REPOGEO REPORT · LITE

ParisNeo/lollms-webui

Default branch main · commit 6d3c22f9 · scanned 6/18/2026, 2:46:09 PM

GitHub: 4,787 stars · 579 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

33 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 ParisNeo/lollms-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

Clarify the current status and purpose of LoLLMs WebUI in the README

Why:

CURRENT

A new lollms project can be found at: https://github.com/ParisNeo/lollms This is a more advanced version with multi users and MCP compatibility. The lollms webui keeps a minimal support and will eventually be completely replaced by the new lollms project.

COPY-PASTE FIX

LoLLMs WebUI (Local, single user, multi models/modal fully integrated webui) is a robust, actively maintained platform for local LLM and multimodal AI experimentation. While a new multi-user version (https://github.com/ParisNeo/lollms) offers advanced features, this repository continues to provide a stable and comprehensive single-user experience.

mediumtopics#2
Add more specific topics to improve categorization
Why:
CURRENT
```
ai, llm, text-generation
```
COPY-PASTE FIX
```
ai, llm, text-generation, webui, local-llm, multimodal-ai, local-ai, ai-playground
```

mediumreadme#3

Emphasize LoLLMs WebUI's unique "all-in-one" and plugin architecture in the README's introduction

Why:

CURRENT

Welcome to LoLLMS WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all), the hub for LLM (Large Language Models) and multimodal intelligence systems. This project aims to provide a user-friendly interface to access and utilize various LLM and other AI models for a wide range of tasks.

COPY-PASTE FIX

Welcome to LoLLMS WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all), the hub for LLM (Large Language Models) and multimodal intelligence systems. It stands out as an all-in-one local AI playground, integrating a wide range of functionalities (e.g., agents, RAG, image generation, voice, internet access) through its highly extensible plugin architecture. This project aims to provide a user-friendly interface to access and utilize various LLM and other AI models for a wide range of tasks.

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 ParisNeo/lollms-webui

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LM Studio

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

LM Studio · recommended 1×
Ollama · recommended 1×
Jan · recommended 1×
oobabooga/text-generation-webui · recommended 1×
LocalAI · recommended 1×

CATEGORY QUERY
What are good web UIs for locally running and interacting with various large language models?
you: not recommended
AI recommended (in order):
1. LM Studio
2. Ollama
3. Jan
4. Text Generation WebUI (oobabooga/text-generation-webui)
5. LocalAI
6. KoboldCpp
AI recommended 6 alternatives but never named ParisNeo/lollms-webui. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a single user web interface to manage and test different multimodal AI systems.
you: not recommended
AI recommended (in order):
1. Gradio
2. Streamlit
3. Hugging Face Spaces
4. Weights & Biases (W&B)
5. Dash by Plotly
AI recommended 5 alternatives but never named ParisNeo/lollms-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
pass
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 ParisNeo/lollms-webui?
pass
AI did not name ParisNeo/lollms-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?
If a team adopts ParisNeo/lollms-webui in production, what risks or prerequisites should they evaluate first?
pass
AI named ParisNeo/lollms-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 ParisNeo/lollms-webui solve, and who is the primary audience?
pass
AI named ParisNeo/lollms-webui explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/ParisNeo/lollms-webui.svg)](https://repogeo.com/en/r/ParisNeo/lollms-webui)

HTML

<a href="https://repogeo.com/en/r/ParisNeo/lollms-webui"><img src="https://repogeo.com/badge/ParisNeo/lollms-webui.svg" alt="RepoGEO" /></a>

Pro

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ParisNeo/lollms-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