everything and writes a clear, concise answer
6. You Get Results - A beautifully formatted answer with clickable sources and relevant images

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🌍 Real-World Use Cases

• Any NLP based model that has the ability to perform tools / function calling can use this
• Completely self hosted, so you can run it on your own infrastructure and customize it to your needs on CPU
• Can surf youtube / web_images / indexed web pages to find information and synthesize it into a single answer
• Can be used as a backend for any search engine, chatbot, or assistant that needs to
• Search the web for information
• Find relevant videos and images
• Synthesize information into a clear answer
• Provide sources for all information
• Can be modified into single endpoints for specific use cases like:
• Product search with reviews and images
• Recipe search with videos and photos
• News search with original sources and summaries
• Location search with details, reviews, and photos

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🛠️ How The System Design HLD

flowchart TD
    A["🔍 You Ask a Question"] --> B["🧠 Query Analysis & Understanding"]
    B --> C{"Cache Hit?"}
    C -- "Yes (cosine > 0.90)" --> J["⚡ Instant Cached Answer"]
    C -- "No" --> D["🔀 Tool Router"]

    D --> E["🌐 Web Search\n(Playwright Agents)"]
    D --> F["🎬 YouTube Search\n(Metadata + Transcripts)"]
    D --> G["🖼️ Image Search"]
    D --> H["📄 Page Fetch\n(Full Text Extraction)"]

    E --> I["📚 RAG Context Assembly\nChunk → Embed → Vector Search"]
    F --> I
    G --> I
    H --> I

    I --> K{"Need More Info?"}
    K -- "Yes (max 3 loops)" --> D
    K -- "No" --> L["🤖 LLM Synthesis\n(Conversation History + RAG + Sources)"]

    L --> M["📡 Stream Response\n(SSE: real-time, word by word)"]
    M --> N["Answer with Sources"]

    M -.-> O[("💾 Save to Cache\n& Session History")]

    style A fill:#4A90D9,stroke:#2C5F8A,color:#fff
    style C fill:#F5A623,stroke:#D4891A,color:#fff
    style J fill:#7ED321,stroke:#5FA318,color:#fff
    style N fill:#7ED321,stroke:#5FA318,color:#000
    style D fill:#9B59B6,stroke:#7D3C98,color:#fff
    style L fill:#E74C3C,stroke:#C0392B,color:#fff

Result: Fast, accurate answers you can trust.

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🎁 Core Capabilities

| Capability | Implementation | |-----------|---------------| | Real-time streaming | Server-Sent Events (SSE) — tokens stream as they're generated, not buffered | | Semantic caching | Redis DB0 with cosine similarity (threshold 0.90) — repeat queries resolve in

❓ Why Use lixSearch?

vs. Regular Search Engines

• Better Understanding - Grasps what you really want, not just keyword matching
• Saves Time - One coherent answer instead of browsing 10 blue links
• Context Aware - Remembers what you were just talking about
• Multimedia - Automatically finds videos, images, and articles

vs. ChatGPT

• Real-Time Info - Connected to the web, not using outdated training data
• Verified Sources - Every fact links to where it came from
• Fresher Results - Gets today's news, not last year's knowledge
• Faster - Streamed results, not waiting for a complete response

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👥 Perfect For

• Students - Research papers, homework, learning topics
• Professionals - Market research, industry updates, competitor analysis
• Home Improvement - DIY guides, product reviews, how-to videos
• Travelers - Travel planning, local info, reviews
• Researchers - Deep dives with cited sources
• News Junkies - Latest updates with original sources

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Each will give you a complete, sourced answer.

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Request Flow

> This is the flow of the request that we have from the CF Reverse proxy

Browser → search.elixpo.com (Cloudflare Pages, edge)
           ↓
         Next.js API route (e.g. /api/search/route.ts)
           ↓
         backendUrl("/api/search") → "http://search.elixpo.com/api/search"
           ↓
         fetch() with headers:
           X-API-Key:            ← nginx auth on :10001
           X-Internal-Key:     ← app-level auth
           ↓
         Your droplet :10001 (nginx) → :9002 (app)

❔ FAQ

How is this different from Google? Google gives you links. lixSearch gives you answers. We do the searching for you and synthesize a coherent response.

Is my search history private? Your privacy is important. [Link to privacy policy]

Can I use this offline? lixSearch needs internet to search the web, but works faster when utilizing local cache.

Why are my results sometimes general? Ask more specifically! "Vegan chocolate chip cookies" gives better results than "recipes."

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🤝 Get Involved

Found a bug? Have ideas for improvement? Contribute on GitHub | Report Issues

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📧 Contact & Support

Questions? Feedback? Suggestions?

• hello@elixpo.com
• lixSearch source

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Happy Searching!

> lixSearch - Search smarter, not harder. Made with ❤️ by Elixpo

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: pollinations
• Source: pollinations/search.elixpo
• License: CC0-1.0
• Homepage: https://search.elixpo.com

Install and usage instructions live in the source repository linked above.