RRepoGEO

REPOGEO REPORT · LITE

NVIDIA/ChatRTX

Default branch release/0.5.0 · commit 142025c1 · scanned 5/20/2026, 3:32:41 AM

GitHub: 3,124 stars · 429 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
35 /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
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 NVIDIA/ChatRTX, 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
  • highabout#1
    Update the repository's 'About' description

    Why:

    CURRENT
    A developer reference project for creating Retrieval Augmented Generation (RAG) chatbots on Windows using TensorRT-LLM
    COPY-PASTE FIX
    A complete, pre-built demo application and developer reference project for local Retrieval Augmented Generation (RAG) chatbots on Windows, optimized for NVIDIA RTX GPUs.
  • mediumreadme#2
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under [specify license(s) here, e.g., a custom NVIDIA license or a combination of licenses]. 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 NVIDIA/ChatRTX
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LM Studio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LM Studio · recommended 1×
  2. PrivateGPT · recommended 1×
  3. Ollama · recommended 1×
  4. LlamaIndex · recommended 1×
  5. ChromaDB · recommended 1×
  • CATEGORY QUERY
    How can I create a secure, local RAG chatbot on my Windows PC for diverse file types?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. PrivateGPT
    3. Ollama
    4. LlamaIndex
    5. ChromaDB
    6. LocalAI
    7. LangChain
    8. FAISS
    9. Jan
    10. GPT4All

    AI recommended 10 alternatives but never named NVIDIA/ChatRTX. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a framework to build fast, private AI assistants leveraging local GPU hardware.
    you: not recommended
    AI recommended (in order):
    1. llama.cpp (ggerganov/llama.cpp)
    2. Ollama (ollama/ollama)
    3. Hugging Face Transformers (huggingface/transformers)
    4. TensorRT-LLM (NVIDIA/TensorRT-LLM)
    5. MLC LLM (mlc-ai/mlc-llm)

    AI recommended 5 alternatives but never named NVIDIA/ChatRTX. 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 NVIDIA/ChatRTX?
    pass
    AI named NVIDIA/ChatRTX explicitly

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

  • If a team adopts NVIDIA/ChatRTX in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NVIDIA/ChatRTX 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 NVIDIA/ChatRTX solve, and who is the primary audience?
    pass
    AI named NVIDIA/ChatRTX explicitly

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

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NVIDIA/ChatRTX — 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