RRepoGEO

REPOGEO REPORT · LITE

GAIR-NLP/O1-Journey

Default branch main · commit 30b9795f · scanned 6/29/2026, 7:52:56 PM

GitHub: 2,001 stars · 61 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 GAIR-NLP/O1-Journey, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ['large-language-models', 'llm-research', 'medical-reasoning', 'mathematical-reasoning', 'deep-thinking', 'replication-study', 'journey-learning', 'ai-reasoning']
  • highreadme#2
    Reposition the README's H1 to clearly state the project's focus

    Why:

    CURRENT
    # O1 Replication Journey
    COPY-PASTE FIX
    # O1 Replication Journey: Advancing LLM Deep Thinking for Medical and Mathematical Reasoning
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the root of the repository to clearly state the project's licensing terms.

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 GAIR-NLP/O1-Journey
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. Llama 2 · recommended 1×
  3. GPT-3.5 (via OpenAI API for fine-tuning) · recommended 1×
  4. Mistral · recommended 1×
  5. OpenAI API (Fine-tuning endpoint) · recommended 1×
  • CATEGORY QUERY
    How can I enhance large language models for deep thinking in medical diagnosis?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Llama 2
    3. GPT-3.5 (via OpenAI API for fine-tuning)
    4. Mistral
    5. OpenAI API (Fine-tuning endpoint)
    6. LangChain
    7. LlamaIndex
    8. Faiss (Facebook AI Similarity Search)
    9. BioBERT
    10. PubMedBERT
    11. Neo4j
    12. OWLAPI
    13. Protégé
    14. Med-PaLM 2 (Google DeepMind)
    15. MONAI (Medical Open Network for AI)

    AI recommended 15 alternatives but never named GAIR-NLP/O1-Journey. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help replicate LLM research and train models for complex reasoning journeys?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning (Lightning-AI/lightning)
    2. Hugging Face Transformers (huggingface/transformers)
    3. DeepSpeed (microsoft/DeepSpeed)
    4. Weights & Biases (wandb/wandb)
    5. Ray (ray-project/ray)
    6. Jupyter Notebooks / JupyterLab
    7. TensorBoard (tensorflow/tensorboard)

    AI recommended 7 alternatives but never named GAIR-NLP/O1-Journey. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 GAIR-NLP/O1-Journey?
    pass
    AI named GAIR-NLP/O1-Journey explicitly

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

  • If a team adopts GAIR-NLP/O1-Journey in production, what risks or prerequisites should they evaluate first?
    pass
    AI named GAIR-NLP/O1-Journey 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 GAIR-NLP/O1-Journey solve, and who is the primary audience?
    pass
    AI named GAIR-NLP/O1-Journey explicitly

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

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GAIR-NLP/O1-Journey — 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