RRepoGEO

REPOGEO REPORT · LITE

langchain-ai/chat-langchain

Default branch master · commit 63e73cdd · scanned 5/20/2026, 7:43:14 PM

GitHub: 6,348 stars · 1,475 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 langchain-ai/chat-langchain, 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
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    A production-ready reference implementation for building RAG-based conversational agents with LangGraph, LangChain, and LangSmith, featuring documentation search, guardrails, and link validation.
  • mediumreadme#2
    Clarify the README's opening statement to emphasize its role as a production-ready reference

    Why:

    CURRENT
    > A simple documentation assistant built with LangGraph.
    COPY-PASTE FIX
    > A production-ready reference implementation for building RAG-based conversational agents with LangGraph, LangChain, and LangSmith.

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 langchain-ai/chat-langchain
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. OpenAI API · recommended 1×
  3. GPT-4 · recommended 1×
  4. GPT-3.5 Turbo · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    How to build a custom AI assistant for searching and answering questions from documentation?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI API
    3. GPT-4
    4. GPT-3.5 Turbo
    5. Pinecone
    6. Chroma
    7. Hugging Face Transformers
    8. sentence-transformers/all-MiniLM-L6-v2
    9. sentence-transformers/all-mpnet-base-v2
    10. FastAPI
    11. Streamlit

    AI recommended 11 alternatives but never named langchain-ai/chat-langchain. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good frameworks for building RAG-based conversational agents with state and guardrails?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. MindsDB
    5. Rasa
    6. OpenAI Assistants API

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

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

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langchain-ai/chat-langchain — 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