RRepoGEO

REPOGEO REPORT · LITE

DonTizi/rlama

Default branch main · commit 571bb1a3 · scanned 5/27/2026, 2:56:58 AM

GitHub: 1,095 stars · 73 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface DonTizi/rlama, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Refine the 'About' description to explicitly state it's a CLI application

    Why:

    CURRENT
    A powerful document AI question-answering tool that connects to your local Ollama models. Create, manage, and interact with RAG systems for all your document needs.
    COPY-PASTE FIX
    An open-source **CLI application** built in Rust for document AI question-answering, connecting to your local Ollama models. Create, manage, and interact with RAG systems for all your document needs.
  • mediumreadme#2
    Reposition the core product description above the 'Project Temporarily Paused' warning in README

    Why:

    CURRENT
    The current README structure where the pause warning appears before the detailed description of RLAMA's function.
    COPY-PASTE FIX
    Move the paragraph 'RLAMA is a powerful AI-driven question-answering tool for your documents, seamlessly integrating with your local Ollama models. It enables you to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems tailored to your documentation needs.' to appear immediately after the `# RLAMA - User Guide` heading, before the 'Project Temporarily Paused' warning.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface DonTizi/rlama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
https://github.com/run-llama/llama_index
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. https://github.com/run-llama/llama_index · recommended 1×
  2. https://github.com/langchain-ai/langchain · recommended 1×
  3. https://github.com/huggingface/transformers · recommended 1×
  4. https://github.com/UKPLab/sentence-transformers · recommended 1×
  5. https://github.com/ollama/ollama · recommended 1×
  • CATEGORY QUERY
    How can I build a RAG system for documents using locally hosted language models?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (https://github.com/run-llama/llama_index)
    2. LangChain (https://github.com/langchain-ai/langchain)
    3. Hugging Face Transformers (https://github.com/huggingface/transformers)
    4. Sentence Transformers (https://github.com/UKPLab/sentence-transformers)
    5. Ollama (https://github.com/ollama/ollama)
    6. Chroma (https://github.com/chroma-core/chroma)
    7. FAISS (https://github.com/facebookresearch/faiss)
    8. Qdrant (https://github.com/qdrant/qdrant)
    9. LanceDB (https://github.com/lancedb/lancedb)
    10. LM Studio (https://github.com/lmstudio-ai/lmstudio)
    11. text-generation-webui (oobabooga) (https://github.com/oobabooga/text-generation-webui)

    AI recommended 11 alternatives but never named DonTizi/rlama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help create a private question-answering system for my documents with local AI?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. PrivateGPT
    4. LlamaIndex
    5. LangChain
    6. Chroma
    7. FAISS

    AI recommended 7 alternatives but never named DonTizi/rlama. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of DonTizi/rlama?
    pass
    AI named DonTizi/rlama explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts DonTizi/rlama in production, what risks or prerequisites should they evaluate first?
    pass
    AI named DonTizi/rlama explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo DonTizi/rlama solve, and who is the primary audience?
    pass
    AI named DonTizi/rlama explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of DonTizi/rlama. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/DonTizi/rlama.svg)](https://repogeo.com/en/r/DonTizi/rlama)
HTML
<a href="https://repogeo.com/en/r/DonTizi/rlama"><img src="https://repogeo.com/badge/DonTizi/rlama.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

DonTizi/rlama — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite