RRepoGEO

REPOGEO REPORT · LITE

streamlit/llm-examples

Default branch main · commit 7cf26074 · scanned 6/13/2026, 9:47:49 AM

GitHub: 921 stars · 1,728 forks

AI VISIBILITY SCORE
22 /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
1 / 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 streamlit/llm-examples, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Strengthen README opening to emphasize interactive web UI examples

    Why:

    CURRENT
    # 🎈 Streamlit + LLM Examples App

[](https://codespaces.new/streamlit/llm-examples?quickstart=1)

Starter examples for building LLM apps with Streamlit.
    COPY-PASTE FIX
    # 🎈 Streamlit + LLM Examples: Interactive Web UIs for Generative AI

[](https://codespaces.new/streamlit/llm-examples?quickstart=1)

Starter examples for building interactive web applications with Large Language Models (LLMs) using Streamlit. This repository provides ready-to-run code for common LLM use cases, focusing on user-friendly interfaces.
  • mediumabout#2
    Refine repository description for clarity and specificity

    Why:

    CURRENT
    Streamlit LLM app examples for getting started
    COPY-PASTE FIX
    Interactive web UI examples for building Streamlit applications with Large Language Models (LLMs).

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 streamlit/llm-examples
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
streamlit/streamlit
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. streamlit/streamlit · recommended 1×
  2. gradio-app/gradio · recommended 1×
  3. langchain-ai/langchain · recommended 1×
  4. run-llama/llama_index · recommended 1×
  5. Hugging Face Spaces · recommended 1×
  • CATEGORY QUERY
    How can I quickly build interactive AI applications with large language models?
    you: not recommended
    AI recommended (in order):
    1. Streamlit (streamlit/streamlit)
    2. Gradio (gradio-app/gradio)
    3. LangChain (langchain-ai/langchain)
    4. LlamaIndex (run-llama/llama_index)
    5. Hugging Face Spaces
    6. Panel (holoviz/panel)

    AI recommended 6 alternatives but never named streamlit/llm-examples. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good examples for getting started building web UIs for large language models?
    you: not recommended
    AI recommended (in order):
    1. Gradio
    2. Streamlit
    3. LangChain UI
    4. Next.js
    5. FastAPI
    6. Panel

    AI recommended 6 alternatives but never named streamlit/llm-examples. 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 streamlit/llm-examples?
    pass
    AI did not name streamlit/llm-examples — 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 streamlit/llm-examples in production, what risks or prerequisites should they evaluate first?
    pass
    AI named streamlit/llm-examples 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 streamlit/llm-examples solve, and who is the primary audience?
    pass
    AI did not name streamlit/llm-examples — 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?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite