REPOGEO REPORT · LITE

brainlid/langchain

Default branch main · commit 77173e6a · scanned 5/17/2026, 5:46:42 AM

GitHub: 1,171 stars · 199 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

Reposition the README H1 and opening sentence to clarify language and project type

Why:

CURRENT

# Elixir LangChain

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

COPY-PASTE FIX

# Elixir LangChain: A Generative AI Framework for Elixir

`Elixir LangChain` is an Elixir-native framework for building generative AI applications, enabling Elixir projects to integrate with and leverage various LLMs and AI services. This project is an independent implementation inspired by the LangChain style, not a fork.

mediumreadme#2

Add a 'Key Features' section emphasizing multi-provider generative AI capabilities

Why:

COPY-PASTE FIX

## Key Features

*   **Multi-Provider Support:** Seamlessly integrate with a wide array of LLM providers including Anthropic, OpenAI, Grok, Google Gemini, DeepSeek, Ollama, Mistral, Perplexity, and more.
*   **Generative AI Application Framework:** Provides a structured approach to build complex AI-powered applications in Elixir, handling chaining, memory, agents, and tools.
*   **Elixir-Native Implementation:** Leverage Elixir's concurrency and fault tolerance for robust and scalable AI solutions.

lowreadme#3

Clarify the project's license in the README

Why:

COPY-PASTE FIX

## License

This project is licensed under the terms specified in the `LICENSE` file. Please refer to the `LICENSE` file for full details on the applicable terms and conditions.

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

OpenAI API

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenAI API · recommended 1×
finch · recommended 1×
jason · recommended 1×
Google Cloud Vertex AI · recommended 1×
Hugging Face Inference API · recommended 1×

CATEGORY QUERY
How to integrate large language models into an Elixir application?
you: not recommended
AI recommended (in order):
1. OpenAI API
2. finch
3. jason
4. Google Cloud Vertex AI
5. Hugging Face Inference API
6. ollama
7. Azure OpenAI Service
8. ex_llama
AI recommended 8 alternatives but never named brainlid/langchain. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What framework helps build generative AI applications using Elixir with multiple LLM providers?
you: not recommended
AI recommended (in order):
1. Nx (Numerical Elixir) (elixir-nx/nx)
2. Axon (elixir-nx/axon)
3. LangChain.ex (langchain-ex/langchain)
4. OpenAI Elixir Library
5. Google Generative AI Elixir Library
6. Hugging Face Transformers.ex
AI recommended 6 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?

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MARKDOWN (README)

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HTML

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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