RRepoGEO

REPOGEO REPORT · LITE

developersdigest/llm-answer-engine

Default branch main · commit 19847197 · scanned 5/25/2026, 4:07:52 AM

GitHub: 5,023 stars · 782 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 developersdigest/llm-answer-engine, 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
    llm-answer-engine, rag, web-search-ai, perplexity-ai, nextjs, langchainjs, groq, mistral-ai, openai, multi-modal-ai
  • highreadme#2
    Reposition the README's opening paragraph to clarify core differentiator

    Why:

    CURRENT
    This repository contains the code and instructions needed to build a sophisticated answer engine that leverages the capabilities of Groq, Mistral AI's Mixtral, Langchain.JS, Brave Search, Serper API, and OpenAI. Designed to efficiently return sources, answers, images, videos, and follow-up questions based on user queries, this project is an ideal starting point for developers interested in natural language processing and search technologies.
    COPY-PASTE FIX
    This repository provides a **web-integrated, multi-modal LLM answer engine**, inspired by Perplexity AI, designed for developers to build sophisticated query response systems. Unlike traditional search engines or local-only RAG solutions, it leverages external APIs like Groq, Mistral AI's Mixtral, Langchain.JS, Brave Search, Serper API, and OpenAI to efficiently return sourced answers, images, videos, and follow-up questions based on real-time web data.
  • mediumabout#3
    Update the repository description for better clarity

    Why:

    CURRENT
    Perplexity Inspired Answer Engine
    COPY-PASTE FIX
    A web-integrated, multi-modal LLM answer engine, inspired by Perplexity AI, leveraging Groq, Mistral, Langchain.JS, Brave Search, Serper API, and OpenAI for comprehensive, sourced responses.

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 developersdigest/llm-answer-engine
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. LlamaIndex · recommended 2×
  3. Elasticsearch · recommended 1×
  4. Apache Solr · recommended 1×
  5. OpenSearch · recommended 1×
  • CATEGORY QUERY
    How can I build a search engine that provides sourced, comprehensive answers and multimedia?
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch
    2. Apache Solr
    3. OpenSearch
    4. Hugging Face Transformers
    5. LangChain
    6. LlamaIndex
    7. FFmpeg
    8. OpenCV
    9. Google Cloud Vision AI
    10. Amazon Rekognition
    11. Azure Cognitive Services
    12. PostgreSQL
    13. MinIO
    14. Amazon S3
    15. Google Cloud Storage
    16. React
    17. Vue.js
    18. Angular
    19. Next.js
    20. Nuxt.js

    AI recommended 20 alternatives but never named developersdigest/llm-answer-engine. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework to integrate LLMs with web search for dynamic, multi-modal query responses.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack (deepset)
    4. Microsoft Semantic Kernel
    5. OpenAI Assistants API

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

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

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