RRepoGEO

REPOGEO REPORT · LITE

huangjia2019/langchain-in-action

Default branch main · commit 6a899d65 · scanned 6/4/2026, 10:57:23 AM

GitHub: 758 stars · 260 forks

AI VISIBILITY SCORE
22 /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
1 / 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 huangjia2019/langchain-in-action, 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
  • highreadme#1
    Reposition README opening to clarify its role as a course companion

    Why:

    CURRENT
    # LangChain实战课

喜欢这个Repo，就要到这里购买此课，支持佳哥

还有，佳哥的新书GPT图解，重磅问世。当然你也要支持一下。此处购买5折。

https://time.geekbang.org/column/intro/100617601
    COPY-PASTE FIX
    # LangChain实战课 - 极客时间课程配套代码与示例

本仓库是极客时间《LangChain实战课》的官方配套代码和实践示例。它提供了LangChain框架早期设计的一系列重点模块的直接而清晰的示例和讲解，旨在帮助学员理解和应用LangChain构建LLM应用。请注意，随着LangChain的快速演进，部分代码可能需要更新版本进行迭代。建议在学习课程概念的同时，自行探索LangChain的最新进展。

喜欢这个Repo，就要到这里购买此课，支持佳哥

还有，佳哥的新书GPT图解，重磅问世。当然你也要支持一下。此处购买5折。

https://time.geekbang.org/column/intro/100617601
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or a custom license if applicable) in the root of the repository, clearly stating the terms under which the code is provided.
  • mediumtopics#3
    Add more specific topics to reflect its educational nature

    Why:

    CURRENT
    agent, langchain, llm
    COPY-PASTE FIX
    agent, langchain, llm, tutorial, course-companion, education, practical-examples, llm-applications

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 huangjia2019/langchain-in-action
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. OpenAI API (GPT-3.5/GPT-4) · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. Cohere API · recommended 1×
  5. Google Gemini API · recommended 1×
  • CATEGORY QUERY
    Seeking practical examples for building real-world applications powered by large language models effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. OpenAI API (GPT-3.5/GPT-4)
    3. Hugging Face Transformers (huggingface/transformers)
    4. Cohere API
    5. Google Gemini API
    6. SpaCy (explosion/spaCy)
    7. Pinecone
    8. ChromaDB (chroma-core/chroma)
    9. LlamaIndex (run-llama/llama_index)
    10. Weaviate (weaviate/weaviate)
    11. GitHub Copilot

    AI recommended 11 alternatives but never named huangjia2019/langchain-in-action. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement conversational AI agents with complex reasoning capabilities efficiently?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. OpenAI Assistants API
    5. Haystack
    6. AutoGPT
    7. BabyAGI

    AI recommended 7 alternatives but never named huangjia2019/langchain-in-action. 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 huangjia2019/langchain-in-action?
    pass
    AI did not name huangjia2019/langchain-in-action — 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 huangjia2019/langchain-in-action in production, what risks or prerequisites should they evaluate first?
    pass
    AI named huangjia2019/langchain-in-action 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 huangjia2019/langchain-in-action solve, and who is the primary audience?
    pass
    AI did not name huangjia2019/langchain-in-action — 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?

Embed your GEO score

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huangjia2019/langchain-in-action — 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