RRepoGEO

REPOGEO REPORT · LITE

huggingface/AnyLanguageModel

Default branch main · commit 701d7e61 · scanned 5/31/2026, 5:31:51 PM

GitHub: 858 stars · 73 forks

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 huggingface/AnyLanguageModel, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    swift, language-model, llm, ai, foundation-models, apple, tool-use, agent, generative-ai, swift-package
  • highhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/huggingface/AnyLanguageModel
  • mediumreadme#3
    Strengthen the README's opening statement to emphasize project's purpose and realness

    Why:

    CURRENT
    # AnyLanguageModel

A Swift package that provides a drop-in replacement for Apple's Foundation Models framework with support for custom language model providers.
    COPY-PASTE FIX
    # AnyLanguageModel

AnyLanguageModel is a robust Swift package designed to empower developers building AI-driven applications. It serves as an API-compatible, drop-in replacement for Apple's Foundation Models framework, uniquely extending support to custom language model providers and advanced tool-use capabilities.

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 huggingface/AnyLanguageModel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain.swift
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain.swift · recommended 2×
  2. GoogleGenerativeAI · recommended 2×
  3. OpenAI Swift Library · recommended 1×
  4. Swift-AI · recommended 1×
  5. Core ML · recommended 1×
  • CATEGORY QUERY
    Swift framework for integrating large language models and custom tools into applications?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Swift Library
    2. LangChain.swift
    3. Swift-AI
    4. Core ML
    5. Alamofire
    6. URLSession
    7. GoogleGenerativeAI

    AI recommended 7 alternatives but never named huggingface/AnyLanguageModel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Swift library to support multiple language model providers and AI agents?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Swift
    2. LangChain.swift
    3. GoogleGenerativeAI
    4. MistralAI/client-swift (MistralAI/client-swift)
    5. llama.cpp (ggerganov/llama.cpp)
    6. Hugging Face Transformers

    AI recommended 6 alternatives but never named huggingface/AnyLanguageModel. 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 huggingface/AnyLanguageModel?
    pass
    AI named huggingface/AnyLanguageModel explicitly

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

  • If a team adopts huggingface/AnyLanguageModel in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name huggingface/AnyLanguageModel — 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?

  • In one sentence, what problem does the repo huggingface/AnyLanguageModel solve, and who is the primary audience?
    pass
    AI named huggingface/AnyLanguageModel explicitly

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

Embed your GEO score

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MARKDOWN (README)
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huggingface/AnyLanguageModel — 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