RRepoGEO

REPOGEO REPORT · LITE

liltom-eth/llama2-webui

Default branch main · commit b61fe72e · scanned 5/16/2026, 8:17:13 PM

GitHub: 1,941 stars · 202 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /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
2 / 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 liltom-eth/llama2-webui, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening sentence to highlight core value

    Why:

    CURRENT
    # llama2-webui

Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
    COPY-PASTE FIX
    # llama2-webui: Simple Web UI & OpenAI API for Local Llama 2 Inference

Run any Llama 2 model locally with a user-friendly Gradio web UI on GPU or CPU (Linux/Windows/Mac), or serve it via an OpenAI-compatible API for your generative agents and applications.
  • mediumabout#2
    Add repository URL as homepage

    Why:

    COPY-PASTE FIX
    https://github.com/liltom-eth/llama2-webui
  • lowtopics#3
    Expand topics for better categorization

    Why:

    CURRENT
    llama-2, llama2, llm, llm-inference
    COPY-PASTE FIX
    llama-2, llama2, llm, llm-inference, gradio, web-ui, openai-compatible-api, local-llm-server, code-llama

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 liltom-eth/llama2-webui
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LM Studio
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LM Studio · recommended 2×
  2. Ollama · recommended 1×
  3. Open WebUI · recommended 1×
  4. Chatbot UI · recommended 1×
  5. Jan · recommended 1×
  • CATEGORY QUERY
    How can I run large language models on my local machine with a web interface?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Open WebUI
    4. Chatbot UI
    5. Jan
    6. text-generation-webui (oobabooga/text-generation-webui)
    7. KoboldCpp
    8. LocalAI

    AI recommended 8 alternatives but never named liltom-eth/llama2-webui. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow me to serve local LLMs via an OpenAI-compatible API for custom applications?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. LM Studio
    3. LocalAI (go-skynet/LocalAI)
    4. vLLM (vllm-project/vllm)
    5. text-generation-inference (huggingface/text-generation-inference)
    6. Llama.cpp (ggerganov/llama.cpp)

    AI recommended 6 alternatives but never named liltom-eth/llama2-webui. 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 liltom-eth/llama2-webui?
    pass
    AI named liltom-eth/llama2-webui explicitly

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

  • If a team adopts liltom-eth/llama2-webui in production, what risks or prerequisites should they evaluate first?
    pass
    AI named liltom-eth/llama2-webui 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 liltom-eth/llama2-webui solve, and who is the primary audience?
    pass
    AI did not name liltom-eth/llama2-webui — likely talking about a different project

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

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liltom-eth/llama2-webui — 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