REPOGEO REPORT · LITE

brainlid/langchain

Default branch main · commit 7d1d2b7a · scanned 6/28/2026, 7:16:55 AM

GitHub: 1,174 stars · 203 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

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 brainlid/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

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Clarify the README's opening to explicitly state it's an independent Elixir implementation, not a Python fork.

Why:

CURRENT

# Elixir LangChain

Elixir LangChain enables Elixir applications to integrate AI services and self-hosted models into an application.

COPY-PASTE FIX

Update the README's initial heading and paragraph to clearly state:

`# LangChain for Elixir: An Elixir-native LLM Orchestration Framework`

`brainlid/langchain is an independent, Elixir-native implementation of the popular LangChain-style framework. It is designed to help Elixir applications integrate, orchestrate, and leverage various AI services and large language models, providing a structured approach for building LLM-powered applications.`

mediumtopics#2

Add more specific topics to highlight the framework and orchestration aspects.

Why:

CURRENT

ai, anthropic, bumblebee, chatgpt, claude-ai, elixir, langchain, llm

COPY-PASTE FIX

ai, anthropic, bumblebee, chatgpt, claude-ai, elixir, langchain, llm, llm-framework, ai-orchestration, elixir-framework, large-language-models, gen-ai

mediumlicense#3

Add a clear statement about the project's license to the README.

Why:

COPY-PASTE FIX

Add a dedicated 'License' section to the README, stating: `This project is licensed under [Specify the actual license(s) here, e.g., "the Apache 2.0 License and the MIT License"]. Please refer to the LICENSE file for complete details.`

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 brainlid/langchain

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

elixir-nx/nx

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

elixir-nx/nx · recommended 1×
elixir-nx/bumblebee · recommended 1×
dillonkearns/openai-elixir · recommended 1×
elixir-google-api/google_generative_ai · recommended 1×
mmariz/req · recommended 1×

CATEGORY QUERY
How can I integrate various large language models into my Elixir application?
you: not recommended
AI recommended (in order):
1. Nx (elixir-nx/nx)
2. Bumblebee (elixir-nx/bumblebee)
3. openai Elixir library (dillonkearns/openai-elixir)
4. google_generative_ai Elixir client (elixir-google-api/google_generative_ai)
5. Req (mmariz/req)
6. Tesla (teamon/tesla)
7. HTTPoison (edgurgel/httpoison)
AI recommended 7 alternatives but never named brainlid/langchain. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What Elixir framework helps orchestrate interactions with diverse AI chat model APIs?
you: not recommended
AI recommended (in order):
1. Nx
2. Axon
3. Bumblebee
4. OpenAI Elixir
5. Tesla
6. HTTPoison
7. Req
AI recommended 7 alternatives but never named brainlid/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
pass
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 brainlid/langchain?
pass
AI named brainlid/langchain explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts brainlid/langchain in production, what risks or prerequisites should they evaluate first?
pass
AI named brainlid/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 brainlid/langchain solve, and who is the primary audience?
pass
AI named brainlid/langchain explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of brainlid/langchain. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/brainlid/langchain.svg)](https://repogeo.com/en/r/brainlid/langchain)

HTML

<a href="https://repogeo.com/en/r/brainlid/langchain"><img src="https://repogeo.com/badge/brainlid/langchain.svg" alt="RepoGEO" /></a>

Pro

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brainlid/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