RRepoGEO

REPOGEO REPORT · LITE

langflow-ai/openrag

Default branch main · commit bfc23783 · scanned 5/9/2026, 10:41:40 AM

GitHub: 3,967 stars · 396 forks

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 langflow-ai/openrag, 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 improve categorization

    Why:

    COPY-PASTE FIX
    rag, retrieval-augmented-generation, llm, large-language-models, ai-platform, document-search, agentic-ai, langflow, opensearch, docling
  • mediumreadme#2
    Strengthen README opening to highlight "pre-packaged platform" differentiator

    Why:

    CURRENT
    OpenRAG is a comprehensive Retrieval-Augmented Generation platform that enables intelligent document search and AI-powered conversations.
    COPY-PASTE FIX
    OpenRAG is a comprehensive, pre-packaged Retrieval-Augmented Generation (RAG) platform designed for intelligent document search and AI-powered conversations, ready to run out-of-the-box.
  • lowreadme#3
    Add a "Why OpenRAG?" or "Comparison" section to README

    Why:

    COPY-PASTE FIX
    ## Why OpenRAG?

While many RAG frameworks like LlamaIndex and LangChain provide powerful code-first libraries for building RAG applications, OpenRAG stands out as a comprehensive, pre-packaged platform with deep and explicit integration with the Langflow visual builder. This allows for rapid iteration and deployment of agentic RAG workflows without extensive coding, making it ideal for developers and ML engineers seeking a ready-to-use solution.

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 langflow-ai/openrag
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 2×
  2. LangChain · recommended 2×
  3. Haystack · recommended 2×
  4. RAGatouille · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How to build a complete RAG system for intelligent document search and AI conversations?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. RAGatouille
    5. Weaviate
    6. Pinecone
    7. OpenSearch

    AI recommended 7 alternatives but never named langflow-ai/openrag. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are pre-packaged platforms for agentic retrieval-augmented generation with document processing?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Azure AI Search
    5. Azure OpenAI Service
    6. AWS Kendra
    7. Amazon Bedrock
    8. Google Cloud Vertex AI Search and Conversation
    9. OpenAI Assistants API

    AI recommended 9 alternatives but never named langflow-ai/openrag. 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 langflow-ai/openrag?
    pass
    AI named langflow-ai/openrag explicitly

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

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

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

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langflow-ai/openrag — 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