RRepoGEO

REPOGEO REPORT · LITE

Abraxas-365/langchain-rust

Default branch main · commit cfc709a7 · scanned 7/1/2026, 10:11:41 AM

GitHub: 1,326 stars · 176 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
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 Abraxas-365/langchain-rust, 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's opening to emphasize 'LLM application framework'

    Why:

    CURRENT
    # 🦜️🔗LangChain Rust

[![Latest Version]][crates.io]

[Latest Version]: https://img.shields.io/crates/v/langchain-rust.svg
[crates.io]: https://crates.io/crates/langchain-rust

⚡ Building applications with LLMs through composability, with Rust! ⚡
    COPY-PASTE FIX
    # 🦜️🔗LangChain Rust: The LLM Application Framework for Rust

[![Latest Version]][crates.io]

[Latest Version]: https://img.shields.io/crates/v/langchain-rust.svg
[crates.io]: https://crates.io/crates/langchain-rust

⚡ Build sophisticated LLM-powered applications in Rust with composability, agents, chains, and vector stores! ⚡
  • hightopics#2
    Add more specific topics for LLM application frameworks

    Why:

    CURRENT
    langchain, llm, llms, openai, rust
    COPY-PASTE FIX
    langchain, llm, llms, openai, rust, ai-applications, llm-framework, orchestration, agents, chains, vector-stores
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://langchain-rust.sellie.tech/get-started/quickstart

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 Abraxas-365/langchain-rust
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
llm
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. llm · recommended 2×
  2. candle · recommended 1×
  3. tract · recommended 1×
  4. tch-rs · recommended 1×
  5. Rustformers · recommended 1×
  • CATEGORY QUERY
    What Rust library helps build sophisticated large language model applications with ease?
    you: not recommended
    AI recommended (in order):
    1. llm
    2. candle
    3. tract
    4. tch-rs
    5. Rustformers

    AI recommended 5 alternatives but never named Abraxas-365/langchain-rust. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Rust framework for orchestrating LLMs, embeddings, and vector stores into AI applications.
    you: not recommended
    AI recommended (in order):
    1. LLM-chain
    2. Tonic
    3. Candle
    4. llama-rs
    5. llm
    6. qdrant-client
    7. milvus-client
    8. pinecone-rs
    9. Actix-web
    10. Axum
    11. reqwest
    12. openai-api
    13. anthropic-rs
    14. Flowistry
    15. Tokio

    AI recommended 15 alternatives but never named Abraxas-365/langchain-rust. 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 Abraxas-365/langchain-rust?
    pass
    AI did not name Abraxas-365/langchain-rust — 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 Abraxas-365/langchain-rust in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Abraxas-365/langchain-rust 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 Abraxas-365/langchain-rust solve, and who is the primary audience?
    pass
    AI did not name Abraxas-365/langchain-rust — 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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MARKDOWN (README)
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Abraxas-365/langchain-rust — 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