RRepoGEO

REPOGEO REPORT · LITE

mozilla-ai/any-llm

Default branch main · commit ca0ef070 · scanned 6/29/2026, 5:22:02 AM

GitHub: 2,087 stars · 184 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 mozilla-ai/any-llm, 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 H1 to specify category

    Why:

    CURRENT
    # any-llm
    COPY-PASTE FIX
    # any-llm: A Unified Python API for Any LLM Provider
  • hightopics#2
    Add specific topics for unified LLM APIs

    Why:

    CURRENT
    ai, anthropic, developer-tools, inference, llm, openai, python, text-completion
    COPY-PASTE FIX
    ai, anthropic, developer-tools, inference, llm, openai, python, text-completion, unified-api, llm-abstraction, multi-llm
  • mediumreadme#3
    Add a comparison section to alternatives

    Why:

    COPY-PASTE FIX
    Add a new section titled "Comparison to Alternatives" or "Why any-llm?" that briefly outlines any-llm's unique approach and benefits compared to popular alternatives like LiteLLM, LangChain, or LlamaIndex, focusing on its "single, unified interface" and "provider-agnostic" nature.

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 mozilla-ai/any-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LiteLLM · recommended 2×
  3. Instructor · recommended 2×
  4. OpenAI Python Client · recommended 1×
  5. Azure OpenAI Service · recommended 1×
  • CATEGORY QUERY
    How can I easily switch between different large language model APIs in my Python application?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LiteLLM
    3. OpenAI Python Client
    4. Azure OpenAI Service
    5. Hugging Face `transformers` library
    6. Instructor
    7. Guidance

    AI recommended 7 alternatives but never named mozilla-ai/any-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python library to interact with multiple LLM providers using a consistent API.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. LiteLLM
    4. OpenLLM
    5. Instructor

    AI recommended 5 alternatives but never named mozilla-ai/any-llm. 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 mozilla-ai/any-llm?
    pass
    AI did not name mozilla-ai/any-llm — 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 mozilla-ai/any-llm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mozilla-ai/any-llm 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 mozilla-ai/any-llm solve, and who is the primary audience?
    pass
    AI named mozilla-ai/any-llm explicitly

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

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mozilla-ai/any-llm — 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