RRepoGEO

REPOGEO REPORT · LITE

deep-diver/LLM-As-Chatbot

Default branch main · commit 99c2c03e · scanned 6/21/2026, 10:52:46 PM

GitHub: 3,323 stars · 376 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
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 deep-diver/LLM-As-Chatbot, 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
    Reposition the README's opening statement to clarify its role as an LLM chatbot deployment service

    Why:

    CURRENT
    The purpose of this repository is to let people to use lots of open sourced instruction-following fine-tuned LLM models as a Chatbot service.
    COPY-PASTE FIX
    LLM as a Chatbot Service provides a ready-to-use framework for deploying open-source instruction-following Large Language Models (LLMs) as robust chatbot services, complete with a Gradio web UI, internet search, and Discord bot integration.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://jarvislabs.ai/

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 deep-diver/LLM-As-Chatbot
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Gradio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Gradio · recommended 1×
  2. Streamlit · recommended 1×
  3. Hugging Face Transformers · recommended 1×
  4. FastAPI · recommended 1×
  5. Flask · recommended 1×
  • CATEGORY QUERY
    How to deploy open-source large language models as a chatbot service with a web UI?
    you: not recommended
    AI recommended (in order):
    1. Gradio
    2. Streamlit
    3. Hugging Face Transformers
    4. FastAPI
    5. Flask
    6. Vue.js
    7. React
    8. Llama.cpp
    9. Angular
    10. LangChain
    11. OpenWebUI
    12. Ollama

    AI recommended 12 alternatives but never named deep-diver/LLM-As-Chatbot. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow integrating internet search and Discord bot support for custom LLM chatbots?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. Botpress
    5. Voiceflow
    6. discord.py (Rapptz/discord.py)
    7. SerpAPI
    8. Google Custom Search API
    9. DuckDuckGo API
    10. Bing Web Search API
    11. OpenAI's API
    12. Hugging Face Transformers (huggingface/transformers)

    AI recommended 12 alternatives but never named deep-diver/LLM-As-Chatbot. 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 deep-diver/LLM-As-Chatbot?
    pass
    AI named deep-diver/LLM-As-Chatbot explicitly

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

  • If a team adopts deep-diver/LLM-As-Chatbot in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deep-diver/LLM-As-Chatbot 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 deep-diver/LLM-As-Chatbot solve, and who is the primary audience?
    pass
    AI did not name deep-diver/LLM-As-Chatbot — 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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deep-diver/LLM-As-Chatbot — 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