REPOGEO REPORT · LITE

yym68686/uni-api

Default branch main · commit 710db813 · scanned 5/25/2026, 5:18:07 AM

GitHub: 1,224 stars · 155 forks

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 yym68686/uni-api, 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 introduction to clearly state its LLM API unification purpose

Why:

CURRENT

For personal use, one/new-api is too complex with many commercial features that individuals don't need. If you don't want a complicated frontend interface and prefer support for more models, you can try uni-api. This is a project that unifies the management of large language model APIs, allowing you to call multiple backend services through a single unified API interface, converting them all to OpenAI format, and supporting load balancing. Currently supported backend services include: OpenAI, Anthropic, Gemini, Vertex, Azure, AWS, xai, Cohere, Groq, Cloudflare, OpenRouter, 0-0.pro and more.

COPY-PASTE FIX

uni-api is a lightweight, no-frontend solution for unifying and managing multiple Large Language Model (LLM) APIs. It allows you to call various backend services through a single, OpenAI-compatible API interface, supporting load balancing and simplifying access to providers like OpenAI, Anthropic, Gemini, Vertex, Azure, AWS, xai, Cohere, Groq, Cloudflare, OpenRouter, and many more.

mediumtopics#2

Add functional topics to better categorize the repository

Why:

CURRENT

aws, azure, claude, gemini, grok, openai, uni-api, vertex

COPY-PASTE FIX

llm-api-gateway, llm-proxy, openai-compatible-api, api-unification, load-balancing, ai-api-management, anthropic, gemini, openai, vertex, openrouter, aws, azure, claude, grok

lowreadme#3

Clarify the mention of '0-0.pro' in the README

Why:

CURRENT

Currently supported backend services include: OpenAI, Anthropic, Gemini, Vertex, Azure, AWS, xai, Cohere, Groq, Cloudflare, OpenRouter, 0-0.pro and more.

COPY-PASTE FIX

Currently supported backend services include: OpenAI, Anthropic, Gemini, Vertex, Azure, AWS, xai, Cohere, Groq, Cloudflare, OpenRouter, and the 0-0.pro service, among others.

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 yym68686/uni-api

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LangChain

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

LangChain · recommended 2×
FastAPI · recommended 2×
OpenAI API · recommended 1×
LlamaIndex · recommended 1×
Pydantic · recommended 1×

CATEGORY QUERY
What's a simple way to consolidate various AI model backends into one unified endpoint?
you: not recommended
AI recommended (in order):
1. OpenAI API
2. LangChain
3. LlamaIndex
4. FastAPI
5. Pydantic
6. Hugging Face Inference Endpoints
7. Transformers Library
8. MLflow
9. Kubernetes
10. Istio
11. Envoy
AI recommended 11 alternatives but never named yym68686/uni-api. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How can I unify diverse large language model APIs into a single OpenAI-compatible interface?
you: not recommended
AI recommended (in order):
1. LiteLLM
2. OpenRouter
3. LocalAI
4. Helicone
5. Portkey.ai
6. LangChain
7. NGINX
8. Flask
9. FastAPI
AI recommended 9 alternatives but never named yym68686/uni-api. 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 yym68686/uni-api?
pass
AI did not name yym68686/uni-api — 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 yym68686/uni-api in production, what risks or prerequisites should they evaluate first?
pass
AI named yym68686/uni-api 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 yym68686/uni-api solve, and who is the primary audience?
pass
AI named yym68686/uni-api 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 yym68686/uni-api. 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/yym68686/uni-api.svg)](https://repogeo.com/en/r/yym68686/uni-api)

HTML

<a href="https://repogeo.com/en/r/yym68686/uni-api"><img src="https://repogeo.com/badge/yym68686/uni-api.svg" alt="RepoGEO" /></a>

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