REPOGEO REPORT · LITE

mythrantic/ollama-docker

Default branch main · commit 4ae2f2b7 · scanned 6/27/2026, 8:58:17 AM

GitHub: 1,408 stars · 254 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 mythrantic/ollama-docker, 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 the README's opening to emphasize 'batteries-included' local LLM server setup

Why:

CURRENT

Welcome to the Ollama Docker Compose Setup! This project simplifies the deployment of Ollama using Docker Compose, making it easy to run Ollama with all its dependencies in a containerized environment.

COPY-PASTE FIX

Welcome to the Ollama Docker Compose Setup! This project provides a pre-configured, 'batteries-included' Docker Compose environment for Ollama, simplifying the deployment of a complete local LLM server with integrated GPU support (NVIDIA and AMD) and optional web UI (like Open WebUI) in a containerized environment.

mediumtopics#2

Add broader AI/LLM-related topics

Why:

CURRENT

docker, docker-compose, ollama

COPY-PASTE FIX

docker, docker-compose, ollama, llm, ai, local-llm, generative-ai, model-deployment, gpu-acceleration, open-webui

lowlicense#3

Clarify the existing license in the README

Why:

COPY-PASTE FIX

Add a section or line in the README, e.g., '## License
This project is licensed under [describe the license(s) present in your LICENSE file, e.g., 'a custom license combining X and Y terms']. Please refer to the `LICENSE` file for full details.'

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 mythrantic/ollama-docker

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

oobabooga/text-generation-webui

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

oobabooga/text-generation-webui · recommended 2×
ollama/ollama · recommended 1×
LM Studio · recommended 1×
ggerganov/llama.cpp · recommended 1×
huggingface/text-generation-inference · recommended 1×

CATEGORY QUERY
What's the easiest way to run open-source large language models locally using Docker?
you: not recommended
AI recommended (in order):
1. Ollama (ollama/ollama)
2. LM Studio
3. text-generation-webui (oobabooga/text-generation-webui)
4. llama.cpp (ggerganov/llama.cpp)
5. Hugging Face Text Generation Inference (huggingface/text-generation-inference)
6. LocalAI (mudler/LocalAI)
AI recommended 6 alternatives but never named mythrantic/ollama-docker. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to set up a local AI model server using Docker Compose for easy deployment?
you: not recommended
AI recommended (in order):
1. Ollama
2. LocalAI
3. text-generation-webui (oobabooga/text-generation-webui)
4. vLLM
5. Triton Inference Server
6. MLflow
AI recommended 6 alternatives but never named mythrantic/ollama-docker. 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 mythrantic/ollama-docker?
pass
AI named mythrantic/ollama-docker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts mythrantic/ollama-docker in production, what risks or prerequisites should they evaluate first?
pass
AI named mythrantic/ollama-docker 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 mythrantic/ollama-docker solve, and who is the primary audience?
pass
AI named mythrantic/ollama-docker 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)

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mythrantic/ollama-docker — 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