REPOGEO REPORT · LITE

serge-chat/serge

Default branch main · commit 3cb250c4 · scanned 6/24/2026, 9:52:05 AM

GitHub: 5,725 stars · 393 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)

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

AI VISIBILITY SCORE

40 /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

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 serge-chat/serge, 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 paragraph for local LLM web UI

Why:

CURRENT

# Serge - LLaMA made easy 🦙

Serge is a chat interface crafted with llama.cpp for running LLM models. No API keys, entirely self-hosted!

COPY-PASTE FIX

# Serge: Self-Hosted Web UI for Local LLM Chat (powered by llama.cpp) 🦙

Serge provides a user-friendly, entirely self-hosted web interface for chatting with large language models (LLMs) locally, built on llama.cpp. Run your own private AI assistant with no API keys.

mediumtopics#2

Add descriptive topics for local LLM web interfaces

Why:

CURRENT

alpaca, docker, fastapi, llama, llamacpp, nginx, python, svelte, sveltekit, tailwindcss, web

COPY-PASTE FIX

alpaca, docker, fastapi, llama, llamacpp, nginx, python, svelte, sveltekit, tailwindcss, web, local-llm, self-hosted, chatbot, ai-assistant, web-ui

mediumcomparison#3

Add a 'Why Serge?' or comparison section to the README

Why:

COPY-PASTE FIX

Add a new section to the README, e.g., "## Why Serge? (Compared to X, Y, Z)" or "## Serge vs. Other Local LLM UIs". Start with: "Serge stands out by offering a fully dockerized, easy-to-deploy web interface specifically for local LLM inference, focusing on a streamlined chat experience without external dependencies."

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 serge-chat/serge

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LM Studio

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

LM Studio · recommended 2×
oobabooga/text-generation-webui · recommended 2×
Ollama · recommended 1×
Jan · recommended 1×
LocalAI · recommended 1×

CATEGORY QUERY
How can I set up a self-hosted web interface for local LLM inference and chat?
you: not recommended
AI recommended (in order):
1. LM Studio
2. Ollama
3. text-generation-webui (oobabooga/text-generation-webui)
4. Jan
5. LocalAI
6. PrivateGPT
7. InvokeAI
AI recommended 7 alternatives but never named serge-chat/serge. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are easy ways to run a local large language model chat interface using Docker?
you: not recommended
AI recommended (in order):
1. Ollama (ollama/ollama)
2. Open WebUI (open-webui/open-webui)
3. Chatbot UI (mckaywrigley/chatbot-ui)
4. LocalAI (go-skynet/LocalAI)
5. text-generation-webui (oobabooga/text-generation-webui)
6. LM Studio
7. Jan (janhq/jan)
8. PrivateGPT (imartinez/privateGPT)
AI recommended 8 alternatives but never named serge-chat/serge. 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 serge-chat/serge?
pass
AI named serge-chat/serge explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts serge-chat/serge in production, what risks or prerequisites should they evaluate first?
pass
AI named serge-chat/serge 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 serge-chat/serge solve, and who is the primary audience?
pass
AI named serge-chat/serge 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 serge-chat/serge. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/serge-chat/serge.svg)](https://repogeo.com/en/r/serge-chat/serge)

HTML

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

Pro

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serge-chat/serge — 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